Oxford Nanopore vs. Sanger Sequencing for Parasite Detection: A Comprehensive Guide for Researchers

Abstract

This article provides a comparative analysis of Oxford Nanopore Technologies (ONT) and Sanger sequencing for parasitic disease research and diagnostics. It explores the foundational principles of each technology, detailing their specific methodological applications in detecting drug resistance, characterizing co-infections, and conducting genomic surveillance. The content addresses key troubleshooting and optimization strategies for field-deployable and resource-limited settings. Furthermore, it presents a rigorous validation of their performance against gold standards and each other, examining metrics such as sensitivity, specificity, turnaround time, and cost. Aimed at researchers, scientists, and drug development professionals, this review synthesizes current evidence to guide technology selection for diverse parasitological applications, from clinical trials to fundamental pathogen genomics.

Understanding the Core Technologies: Principles of Sanger and Nanopore Sequencing in Parasitology

Targeted genotyping is essential for understanding parasite biology, tracking drug resistance, and managing disease outbreaks. For years, Sanger sequencing has served as the gold standard for confirming genetic variations in pathogens due to its exceptional accuracy. The emergence of next-generation sequencing (NGS) platforms, particularly Oxford Nanopore Technologies (ONT), has introduced new paradigms with advantages in speed, portability, and the ability to detect minority clones. This guide objectively compares the performance of Sanger sequencing against Oxford Nanopore and other NGS alternatives for parasite genotyping, providing researchers with experimental data and methodologies to inform their sequencing strategy.

Molecular genotyping of parasites requires precise identification of genetic markers to track drug resistance, distinguish between recrudescence and new infections, and conduct surveillance. Sequencing technologies form the backbone of these efforts, with each platform offering distinct advantages and limitations. Sanger sequencing, developed in the 1970s, has remained the reference method for confirming single nucleotide polymorphisms (SNPs) and mutations in targeted genomic regions due to its proven reliability and accuracy exceeding 99.9% [1] [2]. Next-generation sequencing platforms, including Illumina and Ion Torrent, enable highly multiplexed analysis of numerous samples and markers simultaneously, while third-generation technologies like Oxford Nanopore offer unprecedented portability and long-read capabilities that are revolutionizing field-based genomic surveillance [1] [3].

The choice of sequencing platform depends on multiple factors, including the required accuracy, throughput, turnaround time, cost considerations, and available infrastructure. This guide provides a detailed comparison of these technologies, focusing specifically on their applications in parasite genotyping, with experimental data from recent studies to inform platform selection for different research scenarios.

Technology Comparison: Specifications and Performance Metrics

Table 1: Technical specifications of sequencing platforms used in parasite genotyping

Platform	Sequencing Principle	Max Read Length	Accuracy	Cost per Gb (USD)	Time to Result	Primary Parasitology Applications
Sanger	Dideoxy chain termination	<1 kb	>99.9% [1]	~$13,000 [1]	1-3 days	SNP confirmation, validation of NGS findings, small-scale genotyping
Illumina	Fluorescent reversible terminators	75-150 bp [1]	>99.9% [1] [2]	$50-63 [1]	2-7 days	Multiplexed amplicon sequencing, drug resistance marker screening, population studies
Oxford Nanopore	Nanopore current sensing	10-60 kb [1]	87-98% (raw), >99% with polishing [1] [3]	$21-42 [1]	<48 hours [3]	Field surveillance, haplotype resolution, large structural variant detection
Ion Torrent	Semiconductor pH detection	200-400 bp	~99% [2]	Not specified	1-3 days	Targeted amplicon sequencing, moderate throughput genotyping

Table 2: Performance comparison for parasite genotyping applications

Parameter	Sanger Sequencing	Illumina NGS	Oxford Nanopore	Ion Torrent
SNP Calling Accuracy	99.9% (gold standard) [2]	99.83% vs Sanger [2]	92-100% (depends on chemistry) [4]	99.83% vs Sanger [2]
Minority Variant Detection	Limited to ~15-20% allele frequency	1% at 500X coverage [2]	1% in polyclonal infections [3]	1% at 500X coverage [2]
Multiplexing Capacity	Low (single sample per reaction)	High (96-384 samples) [2]	Moderate to high (24-96 samples) [3]	High (96 samples) [2]
Portability	Low (lab-based)	Low (lab-based)	High (portable MinION) [5]	Low (lab-based)
Workflow Simplicity	Simple, established	Complex library preparation	Moderate, rapid library prep [3]	Moderate complexity

Experimental Data and Performance Benchmarks

SNP Concordance Studies

A comprehensive 2022 study comparing targeted next-generation sequencing for Plasmodium falciparum drug resistance markers demonstrated complete concordance between Sanger sequencing, Illumina MiSeq, and Ion Torrent PGM platforms for 572 SNP calls across six drug resistance genes (pfcrt, pfdhfr, pfdhps, pfmdr1, pfkelch, and pfcytochrome b) [2]. Both NGS platforms achieved sequencing accuracy of 99.83% and variant accuracy of 99.59% when validated against Sanger sequencing as the reference standard [2]. The single discordant position occurred in the pfdhfr gene at position I164L, where Sanger sequencing called a homozygous T while both NGS platforms detected an A/T heterozygote, suggesting potential superior sensitivity of NGS for mixed infections [2].

Minority Clone Detection Sensitivity

The ability to detect minority clones in polyclonal infections is crucial for understanding parasite population dynamics and distinguishing recrudescence from new infections. In laboratory strain mixture experiments, both Illumina and Ion Torrent platforms could reliably detect minor alleles at 1% density with 500X coverage [2]. Recent advances in Oxford Nanopore chemistry have demonstrated similar sensitivity, with a 2025 study showing detection of minority clones in Plasmodium falciparum at ratios as low as 1:100:100:100 in mixed laboratory strains [3]. This sensitivity is particularly valuable for genotyping paired samples in clinical trials to determine if recurrent parasitemia represents recrudescence or new infection.

Accuracy Evolution in Oxford Nanopore

Early Oxford Nanopore technologies showed limitations in raw read accuracy, with a 2018 study reporting average base-call accuracy of 74.3% using flow cell R7.3 for sequencing Plasmodium falciparum drug resistance genes [4]. However, with sufficient coverage (>50 reads per position), SNP calling precision reached 0.92 with a recall rate of 0.8 [4]. Significant improvements came with updated chemistries, where flow cell R9.4 increased precision to 1.0 and recall to 0.97, demonstrating the rapid evolution of this technology [4]. The latest chemistry (R10.4.1) combined with super-accurate basecalling models now enables q-scores ≥20, corresponding to accuracy of ≥99% [3].

Experimental Protocols for Parasite Genotyping

Targeted Amplicon Sequencing for Drug Resistance Markers

Table 3: Research reagent solutions for targeted amplicon sequencing

Reagent/Kit	Function	Application Example
Selective Whole Genome Amplification (SWGA) Primers	Selective amplification of parasite DNA in host background	Enriching Haemoproteus majoris DNA from avian blood samples [6]
Multiplex PCR Panels	Simultaneous amplification of multiple target genes	Amplifying 6 microhaplotype loci in P. falciparum [3]
Native Barcoding Kit 96 V14 (SQK-NBD114.96)	Sample multiplexing for Oxford Nanopore	Barcoding 96 samples for simultaneous sequencing [3]
EquiPhi29 DNA Polymerase	Isothermal amplification for SWGA	Amplifying parasite DNA with minimal bias [6]
Dorado Basecaller	Converting raw electrical signals to nucleotide sequences	High-accuracy basecalling with super-accurate model [3]

Protocol: Multiplexed Amplicon Sequencing for Plasmodium Genotyping

• DNA Extraction: Use whole blood, dried blood spots, or infected vectors. For samples with high host DNA content, consider selective whole genome amplification (SWGA) with parasite-specific primers [6].

• Multiplex PCR Amplification: Amplify target genes simultaneously using optimized primer pools. A recent study targeting six microhaplotype loci in P. falciparum (ama1, celtos, cpmp, cpp, csp, and surfin1.1) used the following cycling conditions [3]:

  • Initial denaturation: 95°C for 3 minutes
  • 35 cycles of: 95°C for 15s, 58°C for 30s, 68°C for 90s
  • Final extension: 68°C for 5 minutes

• Library Preparation: For Oxford Nanopore:

  • Use Native Barcoding Kit 96 V14 (SQK-NBD114.96)
  • Follow manufacturer's instructions with modifications for pathogen sequencing [3]
  • Target sequencing depth: ~25,000 reads per marker per sample

• Sequencing:

  • For Sanger: Purify amplicons and sequence with BigDye terminators
  • For Oxford Nanopore: Use MinION Mk1C with R10.4.1 flow cells and MinKNOW software
  • For Illumina: Use MiSeq with v3 chemistry (600 cycles)

• Data Analysis:

  • Basecalling: For Oxford Nanopore, use dorado (v0.8.2) with super-accurate model, minimum q-score of 20 [3]
  • Variant Calling: For Sanger data, use specialized software like Mutation Surveyor; for NGS, use GATK or platform-specific variant callers
  • Haplotype Reconstruction: For polyclonal infections, use inferential methods considering allele sharing probabilities [3]

Workflow Visualization: Parasite Genotyping Pathways

Adaptive Sampling for Host DNA Depletion

Oxford Nanopore's adaptive sampling feature enables computational enrichment of parasite DNA during sequencing, bypassing laborious wet lab procedures. A 2023 proof-of-concept study demonstrated 3- to 5-fold enrichment of Plasmodium falciparum bases in samples containing 0.1%-8.4% parasite DNA by ejecting human reads after sequencing approximately 400 bases [5]. This method is particularly valuable for field applications where traditional enrichment methods may not be feasible.

Protocol: Adaptive Sampling for Plasmodium Sequencing

• DNA Preparation: Extract DNA from patient blood samples without human DNA depletion.
• Library Preparation: Prepare sequencing library using Ligation Sequencing Kit.
• Adaptive Sampling Setup:
  • Enable adaptive sampling in MinKNOW
  • Use P. falciparum reference genome (Pf3D7) as enrichment target
  • Set human genome as depletion target
• Sequencing: Run on MinION or GridION with R10.4.1 flow cells
• Quality Control: Assess enrichment by comparing percentage of Plasmodium bases to regular sequencing mode

Application in Parasite Research: Case Studies

Distinguishing Recrudescence from New Infection

A 2025 study evaluated nanopore amplicon sequencing for distinguishing recrudescence from new infections in antimalarial drug trials [3]. Using a multiplexed panel targeting six microhaplotype loci, the method demonstrated high sensitivity in detecting minority clones (as low as 1:100:100:100 in laboratory strain mixtures) and robust reproducibility (intra-assay: 98%; inter-assay: 97%) [3]. Across 20 paired patient samples, the assay consistently distinguished recrudescence from new infections in 17/20 cases (85%) for all six markers, demonstrating utility for therapeutic efficacy studies [3].

Trypanosomatid Identification and Genotyping

A 2024 study developed an 18S rDNA amplicon-based sequencing method using Oxford Nanopore for Trypanosomatid detection and genotyping [7]. The method effectively distinguished between 11 Trypanosoma species and 6 Trypanosoma cruzi discrete typing units (TcI to TcVI and TcBat), showing strong concordance with conventional methods (κ index of 0.729) [7]. The assay detected co-infections between Trypanosomatid genera and T. cruzi, with a limit of detection of one parasite per mL, demonstrating high resolution, sensitivity, and accuracy for understanding Trypanosomatid dynamics [7].

Technology Decision Pathway

Sanger sequencing maintains its position as the gold standard for targeted parasite genotyping when maximum accuracy is required for validation of critical findings, particularly in clinical and regulatory contexts. Its exceptional accuracy (>99.9%) and established protocols make it indispensable for confirming drug resistance mutations and resolving discrepancies from other methods [2].

However, Oxford Nanopore technologies have emerged as a transformative platform for parasite research, particularly in resource-limited settings and for applications requiring rapid turnaround. With continued improvements in accuracy through updated chemistries and advanced basecalling algorithms, Oxford Nanopore now achieves >99% accuracy with sufficient coverage [3] [4]. Its portability, scalability, and ability to generate long reads make it particularly valuable for field-based surveillance, outbreak investigations, and comprehensive haplotype resolution.

The future of parasite genotyping lies in leveraging the complementary strengths of these technologies. A hybrid approach using Oxford Nanopore for rapid initial screening and Sanger sequencing for validation of critical SNPs represents a powerful strategy that balances speed with precision. As sequencing technologies continue to evolve, the parasitology research community will benefit from maintaining Sanger sequencing as a reference standard while embracing the advantages of modern platforms that offer unprecedented insights into parasite biology and transmission dynamics.

The study of parasites, with their complex life cycles, diverse hosts, and intricate genomes, has long been a challenging field in infectious disease research. For decades, Sanger sequencing has served as the gold standard for genetic characterization in parasitology, providing accurate data for targeted, small-scale gene sequencing. However, its reliance on pre-defined primers and inability to efficiently handle mixed infections or discover novel pathogens have been significant limitations. The advent of Oxford Nanopore Technologies (ONT) sequencing represents a disruptive force, offering a fundamentally different approach. By enabling the real-time sequencing of long DNA or RNA fragments through the measurement of electrical current changes as nucleic acids pass through a protein nanopore, ONT provides a powerful tool for comprehensive genomic analysis. This article objectively compares the performance of Oxford Nanopore sequencing against Sanger sequencing for parasite research, framing the discussion within the broader thesis of its efficacy for unraveling complex parasitic diseases.

Technical Principles and Comparative Workflow Analysis

The Fundamental Principles of Oxford Nanopore Sequencing

Oxford Nanopore sequencing is characterized by its label-free, direct electronic sensing of nucleic acids. The core technology involves several key steps:

• Library Preparation: DNA or RNA is prepared, often with minimal fragmentation, preserving long native strands. Adaptors are ligated to the ends of the molecules.
• Motor Protein Unzipping: A processive enzyme (motor protein) controls the rate at which the nucleic acid strand passes through the nanopore.
• Nanopore Sensing: The library is loaded onto a flow cell containing an electrically resistant membrane embedded with biological nanopores. An ionic current is passed through the nanopores.
• Basecalling in Real-Time: As individual DNA or RNA bases pass through the pore, each one causes a characteristic disruption in the ionic current. These unique "squiggles" are decoded into nucleotide sequences (basecalling) by sophisticated algorithms in real time.

This direct electronic readout is what allows for the exceptionally long read lengths—from tens of kilobases to over 2 megabases—that are a hallmark of the technology.

Comparative Workflows: A Side-by-Side View

The following diagram illustrates the key procedural differences between the two sequencing methods, highlighting the more streamlined nature of the ONT workflow for comprehensive genomic surveillance.

Quantitative Performance Comparison in Parasite Research

Direct, data-driven comparisons are essential for evaluating the practical impact of a technology shift. The table below summarizes key performance metrics for Sanger and Oxford Nanopore sequencing, drawing from specific applications in parasite detection and characterization.

Table 1: Performance Comparison of Sanger vs. Oxford Nanopore Sequencing for Parasite Research

Parameter	Sanger Sequencing	Oxford Nanopore Sequencing	Supporting Experimental Data
Detection Capability	Single parasite species per reaction [8]	Multiple parasites simultaneously; 11 species in one assay [9]	Metabarcoding detected 11/11 cloned parasites; relative read abundance varied by species (0.9% - 17.2%) [9].
Turnaround Time	Days to weeks (requires culture/PCR) [8]	< 48 hours to < 24 hours; rapid pathogen ID [10]	Metagenomic sequencing for severe infections delivered preliminary results in 2 hours, final reports in 24 hours for 94% of samples [10].
Sensitivity in Mixed Samples	Limited; fails with polymicrobial infections [11]	High; characterizes polymicrobial communities [11]	In paediatric samples, ONT metagenomics detected 50 additional pathogens missed by standard methods, with specificity ≥99% [10].
Drug Resistance Profiling	Requires separate, targeted assays [8]	Comprehensive; identifies known/novel resistance genes in a single run [12] [8]	Targeted nanopore sequencing (NOMADS panel) robustly identified Pfalciparum drug-resistance mutations from dried blood spots [12].
Workflow & Cost	Lower per-target cost; sequential testing can be costly and slow [11]	Faster, consolidated workflow; can reduce time-to-diagnosis by 85% and costs by 38% [13]	In a hypotonia study, ONT reduced the potential diagnostic timeline from 168 to 25 days and cost by $611 per patient on average [13].

Experimental Protocols: From Theory to Practice

To translate these performance metrics into actionable research methodologies, below are detailed protocols for two key applications of ONT in parasitology.

Protocol 1: Metabarcoding for Multi-Parasite Detection

This protocol, adapted from a study that successfully detected 11 intestinal parasites, is ideal for broad-spectrum surveillance from complex samples like stool [9].

• Step 1: DNA Extraction and Quality Control

  • Extract genomic DNA from the sample (e.g., fecal material) using a robust kit like the Fast DNA SPIN Kit for Soil.
  • Quantify DNA concentration using a fluorometer (e.g., Quantus Fluorometer).

• Step 2: PCR Amplification of the 18S rRNA V9 Region

  • Primers: Use eukaryotic metabarcoding primers 1391F (5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG GTACACACCGCCCGTC-3′) and EukBR (5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG TGATCCTTCTGCAGGTTCACCTAC-3′), which include Illumina adapter overhangs [9].
  • Reaction Mix: KAPA HiFi HotStart ReadyMix, primers, and 3 µL of sample DNA.
  • Thermocycling: 95°C for 5 min; 30 cycles of 98°C for 30s, 55°C for 30s, 72°C for 30s; final extension at 72°C for 5 min. Note: Annealing temperature can be adjusted (40-70°C tested) to optimize read distribution among species [9].

• Step 3: Library Preparation and Sequencing (ONT)

  • Perform a limited-cycle PCR (8 cycles) to add ONT-compatible barcodes and adapters.
  • Pool barcoded amplicons and load onto a MinION flow cell (R9.4.1 or later).
  • Sequence for up to 48 hours, basecalling in real-time.

• Step 4: Bioinformatic Analysis

  • Demultiplex samples and trim adapters using tools like Cutadapt.
  • Perform quality filtering, denoising, and chimera removal using DADA2 within the QIIME2 environment [9].
  • Assign taxonomy by comparing Amplicon Sequence Variants to reference databases (e.g., NCBI nucleotide database).

Protocol 2: Targeted Sequencing for Drug Resistance and Virulence

This protocol, based on successful malaria surveillance, is designed for deep characterization of specific genomic loci in a parasite [12].

• Step 1: Selective Whole Genome Amplification (sWGA)

  • Start with DNA extracted from dried blood spots or other low-biomass samples.
  • Perform a reduced-volume sWGA using primers designed to selectively amplify the target parasite's genome (e.g., Plasmodium falciparum). This enriches parasite DNA from the background host DNA, saving approximately $4 per sample [12].

• Step 2: Multiplex PCR with a Custom Panel

  • Panel Design: Use software like multiply to design a multiplex PCR panel targeting genes of interest (e.g., drug-resistance genes, diagnostic antigen genes) with amplicons of 3-4 kbp to leverage long-read capabilities [12].
  • Amplification: Use PCR conditions with reduced annealing and extension temperatures to robustly amplify all targets in a single, multiplex reaction.

• Step 3: ONT Sequencing and Analysis

  • Barcode and pool amplicons using a cost-effective one-pot protocol [12].
  • Sequence on a MinION device.
  • Use real-time analysis software for variant calling (e.g., for single nucleotide polymorphisms linked to drug resistance) and to detect structural deletions (e.g., hrp2/3 deletions causing diagnostic test failure).

The Scientist's Toolkit: Essential Research Reagents and Materials

The successful implementation of the above protocols relies on a set of key reagents and tools.

Table 2: Essential Research Reagent Solutions for Parasite Sequencing

Item	Function	Example Use Case
Fast DNA SPIN Kit for Soil	Efficiently extracts DNA from complex, difficult-to-lyse samples like feces or parasite eggs.	DNA extraction from stool samples for intestinal parasite metabarcoding [9].
sWGA Primers	Set of short primers that bind preferentially to the target parasite genome, enriching it from host DNA.	Enriching Plasmodium falciparum DNA from human blood samples prior to targeted sequencing [12].
multiply Software	Open-source tool for flexibly designing multiplex PCR panels for user-defined genomic targets.	Designing the NOMADS8 and NOMADS16 panels for malaria surveillance [12].
ONT Barcoding Kits (e.g., Native Barcoding)	Allows for the pooling of multiple samples on a single flow cell, reducing per-sample cost.	Running multiple clinical samples or trios (e.g., for rare disease research) in a single sequencing run [13] [10].
QIIME 2 & DADA2	Bioinformatic pipelines for processing and analyzing metabarcoding data, including denoising and taxonomy assignment.	Analyzing 18S rRNA data to identify and relative abundance of multiple parasite species in a sample [9].
(S)-Licoisoflavone A	(S)-Licoisoflavone A, MF:C20H20O6, MW:356.4 g/mol	Chemical Reagent
cinchonain IIa	cinchonain IIa, MF:C39H32O15, MW:740.7 g/mol	Chemical Reagent

The evidence from recent, rigorous applications demonstrates that Oxford Nanopore sequencing is not merely an incremental improvement but a categorical disruptor in parasite genomics. While Sanger sequencing retains its value for high-throughput, targeted confirmation of known sequences, its utility is confined to a narrow scope of questions. ONT's capacity for untargeted pathogen discovery, comprehensive resistance profiling, and rapid turnaround directly addresses the most pressing challenges in modern parasitology: complex infections, evolving drug resistance, and the need for rapid diagnostic informatics. The transition from a single-gene to a whole-genome, metagenomic perspective, powered by long-read technologies, is redefining the frontiers of what is possible in parasite research and outbreak response.

This guide objectively compares the performance of Oxford Nanopore Technologies (ONT) and Sanger sequencing in the context of parasite research, focusing on the critical parameters of read length, throughput, and real-time data analysis.

Technology Comparison at a Glance

The following table summarizes the core performance differentiators between Oxford Nanopore and Sanger sequencing methodologies.

Feature	Oxford Nanopore Technologies	Sanger Sequencing
Read Length	Long-reads; single-molecule sequencing of entire plasmids or genomic fragments [14].	Short-reads; typically limited to < 1 kb per reaction [14].
Throughput	High-throughput; capable of processing multiple samples in a run, with services offering 24-hour turnaround [14] [15].	Low-throughput; one sample per reaction, limiting scalability [14].
Data Analysis	Real-time; basecalling and analysis occur during the sequencing run, enabling immediate insights [16] [17].	Post-process; analysis only begins after the entire sequencing run is complete.
Primary Strength	Resolving complex genomic structures (hairpins, repeats, GC-rich regions), detecting mixed infections, and identifying large structural variants [14] [18].	High accuracy for confirming known sequences or specific, targeted points.
Key Limitation	Higher raw error rate compared to Sanger, though sufficient coverage mitigates this for consensus accuracy [19] [20].	Inability to sequence through complex DNA structures and low sensitivity for heterogeneous samples [14].

Experimental Evidence in Parasite Research

The practical advantages of ONT translate into enhanced methodologies for specific parasite research applications.

Multiplexed Detection of Intestinal Parasites

Objective: To simultaneously detect and differentiate 11 species of intestinal parasites from a single sample using 18S rRNA metabarcoding [9]. Methodology: The 18S rDNA V9 region from 11 parasite species was cloned into plasmids. These plasmids were pooled, and the region was amplified and sequenced on an Illumina iSeq 100 platform (a short-read, high-throughput technology conceptually similar to ONT in throughput, but not read length). This study highlights the high-throughput paradigm that Sanger sequencing cannot achieve [9]. Key Outcome: All 11 parasite species were successfully detected in a single run, demonstrating the power of high-throughput sequencing for comprehensive screening. The number of reads for each species varied, influenced by factors like DNA secondary structure [9].

Targeted Surveillance of Drug Resistance in Malaria

Objective: To create an efficient workflow for molecular surveillance of Plasmodium falciparum, focusing on antimalarial drug resistance markers and vaccine targets [17]. Methodology: The DRAG2 (Drug Resistance + Antigen Multiplex PCR) assay uses a two-panel multiplex PCR to amplify specific genomic regions of interest. Amplicons are then sequenced using ONT [17]. Key Outcome: The nanopore-based workflow is low-cost (<$25/sample) and rapid (under 29 hours from DNA extraction to results), making it suitable for resource-limited settings. It accurately detects drug-resistance mutations and gene deletions, even from dried blood spots [18] [17]. The protocol's real-time nature allows for rapid analysis and decision-making.

Experimental Workflow Diagram

The typical workflow for a targeted sequencing experiment using ONT, such as the DRAG2 assay for malaria, can be visualized as follows:

Figure 1: Targeted ONT Workflow for Parasite Surveillance

The Scientist's Toolkit: Essential Research Reagents

The table below details key reagents and their functions in a typical ONT targeted sequencing experiment for parasites [15] [17].

Item	Function in the Experiment
Pathogen-Specific Primers	Designed to conserved genomic regions for multiplex PCR amplification of target genes from the parasite.
Universal Primers (16S/18S/ITS)	Amplify broad taxonomic targets for unbiased detection or species identification [15].
High-Fidelity DNA Polymerase	Ensures accurate amplification during PCR with minimal introduction of errors.
ONT Ligation Sequencing Kit	Prepares the amplified DNA library for sequencing by adding sequencing adapters.
ONT Native Barcoding Kit	Allows for sample multiplexing by adding unique barcodes to each sample's DNA, enabling pooled sequencing.
Synthetic Control Plasmids	Act as positive controls and internal standards to monitor assay performance and detect contamination [17].
Flow Cell (MinION/PromethION)	The consumable containing nanopores through which DNA is sequenced.
Reference Genome Database	A curated set of genomic sequences for bioinformatic alignment and variant calling.
cis-Emodin bianthrone	cis-Emodin bianthrone, MF:C30H22O8, MW:510.5 g/mol
Vitexdoin A	Vitexdoin A|For Research

For parasite research, the choice between Oxford Nanopore and Sanger sequencing is defined by the experimental goal. Sanger sequencing remains a reliable, low-cost method for validating specific known sequences. However, Oxford Nanopore Technologies provides a superior solution for applications requiring the resolution of complex genomic regions, high-throughput screening for multiple parasites or resistance markers, and rapid, real-time turnaround crucial for surveillance and outbreak response. Its long-read capability and real-time data analysis make it uniquely effective for comprehensive parasite characterization.

The accurate characterization of parasites is fundamental to disease control, drug development, and understanding transmission dynamics. For decades, Sanger sequencing has served as the gold standard for confirming single-gene mutations and validating results from other assays. Its high accuracy for targeted, short fragments makes it ideal for focused applications but limits its utility in complex genomic studies [21]. In contrast, Oxford Nanopore Technology (ONT) enables real-time, long-read sequencing that ranges from targeted amplicon analysis to complete telomere-to-telomere genome assembly [22] [23]. This guide objectively compares the performance of these technologies within parasitology research, providing experimental data to inform platform selection based on application requirements.

Technical Performance Comparison

The following table summarizes the core technical characteristics of Sanger sequencing and Oxford Nanopore sequencing, highlighting their distinct operational profiles.

Table 1: Technical and Operational Comparison of Sanger and Nanopore Sequencing

Feature	Sanger Sequencing	Oxford Nanopore Sequencing
Sequencing Principle	Dideoxy chain termination	Nanopore electrical signal modulation
Typical Read Length	400–900 base pairs [21]	Up to megabase scales (long reads) [22]
Single-Raw Read Accuracy	>99% [21]	>99% (with Q20+ chemistry) [22]
Typical Sensitivity (VAF)	15–20% [21]	<1% (for variant detection) [21] [3]
Key Strength	High accuracy for single, short targets; cost-effective for low throughput	Long reads, structural variant detection, real-time analysis, portability
Main Limitation	Low sensitivity for mixed infections; limited scalability	Higher initial DNA input may be required; computational demands

Application in Parasite Research: A Comparative Analysis

Resolving Complex Co-infections and Cryptic Diversity

The ability to resolve co-infections is critical in parasitology, particularly for understanding drug resistance and disease recurrence. Sanger sequencing struggles with polyclonal infections where the variant allele fraction (VAF) of a minority clone falls below its 15-20% detection threshold [21]. This can lead to missed co-infections and an inaccurate picture of parasite diversity.

Nanopore sequencing demonstrates a clear advantage in this domain. A study on avian haemosporidian parasites (Lophura swinhoii) used ONT to successfully resolve cryptic co-infections that presented ambiguities with Sanger sequencing. The long reads enabled unfragmented mitogenome assembly, allowing phylogenetic reconstruction that identified two novel Haemoproteus lineages and one Plasmodium lineage within the same host [24]. This application highlights ONT's power in detecting co-infecting parasites and advancing parasite taxonomy through integrated genomics and morphology.

Distinguishing Parasite Recrudescence from New Infection

The following case study and workflow illustrate the application of Nanopore sequencing in a critical clinical trial context.

Table 2: Performance of a Nanopore Amplicon Sequencing Assay for P. falciparum Genotyping [3]

Performance Metric	Result
Sensitivity for Minority Clones	Detected as low as 1:100:100:100 (Minority:Majority ratio)
Specificity (False Positive Haplotypes)	< 0.01%
Reproducibility (Intra-assay)	98%
Reproducibility (Inter-assay)	97%
Genetic Diversity of Markers	Highest for cpmp (HE=0.99; 28 unique haplotypes)
Concordance in Paired Sample Classification	85% (17/20 cases)

In therapeutic efficacy studies for malaria, determining whether a recurrent Plasmodium falciparum infection is a recrudescence (treatment failure) or a new infection is essential for accurate drug efficacy estimates [3]. A multiplexed nanopore amplicon sequencing (AmpSeq) assay targeting six highly polymorphic microhaplotype loci was developed for this purpose. The assay demonstrated high sensitivity and specificity in detecting minority clones in polyclonal infections, a scenario where Sanger sequencing provides limited resolution [3]. The workflow, from sample to result, can be completed rapidly, showcasing ONT's utility in near real-time surveillance and genotyping.

Genomic Surveillance and Large-Scale Variation Analysis

For comprehensive genomic surveillance—tracking drug resistance, diagnosing test evasion, and understanding population dynamics—Sanger sequencing is impractical due to its targeted, low-throughput nature.

Oxford Nanopore sequencing is increasingly deployed for this purpose, especially in resource-limited settings. A continental-scale surveillance program in Africa successfully used ONT to sequence over 1,000 P. falciparum dried blood spots. The protocol was low-cost (<$25/sample) and rapid (under 29 hours), accurately detecting drug-resistance mutations and hrp2/3 gene deletions associated with diagnostic test evasion [18]. Furthermore, ONT's long reads excel at resolving structural variants (SVs) and complex genomic regions often missed by short-read methods. One study found that long-read sequencing identified 2.86 times more SVs than Illumina short-read sequencing, excelling at detecting large variants (>6 kb) [25]. This capability is vital for uncovering the full spectrum of genomic changes in parasites.

Experimental Protocols

This protocol is designed for genotyping P. falciparum to distinguish recrudescence from new infection.

• Sample Preparation: Extract DNA from whole blood or dried blood spots (DBS).
• Multiplex PCR: Amplify six polymorphic microhaplotype loci (ama1, celtos, cpmp, cpp, csp, surfin1.1) in a single reaction. Use optimized primer pools and cycling conditions for uniform coverage.
• Library Preparation: Use the Native Barcoding Kit 96 V14 (SQK-NBD114.96) following the manufacturer's instructions. Pool barcoded samples for multiplexed sequencing.
• Sequencing: Load the library onto a MinION Mk1C platform with an R10.4.1 flow cell. Sequence until a target depth of ~150,000 reads per sample is reached.
• Bioinformatic Analysis:
  • Basecalling & Demultiplexing: Use Dorado (v0.8.2) for simplex basecalling with the sup model, minimum Q-score of 20.
  • Alignment & Variant Calling: Map reads to a reference genome and use a custom haplotype inference workflow with rigorous cutoff criteria to identify minority clones.

This protocol is used for resolving co-infections and phylogenetic analysis.

• Sample Source: Begin with blood samples from the avian host (Lophura swinhoii).
• Microscopy & DNA Extraction: Prepare blood smears for morphological observation. Extract genomic DNA from the blood.
• Long-Range PCR & Sequencing: Perform long-range PCR to amplify target genomic regions. Prepare the library using ONT kits (e.g., Ligation Sequencing Kit). Sequence on a GridION or PromethION platform using R9.4.1 or later flow cells.
• Genome Assembly & Analysis:
  • Basecalling: Perform basecalling in high-accuracy mode using MinKNOW or Dorado.
  • Assembly: Assemble unfragmented mitogenomes from long reads using a assembler like Flye or Canu.
  • Phylogenetics: Annotate mitochondrial genes and perform multiple sequence alignment. Construct a phylogenetic tree (e.g., Maximum-Likelihood method) to place novel lineages within known clades.

Essential Research Reagent Solutions

The following table lists key reagents and their functions for setting up the featured nanopore sequencing experiments.

Table 3: Key Research Reagents for Featured Nanopore Sequencing Protocols

Reagent / Kit	Function / Application
Native Barcoding Kit 96 V14 (SQK-NBD114.96)	Allows multiplexing of up to 96 samples by adding unique barcodes to each during library prep [3].
Ligation Sequencing Kit V14	Standard kit for preparing genomic DNA libraries for sequencing on Nanopore flow cells [22].
R10.4.1 Flow Cell	Nanopore flow cell version with improved accuracy for basecalling and modification detection [22] [3].
Dorado Basecaller	Software for converting raw electrical signal data into nucleotide sequences; offers Fast, HAC, and SUP (super-accurate) models [22].
MinKNOW Software	The operational software for Oxford Nanopore devices, controlling sequencing runs, and performing real-time analysis [3].

The choice between Sanger and Nanopore sequencing is not a matter of superior technology, but of appropriate application. Sanger sequencing remains a reliable, cost-effective choice for high-throughput validation of known, single-gene variants where high VAF is expected, such as confirming a known drug-resistance SNP.

However, Oxford Nanopore sequencing provides a transformative toolset for modern parasitology. Its capacity to resolve complex co-infections, detect low-frequency variants, characterize structural variations, and enable rapid, portable genomic surveillance makes it uniquely suited for everything from detailed taxonomic studies to large-scale public health interventions. As protocols become more standardized and cost-effective, ONT is poised to become an indispensable technology for advancing our understanding and management of parasitic diseases.

Applied Workflows: Deploying Sanger and Nanopore in Parasite Research and Surveillance

Rapid Multiplexed Amplicon Sequencing (AmpSeq) for High-Throughput Genotyping

The efficacy of antimalarial drugs is critically dependent on the ability to distinguish between recrudescent (treatment-failed) and new malaria infections, a process known as molecular correction or PCR-correction [3]. For years, Sanger sequencing has served as a foundational technology for genotyping pathogens. However, in the context of complex, polyclonal parasitic infections, its utility is limited—it typically detects only the majority clone in a sample and struggles with the high-throughput needs of modern drug efficacy trials [3]. The emergence and spread of artemisinin-resistant Plasmodium falciparum parasites has intensified the need for more powerful and scalable genotyping solutions [3].

Rapid Multiplexed Amplicon Sequencing (AmpSeq) represents a significant evolution in genotyping technology. By using multiplex PCR to simultaneously amplify dozens to hundreds of targeted genetic loci, followed by high-throughput sequencing, AmpSeq enables the detailed characterization of complex parasite populations [26] [27]. When implemented on Oxford Nanopore Technology (ONT) platforms, this approach offers a paradigm shift. ONT offers a unique combination of long-read capabilities, portability, rapid turnaround times, and scalability that is particularly suited for deployment in resource-limited, malaria-endemic settings [3] [5]. This guide provides a detailed, data-driven comparison of the performance of AmpSeq, with a focus on Oxford Nanopore, against traditional Sanger sequencing for parasite genotyping in drug development research.

Performance Comparison: AmpSeq vs. Sanger Sequencing

The transition from Sanger sequencing to AmpSeq, particularly on nanopore platforms, brings transformative improvements in detecting complex infections and quantitative accuracy. Key performance differences are summarized in the table below.

Table 1: Performance Comparison of Sanger Sequencing and AmpSeq for Parasite Genotyping

Performance Metric	Sanger Sequencing	Multiplexed AmpSeq (Oxford Nanopore)
Detection of Minor Clones	Limited to majority clone	High sensitivity; detects minority clones at frequencies as low as 0.01% (1:100 ratio) [3]
Throughput & Multiplexing	Low; typically one sample and one locus per reaction	High; can genotype hundreds of samples and dozens of loci simultaneously [3] [27]
Turnaround Time	Days, including capillary electrophoresis	Hours from library preparation to results; sequencing itself can be as short as 10 minutes for some applications [3] [28]
Quantitative Accuracy	Poor; not quantitative for mixed infections	High; allele frequencies correlate well with expected ratios in controlled mixtures [3] [26]
Data Richness	Single haplotype per reaction	Polyallelic microhaplotypes providing high-resolution strain discrimination [3] [27]
Portability & Deployment	Requires lab infrastructure; not field-deployable	Suitable for field deployment; MinION is a portable, USB-powered device [5]

Quantitative Superiority in Detecting Complex Infections

AmpSeq's most significant advantage is its ability to detect multiple parasite strains within a single infection, known as complexity of infection (COI). A 2025 study demonstrated that a nanopore AmpSeq assay targeting six microhaplotype loci exhibited exceptional sensitivity in detecting minority clones in polyclonal laboratory mixtures, reliably identifying strains present at a ratio of 1:100:100:100 [3]. This translates to detecting a clone representing just 0.01% of the population, a feat impossible with Sanger sequencing. The same assay demonstrated high specificity, with false-positive haplotypes occurring at a rate of less than 0.01% [3].

High Concordance with Established Methods

The accuracy of AmpSeq is not achieved at the expense of reliability. In a comparative evaluation, a nanopore AmpSeq assay successfully distinguished between recrudescence and new infections in 85% (17/20) of paired patient samples, a critical task in therapeutic efficacy studies [3]. Furthermore, a study using a different AmpSeq panel, Pf-SMARRT, reported strong concordance for antimalarial resistance mutations when compared to an established Molecular Inversion Probe (MIP) sequencing method [26]. These results confirm that AmpSeq data is robust enough for primary analysis in clinical research.

Experimental Protocols for AmpSeq Workflow

A standardized, optimized wet-lab and computational protocol is essential for generating high-quality, reproducible AmpSeq data. The following section details a proven workflow for parasite genotyping using Oxford Nanopore technology.

Wet-Lab Protocol: From Sample to Sequencer

The following diagram illustrates the streamlined AmpSeq laboratory workflow.

Step 1: DNA Extraction. Genomic DNA is extracted from patient samples, such as dried blood spots or whole blood, using standard commercial kits. For Plasmodium, the initial sample often contains a high proportion of human DNA, which can be addressed with selective whole-genome amplification or, in the case of ONT, adaptive sampling during sequencing [5] [26].

Step 2: Multiplex PCR Amplification. This is the core of the AmpSeq assay. Two consecutive multiplex PCR reactions are typically performed:

• Primary Multiplex PCR: A single reaction containing multiple primer pairs (e.g., a pool of 24 primers for the Pf-SMARRT panel) is used to amplify all target loci simultaneously from the genomic DNA template [26]. This step requires careful optimization of primer concentrations and reaction conditions to ensure uniform amplification across all targets [3].
• Secondary Indexing PCR: A second PCR is performed to attach unique barcode sequences to the amplicons from each sample. This enables the pooling (multiplexing) of hundreds of samples into a single sequencing library [3] [26].

Step 3: Library Preparation & Sequencing. The barcoded amplicons are pooled, and the final sequencing library is prepared using a kit such as the ONT Native Barcoding Kit. The library is loaded onto a flow cell (e.g., R10.4.1) and sequenced on a MinION Mk1C device. Sequencing is often stopped once a target depth of approximately 25,000 reads per marker per sample is achieved [3].

Bioinformatics Protocol: From Raw Data to Genotypes

The computational analysis of AmpSeq data is a critical component of the workflow. A robust, open-source pipeline ensures accurate haplotype calling.

Table 2: Key Steps in the AmpSeq Bioinformatics Pipeline [3] [29]

Step	Tool/Software	Function and Key Parameters
Basecalling & Demultiplexing	Dorado (v0.8.2)	Converts raw electrical signals to nucleotide sequences (FASTQ) and assigns reads to samples based on barcodes. Uses a super-accurate (sup) model with a minimum Q-score of 20 (≥99% accuracy).
Read Filtering & Trimming	Trimmomatic, Porechop	Removes low-quality sequences, adapter contamination, and primer sequences from the ends of reads.
Alignment & Variant Calling	BWA, SAMtools	Maps filtered reads to a reference genome (e.g., P. falciparum 3D7). SAMtools is used to sort, index, and call sequence variants.
Haplotype Inference	Custom scripts (e.g., in R/Python)	A critical step for polyclonal infections. Uses population genetic models and rigorous cutoff criteria (e.g., based on read depth and allele frequency) to infer distinct haplotypes, including minority clones.

The Scientist's Toolkit: Essential Research Reagents & Materials

Successful implementation of an AmpSeq assay relies on a carefully selected set of reagents and materials. The following table catalogs the key components required.

Table 3: Essential Research Reagents and Materials for AmpSeq

Item	Function	Example Products / Notes
Multiplex PCR Assay	Targets specific genomic loci for amplification.	Custom-designed panels (e.g., 6-plex microhaplotypes [3], 24-plex Pf-SMARRT [26]); primers must be optimized for concentration and compatibility.
DNA Polymerase	Amplifies target regions in multiplex PCR.	Must be a high-fidelity, multiplex-capable enzyme (e.g., Q5 Hot Start High-Fidelity from NEB). Non-proprietary reagents are recommended for cost-effectiveness and accessibility [26].
Oxford Nanopore Kit	Prepares amplicons for sequencing.	Native Barcoding Kit 96 V14 (SQK-NBD114.96) [3]. Includes barcodes and sequencing adapters.
Sequencing Device	Generates nucleotide sequence data.	MinION Mk1C; a portable, real-time sequencer ideal for field deployment [3] [5].
Flow Cell	The consumable containing nanopores.	R10.4.1 flow cells; the latest chemistry offers improved basecalling accuracy, especially in homopolymer regions [3].
Bioinformatics Pipeline	Analyzes raw sequencing data to produce genotypes.	Open-source pipelines like Dorado for basecalling and custom scripts for haplotype inference [3]. The BiosearchCaller pipeline is another license-free option [30].
Celangulatin D	Celangulatin D, MF:C31H36O15, MW:648.6 g/mol	Chemical Reagent
Typhatifolin B	Typhatifolin B, MF:C34H32O5, MW:520.6 g/mol	Chemical Reagent

The evidence from recent studies firmly establishes Rapid Multiplexed Amplicon Sequencing on Oxford Nanopore platforms as a superior genotyping tool compared to Sanger sequencing for parasite research and drug development. The transition is not merely incremental but transformative, enabling researchers to move from a limited, single-clone view to a comprehensive, population-level understanding of parasitic infections.

The key takeaways for researchers are:

• Unmatched Sensitivity: AmpSeq on ONT can detect minority parasite clones at frequencies as low as 0.01%, crucial for accurately identifying recrudescence in drug trials and understanding complex infection dynamics [3].
• Operational Efficiency: The technology offers a rapid, high-throughput, and potentially field-deployable solution that can significantly accelerate the timeline from sample collection to actionable data, a critical factor in public health responses to drug resistance [3] [5].
• Proven Reliability: AmpSeq assays demonstrate high concordance with established genotyping methods and robust reproducibility, giving confidence in the data for making critical decisions in antimalarial drug efficacy monitoring [3] [26].

For the research community focused on combating parasitic diseases, adopting Oxford Nanopore-based AmpSeq represents a strategic advancement. It provides the resolution, scale, and speed necessary to track drug resistance with unprecedented precision and to ultimately inform more effective malaria control and elimination strategies.

Resolving Complex Co-infections and Cryptic Species with Unfragmented Long Reads

The study of parasitic organisms presents a unique set of genomic challenges, including the frequent occurrence of complex co-infections with morphologically similar species and the presence of cryptic species diversity that eludes traditional detection methods. For decades, Sanger sequencing has served as the gold standard for genetic characterization in parasitology, providing highly accurate data for single targets but struggling with mixed infections and requiring prior knowledge of potential pathogens. The emergence of Oxford Nanopore Technology (ONT) with its capacity to generate unfragmented long reads represents a transformative advancement, enabling researchers to resolve complex parasitic communities with unprecedented clarity. This technological shift is particularly crucial for understanding parasite epidemiology, drug resistance mechanisms, and transmission dynamics, where accurate detection of all circulating species and strains directly impacts disease management strategies and treatment outcomes.

The fundamental limitation of Sanger sequencing in detecting co-infections stems from its inability to resolve mixed templates in a single reaction. When multiple parasite species or genotypes are present in a sample, Sanger sequencing produces ambiguous chromatograms with overlapping signals, making interpretation difficult or impossible. While next-generation sequencing (NGS) platforms offered some solutions through clonal amplification, their short read lengths often fail to resolve complex genomic regions or provide complete haplotype information. In contrast, long-read sequencing technologies like ONT generate reads spanning thousands of bases, enabling unambiguous resolution of multiple pathogens simultaneously and providing complete genetic information for individual organisms within a mixed infection.

Performance Comparison: Sanger Sequencing vs. Oxford Nanopore

Extensive comparative studies across various parasitic systems have quantified the performance differences between these technologies. The table below summarizes key performance metrics relevant to parasite research:

Table 1: Overall Performance Metrics for Parasite Genomics

Parameter	Sanger Sequencing	Oxford Nanopore
Single-Read Accuracy	>99% [21]	>99% (after basecalling improvements) [21]
Maximum Read Length	400-900 base pairs [21]	Up to megabase scales [21]
Sensitivity (Variant Detection)	15-20% [21]	<1% [21]
Turnaround Time (Total)	3-4 days [21]	2-3 days (can be <24 hours for urgent cases) [21]
Co-infection Resolution	Limited; produces mixed chromatograms [31]	Excellent; resolves multiple species simultaneously [24] [32]
Cryptic Species Detection	Requires prior knowledge and separate assays	Can discover novel species through full-length gene analysis [32]

The application-specific performance reveals even more striking advantages for complex parasitological investigations:

Table 2: Application-Specific Performance in Parasite Research

Parasite/Application	Sanger Sequencing Performance	Oxford Nanopore Performance	Evidence
Avian Haemosporidians	Missed cryptic co-infections; ambiguous results for multiple infections	Resolved three mitochondrial lineages in a single host; identified novel Haemoproteus and Plasmodium lineages [24]	Study of Swinhoe's pheasant co-infections [24]
Cryptosporidium Genotyping	Showed mixed chromatograms for python samples; missed 18S rRNA Type B sequences in C. parvum isolates	Clearly identified C. muris and mixed C. muris/C. tyzzeri infections; detected 18S rRNA Type B in 4/6 C. parvum isolates [31]	Comparison at 18S rRNA and actin loci [31]
Filarial Worm Detection	Limited ability to detect coinfections and novel pathogens	Identified >15% more mono- and coinfections; detected full spectrum of filarioids from diverse genera [33]	Canine blood sample analysis [33]
Plasmodium from Blood Samples	Required human DNA depletion or parasite enrichment	3-5× enrichment of P. falciparum DNA directly from blood; eliminated need for pre-processing [34]	Adaptive sampling on unenriched patient blood [34]
Blastocystis Subtyping	Challenging for mixed subtypes; requires cloning	Successfully generated full-length SSU rRNA sequences from mixed ST10/ST14 infection [35]	Validation using cultured and fecal isolates [35]

Experimental Evidence and Workflows

Resolving Cryptic Co-infections in Avian Haemosporidians

A compelling demonstration of long-read sequencing's advantage comes from research on avian haemosporidian parasites, where traditional methods frequently failed to resolve complex infections. In a study of Swinhoe's pheasant (Lophura swinhoii), researchers employed ONT to resolve co-infections that had proven challenging with conventional approaches [24].

Experimental Protocol:

• Sample Collection: Blood samples were obtained from host birds
• Morphological Analysis: Blood smears were examined, revealing two distinct gametocyte forms: roundish and circumnuclear
• Molecular Analysis: Long-read sequencing was performed using Oxford Nanopore Technologies
• Mitogenome Assembly: Unfragmented mitochondrial genomes were assembled from sequencing data
• Phylogenetic Reconstruction: Relationships between parasite lineages were determined through phylogenetic analysis

The implementation of this workflow resolved three separate mitochondrial lineages from what initially appeared to be a simple infection: two novel Haemoproteus lineages (hLOPSWI01 and hLOPSWI02) and one Plasmodium lineage (pNILSUN01) [24]. Phylogenetic reconstruction placed the Haemoproteus lineages within the Parahaemoproteus clade, while the Plasmodium lineage clustered in the Giovannolaia-Haemamoeba clade. This study highlighted the efficacy of unfragmented long reads in resolving cryptic co-infections through comprehensive mitogenome assembly, successfully overcoming the ambiguities inherent to Sanger sequencing and providing a more accurate representation of parasite diversity in understudied avian hosts [24].

Adaptive Sampling for Plasmodium Detection in Human Blood

The detection of Plasmodium parasites in human blood samples presents a particular challenge due to the overwhelming predominance of human DNA. Traditional methods require time-consuming laboratory procedures to deplete human DNA or enrich parasite DNA, adding complexity and cost to genomic surveillance of malaria. Researchers have investigated the potential of nanopore adaptive sampling to enrich Plasmodium falciparum reads during sequencing of unenriched patient blood samples [34].

Experimental Protocol:

• Sample Preparation: Blood samples with varying levels of parasitemia (0%-84% P. falciparum DNA in human DNA) were prepared
• Sequencing Setup: Half of the MinION flow cell channels were run in adaptive sampling mode, enriching for the P. falciparum reference genome
• Comparison: Regular sequencing was performed simultaneously on other channels as a control
• Validation: 38 drug resistance loci were compared to Sanger sequencing results for concordance

The results demonstrated a three- to five-fold enrichment of P. falciparum bases in samples containing 0.1%-8.4% P. falciparum DNA [34]. When applied to patient blood samples with common parasitemia levels (0.1%, 0.2%, and 0.6%), the estimated enrichment was 5.8, 3.9, and 2.7, respectively. This enrichment was sufficient to cover at least 97% of the P. falciparum reference genome at a median depth of 5 (for the lowest parasitemia) or 355 (for the highest parasitemia) [34]. Most importantly, comparison of 38 drug resistance loci with Sanger sequencing results showed high concordance, suggesting the obtained sequencing data were of sufficient quality to address common clinical research questions for patients with parasitemias of 0.1% and higher.

Figure 1: Comparative Workflows for Parasite Detection. The simplified Sanger workflow requires extensive sample preprocessing and produces ambiguous results for co-infections, while Nanopore sequencing minimizes preprocessing and clearly resolves multiple species.

Full-Length Gene Sequencing for Cryptic Species Detection

The resolution of cryptic species—genetically distinct but morphologically identical organisms—represents another area where long-read technologies provide substantial advantages. Traditional barcoding approaches that rely on short genomic segments may miss subtle but evolutionarily significant genetic differences between parasite lineages.

In a study on North American owls, researchers utilized PacBio HiFi long-read sequencing (a technology with similar advantages to ONT for this application) to characterize haemosporidian infections [32]. The experimental approach involved:

Experimental Protocol:

• Sample Collection: 53 owl individuals from six species were obtained from rehabilitation centers
• Screening: All samples were screened using polymerase chain reaction; available blood smears were examined microscopically
• Sequencing: Parasite mitochondrial genomes were obtained using a long-read sequencing method
• Analysis: Relationships between parasite lineages were estimated using phylogenetic and haplotype network methods

This long-read approach enabled the detection of mixed infections in a single host and revealed that all cytochrome b lineages from previously identified Haemoproteus syrnii—based on erythrocytic stages—were not monophyletic, indicating the existence of an undescribed species [32]. Similarly, research on Blastocystis subtypes demonstrated that ONT MinION sequencing could generate high-quality full-length SSU rRNA gene sequences directly from fecal specimens, successfully resolving a mixed ST10/ST14 infection that would have been challenging to characterize with Sanger sequencing [35].

Table 3: Key Research Reagent Solutions for Long-Read Parasite Genomics

Reagent/Kit	Application	Function	Evidence
SQK-LSK114 Ligation Sequencing Kit	Library preparation for direct cDNA sequencing	Facilitates PCR-free library construction minimizing bias in transcript representation	Yersinia pestis transcriptomics [36]
SQK-NBD114.24 Native Barcoding Kit	Multiplexing of samples	Allows simultaneous sequencing of up to 24 samples, significantly reducing costs	Bacterial transcriptomic workflow [36]
SQK-LSK109 1D Ligation Sequencing Kit	Amplicon sequencing	Optimized for sequencing full-length PCR amplicons like the Blastocystis SSU rRNA gene	Blastocystis subtyping research [35]
R9.4 or R10.4 Flow Cells	All nanopore sequencing	Pores with different characteristics; R10 improves accuracy in homopolymer regions	Multiple applications [36] [35]
KAPA HiFi HotStart ReadyMix	High-fidelity PCR amplification	Proofreading polymerase for accurate amplification of long targets	Blastocystis full-length SSU rRNA amplification [35]
MICROBExpress Kit (Ambion)	Ribosomal RNA depletion	Removes ~95% of 16S and 23S rRNA, enriching mRNA content	Bacterial transcriptomics [36]

The evidence from multiple studies across diverse parasitic systems demonstrates that Oxford Nanopore sequencing provides substantial advantages over Sanger sequencing for resolving complex co-infections and detecting cryptic species. The capacity to generate unfragmented long reads enables researchers to obtain complete haplotype information, resolve multiple infections unambiguously, and discover novel pathogen diversity that would escape detection with traditional methods. While Sanger sequencing maintains utility for targeted analysis of single infections, its limitations in mixed infections and requirement for prior knowledge of targets make it increasingly unsuitable for comprehensive parasite surveillance.

The implementation of adaptive sampling for Plasmodium detection directly from blood samples represents a particularly significant advancement, potentially eliminating the need for time-consuming laboratory pre-processing and accelerating the timeline from sample collection to results [34]. Similarly, the application of long-read metabarcoding for filarial worm detection demonstrates how this technology can reveal a broader spectrum of pathogens in a single assay [33]. As these technologies continue to evolve with improving accuracy and decreasing costs, long-read sequencing is poised to become the new gold standard for parasite genomics, particularly in applications requiring comprehensive detection of complex parasitic communities and resolution of cryptic diversity.

Comprehensive Genomic Surveillance of Drug Resistance Markers

The relentless evolution of drug-resistant parasites poses a significant threat to global disease control efforts, making genomic surveillance an indispensable tool for public health. Traditional Sanger sequencing has long served as the benchmark for detecting genetic variants associated with drug resistance. However, the emergence of Oxford Nanopore sequencing represents a transformative advancement, offering real-time, portable genomic analysis that is particularly valuable for parasite research in resource-limited settings. This technology enables comprehensive surveillance of resistance markers, providing researchers and public health officials with critical data to inform treatment policies and containment strategies.

The efficacy of Oxford Nanopore versus Sanger sequencing for parasites research represents a pivotal consideration for laboratories worldwide. As parasitic diseases like malaria, schistosomiasis, and Chagas disease continue to affect millions, primarily in tropical and subtropical regions, the choice of sequencing technology directly impacts the speed, accuracy, and depth of resistance monitoring. This comparison guide objectively evaluates the performance characteristics of both platforms to assist researchers, scientists, and drug development professionals in selecting appropriate methodologies for their surveillance needs.

Performance Comparison: Oxford Nanopore vs. Sanger Sequencing

Direct comparative studies demonstrate significant differences in technical capabilities between Oxford Nanopore and Sanger sequencing technologies. The table below summarizes key performance metrics relevant to parasite surveillance applications.

Table 1: Performance comparison between Sanger and Oxford Nanopore sequencing technologies

Parameter	Sanger Sequencing	Oxford Nanopore Sequencing
Sequencing Method	Dideoxynucleotide chain termination	Nanopore-based electronic signal detection
Single-Read Accuracy	>99% [21]	>99% (latest chemistry) [21] [37]
Read Length	400-900 base pairs [21]	Up to megabase ranges [21]
Sensitivity (Variant Detection)	15-20% [21]	<1% [21]
Error Rate	0.001% [21]	~5% (areas of ongoing improvement) [21]
Turnaround Time	3-4 days [21]	2-3 days (can be <24 hours for urgent cases) [21]
Applications	SNVs and INDELs detection [21]	SNVs, INDELs, complex structural variations [21]
Real-time Analysis	Not available	Available [21]

The data reveals that Oxford Nanopore technologies offer substantial advantages in read length, sensitivity, and turnaround time, while Sanger sequencing maintains an edge in raw accuracy. For surveillance programs requiring detection of low-frequency variants or complex genomic rearrangements, Nanopore's enhanced sensitivity (<1% versus 15-20%) enables identification of emerging resistance mutations that might be missed by Sanger methods [21]. This capability is particularly valuable for monitoring heterogenous parasite populations where resistant subpopulations may initially present at low frequencies.

The portability and flexibility of Nanopore devices like MinION provide additional strategic advantages for field deployment and outbreak investigations. Studies have successfully implemented complete workflows in endemic countries for malaria surveillance, demonstrating the practical utility of this technology in resource-limited settings [37] [18]. The ability to perform sequencing with minimal infrastructure requirements represents a significant advancement over traditional methods that often require sample shipment to centralized laboratories, potentially delaying critical public health responses.

Applications in Parasitic Disease Surveillance

Malaria

Genomic surveillance of Plasmodium falciparum has emerged as a critical application for both Sanger and Nanopore sequencing technologies. Research in Ghana demonstrated that Nanopore sequencing could accurately detect antimalarial resistance markers and vaccine target variations directly from dried blood spot samples, providing a low-cost, portable solution for endemic regions [37]. The workflow successfully monitored mutations in genes including crt, dhfr, dhps, mdr1, and kelch13, with the latter being particularly crucial for monitoring artemisinin resistance emergence.

A recent study in Rwanda utilizing both Oxford Nanopore and Sanger methods analyzed 250 clinical P. falciparum isolates, revealing a high prevalence of resistance-associated mutations [38]. The research identified pfkelch13 mutations in 50.4% of isolates, including validated R561H (25.6%) and candidate P441L mutations, with Nanopore sequencing enabling comprehensive haplotype analysis. The persistence of pfcrt 76T mutations (26%) despite chloroquine withdrawal highlights the value of ongoing genomic surveillance for understanding parasite population dynamics [38].

Table 2: Malaria drug resistance markers detected by genomic surveillance

Gene	Associated Drug Resistance	Key Mutations	Detection Method
pfcrt	Chloroquine	K76T [38]	Sanger, Nanopore [38]
pfmdr1	Lumefantrine, mefloquine	N86Y, Y184F [38]	Sanger, Nanopore [38]
pfdhfr	Pyrimethamine	N51I, C59R, S108N [38]	Sanger, Nanopore [38]
pfdhps	Sulfadoxine	A437G, K540E [38]	Sanger, Nanopore [38]
kelch13	Artemisinin	R561H, A675V, P441L [38]	Sanger, Nanopore [38]

Schistosomiasis and Other Helminth Infections

Research on Schistosoma mansoni has evaluated the Nanopore adaptive sampling feature for selectively enriching parasite DNA from contaminated larval samples [39]. This approach aimed to overcome challenges associated with environmental contamination in miracidia samples preserved on FTA cards, though results indicated that physical washing steps remained necessary for effective DNA purification [39]. The study highlighted both the potential and current limitations of computational enrichment strategies for complex sample types.

For parasites with highly repetitive genomes like Trypanosoma cruzi (causative agent of Chagas disease), Nanopore sequencing has demonstrated unique advantages over short-read technologies [40]. The long-read capability enabled researchers to resolve complex genomic regions, including multi-copy gene families and transposable elements, which are challenging for conventional methods [40]. This advancement provides new opportunities to understand genomic diversity and its relationship to variable clinical presentations in Chagas disease.

Comparative Sensitivity Studies

A comprehensive comparison between next-generation sequencing (including Nanopore technologies) and Sanger sequencing for HIV drug resistance testing revealed important insights relevant to parasite surveillance. The study demonstrated that NGS exhibited superior sensitivity for detecting low-abundance drug-resistant variants compared to Sanger sequencing, with 87.0% sensitivity at a 5% detection threshold [41]. This enhanced sensitivity is particularly valuable for identifying emerging resistance patterns in heterogeneous pathogen populations before they become dominant.

The consistency between NGS and Sanger varied by drug class, with NGS showing >90% consistency for protease inhibitors and integrase inhibitors but lower consistency (61.25-87.50%) for nucleotide reverse transcriptase inhibitors [41]. These findings highlight the importance of validating sequencing approaches for specific genetic targets and resistance mechanisms, as performance characteristics may vary depending on the genomic context and mutation type.

Experimental Protocols and Methodologies

Targeted Amplicon Sequencing for Malaria Surveillance

The following workflow illustrates a generalized protocol for targeted sequencing of drug resistance markers in Plasmodium falciparum:

Diagram 1: Workflow for genomic surveillance of drug resistance markers

The experimental protocol begins with sample collection and DNA extraction. For malaria surveillance, this typically involves peripheral blood or dried blood spot samples from infected individuals [37] [38]. Extraction methods must be optimized for the specific sample type and expected parasite DNA concentration, which can vary significantly depending on parasitemia levels.

For targeted amplification, researchers typically employ multiplex PCR approaches to simultaneously amplify key resistance genes. In the Rwandan malaria study, four P. falciparum genes (crt, mdr1, dhfr, and dhps) were amplified using multiplex PCR, while kelch13 was amplified separately due to its larger size and importance for artemisinin resistance monitoring [38]. Primer design follows established protocols with modifications as needed for specific sequencing platforms.

Library preparation differs significantly between platforms. For Sanger sequencing, purified PCR products are typically prepared using chain termination methods with fluorescently labeled dideoxynucleotides. For Nanopore sequencing, libraries are prepared using ligation-based approaches with native barcoding kits (e.g., SQK-NBD114.24) that enable sample multiplexing [38]. The prepared libraries are then sequenced on appropriate devices—capillary electrophoresis systems for Sanger or MinION/Flongle flow cells for Nanopore.

Bioinformatic analysis represents a critical differentiator between the technologies. For Nanopore sequencing, basecalling and barcoding are performed using integrated software (e.g., Guppy within MinKNOW) with minimum quality score filters [38]. Reads are then mapped to reference genomes using aligners like Minimap2, followed by variant calling and resistance annotation using established pipelines. The real-time analysis capability of Nanopore sequencing enables preliminary results to be generated even while sequencing is ongoing, potentially accelerating the surveillance process.

Whole Genome Sequencing for Complex Parasites

For parasites with complex genomic architectures like Trypanosoma cruzi, long-read Nanopore sequencing enables assembly of challenging regions that are difficult to resolve with short-read technologies [40]. The protocol involves high-molecular-weight DNA extraction, library preparation with ligation sequencing kits, and sequencing across multiple flow cells (e.g., R9.4.1 and R10.4.1) to generate sufficient coverage. Duplex reading mode can be employed to achieve very high accuracy results through template-complement consensus [40].

Genome assembly is performed using specialized tools like NextDenovo, with subsequent annotation of multi-gene families, transposable elements, and structural variants [40]. This approach has revealed insights into genome diversification mechanisms in T. cruzi, including the role of transposable elements in driving genetic variation through homologous recombination near multi-copy gene families.

Essential Research Reagent Solutions

Successful implementation of genomic surveillance programs requires specific reagents and materials optimized for the target parasites and sequencing platforms. The following table details key research solutions employed in the cited studies:

Table 3: Essential research reagents for genomic surveillance of parasite drug resistance

Reagent Category	Specific Examples	Function & Application	Technology Compatibility
DNA Extraction Kits	Maxwell RSC Whole Blood DNA Kit [38]	Isolation of high-quality genomic DNA from blood samples	Sanger, Nanopore
PCR Master Mixes	GoTaq Hot Start Green Master Mix [38]	Amplification of target resistance genes with high fidelity	Sanger, Nanopore
Library Preparation Kits	Ligation Sequencing Amplicons - Native Barcoding Kit (SQK-NBD114.24) [38]	Preparation of multiplexed libraries for sequencing	Nanopore
Sequencing Flow Cells	Flongle Flow Cells (R10.4.1) [38]	Miniaturized format for cost-effective targeted sequencing	Nanopore
DNA Preservation Solutions	DNA/RNA Shield [38]	Stabilization of nucleic acids during sample storage and transport	Sanger, Nanopore
PCR Clean-up Systems	Wizard SV Gel and PCR Clean-Up System [38]	Purification of amplification products prior to sequencing	Sanger, Nanopore

The selection of appropriate DNA extraction methods is critical for success, particularly when working with challenging sample types like dried blood spots or environmentally contaminated specimens. The Maxwell RSC Whole Blood DNA Kit has been successfully implemented in malaria surveillance studies, providing sufficient DNA quality and quantity for subsequent amplification steps [38]. For preserved samples, DNA/RNA Shield provides effective stabilization, preventing degradation during transportation from collection sites to sequencing facilities.

For library preparation, the Native Barcoding Kit enables efficient multiplexing of samples, making surveillance programs more cost-effective by allowing multiple specimens to be sequenced simultaneously [38]. The combination of Flongle flow cells with native barcoding represents a particularly economical approach for targeted surveillance applications, bringing down per-sample costs while maintaining data quality sufficient for variant calling.

The comprehensive comparison between Oxford Nanopore and Sanger sequencing technologies for genomic surveillance of parasite drug resistance markers reveals a complex landscape where each platform offers distinct advantages. Sanger sequencing maintains its position as a highly accurate, established method suitable for focused surveillance of known variants in single genes or small target regions. However, Oxford Nanopore technologies demonstrate superior capabilities in sensitivity, turnaround time, and portability, making them increasingly suitable for comprehensive surveillance programs in endemic settings.

The emergence and spread of antimalarial drug resistance in Africa, particularly the concerning appearance of kelch13 mutations associated with artemisinin partial resistance, underscores the critical importance of robust genomic surveillance [38]. The ability of Nanopore sequencing to provide rapid, local results with minimal infrastructure requirements represents a significant advancement for monitoring programs in resource-limited settings. This technology enables near-real-time detection of emerging resistance patterns, potentially allowing for more timely public health interventions.

For parasites with complex genomic architectures like Trypanosoma cruzi, the long-read capabilities of Nanopore sequencing provide insights that were previously inaccessible with short-read technologies [40]. The resolution of repetitive regions, multi-copy gene families, and transposable elements opens new avenues for understanding the genetic basis of treatment failures and variable clinical presentations. As sequencing technologies continue to evolve, the integration of multiple platforms may offer the optimal approach for comprehensive surveillance—combining the accuracy of established methods with the innovative capabilities of emerging technologies to protect the efficacy of antiparasitic treatments worldwide.

In genomic studies of pathogens, particularly those obtained directly from clinical or environmental samples, a significant technical challenge is the overwhelming presence of host DNA that obscures the target pathogen's genetic material. This problem is especially acute in parasite research, where pathogen load can be exceptionally low and host contamination substantial. Selective Whole Genome Amplification (SWGA) and Nanopore Adaptive Sampling represent two powerful but fundamentally different approaches to overcoming this host DNA background. SWGA achieves enrichment through biochemical amplification using species-specific primers, while adaptive sampling employs computational selection during nanopore sequencing to selectively sequence target DNA. This guide provides an objective comparison of these technologies, their experimental protocols, and their efficacy within parasite genomics, contextualized within the broader evaluation of Oxford Nanopore versus Sanger sequencing for parasitic disease research.

Selective Whole Genome Amplification (SWGA) is a primer-based enrichment method that uses the highly processive phi29 polymerase for multiple displacement amplification (MDA). Its selectivity derives from primers designed to bind motifs that are frequent in the target genome but rare in the host background [42] [43]. In contrast, Oxford Nanopore's Adaptive Sampling is a software-based, real-time enrichment method. During sequencing, the initial ~400 bases of a DNA strand are basecalled and aligned to a reference database; strands matching desired targets are sequenced to completion, while off-target strands are ejected from the pore [16].

The table below summarizes the core characteristics of each method:

Table 1: Fundamental characteristics of SWGA and Adaptive Sampling

Feature	Selective Whole Genome Amplification (SWGA)	Nanopore Adaptive Sampling
Enrichment Principle	Biochemical amplification with selective primers	Computational selection during sequencing
Library Preparation	Requires specialized primer sets and phi29 polymerase	Standard library prep (e.g., Ligation Sequencing Kit)
Sequencing Platform	Any (enrichment is performed prior to sequencing)	Oxford Nanopore Technologies (ONT) only
Key Requirement	Prior knowledge of target genome for primer design	Reference genome for real-time alignment
Typical Workflow	Pre-sequencing enrichment step	Integrated enrichment during the sequencing run
Data Type	Enriched genomic DNA for short- or long-read sequencing	Long-read data with increased on-target coverage

Performance and Efficacy in Parasite Research

Enrichment Efficiency and Coverage

The primary metric for evaluating these technologies is their ability to enrich pathogen DNA from a complex host background. The following table compiles quantitative performance data from studies on various parasites:

Table 2: Enrichment performance of SWGA and Adaptive Sampling on parasite DNA

Parasite / Application	Method	Starting Parasite DNA	Enrichment Factor / Result	Key Outcome
Leishmania braziliensis from patient biopsies [43]	SWGA	0.1% - 1%	≥60% parasite-mapping reads	Robust genome amplification from low-biomass clinical samples; enabled population genomics.
Plasmodium malariae from clinical samples [44]	SWGA	Various parasitemias	14-fold increase in genome coverage (≥5 reads)	Made WGS feasible from low parasitemia samples (as low as 0.0064%).
Plasmodium falciparum from blood samples [5]	Adaptive Sampling	0.1% - 8.4%	3- to 5-fold enrichment of P. falciparum bases	Sufficient for covering >97% of the genome at common parasitemia levels (0.1%-0.6%).
Schistosoma mansoni from larval miracidia [39]	Adaptive Sampling	Washed and unwashed samples	Failed to generate sufficient reads for WGS	Washing samples for contamination removal remained critically necessary.

Variant Detection and Drug Resistance Profiling

Accurate detection of genetic variants, including single nucleotide polymorphisms (SNPs) and structural variations (SVs), is crucial for understanding drug resistance and parasite biology.

• SWGA for Population Genomics and Resistance Marker Identification: SWGA has proven highly effective in generating whole-genome data for population studies. For Plasmodium malariae, SWGA enabled the identification of 868,476 genome-wide SNPs and allowed for the analysis of orthologs of P. falciparum drug resistance-associated genes like Pfdhfr, Pfdhps, and Pfcrt [44]. Similarly, for Leishmania braziliensis, SWGA provided sufficient coverage to investigate SNPs, indels, and somy directly from patient biopsies, revealing geographic population structure [43].

• Adaptive Sampling for Comprehensive Variant Profiling: Adaptive sampling excels at detecting structural variations and providing haplotype-resolved data. In a study on pediatric leukemia, a different application of targeted enrichment, adaptive sampling demonstrated high recall rates for SVs (85.3%) and the ability to accurately pinpoint breakpoints, though it showed lower recall for SNVs (60.9%) and small indels (17.6%) compared to short-read whole-genome sequencing [45]. For parasites, a MinION-based approach (without adaptive sampling) successfully genotyped nine drug-resistance-associated genes in P. falciparum, showing that with the improved R9.4 flow cell, SNP calling precision and recall could reach 1 and 0.97, respectively, when sufficient reads covered a position [4].

Experimental Protocols

Workflow for Selective Whole Genome Amplification (SWGA)

The following diagram illustrates the key steps in a typical SWGA protocol:

Diagram 1: Step-by-step SWGA experimental workflow.

Detailed Methodology:

• Step 1: In Silico Primer Design. The process begins computationally. A script (e.g., SWGA2.0) identifies short oligonucleotide primers (typically 7-12 bp) that bind to sequence motifs with high frequency in the target parasite genome but low frequency in the host genome [42] [43]. For Leishmania, this resulted in a ~60-fold enrichment in predicted binding to the parasite over the human genome [43].
• Step 2: Primer Selection and Filtering. Designed primers are filtered based on properties like melting temperature (Tm), avoidance of self-complementarity, and minimal binding to host organellar genomes (e.g., mitochondria) [42]. Multiple primers (e.g., 5-10) are combined into a set for the reaction.
• Step 3: SWGA Reaction. The genomic DNA sample is mixed with the selective primer set and the phi29 polymerase. The isothermal amplification (often at ~30°C) runs for several hours (e.g., 16 hours), selectively amplifying the target genome in a high-fidelity manner [43] [44].
• Step 4: Post-Amplification Processing. The amplified product is purified and quantified before being used to prepare a sequencing library for the platform of choice (e.g., Illumina or Nanopore).

Workflow for Nanopore Adaptive Sampling

The diagram below outlines the foundational steps for conducting a sequencing run with adaptive sampling.

Diagram 2: Key steps of the Nanopore Adaptive Sampling process.

Detailed Methodology:

• Step 1: Define Target Regions. The researcher prepares a BED file specifying the genomic coordinates to be enriched or depleted and provides a corresponding reference genome [16]. No special wet-lab steps are required.
• Step 2: Load Library and Start Run. The native DNA library, prepared with a standard kit like the Ligation Sequencing Kit, is loaded onto a Nanopore flow cell. The run is initiated and managed through the MinKNOW software, where the adaptive sampling mode is selected [16].
• Step 3-5: Real-time Selection Cycle. As each DNA molecule enters a pore, its initial sequence (~400 bases) is basecalled in real-time and aligned to the reference. MinKNOW then makes a decision: if the sequence matches a target region, the molecule is sequenced to completion; if not, the voltage across the pore is reversed to eject the molecule, freeing the pore for a new one [5] [16]. This cycle continues throughout the run, dynamically enriching the output.

The Scientist's Toolkit: Essential Research Reagents and Materials

Successful implementation of these enrichment strategies requires specific reagents and materials. The following table lists key solutions for each method.

Table 3: Essential research reagents and materials for SWGA and Adaptive Sampling

Item	Function / Application	Method
phi29 Polymerase	High-fidelity, strand-displacing enzyme used for multiple displacement amplification in SWGA.	SWGA [42] [44]
Selective Primer Sets	Short oligonucleotides designed to bind frequently to the target genome and initiate amplification.	SWGA [43] [44]
Nanopore Ligation Sequencing Kit	Standard kit for preparing native DNA libraries for sequencing on Oxford Nanopore devices.	Adaptive Sampling [16]
Oxford Nanopore Flow Cell	The consumable containing the nanopores used for sequencing; required for adaptive sampling.	Adaptive Sampling [5] [16]
BED File	A text file defining the genomic coordinates of target regions for enrichment/depletion during adaptive sampling.	Adaptive Sampling [16]
Whatman FTA Cards	Used for preserving parasite DNA (e.g., miracidia) from field samples at ambient temperature.	Sample Collection [39]
Ophiocordylongiiside A	Ophiocordylongiiside A, MF:C42H79NO8, MW:726.1 g/mol	Chemical Reagent
Neoartanin	Neoartanin, MF:C16H18O5, MW:290.31 g/mol	Chemical Reagent

Both SWGA and Adaptive Sampling are powerful for overcoming host DNA background in parasite genomics, yet they serve different strategic goals. SWGA is a highly effective, platform-agnostic method for generating sufficient pathogen DNA from extremely low-biomass and complex clinical samples, making it indispensable for population genomic studies of uncultivable parasites like Leishmania and P. malariae. Its requirement for careful in-silico primer design and a separate enrichment step adds complexity but yields high enrichment factors.

Adaptive Sampling offers a streamlined, wet-lab simplified workflow that leverages the real-time nature of Nanopore sequencing. It provides moderate enrichment (typically 3-5 fold) and is particularly powerful for targeting large genomic regions, detecting structural variations, and when rapid turnaround is desired. However, its success is contingent on having sufficient starting target material, and it may be less effective for samples with extremely high host-to-pathogen DNA ratios, as seen with unwashed Schistosoma samples.

The choice between them depends on the research question, sample type, and available infrastructure. SWGA is the method of choice for the most challenging samples where maximum enrichment is needed, while Adaptive Sampling offers a more integrated and flexible approach for real-time target enrichment within the Nanopore ecosystem.

Genomic surveillance of parasitic diseases is a critical component of modern public health efforts, particularly in endemic regions where timely data can inform treatment policies and control strategies. The efficacy of this surveillance hinges on the choice of sequencing technology, which must balance accuracy, portability, cost, and ease of use. This guide provides an objective comparison between Oxford Nanopore Technologies (ONT) and Sanger sequencing for parasite research, focusing on their application in field-deployable diagnostics. We summarize performance metrics from recent studies, detail experimental methodologies, and visualize workflows to assist researchers, scientists, and drug development professionals in selecting appropriate tools for their specific contexts.

Performance Comparison: Oxford Nanopore vs. Sanger Sequencing

Direct comparative studies and independent validations demonstrate that ONT and Sanger sequencing offer distinct advantages for different applications in parasite research. The following tables summarize key performance metrics based on recent experimental data.

Table 1: Overall Technology Comparison for Parasite Research

Feature	Oxford Nanopore Technologies (ONT)	Sanger Sequencing
Portability	High (pocket-sized MinION; suitcase labs) [46] [47]	Low (requires large, fixed lab equipment)
Turnaround Time	Hours to a day (real-time data analysis) [46] [12]	Days to weeks (including sample transport)
Read Length	Long reads (kb to Mb) [48]	Short reads (up to ~1 kb)
Key Strengths	Genomic surveillance, identifying complex variants, detecting minority clones [3] [12]	High accuracy for single targets, validating specific mutations [5] [49]
Best Suited For	Multiplexed target sequencing, complex genotype analysis, field deployment [3] [12]	Sequencing single, specific amplicons or validating known mutations [50]

Table 2: Comparative Experimental Performance from Recent Studies

Study & Parasite	Metric	Oxford Nanopore Performance	Sanger Sequencing Performance
P. falciparum (Malaria) [5]	Concordance at Drug Resistance Loci	38/38 loci matched Sanger results [5]	Reference standard (100%) [5]
P. falciparum (Malaria) [3]	Sensitivity for Minority Clones	Detected clones at 1:100 ratio [3]	Not quantified in study [3]
Various Bacteria/Fungi [49]	Diagnostic Sensitivity	94.5%	Not the primary focus (used for validation) [49]
Leishmania spp. [50]	Species Discrimination & Coinfection Identification	Effective with 771bp HSP70-Long marker [50]	Effective but can be time-consuming for multiple targets [50]

Detailed Experimental Protocols and Methodologies

Protocol 1: Targeted Amplicon Sequencing ofPlasmodium falciparumwith ONT

This protocol, used for genotyping in antimalarial drug trials and surveillance, highlights the multiplexing capability of ONT [3] [12].

• Sample Input: Dried blood spots (DBS) or whole blood [12].
• DNA Extraction: Standard commercial kits, optionally followed by a reduced-volume selective whole-genome amplification (sWGA) to enrich for parasite DNA [12].
• Multiplex PCR: A single PCR reaction is performed using a pre-designed primer pool (e.g., the NOMADS8 or NOMADS16 panel) targeting multiple genomic regions of interest, such as drug-resistance genes (kelch13, dhfr, dhps), vaccine targets (csp), and polymorphic markers [3] [12]. Amplicons are designed to be 3-4 kbp to leverage long-read capabilities.
• Library Preparation: Amplicons are barcoded using a native barcoding kit (e.g., SQK-NBD114.96) to allow sample pooling. The pooled library is loaded onto a MinION flow cell (R9.4.1 or R10.4.1) [3] [12].
• Sequencing & Analysis: Sequencing is performed on a MinION Mk1C. Real-time basecalling is performed using super-accurate (SUP) mode in MinKNOW or Dorado. Reads are demultiplexed and aligned to reference sequences for variant calling and haplotype inference [3].

Protocol 2: Validation of ONT Data forLeishmaniaSpecies Identification

This protocol describes a common approach to validate the accuracy of ONT-based identification using Sanger sequencing as a reference [50].

• Sample and PCR: DNA from clinical samples is amplified using primers targeting a specific gene, such as the 771-bp HSP70-Long marker for Leishmania [50].
• Parallel Sequencing: The resulting amplicons are split and processed in parallel:
  • ONT Path: The amplicons are barcoded and sequenced directly on the MinION platform. Consensus sequences for each sample are generated from the read data [50].
  • Sanger Path: The amplicons are cloned into a plasmid vector. Multiple bacterial colonies are picked and Sanger sequenced to generate a set of sequences for each sample [50].
• Data Comparison: The consensus sequence from ONT is compared to the sequences obtained via the Sanger method. The percentage of ONT results that are confirmed by the Sanger sequences is reported as the accuracy rate [50].

Workflow Visualization

The following diagrams illustrate the core workflows for the ONT and Sanger sequencing protocols described above, highlighting the key differences in process flow and time.

Diagram 1: A comparison of the ONT targeted amplicon workflow and the Sanger validation workflow. The ONT path is more streamlined for multiplexed analysis, while the Sanger path involves a more laborious cloning step.

Diagram 2: A decision logic flowchart to guide researchers in selecting the most appropriate sequencing technology based on their primary research needs and constraints.

The Scientist's Toolkit: Essential Research Reagents and Materials

Table 3: Key Reagents and Materials for Portable Sequencing in Parasite Research

Item	Function	Example Use Case
Dried Blood Spot (DBS) Cards	Simple, non-invasive sample collection and storage; easy to transport from remote areas. [12]	Collecting blood from malaria patients in field settings for later DNA analysis. [12]
Selective Whole Genome Amplification (sWGA) Kit	Enriches parasite DNA by selectively amplifying AT-rich P. falciparum genome, improving sequencing yield from complex host-pathogen samples. [12]	Preparing DNA from DBS for targeted sequencing of malaria parasites. [12]
Multiplex PCR Primer Panels	Pre-designed sets of primers that simultaneously amplify multiple genomic targets in a single reaction. [3] [12]	Amplifying a panel of drug-resistance genes and microhaplotypes from P. falciparum DNA. [3] [12]
ONT Native Barcoding Kit	Allows for the attachment of unique molecular barcodes to amplicons from different samples, enabling sample multiplexing in a single sequencing run. [3]	Pooling 96 patient samples on one MinION flow cell for cost-effective surveillance. [3]
Magnetic Bead-based DNA Purification Kits	Rapid and efficient purification of nucleic acids, often performed in a single tube; suitable for field labs with limited equipment. [47]	Extracting DNA from clinical samples (e.g., tissue for Leishmania) in a mobile suitcase laboratory. [47]
SerSA	SerSA, MF:C13H19N7O8S, MW:433.40 g/mol	Chemical Reagent
(25S)-Antcin B	(25S)-Antcin B	(25S)-Antcin B is a steroidal triterpenoid for research of antiviral and anticancer mechanisms. This product is For Research Use Only. Not for human or diagnostic use.

The choice between Oxford Nanopore and Sanger sequencing for parasite research in endemic areas is not a matter of one technology being universally superior. Instead, it depends on the specific application. Sanger sequencing remains the gold standard for validating specific mutations and sequencing single targets with very high accuracy. However, Oxford Nanopore sequencing offers a transformative, field-deployable solution for comprehensive genomic surveillance. Its strengths in multiplexed amplicon sequencing, long-read capability, portability, and rapid turnaround time make it uniquely suited for monitoring drug resistance, investigating complex infections, and informing public health policy directly in endemic countries. The continued development of tailored panels and streamlined bioinformatics pipelines will further solidify its role in the global effort to control and eliminate parasitic diseases.

Optimizing Performance: Strategies for Enhancing Accuracy and Efficiency in Parasite Sequencing

The genomic surveillance of parasites, critical for understanding drug resistance and population dynamics, is fundamentally constrained by a persistent wet-lab challenge: the isolation of sufficient, high-quality parasite DNA from complex biological samples. Clinical samples from patients with parasitic infections, such as malaria, typically contain an overwhelming abundance of host DNA, which can drastically reduce the yield and efficiency of parasite sequencing [5] [51]. The choice of downstream sequencing technology—whether the gold standard Sanger sequencing or the long-read, real-time capabilities of Oxford Nanopore Technology (ONT)—is deeply intertwined with the initial sample preparation. This guide objectively compares wet-lab protocols designed to maximize parasite DNA yield, providing the experimental data and methodologies necessary to inform researchers' strategies in parasite genomics and drug development.

Comparative Performance of Sequencing Technologies and Pre-Sequencing Enrichment

Before delving into specific extraction protocols, it is essential to frame the comparison within the broader efficacy of ONT versus Sanger sequencing for parasite research. The following table summarizes the key characteristics of each technology in this context.

Table 1: Comparison of Sequencing Technologies for Parasite Research

Feature	Sanger Sequencing	Oxford Nanopore Technology (ONT)
Typical Application	Sequencing of short, single gene fragments or hotspots [21]	Whole-genome sequencing, targeted amplicon sequencing, metagenomics [5] [4]
Read Length	400–900 base pairs [21]	Up to megabase lengths; typically thousands of base pairs [21] [4]
Turnaround Time (TAT)	3–4 days (outsourced); ~20 min–3 hours per run [21]	Under 24 hours for urgent cases; real-time data analysis [21]
Sensitivity (Variant Detection)	15–20% [21]	<1% (equivalent to NGS) [21]
Error Rate	~0.001% [21]	~5%, but constantly improving with software updates [21]
Key Parasitology Advantage	Well-established for single-gene drug resistance mutation detection [4]	Enrichment via Adaptive Sampling; enables whole-genome sequencing from unenriched blood; portability for field use [5]

A critical wet-lab challenge for any sequencing method is host DNA contamination. In a patient blood sample with 1% parasitemia, the human genome, being roughly 100 times larger than the Plasmodium genome and diploid, means that over 99% of the DNA in a sample can be of human origin [51]. This makes pre-sequencing enrichment a paramount concern. ONT's adaptive sampling feature provides a bioinformatics-based enrichment method during the sequencing run itself. This technique selectively ejects human DNA molecules from the nanopores after a short scan, enriching for target parasite sequences and achieving a 3- to 5-fold enrichment of Plasmodium falciparum bases in samples with only 0.1%–8.4% parasite DNA [5].

Comparison of DNA Extraction and Enrichment Methodologies

The efficacy of genomic analysis is profoundly affected by the initial DNA extraction and purification steps. The table below compares several key methodologies.

Table 2: Comparison of DNA Extraction and Enrichment Methods for Parasite Genomics

Method Name	Principle	Best For	Performance Data	Key Limitations
Lymphoprep + Plasmodipur Filtration [51]	Density-gradient centrifugation to separate WBCs, followed by filtration to retain parasites.	Purifying P. falciparum from fresh clinical blood samples.	>70% of samples had <30% human DNA; enables ~40x genome coverage in one Illumina lane [51].	Requires fresh blood; moderate variability in human DNA removal.
Quick-DNA HMW MagBead Kit [52]	Magnetic bead-based purification with gentle lysis to preserve high molecular weight (HMW) DNA.	Shotgun metagenomics and long-read sequencing of complex samples.	Produced the highest yield of pure HMW DNA; enabled accurate detection of bacterial mock communities [52].	Performance may vary with different sample matrices.
FTA Card Storage + Low-Input Extraction [53]	Chemical preservation of samples on cards for transport, followed by low-input DNA extraction.	Immature, non-invasive parasite stages (e.g., eggs, miracidia) from remote locations.	Enabled whole-genome sequencing for 6 of 8 helminth species without whole-genome amplification [53].	Not all species/life stages yielded sufficient DNA; risk of bacterial contamination.
ONT Adaptive Sampling [5]	In silico enrichment; real-time ejection of off-target (e.g., human) DNA during nanopore sequencing.	Sequencing low-parasitemia samples without prior physical enrichment.	5.8-fold enrichment in a 0.1% parasitemia sample, yielding 97% genome coverage at median depth of 5 [5].	Requires a reference genome; reduces overall sequencing throughput.

Detailed Experimental Protocols

Two-Step Wet-Lab Enrichment forPlasmodium falciparum

This protocol, validated on 76 patient samples in Burkina Faso, effectively reduces human DNA contamination for downstream whole-genome sequencing [51].

• Sample Collection: Collect peripheral blood in EDTA-containing Vacutainer tubes. Store at 4–8°C and process as soon as possible.
• Lymphoprep Density-Gradient Centrifugation:
  • Layer the patient blood carefully onto the Lymphoprep solution in a centrifuge tube.
  • Centrifuge at 800 x g for 20 minutes at room temperature with the brake turned off.
  • After centrifugation, the peripheral blood mononuclear cells (PBMCs, containing human DNA) will form a distinct layer at the plasma-Lymphoprep interface. Carefully aspirate and discard this layer.
  • Harvest the red blood cell (RBC) pellet, which contains the parasites, from the bottom of the tube.
• Plasmodipur Filtration:
  • Reconstitute the RBC pellet and pass it through a Plasmodipur filter, which is designed to retain white blood cells.
  • The filtrate, now enriched with Plasmodium-infected RBCs, is collected.
• DNA Extraction: Proceed with standard DNA extraction protocols on the enriched RBC fraction. The study found this two-step method resulted in over 70% of sample preparations having ≤30% human DNA content [51].

Nanopore Sequencing with Adaptive Sampling

This protocol leverages ONT technology to sequence P. falciparum directly from patient blood with minimal preprocessing, demonstrating the synergy between wet-lab and computational methods [5].

• DNA Extraction: Extract total DNA from a patient blood sample without prior leukocyte depletion or parasite enrichment. The DNA does not require size selection, though the enrichment efficiency is influenced by fragment size.
• Library Preparation & Sequencing:
  • Prepare the sequencing library according to the standard ONT protocol for ligation sequencing.
  • Load the library onto a MinION flow cell.
  • In the MinKNOW software, initiate the sequencing run in "adaptive sampling" mode.
  • Provide the software with the reference genome for Plasmodium falciparum (e.g., the 3D7 strain).
  • During sequencing, MinKNOW performs real-time base calling. Reads that are classified as not mapping to the P. falciparum reference (e.g., human reads) are selectively ejected from the pores by reversing the voltage.
• Validation: The resulting data can be used for variant calling. In one study, 38 drug resistance loci were called with high concordance to Sanger sequencing results, confirming the method's suitability for addressing clinical research questions [5].

The following workflow diagram illustrates the comparative pathways of the standard wet-lab enrichment versus the adaptive sampling approach.

The Scientist's Toolkit: Essential Research Reagents

Successful parasite genomics relies on a combination of specific reagents and tools. The following table details key items used in the featured experiments.

Table 3: Key Research Reagents and Their Functions in Parasite DNA Studies

Reagent / Tool	Function in the Protocol	Example Use Case
Lymphoprep [51]	Density-gradient medium for isolating peripheral blood mononuclear cells (PBMCs) by centrifugation.	First-step enrichment of Plasmodium by depleting human white blood cells from whole blood.
Plasmodipur Filter [51]	A filter unit designed to retain white blood cells while allowing infected red blood cells to pass through.	Second-step enrichment of Plasmodium in a two-step wet-lab protocol.
Whatman FTA Cards [53]	Chemically treated cellulose-based cards for room-temperature storage and preservation of DNA from biological samples.	Collection and storage of individual immature parasite stages (e.g., helminth eggs) from field sites.
Quick-DNA HMW MagBead Kit [52]	Utilizes magnetic beads to bind and purify high molecular weight DNA with minimal shearing.	Isolation of high-quality, long-fragment DNA optimal for long-read sequencing technologies like ONT.
MinION Flow Cell (R9.4+) [5] [4]	The consumable containing nanopores used for sequencing on the MinION device.	Enabling real-time, long-read sequencing and adaptive sampling for parasite genome enrichment and variant calling.
Anti-HLA1 Dynabeads [51]	Magnetic beads coated with antibodies that bind to human leukocyte antigen (HLA) class I on nucleated cells.	An alternative method for immunomagnetic depletion of human white blood cells from a sample.
Volucrin	Volucrin, MF:C32H26O8, MW:538.5 g/mol	Chemical Reagent

The journey from a complex clinical sample to high-quality parasite genomic data is multifaceted. Traditional wet-lab methods like filtration and density-gradient centrifugation provide a robust, physical means of enrichment that is compatible with all sequencing platforms, including Sanger and ONT [51]. However, the emergence of ONT and its adaptive sampling feature represents a paradigm shift, offering a powerful in silico alternative that can streamline workflows, reduce turnaround times to under 24 hours, and make genomic surveillance feasible in endemic field settings [5] [21]. The choice of protocol is not a matter of selecting one over the other, but of strategic integration. For the highest sensitivity and completeness in whole-genome analyses, a combination of optimized wet-lab extraction to obtain HMW DNA [52] followed by ONT sequencing with adaptive sampling may constitute the most powerful approach. This synergy between advanced wet-lab protocols and innovative sequencing technologies is poised to accelerate drug development and genomic surveillance of parasitic diseases.

The field of parasitology has undergone a significant transformation with the advent of advanced sequencing technologies. For decades, Sanger sequencing has served as the gold standard for validating genetic variants in short DNA fragments, providing a foundation for genetic diagnosis and discovery [21]. However, the limitations of Sanger sequencing—particularly its low throughput and inability to detect low-frequency variants—have driven researchers to explore third-generation sequencing platforms such as Oxford Nanopore Technology (ONT) [21]. The unique challenges of parasite research, including complex life cycles, diverse genomic structures, and the need for field-deployable solutions, make the comparison between these technologies particularly relevant for the modern parasitologist.

The efficacy of Oxford Nanopore versus Sanger sequencing represents a critical decision point that influences experimental design, resource allocation, and ultimately, the biological insights that can be gained from genomic studies of parasites [54]. This guide provides an objective comparison of these technologies, focusing on their application to variant calling and the error correction pipelines essential for producing reliable genomic data in parasite research.

Technology Comparison: Oxford Nanopore vs. Sanger Sequencing

Fundamental Technical Specifications

The following table summarizes the core technical differences between Sanger sequencing, Next-Generation Sequencing (NGS), and Oxford Nanopore sequencing:

Table 1: Core technical specifications of sequencing platforms relevant to parasite research [21]

Feature	Sanger Sequencing	NGS (Illumina)	Oxford Nanopore (MinION)
Sequencing Method	Dideoxy chain termination	Massively parallel sequencing	Nanopore sequencing
Single-Read Accuracy	>99% [21]	>99% [21]	>99% (Q20 chemistry) [22] [55]
Read Length	400–900 base pairs [21]	50–500 base pairs [21]	Up to megabases [21]
Time per Run	20 minutes–3 hours [21]	~48 hours [21]	1 minute–48 hours (real-time) [21]
Variant Sensitivity	15–20% [21]	~1% [21]	<1% [21]
Error Rate	0.001% [21]	0.1–1% [21]	~5% (historically), ongoing improvements [21]
Key Applications	SNVs and INDELs in short fragments	SNVs, INDELs, targeted panels	SNVs, INDELs, complex structural variants, epigenetics [21]

Performance in Parasite Genomics

In the specific context of parasite research, the technologies show distinct advantages:

Table 2: Performance comparison for parasite genomics applications

Application	Sanger Sequencing	Oxford Nanopore
Species Identification	Low throughput, requires prior knowledge [54]	High-throughput DNA metabarcoding of multiple species simultaneously [54]
Whole Genome Assembly	Not feasible	Produces contiguous, reference-quality genomes for parasitic nematodes [56]
Turnaround Time	3–4 days [21]	2–3 days (can be under 24 hours for urgent cases) [21]
Field Deployment	Not practical	Portable (MinION), used in remote locations [57]
Variant Detection Sensitivity	Limited to dominant variants	Can detect low-frequency variants (<1% VAF) crucial for mixed infections [21]

For parasite identification, DNA metabarcoding with Nanopore has emerged as a powerful alternative to traditional morphological methods and Sanger-based barcoding. It allows for the simultaneous identification of multiple helminth species from complex samples without prior knowledge of community composition, offering higher taxonomic resolution and throughput [54].

For de novo genome assembly, studies on parasitic nematodes like Brugia malayi, Trichuris trichiura, and Ancylostoma caninum have demonstrated that assemblies using only MinION data can achieve contiguity and completeness similar or superior to current reference genomes. Polishing these assemblies with short-read Illumina data improves gene-level accuracy only moderately, indicating the high quality of Nanopore-only assemblies for helminths [56].

Experimental Protocols for Performance Validation

Protocol 1: Targeted SNV Detection using Oxford Nanopore

This protocol, adapted from a study on the PCSK9 gene, demonstrates a workflow for accurate Single Nucleotide Variation (SNV) detection, which can be applied to parasite drug resistance genes [55].

• Primer Design: Design overlapping primer pairs (e.g., using PrimalScheme) to cover the entire genomic region of interest.
• PCR Amplification: Amplify the target locus in ~10 kb overlapping fragments from purified genomic DNA.
• Library Preparation: Pool and purify PCR products. For multiplexed samples, use Native Barcoding kits (e.g., EXP-NBD104) followed by ligation sequencing kit (e.g., SQK-LSK109).
• Sequencing: Load the library onto a MinION (FLO-MIN106) or Flongle (FLO-FLG001) flow cell on a GridION or Mk1C device.
• Basecalling: Perform basecalling in Super High Accuracy (SUP) mode using Guppy or Dorado to translate raw signals into nucleotide sequences [55].
• Variant Calling: Use a long-read-aware variant caller such as Longshot for SNV detection [55].
• Validation: Confirm SNV calls against a reference method, such as Sanger sequencing.

This workflow achieved a perfect F1-score of 100% for SNV detection with a MinION flow cell and 98.2% with the more cost-effective Flongle, demonstrating its potential for targeted parasite gene sequencing [55].

Protocol 2: Parasite Genome Assembly and Polishing

This protocol outlines the steps for generating a de novo genome assembly for a parasitic helminth using Nanopore data [56].

• DNA Extraction: Use modified protocols (e.g., optimized for individual worms) to obtain sufficient high-molecular-weight genomic DNA [56].
• Library Preparation & Sequencing: Prepare a library using a ligation kit (e.g., LSK-110) and sequence on a MinION device to achieve high coverage.
• Basecalling and Quality Control: Convert FAST5 to FASTQ using Dorado SUP model. Assess read quality and length distribution.
• De Novo Assembly: Assemble the genome using a long-read assembler such as Flye or Necat.
• Assembly Polishing (Optional): Polish the initial assembly using:
  • Medaka: A tool that uses neural networks to correct consensus sequences based on raw Nanopore signal data.
  • Hybrid Polishing: Alternatively, use short-read Illumina data with tools like HyPo to correct residual errors, though this may offer only marginal improvements for parasite genomes [56].
• Assembly Assessment: Evaluate contiguity (N50), completeness (BUSCO), and gene content against reference datasets.

Figure 1: Bioinformatic workflow for de novo genome assembly of parasites using Oxford Nanopore data.

Error Correction: A Critical Component of Nanopore Pipelines

The relatively higher raw read error rate of Nanopore sequencing makes robust error correction essential for accurate variant calling and genome assembly.

Strategies for Error Correction

Table 3: Error correction strategies for Oxford Nanopore data in parasite genomics

Strategy	Principle	Best For	Tools
Hybrid Correction	Uses high-accuracy short reads (Illumina) to correct long Nanopore reads [58].	Projects with existing or easy access to Illumina data.	Nanocorr [58], HyPo
Assembly Polishing	Corrects the consensus sequence of an assembly using Nanopore reads or signals.	Final step in de novo genome assembly.	Medaka, Homopolish [59]
Basecaller Improvement	Improves raw read accuracy via advanced machine learning models on raw signals.	All Nanopore workflows; the first line of defense.	Dorado SUP, NanoReviser [60]
Reference-Based Correction	Leverages evolutionary conservation and reference genomes to identify/correct errors.	Isolates with extensive novel modifications; species with good reference databases.	Modpolish [59]

Addressing Modification-Mediated Errors

A significant source of systematic errors in Nanopore sequencing is the presence of DNA modifications. Basecallers are trained on common modifications (e.g., 5mC, 6mA), but novel modifications in parasite genomes can cause basecalling errors that are not fixed by standard polishing [59]. Two solutions exist:

• WGA Demodification: Physically removing modifications via Whole-Genome Amplification (WGA) before sequencing. This improves quality but loses epigenetic information and increases costs [59].
• Computational Correction (Modpolish): A reference-based method that corrects errors by leveraging basecalling quality and evolutionary conservation from closely-related public genomes, while preserving native modification signals [59].

Figure 2: Addressing modification-mediated errors in nanopore sequencing.

The Scientist's Toolkit: Essential Reagents and Software

Table 4: Key research reagents and software for Nanopore-based parasite genomics

Item	Function	Example Products/Kits
DNA Extraction Kit	Obtain high-quality, high-molecular-weight DNA crucial for long reads.	QIAamp DNA Mini Kit [55], DNeasy PowerSoil Pro Kit [57]
Library Prep Kit	Prepare genomic DNA for sequencing.	Ligation Sequencing Kits (SQK-LSK110) [55], Native Barcoding Kits (EXP-NBD104) [55]
Flow Cell	The consumable containing nanopores for sequencing.	MinION Flow Cells (FLO-MIN106), Flongle (FLO-FLG001) [55]
Basecaller	Translate raw electrical signals to nucleotide sequences.	Dorado (Super Accuracy model) [22] [55], Guppy
Variant Caller	Identify genetic variants from sequenced reads.	Longshot (for SNVs) [55], Clair3, PEPPER-Margin-DeepVariant
Assembler	Reconstruct genomes from long reads.	Flye [57] [22], Canu, Shasta, Necat
Polisher	Correct errors in draft genome assemblies.	Medaka [22] [59], Homopolish [59], Modpolish [59]

The choice between Oxford Nanopore and Sanger sequencing for parasite research is not a simple binary decision but depends on the specific research question. Sanger sequencing remains a reliable, cost-effective method for validating known variants or sequencing single, short amplicons. However, for comprehensive parasite identification, whole-genome assembly, resolving complex genomic regions, and detecting low-frequency variants, Oxford Nanopore technology offers a powerful, versatile, and increasingly accurate alternative.

The successful implementation of Nanopore sequencing hinges on selecting appropriate bioinformatic pipelines for error correction and variant calling. As the technology and its associated algorithms continue to mature, ONT is poised to become an even more indispensable tool in the parasitologist's arsenal, potentially enabling real-time genomic surveillance of parasitic outbreaks in the field.

Genomic studies of parasites are fundamental to understanding transmission, drug resistance, and pathogenicity. However, these studies are often hampered by specific genomic features common in parasitic organisms, particularly high A+T content and extensive homopolymer regions (stretches of identical consecutive nucleotides). These characteristics pose significant challenges for conventional short-read sequencing technologies, which frequently produce misassemblies, base-calling errors, and gaps in these problematic regions. This comparison guide objectively evaluates the efficacy of Oxford Nanopore Technologies (ONT) against the established gold standard of Sanger sequencing for parasite research, providing researchers with performance data and methodological frameworks to inform their sequencing strategy selection.

Technology Comparison: Performance in Problematic Regions

Technical Capabilities and Limitations

The following table compares the fundamental technical attributes of ONT and Sanger sequencing that directly impact their performance with high A+T and homopolymer-rich parasite genomes.

Table 1: Core Technology Comparison for Challenging Genomic Regions

Feature	Oxford Nanopore Technologies	Sanger Sequencing
Read Length	Ultra-long (kilobases to megabases); capable of spanning repetitive regions [61]	Short (typically 500-1000 bp); fragments at repetitive sequences
Homopolymer Resolution	Moderate; accuracy has improved with recent chemistry and basecallers [62]	High; considered the gold standard for accuracy
A+T-rich Sequence Handling	Effective; single-molecule sequencing without PCR amplification reduces bias [61]	Effective but requires optimized PCR; can be problematic
Template Preparation	Can sequence native DNA without amplification (PCR-free)	Almost always requires PCR amplification
Throughput	Very high; capable of generating entire genomes [56]	Low; one reaction per template
Cost per Sample	Low for high-throughput applications	High for large-scale projects

Experimental Performance Data

Recent studies directly demonstrate how these technological differences translate into practical outcomes for parasite genomics. The table below summarizes key performance metrics from published research.

Table 2: Experimental Performance in Parasite Genomics Applications

Application	Oxford Nanopore Technologies Performance	Sanger Sequencing Performance	Reference
Full-Length SSU rRNA Gene Sequencing (Blastocystis)	Generated highly accurate full-length (~1800 bp) sequences from cultured and fecal isolates; identified mixed subtypes (ST10/ST14) [61]	Provides reference-quality reads but cannot resolve mixed infections in a single reaction or generate full-length genes in one read	[61]
De Novo Genome Assembly (Parasitic Nematodes)	Assembled reference-quality genomes for Brugia malayi, Trichuris trichiura, and Ancylostoma caninum using only MinION data [56]	Not practical for de novo genome assembly due to short read length and low throughput	[56]
Resolution of Co-infections (Avian Haemosporidians)	Resolved cryptic co-infections through unfragmented mitogenome assembly; identified three mitochondrial lineages in a single host [24]	Ambiguous for co-infections; typically reveals only the dominant haplotype in mixed infections	[24]
Sensitivity for Low-Density Infections	Successfully identified drug-resistance mutations and gene deletions in Plasmodium falciparum from dried blood spots, even at low parasite levels [18]	Limited by sensitivity to detect minor variants in polyclonal infections; lower throughput for surveillance	[63]

Experimental Protocols for Parasite Genomics

ONT Protocol for Full-Length Parasite Gene Sequencing

The workflow for generating full-length ribosomal RNA gene sequences from parasites using ONT technology, as validated for Blastocystis subtypes, involves a structured wet lab and computational process [61].

Figure 1: ONT full-length SSU rRNA gene sequencing workflow. This diagram outlines the key steps for generating reference-quality sequences from parasite samples [61].

Detailed Methodology [61]:

• DNA Source: The protocol is flexible and can use genomic DNA from both cultured parasite isolates and direct fecal samples.
• PCR Amplification: Amplify the nearly full-length small subunit (SSU) rRNA gene (~1800 bp) using universal eukaryotic primers Af (5′-AAC CTG GTT GAT CCT GCC AGT AGT C-3′) and Br (5′-TGA TCC TTC TGC AGG TTC ACC TAC G-3′). Use a high-fidelity proofreading polymerase (e.g., KAPA HiFi HotStart ReadyMix) to minimize PCR errors.
• Library Preparation and Sequencing: Prepare the sequencing library using the ONT Ligation Sequencing Kit (SQK-LSK109), following the manufacturer's protocol for 1D amplicons. Input 100-200 fmol of amplicon DNA. Load the library onto a MinION R9.4 flow cell and sequence for 1-24 hours, targeting approximately 500,000 reads per sample.
• Bioinformatic Analysis:
  • Basecalling and Filtering: Perform basecalling with Guppy (min. Q-score: 7). Filter reads to retain sequences between 1000-2100 bp.
  • Error Correction: Use Canu assembler (genomeSize=1.7k, minOverlapLength=1000) for read correction and trimming.
  • Variant Calling: Identify reads with intact primer sequences using BBTools' bbduk.sh. A Blastocystis-specific reference database from NCBI is used to filter on-target sequences before final assembly and phylogenetic analysis.

Sanger Sequencing Protocol for Parasite Gene Fragments

The conventional approach for parasite genotyping relies on sequencing specific gene fragments.

Figure 2: Sanger sequencing workflow for parasite genotyping. This process generates accurate short sequences, ideal for identifying known subtypes [61].

Detailed Methodology [61]:

• DNA Extraction and PCR: Extract genomic DNA from the sample. Amplify a short, informative region of the target gene (e.g., a ~500 bp fragment of the Blastocystis SSU rRNA gene suitable for subtype identification) using subtype-specific primers.
• PCR Cleanup: Purify the PCR product to remove excess primers and nucleotides.
• Sequencing Reaction: Set up the Sanger sequencing reaction using fluorescently labeled dideoxynucleotides (ddNTPs) in a cycle sequencing protocol.
• Capillary Electrophoresis: The reaction products are separated by size via capillary electrophoresis, generating a chromatogram.
• Data Analysis: Analyze the chromatogram for base-calling errors and assemble a consensus sequence. This sequence is compared to reference databases for subtype identification.

The Scientist's Toolkit: Essential Research Reagents

Successful implementation of the protocols above requires specific reagents and tools. The following table details the key solutions for long-read parasite genomics.

Table 3: Essential Research Reagent Solutions for Parasite Sequencing

Item	Function	Example Use Case
Universal Eukaryotic SSU rRNA Primers (Af/Br)	Amplifies nearly full-length 18S rRNA gene from diverse eukaryotes, enabling discovery of novel parasite subtypes without prior sequence knowledge [61]	Generating full-length reference sequences for protist parasites like Blastocystis directly from fecal samples [61]
High-Fidelity PCR Master Mix	Reduces PCR errors during amplicon generation, ensuring high-fidelity sequencing reads for accurate haplotype determination	Critical for all amplicon-based sequencing (ONT or Sanger) to minimize sequencing artifacts mistaken for true genetic variation
ONT Ligation Sequencing Kit (SQK-LSK109)	Prepares DNA libraries for nanopore sequencing by adding motor proteins and adapters; compatible with long amplicons and native DNA [61]	Standard workflow for sequencing full-length PCR amplicons or genomic DNA for de novo assembly of parasite genomes [56] [61]
ONT Rapid Sequencing Kits	Provides a faster, streamlined library preparation method, beneficial for time-sensitive applications like pathogen surveillance	Rapid detection of drug-resistance mutations in Plasmodium falciparum from dried blood spots in resource-limited settings [18]
R9.4 / R10.4 Flow Cells	The consumable containing nanopores; R10.4 offers improved base-calling accuracy across homopolymer regions [62]	All MinION and PromethION sequencing runs; choice of flow cell type impacts output and accuracy for challenging sequences
Dorado Basecaller with Modified Model	ONT's software for translating raw electrical signals into nucleotide sequences; modified models enhance accuracy for specific applications like short-fragment mode [62]	Real-time basecalling during sequencing; essential for adaptive sampling and rapid analysis of amplicon or capture-based data

The choice between Oxford Nanopore and Sanger sequencing for parasite research involving high A+T content and homopolymer regions is not a simple matter of one technology being superior to the other. Instead, the decision should be strategically aligned with the specific research objectives.

• Select Oxford Nanopore Technologies when your project requires discovery and comprehensiveness. This includes generating full-length reference sequences, conducting de novo genome assemblies, resolving complex co-infections, and detecting all forms of genetic variation (SNVs, SVs, methylation) in a single run [18] [56] [61]. Its scalability makes it ideal for large-scale surveillance studies.

• Rely on Sanger Sequencing for targeted, high-accuracy validation. It remains the gold standard for confirming specific genetic variants, sequencing dominant haplotypes in pure samples, and for low-throughput diagnostics where maximum per-base accuracy in short regions is the paramount concern.

Ultimately, many modern parasite genomics pipelines are most effective when they leverage the strengths of both technologies: using ONT for broad discovery and initial assembly, and employing Sanger sequencing for spot-validation of critical, difficult-to-sequence regions. This synergistic approach allows researchers to overcome the historical challenges posed by complex parasite genomes, driving forward our understanding of parasite biology, evolution, and transmission.

In the field of parasitic disease research, accurate genetic data is crucial for everything from species identification and tracking drug resistance to understanding transmission dynamics. For years, Sanger sequencing has served as the gold standard for validating genetic variants in short DNA fragments. However, the increasing demand for faster turnaround times (TATs) and higher sensitivity in variant detection is driving the need for more efficient methods [21]. Oxford Nanopore Technologies (ONT), a representative of third-generation sequencing, has emerged as a powerful alternative, offering rapid sequencing and the ability to process long DNA fragments. This guide provides an objective comparison of these technologies, focusing on their application in parasite research, to help scientists make informed decisions that balance turnaround time, cost, and data quality.

Technology Comparison: Sanger Sequencing vs. Oxford Nanopore

The following table summarizes the core technical characteristics of Sanger sequencing and Oxford Nanopore sequencing, highlighting key differences that impact their application in research workflows.

Table 1: Technical comparison between Sanger sequencing and Oxford Nanopore Technologies

Feature	Sanger Sequencing	Oxford Nanopore MinION
Sequencing Method	Dideoxy chain termination	Nanopore-based electronic signal detection
Single-Read Accuracy	>99% [21]	>99% (with updates); error rate can be ~5% but is an area of ongoing improvement [21]
Read Length	400–900 base pairs [21]	Up to a megabase (millions of bases) [21]
Time per Run	20 minutes – 3 hours [21]	1 minute – 48 hours (real-time data analysis) [21]
Sensitivity (Variant Detection)	15–20% [21]	<1% (equivalent to NGS sensitivity) [21]
Key Applications	SNVs and INDELs in short, targeted regions [21]	SNVs, INDELs, complex structural variants, GC-rich regions, and repetitive regions [21]
Typical Turnaround Time (TAT)	3–4 days (in an outsourced lab setting) [21]	2–3 days; can be under 24 hours for urgent cases [21]

The data shows a clear trade-off. Sanger provides high accuracy for targeted, short-read applications but lacks the sensitivity and speed for broader genomic investigations. ONT offers unparalleled speed and the ability to sequence any length of DNA or RNA natively, though its raw read accuracy has traditionally been lower. However, it is critical to note that ONT's accuracy is continually improving through software updates, and its high sensitivity allows for the detection of low-frequency variants that Sanger would miss [21].

Performance Analysis in Parasite Research

Species Identification and Detection of Co-infections

The ability to accurately identify parasite species and detect mixed infections is vital for diagnosis and treatment. A study on Leishmania species identification compared two genetic markers sequenced on the MinION platform. Researchers designed a new 771-bp marker (HSP70-Long) and compared it to a previously established 330-bp marker (HSP70-Short). The HSP70-Long marker demonstrated outstanding specificity and was highly effective at discriminating between diverse Leishmania species and identifying coinfections within clinical samples from humans, dogs, and cats. While the longer marker showed slightly lower sensitivity than the shorter one, the increased sequence length provided greater discriminatory power for precise species identification [50].

Workflow Simplification and Genome Assembly

ONT sequencing can significantly streamline complex research workflows. For example, in paediatric cancer research, which shares similar diagnostic challenges with complex parasitology, a single ONT assay was able to replace multiple genetic tests. This approach detected key mutations, fusions, and methylation patterns within hours, demonstrating the potential to consolidate multiple diagnostic procedures into one rapid and affordable workflow [10].

Furthermore, for foundational genomics research, ONT has proven capable of generating high-quality de novo genome assemblies for parasitic nematodes. One study found that genome assemblies for three species (Brugia malayi, Trichuris trichiura, and Ancylostoma caninum) generated using only MinION data were of "reference-quality," with contiguity and completeness similar or superior to current references. Remarkably, modified protocols even enabled whole-genome sequencing from individual helminths, simplifying a traditionally challenging sample preparation process [56].

Enrichment of Parasite DNA in Complex Samples

A major hurdle in sequencing parasites from patient blood samples is the overwhelming amount of human DNA. ONT's adaptive sampling feature computationally enriches for target DNA during the sequencing run, effectively depleting human reads. A proof-of-concept study on Plasmodium falciparum demonstrated that this method achieved a 3- to 5-fold enrichment of parasite DNA in samples with parasitemia levels between 0.1% and 8.4%. For patient samples with common parasitemia levels (0.1%–0.6%), this enrichment was sufficient to cover at least 97% of the P. falciparum genome. The data were of high enough quality to sensitively compare 38 drug resistance loci, with results showing high concordance with Sanger sequencing [5]. This shows that adaptive sampling can circumvent time-consuming wet-lab enrichment steps, simplifying and accelerating the workflow from blood collection to parasite sequencing.

Experimental Protocols and Workflows

A Generalized Workflow for Targeted Parasite Sequencing

The following diagram illustrates a common workflow for targeted sequencing on the MinION platform, as applied in parasite identification studies.

Diagram 1: Targeted sequencing workflow for parasite identification.

Detailed Protocol: Leishmania Species Identification

This protocol is adapted from a study that validated ONT for Leishmania species identification [50].

• Step 1: Primer and Assay Design. The researchers developed a new primer set (HSP70-Long) targeting a 771-bp region of the hsp70 gene. An in-house database of 414 Leishmania HSP70 sequences was compiled from public repositories, and haplotypes were extracted for primer design using PRIMER BLAST. Primers were validated for specificity and physico-chemical properties.
• Step 2: Sample Collection and DNA Extraction. The study used a dataset of 27 samples from humans, dogs, and cats affected by cutaneous and visceral leishmaniasis. DNA was extracted from each sample using standard commercial kits.
• Step 3: PCR Amplification. Conventional PCR was performed using both the novel HSP70-Long primers and a previously published HSP70-Short primer set. The PCR products were purified.
• Step 4: Library Preparation and Sequencing. The purified amplicons were prepared for sequencing using the ONT LSK-109 ligation sequencing kit, following the manufacturer's protocol. The prepared library was loaded onto a MinION flow cell and sequenced using a MinION Mk1B device.
• Step 5: Data Analysis. Basecalling was performed in real-time using MinKNOW software. The resulting FASTQ files were aligned to a reference database of Leishmania sequences for taxonomic classification and identification of co-infections.

Detailed Protocol: Metagenomic Detection of Intestinal Parasites

Metabarcoding via NGS allows for the simultaneous screening of multiple parasite species from a single sample. One study optimized this for 11 intestinal parasites using the 18S rRNA V9 region [9]. The workflow is summarized below.

Diagram 2: Metabarcoding workflow for multi-parasite detection.

Key methodological considerations from this study include:

• Cloning and Pooling: The 18S rDNA V9 region of 11 parasite species was cloned into plasmids. These plasmids were pooled in equal concentrations to create a standardized sample for benchmarking [9].
• PCR Optimization: The study found that both the DNA secondary structure of the target region and the amplicon PCR annealing temperature significantly affected the relative abundance of output reads for each parasite. This highlights the need for careful optimization of library preparation protocols to avoid bias [9].
• Bioinformatic Analysis: Data was processed using a standardized pipeline in QIIME 2. Sequences were demultiplexed, quality-filtered, denoised, and checked for chimeras with DADA2. Taxonomic assignment was performed using a comprehensive database built from NCBI nucleotide sequences [9].

The Scientist's Toolkit: Essential Research Reagents and Materials

The following table lists key reagents and materials used in the featured ONT sequencing experiments for parasite research.

Table 2: Key research reagent solutions for parasite sequencing workflows

Item	Function/Application	Example from Literature
Fast DNA SPIN Kit	DNA extraction from complex samples like preserved parasite specimens.	Used to extract DNA from helminths preserved in ethanol [9].
TOPcloner TA Kit	Cloning of PCR amplicons into plasmids for creating control materials.	Used for cloning the 18S V9 regions of 11 intestinal parasites [9].
KAPA HiFi HotStart ReadyMix	High-fidelity PCR amplification to minimize errors in target amplification.	Used for amplicon PCR in the intestinal parasite metabarcoding study [9].
ONT Ligation Sequencing Kit (LSK-109)	Prepares DNA libraries for sequencing on Nanopore devices by adding sequencing adapters.	Standard library preparation kit used across many studies, including Leishmania identification [50].
MinION Flow Cell (R9.4.1)	The consumable containing nanopores used for sequencing on the MinION device.	The core sequencing unit used in the Leishmania and Plasmodium studies [5] [50].
QIIME 2, DADA2	Bioinformatic packages for processing and analyzing amplicon sequencing data.	Used for demultiplexing, quality control, and denoising in the intestinal parasite study [9].
Kraken2	A system for fast k-mer-based taxonomic classification of sequencing reads.	Used in the PGIP platform for reads mapping-based identification of parasite genomes [64].

The choice between Sanger and Nanopore sequencing for parasite research is not a simple matter of one technology being superior to the other. Instead, it is a strategic decision based on the specific needs of the project.

• Sanger sequencing remains a robust, highly accurate, and cost-effective solution for projects requiring sequencing of a single gene or a few known, short genetic targets. Its main limitations are lower sensitivity and low throughput.
• Oxford Nanopore sequencing offers a transformative approach with its rapid turnaround time, high sensitivity, and ability to discover a wide range of genetic variation, from single nucleotides to large structural variants. Its capacity to generate long reads simplifies genome assembly and can resolve complex regions, while features like adaptive sampling streamline workflows by reducing or eliminating the need for upfront target enrichment.

For modern parasitology, ONT provides a powerful, all-in-one tool that can accelerate everything from routine species identification and drug resistance monitoring to large-scale genomic surveillance and the discovery of new pathogens. As the technology continues to evolve, with ongoing improvements in accuracy and bioinformatic tools, its role in optimizing the balance between turnaround time, cost, and data quality is set to expand further.

Head-to-Head Comparison: Validating Nanopore Performance Against Sanger and Other Benchmarks

The continuous monitoring of drug resistance is a cornerstone in the management and control of parasitic and viral diseases. For researchers and clinicians, selecting the appropriate genotyping method is critical for obtaining accurate, timely, and actionable data. This guide provides an objective comparison of two sequencing technologies—Oxford Nanopore Technology (ONT) and Sanger sequencing—focusing on their performance in identifying drug resistance mutations in pathogens such as Plasmodium falciparum and HIV-1. The evaluation is centered on key performance metrics including concordance, sensitivity, limit of detection, and practicality for use in both research and resource-limited settings. By presenting experimental data and detailed methodologies, this article aims to inform researchers, scientists, and drug development professionals in their selection of sequencing platforms for drug resistance surveillance.

Performance Comparison: ONT vs. Sanger Sequencing

The following tables summarize key quantitative metrics from recent studies directly comparing Oxford Nanopore and Sanger sequencing for genotyping drug resistance markers.

Table 1: Overall Concordance and Accuracy Metrics

Pathogen	Gene/Marker Target	Sequencing Technology	Concordance with Reference	Sensitivity for Minority Variants	Key Findings	Source
Plasmodium falciparum	6 microhaplotypes	ONT AmpSeq	N/A	1% (in polyclonal mixtures)	Robust reproducibility (intra-assay: 98%; inter-assay: 97%)	[3]
HIV-1	Near-full-length genome (DR genotypes)	ONT (Duplex reads)	92.5% (DR), 98.1% (tropism)	15% threshold	Duplex reads >10x more accurate than simplex; required ≥100x coverage	[65]
HIV-1	Transmitted/Founder virus identification	ONT	89.7% sensitivity	N/A	Sequence similarity with Sanger-derived T/Fs averaged 99.81%	[66]
Oncohematology	15 gene panel	MinION	99.43%	<1% (VAF equivalent to NGS)	Offers significant advantage over Sanger in sensitivity and speed	[21]

Table 2: Technical and Operational Characteristics

Parameter	Sanger Sequencing	Oxford Nanopore Technology (MinION)
Single-Read Accuracy	>99% [21]	>99% (after basecalling & filtering) [21] [3]
Typical Sensitivity (VAF)	15–20% [21]	<1% (comparable to NGS) [21]
Limit of Detection (Minority Clones)	~15-25% [65]	1% [2] [3]
Primary Error Type	Generally low error rate	Deletions more prevalent, especially in homopolymers [65]
Turnaround Time (TAT)	3–4 days [21]	2–3 days; can be under 24 hours for urgent cases [21]
Key Advantage for DR Calling	Established gold standard; low per-sample cost for single targets.	High sensitivity, long reads, rapid TAT, and portability for decentralized use.

Experimental Protocols and Methodologies

To critically assess the data presented in the performance tables, it is essential to understand the experimental workflows from which they were derived. The following sections detail the key methodologies used in the cited studies.

Nanopore Amplicon Sequencing forP. falciparumMicrohaplotypes

A 2025 study [3] developed a robust multiplexed AmpSeq assay to distinguish recrudescence from new infection in antimalarial drug trials. The detailed protocol is as follows:

• Multiplex PCR: A panel of six polymorphic microhaplotype loci (ama1, celtos, cpmp, cpp, csp, and surfin1.1) was amplified using a single, optimized multiplex PCR reaction. Primer pool concentrations and thermal cycling conditions were carefully calibrated to ensure uniform amplification across all targets.
• Library Preparation & Sequencing: Libraries were prepared using the Native Barcoding Kit 96 V14 (SQK-NBD114.96) on the MinION Mk1C platform with R10.4.1 flow cells. Sequencing was performed targeting approximately 25,000 reads per marker per sample.
• Bioinformatics & Haplotype Calling: Raw data was basecalled with Dorado (v0.8.2) using a super-accurate model, demultiplexed, and filtered for a minimum Q-score of 20. A custom bioinformatics workflow was used to infer haplotypes from polyclonal infections, applying rigorous cutoff criteria for accurate haplotype calling, including for minority clones.

Population-Based Nanopore Sequencing for HIV-1 Drug Resistance

A 2024 study [65] established a protocol for population-based nanopore sequencing of the HIV-1 pangenome to identify drug resistance mutations.

• Sample Preparation: Viral pangenomic DNA was amplified from clinical samples via PCR. To minimize the detection of PCR-induced errors, a mixture of three independent amplicons was subjected to sequencing.
• Sequencing Technology: The protocol utilized the latest ONT chemistry, including R10 flow cells and duplex sequencing, where the sequences of both strands of a DNA molecule are determined in succession. This method produces duplex reads with significantly higher accuracy than simplex reads.
• Variant Calling and Genotyping: The entire viral coding sequence (vCDS) was covered with a minimum of 100x duplex reads. A 15% threshold was set for detecting minority variants. Drug resistance genotypes were called using the ANRS algorithm by comparing the sequencing reads to a reference.

Computational Deconvolution of Sanger Chromatograms for Polyclonal Infections

A 2024 study [67] enhanced the utility of Sanger sequencing for polyclonal malaria infections through a novel computational deconvolution method.

• Principle: The method models the electropherogram data at the level of 3-base codons rather than single nucleotides or the entire chromatogram. This allows for the quantification of the relative percentages of different amino acids at each codon position.
• Validation: The approach was validated using laboratory mixtures of P. falciparum strains (V1/S and FCR3) at varying known proportions (0-100%). The predicted proportions showed a highly significant correlation with the measured proportions.
• Application: When applied to field samples, the method provided both the mean fraction of resistance alleles in individual samples and the prevalence of infections carrying resistant parasites, offering a more nuanced view of the parasite population.

The following diagram illustrates the core workflow for nanopore-based detection of drug resistance mutations, from sample to analysis:

Figure 1: Workflow for Nanopore-based Drug Resistance Genotyping. The process from sample collection to final drug resistance report, highlighting key steps like multiplex PCR and duplex sequencing that contribute to high accuracy.

Essential Research Reagent Solutions

The successful implementation of the described protocols relies on a set of key reagents and kits. The following table details these essential research solutions and their functions in the context of drug resistance mutation sequencing.

Table 3: Key Research Reagents and Kits for Sequencing Drug Resistance Markers

Reagent / Kit Name	Function in the Workflow	Specific Application Example
Native Barcoding Kit 96 V14 (SQK-NBD114.96) [3]	Allows for high-throughput, multiplexed library preparation by tagging individual samples with unique barcodes for pooled sequencing.	Used in the P. falciparum microhaplotype study to sequence 96 samples simultaneously on one MinION flow cell.
KAPA HiFi HotStart ReadyMix [9]	A high-fidelity PCR enzyme mix crucial for accurate amplification of target regions with minimal errors prior to sequencing.	Employed in metabarcoding studies for the amplification of the 18S rRNA V9 region from intestinal parasites.
R10.4.1 Flow Cells (ONT) [3]	The latest nanopore flow cell chemistry that provides improved raw read accuracy, which is fundamental for reliable variant calling.	Central to the high sensitivity and specificity achieved in the 2025 P. falciparum nanopore AmpSeq assay.
Fast DNA SPIN Kit for Soil [9]	DNA extraction kit optimized for complex biological samples, ensuring efficient lysis of tough pathogens and high-yield DNA recovery.	Used for extracting DNA from a variety of preserved helminth specimens and cultured protozoa.
Custom Bioinformatic Pipelines (e.g., with Dorado) [3]	Software for basecalling, demultiplexing, and read filtering. Essential for transforming raw electrical signals into high-quality, analyzable sequence data.	Critical for achieving a read accuracy of ≥99% in the P. falciparum study by applying a Q20 quality filter.

The choice between Oxford Nanopore and Sanger sequencing for calling drug resistance mutations is not a simple matter of one technology being universally superior. Instead, the decision should be guided by the specific requirements of the research or surveillance objective.

• For Maximum Sensitivity and Quantification of Complex Infections: ONT is the clear choice. Its ability to detect minority variants down to 1% [2] [3] and to handle polyclonal infections through deep amplicon sequencing provides a resolution that Sanger sequencing cannot match. This is critical for the early detection of emerging resistance and for understanding the dynamics of heterogeneous pathogen populations.
• For Routine Surveillance of Dominant Variants in a Single Gene: Sanger sequencing remains a reliable and cost-effective option, especially in labs with established infrastructure. Its high per-base accuracy is sufficient for identifying dominant resistance mutations present at levels above its 15-20% detection threshold [65] [21]. The recent development of computational deconvolution tools [67] can further extend its utility for semi-quantitative analysis of mixed infections.
• For Speed and Portability in Decentralized Settings: The portability of MinION devices and the potential for a turnaround time of under 24 hours [21] make ONT uniquely suited for rapid response and near-point-of-care surveillance, a significant advantage over the more time-consuming and centralized Sanger workflow.

In conclusion, while Sanger sequencing retains its utility for specific, targeted applications, Oxford Nanopore Technology offers a powerful, sensitive, and flexible alternative that is increasingly capable of meeting the complex demands of modern drug resistance research and surveillance. Its performance in terms of concordance, sensitivity, and throughput, as evidenced by recent studies, positions it as a transformative tool for guiding effective disease control strategies.

The ability to detect minority clones in polyclonal infections represents a critical challenge and opportunity in parasitology research, particularly for malaria. In high-transmission settings, polyclonal infections containing multiple genetically distinct parasite strains are highly prevalent, occurring in greater than 50% of sampled isolates in some regions [67]. These complex infections influence disease development, transmission rates, and the spread of drug resistance, making accurate genotyping essential for both research and public health surveillance [67].

The conventional approach to genotyping has historically faced limitations in discriminating mixed infections, often categorizing samples binarily as resistant or sensitive despite the potential presence of both sensitive and resistant alleles at varying proportions [67]. This simplification obscures the true complexity of parasite populations and may delay the detection of emerging resistance. Technological advancements in sequencing platforms now offer researchers powerful tools to characterize this diversity with unprecedented resolution.

This guide provides an objective comparison of two sequencing approaches—Oxford Nanopore Technologies (ONT) and Sanger sequencing—for detecting minority clones in polyclonal parasitic infections. By examining their respective experimental protocols, performance metrics, and practical applications, we aim to equip researchers with the data necessary to select appropriate methodologies for their specific research contexts, particularly within the framework of parasite genomics and antimalarial resistance surveillance.

Oxford Nanopore Technology (ONT)

Nanopore sequencing operates by measuring changes in electrical current as DNA molecules pass through protein nanopores. This platform offers several advantages for parasite genomics, including real-time sequencing, portability, long reads, and the ability to perform adaptive sampling for target enrichment [5] [3]. For minority variant detection, ONT's capacity for deep amplicon sequencing makes it particularly valuable.

Recent advancements in ONT chemistry have significantly improved its application in parasite research. The development of multiplexed amplicon sequencing (AmpSeq) panels targeting highly polymorphic microhaplotype loci has enabled high-resolution discrimination of parasite strains [3]. These panels demonstrate exceptional sensitivity in detecting minority clones at frequencies as low as 0.1% in polyclonal infections under controlled conditions [3] [68].

Sanger Sequencing

Sanger sequencing, based on Frederick Sanger's chain-termination method, has long been the gold standard for genetic analysis. While highly accurate for clonal samples, its limitation in resolving mixed infections stems from the binary nature of its chromatogram output, which becomes uninterpretable when multiple alleles are present at the same position [67].

To address this limitation, computational deconvolution approaches have been developed that transform Sanger sequencing from a qualitative to a quantitative tool. These methods analyze the chromatogram traces to quantify the relative proportions of different alleles present in a mixed infection [67]. This innovation has extended the utility of Sanger sequencing in resource-limited settings where next-generation sequencing platforms may be unavailable.

Performance Comparison

Table 1: Direct comparison of ONT and Sanger sequencing for detecting minority clones

Parameter	Oxford Nanopore Technology	Sanger Sequencing with Deconvolution
Sensitivity for Minority Clones	0.1% - 1% frequency [3] [68]	Quantitative across full range (0-100%) [67]
Specificity/False Positive Rate	<0.01% false haplotypes [3]	High correlation between predicted and measured proportions (p<0.001) [67]
Multiplexing Capacity	High (6-plex microhaplotype panel demonstrated) [3]	Limited to single amplicons per reaction
Throughput	High (96 samples multiplexed in one run) [3]	Low to moderate
Turnaround Time	~24 hours from sample to result [3]	Several days including computational analysis
Cost Considerations	Higher per-run costs but lower per-sample cost when multiplexed	Lower equipment costs but higher per-sample reagent costs
Portability/Field Deployment	MinION platform is portable and suitable for field use [5]	Requires traditional lab infrastructure
Reproducibility	Intra-assay: 98%; Inter-assay: 97% [3]	High correlation in repeated experiments [67]
Variant Calling in Mixed Infections	Direct haplotype inference from sequence data [3]	Computational deconvolution of chromatograms [67]

Table 2: Application-specific performance metrics

Application	ONT Performance	Sanger with Deconvolution Performance
Distinguishing Recrudescence from New Infection	85% consistency across paired samples (6 markers) [3]	Not specifically validated for this application
Antimalarial Resistance Monitoring	38 drug resistance loci compared to Sanger with high concordance [5]	Validated for Pfdhfr and Pfdhps resistance alleles [67]
Polyclonal Infection Analysis	Detects multiple clones and their relative abundances [3] [68]	Quantifies allele proportions at specific codons [67]
Limit of Detection	10 parasites/μL in laboratory strain mixtures [3]	Not explicitly stated but demonstrated with various dilution ratios [67]

Experimental Protocols

Oxford Nanopore Amplicon Sequencing Workflow

The nanopore amplicon sequencing approach for detecting minority clones involves a streamlined workflow that can be completed within 24-48 hours:

Sample Preparation and DNA Extraction:

• Collect patient blood samples (venous blood or dried blood spots) [17]
• Extract genomic DNA using commercial kits (e.g., DNeasy Powersoil Pro Kit) [69]
• Quantify DNA concentration and quality; note that high human DNA background is common in patient samples [5]

Multiplex PCR Amplification:

• Design primers targeting informative microhaplotype loci or resistance genes [3] [17]
• For Plasmodium falciparum, a 6-plex panel targeting highly diverse loci (ama1, celtos, cpmp, csp, etc.) has been validated [3]
• Optimize primer pool concentrations and reaction conditions to ensure uniform amplification [3]
• Include negative controls (nuclease-free water) and positive controls (e.g., laboratory strain FCB1) [3]

Library Preparation and Sequencing:

• Prepare sequencing libraries using Native Barcoding Kit (e.g., SQK-NBD114.96) [3]
• Pool barcoded libraries in equimolar ratios
• Load onto MinION flow cells (R10.4.1 chemistry recommended) [3]
• Sequence on MinION Mk1C platform with MinKNOW software
• Target approximately 25,000 reads per marker per sample to ensure sufficient depth for minority variant detection [3]

Data Analysis:

• Perform simplex basecalling and demultiplexing with Dorado basecaller using super-accurate (sup) model [3]
• Set minimum Q-score threshold of 20 (accuracy ≥99%) to minimize erroneous reads [3]
• Use custom bioinformatics workflows for haplotype inference from polyclonal infections [3]
• Apply rigorous cutoff criteria for accurate haplotype calling of minority clones [3]

Figure 1: Oxford Nanopore amplicon sequencing workflow for minority clone detection

Sanger Sequencing with Computational Deconvolution

The deconvolution method for Sanger sequencing chromatograms extends the technology's utility for analyzing mixed infections:

Sample Processing and PCR:

• Extract genomic DNA from clinical samples
• Amplify target genes (e.g., Pfdhfr, Pfdhps for antimalarial resistance) using standard PCR protocols [67]
• Include control samples with known allele mixtures for validation [67]

Sanger Sequencing:

• Purify PCR products
• Perform Sanger sequencing with standard capillary electrophoresis platforms
• Export chromatogram files for analysis [67]

Computational Deconvolution:

• Develop or utilize specialized software for chromatogram deconvolution
• The unique aspect of this approach is modeling 3-base codons as atomic units rather than single nucleotides or entire chromatograms [67]
• Algorithm quantifies relative percentages of observed protein amino acids directly from mixed chromatograms [67]
• Validate results using laboratory-created mixtures with known proportions of different alleles [67]

Data Interpretation:

• Calculate mean fraction of resistance alleles in individual samples [67]
• Determine prevalence of infections carrying resistant parasites in population studies [67]
• The output provides quantitative (percentage) rather than binary (present/absent) data for each allele [67]

Research Reagent Solutions

Table 3: Essential research reagents and materials for minority clone detection studies

Category	Specific Products/Assays	Application and Function
Sample Collection	Venous blood collection tubes; Dried blood spot (DBS) cards	Preserve patient samples for DNA analysis [17]
DNA Extraction Kits	DNeasy Powersoil Pro Kit (Qiagen)	Extract high-quality genomic DNA from complex samples [69]
PCR Reagents	Multiplex PCR master mixes; Custom primer panels	Amplify target loci with high specificity and uniformity [3] [17]
Sequencing Kits	Native Barcoding Kit 96 V14 (SQK-NBD114.96); Flow cells (R10.4.1)	Prepare sequencing libraries; Generate sequence data [3]
Positive Controls	Laboratory P. falciparum strains (3D7, K1, HB3, FCB1); Synthetic plasmids with control SNPs	Validate assay performance and monitor contamination [3] [17]
Analysis Software	Dorado basecaller; Custom haplotype inference pipelines; Chromatogram deconvolution tools	Process sequence data and identify minority variants [3] [67]
Validation Tools	Sanger sequencing platforms; Laboratory strain mixtures at defined ratios	Confirm results and establish sensitivity limits [3] [67]

Discussion and Research Implications

The comparison between Oxford Nanopore and Sanger sequencing for detecting minority clones reveals complementary strengths that serve different research needs. ONT amplicon sequencing provides superior throughput, sensitivity, and ability to simultaneously monitor multiple genetic loci, making it ideal for large-scale surveillance studies and clinical trials where distinguishing recrudescence from new infection is critical [3]. The technology's portability further enhances its utility for decentralized surveillance in endemic regions [5] [17].

Sanger sequencing with computational deconvolution offers a cost-effective, quantitative approach for focused surveillance of known resistance markers, particularly in settings with limited infrastructure [67]. Its ability to provide quantitative data on allele frequencies without requiring deep sequencing makes it valuable for monitoring the emergence and spread of specific resistance mutations.

For researchers studying parasite evolution and transmission dynamics, the choice between platforms should consider the specific research questions, sample throughput requirements, available infrastructure, and the need for discovery versus monitoring of known variants. As both technologies continue to evolve, their combined application may offer the most comprehensive approach to understanding and managing polyclonal infections in parasite populations.

Turnaround Time and Cost-Benefit Analysis for Clinical and Research Settings

The field of parasitology demands diagnostic and research tools that are not only accurate but also rapid and cost-effective, especially in resource-limited settings where many parasitic diseases are endemic. For decades, Sanger sequencing has been the cornerstone of genetic analysis for parasite identification and research. However, the emergence of Oxford Nanopore Technologies (ONT) presents a compelling alternative, promising real-time sequencing and portability. This guide provides an objective comparison of the efficacy of Oxford Nanopore versus Sanger sequencing specifically for parasite research, based on current experimental data and cost analyses. The analysis is framed around two critical metrics for laboratory efficiency: turnaround time and cost-benefit, providing researchers and drug development professionals with the data needed to make informed technological choices.

Performance Comparison: Nanopore vs. Sanger

A direct comparison of the technical specifications and performance metrics of Sanger and Nanopore sequencing reveals a trade-off between raw accuracy and comprehensive, rapid data acquisition.

Table 1: Comparative Technical Specifications of Sanger and Oxford Nanopore Sequencing

Feature	Sanger Sequencing	Oxford Nanopore Sequencing
Sequencing Method	Dideoxy chain termination	Nanopore-based electronic sensing
Read Length	400–900 base pairs [21]	Up to megabase lengths [21]
Single-Run Time	20 minutes - 3 hours [21]	1 minute - 48 hours (real-time data) [21]
Typical Workflow TAT	3-4 days [21]	2-3 days (can be <24 hours for urgent cases) [21]
Sensitivity (Variant Detection)	15–20% [21]	<1% (comparable to NGS) [21]
Error Rate	~0.001% [21]	~5% (ongoing improvement with new chemistries) [21] [70]
Raw Read Accuracy	>99% (Q>20) [21]	~96.84% (Q15) [70]
Key Applications in Parasitology	Single-gene variant analysis, confirmation of known targets	Species identification, coinfections detection, resistome analysis, genome assembly [71] [50]

The data shows that while Sanger sequencing offers a lower error rate, ONT provides significant advantages in speed, read length, and the ability to detect low-frequency variants. For parasite research, the long reads of ONT are particularly beneficial for differentiating between closely related species and resolving complex genomic regions.

Turnaround Time Analysis in Practice

Turnaround time (TAT) is a critical factor in both clinical diagnostics and research. The defining feature of ONT—real-time data generation—fundamentally alters the TAT equation. With ONT, data analysis can begin minutes after a run starts, unlike Sanger or other NGS methods that require the run to complete before analysis [21] [10].

Evidence from clinical metagenomics studies demonstrates this practical impact. One study reported preliminary pathogen identification from respiratory samples within two hours of starting sequencing, with final reports delivered within 24 hours for 94% of samples [10]. Another study adapting the same protocol for a paediatric population successfully identified causative pathogens within 24 hours [10]. This rapid TAT is instrumental for timely therapeutic decisions and antimicrobial stewardship.

In a dedicated parasitology application, researchers developed a targeted ONT test for blood parasites that successfully detected Trypanosoma brucei rhodesiense, Plasmodium falciparum, and Babesia bovis in spiked human blood samples [71]. The workflow—from sample to result—was designed for settings requiring rapid answers, leveraging the portability and speed of the MinION platform.

Cost-Benefit Considerations

A comprehensive cost-benefit analysis must extend beyond the list price of equipment to include consumables, labor, and the value of faster results.

Initial Investment and Consumables

Table 2: Cost Overview of Oxford Nanopore Sequencing Platforms and Kits

Product Category	Product Name	Description	List Price (USD)
Sequencing Devices	MinION Mk1D Pack	Portable sequencer; includes device and support [72]	$4,950.00
	GridION	Benchtop; runs up to five MinION flow cells [72]	$58,800.00
Flow Cells	MinION Flow Cell		~$500 - $900 each [73]
Library Prep Kits	Ligation Sequencing Kit V14	Standard kit for genomic DNA [72]	$690.00
	16S Barcoding Kit 24 V14	For genus-level bacterial identification [72]	$1,100.00
	Microbial Amplicon Barcoding Kit 24 V14	For full-length 16S/ITS profiling [72]	$800.00

The table shows a range of entry points for ONT. The portable MinION, at under $5,000, requires minimal capital investment, making it accessible for individual labs or field work [72]. For higher throughput, the GridION and PromethION systems are available.

Consumable costs are a major factor. A single MinION flow cell can generate up to 50 Gb of data [73], which can be partitioned for multiple samples via barcoding. For example, the Native Barcoding Kit 24 V14 ($800) allows for multiplexing 24 samples on a single flow cell [72], significantly reducing the per-sample cost.

Strategic and Operational Benefits

The cost-benefit analysis must also consider strategic advantages:

• Scalability and Flexibility: ONT's ability to run a single flow cell without wasting capacity is a key advantage over high-throughput Illumina runs for low-to-medium sample volumes [74]. This "pay-as-you-go" model is highly cost-effective for labs without a constant, high stream of samples.
• Workflow Consolidation: ONT can detect a wide range of genetic variation (SNVs, INDELs, structural variants, methylation) in a single assay [21] [10]. This can replace multiple legacy methods (including Sanger), potentially saving on reagent costs, labor, and TAT.
• Elimination of Capital Equipment: The MinION device itself is relatively low-cost and plugs into a laptop via USB, eliminating the need for multi-million dollar sequencing infrastructure [74].

Experimental Protocols for Parasite Research

The application of ONT in parasitology is demonstrated through specific, validated experimental protocols.

Protocol 1: 18S rDNA Barcoding for Blood Parasite Identification

This protocol is designed for comprehensive detection and species-level identification of eukaryotic blood parasites from the phyla Apicomplexa and Euglenozoa [71].

Key Research Reagent Solutions:

• Primers F566 and 1776R: Universal primers amplifying the V4–V9 hypervariable regions of the 18S rDNA gene, producing a >1 kb amplicon for improved species resolution [71].
• Blocking Primers (3SpC3Hs1829R and PNAHs18S_513): Designed to bind specifically to host (human or mammalian) 18S rDNA. Their modifications (C3 spacer or Peptide Nucleic Acid) inhibit polymerase elongation, selectively reducing host DNA amplification and enriching for parasite DNA [71].
• Oxford Nanopore Microbial Amplicon Barcoding Kit (SQK-MAB114.24): Used for library preparation from the PCR amplicons, enabling multiplexing of up to 24 samples per sequencing run [72].

Workflow Diagram:

Diagram Title: Workflow for Blood Parasite ID via 18S rDNA Barcoding

Protocol 2: hsp70 Gene Sequencing forLeishmaniaSpeciation

This protocol uses a longer amplicon of the heat-shock protein 70 (hsp70) gene to achieve precise identification of Leishmania species and detect coinfections [50].

Key Research Reagent Solutions:

• HSP70-Long Primers: A novel primer set generating a 771-bp amplicon from the hsp70 gene. The increased length, compared to a previously published 330-bp target, captures more nucleotide variation, enhancing discriminatory power for closely related Leishmania species [50].
• HSP70-Short Primers: A previously published primer set generating a 330-bp amplicon. It offers high analytical sensitivity but potentially lower species resolution than the longer amplicon [50].
• Ligation Sequencing Kit (SQK-LSK114): A standard ONT library prep kit used for sequencing the generated hsp70 amplicons, optimized for high raw read accuracy (Q20+) [72] [50].

Workflow Diagram:

Diagram Title: Workflow for Leishmania Species Identification

The choice between Oxford Nanopore and Sanger sequencing for parasite research is not a simple matter of declaring one superior to the other. Instead, it depends heavily on the specific requirements of the project.

• Sanger sequencing remains a robust, highly accurate, and likely cost-effective choice for projects focused on a single, known genetic target or for confirming a limited number of specific variants. Its lower per-sample cost for very small batches and high raw accuracy are its key strengths.

• Oxford Nanopore sequencing is a transformative technology for applications requiring speed, comprehensive genomic characterization, and scalability. Its major advantages are the dramatically reduced turnaround time (enabling same-day results), the ability to detect coinfections and mixed strains, and its portability for field deployment. The higher error rate is a consideration but is often mitigated by high coverage and bioinformatic polishing, and is frequently an acceptable trade-off for the wealth of information gained.

For laboratories engaged in diverse parasitology research, from outbreak surveillance to species discovery and drug resistance monitoring, ONT offers a versatile and powerful platform that can consolidate multiple workflows into one, providing rapid, actionable data that can directly influence research directions and clinical outcomes.

Comparative Analysis with Other NGS Platforms like Illumina

The field of parasitology is undergoing a significant transformation, driven by the need for more precise, efficient, and accessible diagnostic tools. For decades, Sanger sequencing has served as the gold standard for characterizing genetic variants in short DNA fragments, providing high accuracy for targeted sequencing of individual genes or small genomic regions [21]. However, the growing demands for comprehensive genomic surveillance, outbreak investigation, and the detection of mixed infections necessitate technologies with higher throughput and scalability. Within this context, Next-Generation Sequencing (NGS) platforms, particularly Illumina and Oxford Nanopore Technologies (ONT), have emerged as powerful tools. This guide provides an objective, data-driven comparison of these platforms, framing their efficacy within the specific application of parasite research and diagnostics. The choice between these technologies often involves a trade-off between the high accuracy and maturity of Illumina and the long-read capability, portability, and real-time analysis of ONT, a decision that must be informed by the specific requirements of the parasitological study.

Understanding the fundamental sequencing principles of each platform is crucial for evaluating their performance characteristics. The table below summarizes the core technologies and their implications for parasite research.

Table 1: Fundamental Sequencing Technologies and Characteristics

Feature	Sanger Sequencing	Illumina (Short-Read)	Oxford Nanopore (Long-Read)
Sequencing Principle	Dideoxy chain termination	Sequencing by synthesis	Nanopore-based electronic sensing
Read Length	400–900 base pairs [21]	50–500 base pairs [21]	Up to megabases [21] [75]
Primary Applications	SNVs and INDELs detection [21]	SNVs, INDELs detection, metabarcoding [21] [9]	SNVs, INDELs, complex structural variants, direct RNA/epigenetic detection [21] [75]
Key Parasitology Differentiator	Targeted confirmation; single-gene diagnostics	High-sensitivity variant detection; metabarcoding	Genome assembly; surveillance of complex regions; field deployment

The most significant differentiator is read length. Illumina produces massive volumes of ultra-short reads, which are excellent for detecting single-nucleotide variants but struggle to resolve repetitive or structurally complex genomic regions common in parasite genomes [75]. In contrast, ONT generates long reads that can span these difficult regions, enabling more complete genome assemblies and the detection of large structural variations, such as the gene deletions underlying rapid diagnostic test failure in Plasmodium falciparum [12].

Performance Comparison: Quantitative and Qualitative Metrics

A direct comparison of key performance metrics reveals the inherent strengths and limitations of each platform for parasitology applications.

Table 2: Comparative Performance Metrics for Parasite Research

Performance Metric	Sanger Sequencing	Illumina	Oxford Nanopore
Single-Read Accuracy	>99% [21]	>99% [21]	>99% (with Q20+ chemistry) [75] [22]
Consensus Accuracy (QV)	N/A	Very High (QV40+)	High (e.g., Q50 at 10-20x coverage for bacterial mock community) [22]
Sensitivity (VAF)	15–20% [21]	~1% [21]	<1% [21]
Typical Turnaround Time	3–4 days [21]	Around 48 hours to 14 days [21]	1 min – 48 hrs; can be under 24 hrs [21]
Portability & Scalability	Benchtop machines	Large, centralized instruments	Portable (MinION); scalable (GridION, PromethION)
Cost per Sample	Low for few targets	Lower for high-throughput	Flexible; can be cost-effective for targeted panels (e.g., ~$25/sample for malaria panel) [12] [18]

Sensitivity and Specificity: In a direct comparison for detecting aquatic parasites, one study found that Illumina sequencing remained more efficient at assigning reads to a species level. However, Nanopore sequencing under optimal conditions showed similar detection rates for a host species (Pseudorasbora parva) and even detected an intracellular cryptic parasite (Sphaerothecum destruens) that Illumina failed to identify, highlighting how bioinformatic pipelines and technological error profiles can influence outcomes [19].

Turnaround Time and Portability: The real-time nature of ONT sequencing offers a dramatic reduction in time-to-result. This is critical during outbreak responses, as demonstrated during the Ebola and COVID-19 pandemics [75]. For routine parasitology, ONT enables same-day diagnosis, which was leveraged for malaria surveillance across sub-Saharan Africa, processing samples from dried blood spots in under 29 hours from DNA extraction to result [18].

Applications in Parasite Research: Experimental Data and Protocols

The theoretical advantages of each platform are best understood through their practical application in parasitology research.

Genomic Surveillance and Drug Resistance Monitoring

Malaria Surveillance with Targeted Nanopore Sequencing: A significant application of ONT is the flexible and cost-effective genomic surveillance of Plasmodium falciparum.

• Experimental Protocol: Researchers developed an approach using the NOMADS8 and NOMADS16 amplicon panels, targeting genes associated with antimalarial drug resistance and diagnostic test evasion.
  • Input: DNA extracted from dried blood spots (DBS).
  • Target Enrichment: A reduced-volume selective whole-genome amplification (sWGA) is performed, followed by a multiplex PCR using primers designed with the multiply software.
  • Library Prep & Sequencing: Amplicons are barcoded and pooled using a one-pot protocol, then sequenced on a MinION flow cell (R9.4.1 or R10.4.1).
  • Analysis: Real-time basecalling and variant calling are performed on a laptop [12] [18].
• Supporting Data: This protocol, costing approximately USD $25 per sample, provided robust coverage of target genes and accurately detected drug-resistance mutations and hrp2/3 deletions across over 1,000 DBS samples sequenced in local African labs [12] [18].

Species Identification and Detection of Coinfections

Leishmania Species Identification with Amplicon Sequencing: Both Illumina and ONT have been applied to the challenging task of distinguishing Leishmania species, which is crucial for determining clinical prognosis and treatment.

• Experimental Protocol (ONT):
  • DNA Extraction: From clinical samples (e.g., skin lesions, blood).
  • PCR Amplification: Using primers targeting the hsp70 gene. Studies have compared a shorter ~330 bp fragment (HSP70-Short) and a longer ~771 bp fragment (HSP70-Long) for improved discriminatory power.
  • Library Prep & Sequencing: Amplicons are prepared for sequencing on the MinION platform.
  • Analysis: Real-time basecalling and phylogenetic analysis for species assignment [50].
• Supporting Data: The hsp70-based MinION sequencing demonstrated high specificity and was successful not only in discriminating diverse Leishmania species but also in identifying coinfections with multiple species in samples from humans, dogs, and cats [50]. While ONT offers rapid turnaround, Illumina-based 18S rRNA metabarcoding has also been successfully used for the simultaneous detection of multiple intestinal parasites (e.g., Clonorchis sinensis, Strongyloides stercoralis), though factors like DNA secondary structure and PCR conditions can bias read abundance [9].

Metagenomic Analysis of Complex Samples

16S/18S rRNA Metabarcoding for Microbiome and Parasite Detection: Both platforms can be used for amplicon-based metagenomic studies to characterize microbial communities, including parasites.

• Experimental Protocol (ONT for 16S rRNA):
  • Sample Processing: Bead-beating of clinical samples from sterile sites (e.g., tissue, CSF).
  • DNA Extraction: Using one of several validated kits.
  • Full-Length 16S rRNA PCR: Amplifying the entire ~1500 bp gene.
  • ONT Sequencing & Analysis: Sequencing on MinION and using bioinformatic pipelines for taxonomic classification [11].
• Supporting Data: A key advantage of ONT in this context is its ability to sequence the full-length 16S rRNA gene, which provides higher taxonomic resolution than the short hypervariable regions typically sequenced by Illumina. Furthermore, ONT is superior for analyzing polymicrobial infections, as it overcomes the issue of mixed electropherograms that renders Sanger sequencing ineffective in these cases [11].

The Scientist's Toolkit: Essential Research Reagents and Materials

Successful implementation of these sequencing technologies relies on a suite of specialized reagents and kits.

Table 3: Key Research Reagent Solutions for Parasite Sequencing

Item	Function/Description	Example Use Case
Dried Blood Spot (DBS) Cards	Non-invasive, easy-to-collect source material for DNA; ideal for field collection and transport.	Genomic surveillance of Plasmodium falciparum in remote settings [12] [18].
Selective Whole-Genome Amplification (sWGA) Kits	Enriches parasite DNA from a background of host DNA, improving sequencing yield.	Preparation of P. falciparum samples from human DBS for targeted sequencing [12].
Target-Specific Multiplex PCR Panels	Amplifies multiple genomic targets of interest in a single reaction for targeted sequencing.	NOMADS panel for malaria drug-resistance genes [12]; hsp70 primers for Leishmania speciation [50].
ONT Ligation Sequencing Kits	Prepares DNA libraries for sequencing by attaching motor proteins and adapters to dsDNA.	Standard whole-genome and amplicon sequencing of parasites (e.g., Kit V14) [22].
ONT Native Barcoding Kits	Allows for multiplexing of multiple samples on a single flow cell by attaching unique barcode sequences.	Cost-effective sequencing of dozens of parasite isolates simultaneously [75].
High-Accuracy Basecalling Models (e.g., Dorado SUP)	Software models that translate raw electrical signals into nucleotide sequences with very high accuracy.	Essential for sensitive variant calling and consensus generation in parasite genomes [75] [22].

The comparative analysis of Sanger, Illumina, and Oxford Nanopore technologies reveals a landscape defined by complementary strengths. Sanger sequencing retains its niche for low-throughput, targeted confirmation. Illumina remains the leader for applications demanding the highest possible base-level accuracy and cost-effectiveness for high-volume, short-read projects, such as broad metabarcoding studies. However, Oxford Nanopore Technology offers a compelling and often superior alternative for a wide range of parasite research applications, particularly those that benefit from long reads, rapid turnaround, and portability. The ability of ONT to generate complete haplotypes, detect structural variants, and provide real-time data in the field is transforming genomic surveillance, outbreak response, and the diagnosis of complex parasitic infections. The choice of platform must ultimately align with the specific experimental goals, weighing factors such as the required resolution, the need for speed, the complexity of the genomic target, and the operational environment.

Distinguishing recrudescence (treatment failure) from new infections is critical for accurate assessment of antimalarial drug efficacy in clinical trials. Traditional methods relying on capillary electrophoresis of size-polymorphic markers face limitations in resolving complex, polyclonal infections common in high-transmission areas. This case study compares the performance of Oxford Nanopore Technologies (ONT) sequencing against the established Sanger sequencing method for molecular genotyping, demonstrating how nanopore-based approaches provide superior resolution, sensitivity, and operational flexibility for determining treatment outcomes.

In antimalarial clinical trials, patients with recurrent parasitemia after treatment can experience either recrudescence (true treatment failure where the original infection persists) or a new infection (from a new mosquito bite) [76]. Misclassifying these outcomes directly impacts drug efficacy estimates. In high-transmission settings where mixed-strain infections are common, the interpretation of genotyping results has a major impact on efficacy estimates—with failure rates for some drug combinations varying from 12% to 57% depending on how mixed infections are classified [76].

The World Health Organization recommends genotyping with capillary electrophoresis of size-polymorphic markers (msp1, msp2, and microsatellites) to distinguish these outcomes. While Sanger sequencing provides higher-resolution single nucleotide polymorphism (SNP) data, its implementation in field settings and for processing large sample volumes has been limited. This case study examines how nanopore sequencing addresses these limitations while maintaining analytical rigor.

Technological Comparison: Oxford Nanopore vs. Sanger Sequencing

Table 1: Platform Characteristics Comparison

Feature	Oxford Nanopore Technologies	Sanger Sequencing
Portability	USB-powered, portable (MinION)	Laboratory-bound equipment
Read Length	Long reads (1,654-2,736 bp average) [4]	Short reads (∼800-1000 bp)
Throughput	High-throughput, scalable	Low to moderate throughput
Cost Model	Lower initial instrument investment	High instrument costs
Turnaround Time	Rapid (library prep <4 hours, real-time analysis)	Slower (typically days)
Error Profile	Mainly indels in homopolymer regions [4]	Mainly substitution errors
Polyclonal Detection	Excellent for minority clones (sensitivity to 1%) [3]	Limited for minority variants
Data Analysis	Real-time basecalling, requires bioinformatics pipeline	Direct chromatogram interpretation

Experimental Data: Performance Comparison

Analytical Performance Metrics

Table 2: Performance Metrics for Malaria Parasite Genotyping

Parameter	Oxford Nanopore Technologies	Sanger Sequencing
SNP Calling Precision	1.0 (with R9.4 flow cells) [4]	>0.99
SNP Recall Rate	0.97 (with R9.4 flow cells) [4]	>0.99
Minority Clone Detection	1:100:100:100 ratio sensitivity [3]	Limited to ∼20% minority
Assay Reproducibility	Intra-assay: 98%; Inter-assay: 97% [3]	>99%
Multiplexing Capacity	6-plex microhaplotype panel demonstrated [3]	Typically single-plex
Genetic Diversity Resolution	High (HE=0.99 for cpmp marker, 28 haplotypes) [3]	Moderate

Clinical Sample Performance

In a direct evaluation using 20 paired patient samples from a multicenter clinical trial, the nanopore amplicon sequencing approach consistently distinguished recrudescence from new infections in 17/20 cases (85%) across all six microhaplotype markers [3]. The assay demonstrated robust performance across diverse sample types with parasitemia ranging from 31 to 33,930 parasites/μL [3].

For drug resistance profiling, nanopore sequencing of 38 drug resistance loci showed high concordance with Sanger sequencing results, suggesting sufficient quality for addressing common clinical research questions [5]. The technology has proven effective for genotyping key drug-resistance-associated genes including PfCRT, PfMDR1, PfDHFR, PfDHPS, and K13 [4].

Detailed Methodologies

Nanopore Amplicon Sequencing Workflow

The optimized protocol for distinguishing recrudescence from new infection involves these critical steps:

• DNA Extraction: From whole blood samples (minimum 10 parasites/μL)
• Multiplex PCR: Six polymorphic microhaplotype loci (ama1, celtos, cpmp, cpp, csp, and surfin1.1) amplified using barcoded primers [3]
• Library Preparation: Native Barcoding Kit 96 V14 (SQK-NBD114.96) with R10.4.1 flow cells
• Sequencing: MinION Mk1C platform with MinKNOW software (target: 25,000 reads/marker/sample)
• Bioinformatics: Dorado basecalling (sup model, q-score ≥20) followed by haplotype inference using population-frequency-aware algorithms [3]

Adaptive Sampling for Whole Genome Enrichment

For comprehensive genomic surveillance, adaptive sampling provides an innovative enrichment approach:

• Sample Preparation: Unenriched patient blood samples (0.1%-0.6% parasitemia)
• Sequencing with Selection: MinION flow cells with half channels in adaptive sampling mode
• Real-Time Enrichment: Reads matching human reference genome ejected after ∼400 bases
• Data Generation: 3- to 5-fold enrichment of Plasmodium bases achieved [5]

This method enables sufficient genome coverage (97% of reference at median depth 5-355×) without prior laboratory enrichment, significantly simplifying the workflow from blood collection to sequencing [5].

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagents for Nanopore-Based Genotyping

Reagent/Kit	Application	Function	Specific Example
Native Barcoding Kit 96 V14	Library preparation	Attaches barcodes for multiplexing	SQK-NBD114.96 [3]
R10.4.1 Flow Cells	Sequencing	Improved accuracy for SNP calling	84.56% read identity [4]
Microhaplotype Primer Panels	Target amplification	Amplifies polymorphic loci	6-plex: ama1, celtos, cpmp, cpp, csp, surfin1.1 [3]
Plasmodipur Filters	Sample preparation	Selective removal of human WBCs	15.7% human read retention [5]
Dorado Basecaller	Data processing	Real-time basecalling with quality filtering	q-score ≥20 (accuracy ≥99%) [3]

Comparative Workflow Analysis

Oxford Nanopore sequencing represents a paradigm shift for molecular genotyping in antimalarial clinical trials. The technology demonstrates equivalent accuracy to Sanger sequencing for SNP calling while providing superior resolution for detecting minority clones in polyclonal infections [4] [3]. The portability and rapid turnaround of nanopore sequencing make it particularly valuable for endemic regions where timely drug efficacy data is critical for public health response [5].

For researchers designing clinical trials in high-transmission settings, nanopore sequencing offers a robust, field-deployable solution that maintains analytical precision while expanding the scope of genotyping analysis. As the technology continues to evolve with improved chemistry and bioinformatics, it is poised to become the standard methodology for molecular correction in antimalarial efficacy studies.

Conclusion

The choice between Oxford Nanopore and Sanger sequencing is not a simple replacement but a strategic decision based on project goals. Sanger sequencing remains the robust, cost-effective choice for high-confidence, targeted genotyping of known variants. In contrast, Oxford Nanopore technology offers a transformative, all-in-one solution for discovery-based research, providing unparalleled capabilities in resolving complex co-infections, uncovering novel structural variants, and generating complete genomes with rapid, field-deployable workflows. For the future of parasitology, an integrated approach is emerging: using Nanopore for broad, real-time surveillance and discovery, with Sanger serving as a final validation step for critical mutations. This synergy will accelerate genomic surveillance, refine drug efficacy trials, and ultimately empower more effective, data-driven control of parasitic diseases globally.

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