Using a mobile nanopore sequencing lab for end-to-end genomic surveillance of Plasmodium falciparum: A feasibility study

Sensitive and modular amplicon sequencing of Plasmodium falciparum diversity and resistance for research and public health

Targeted amplicon sequencing is a powerful and efficient tool for interrogating the Plasmodium falciparum genome, generating actionable data from infections to complement traditional malaria epidemiology. For maximum impact, genomic tools should be multi-purpose, robust, sensitive, and reproducible. We developed, characterized, and implemented MAD4HatTeR, an amplicon sequencing panel based on Multiplex Amplicons for Drug, Diagnostic, Diversity, and Differentiation Haplotypes using Targeted Resequencing, along with a bioinformatic pipeline for data analysis. Additionally, we introduce an analytical approach to detect gene duplications and deletions from amplicon sequencing data. Laboratory control and field samples were used to demonstrate the panel's high sensitivity and robustness. MAD4HatTeR targets 165 highly diverse loci, focusing on multiallelic microhaplotypes, key markers for drug and diagnostic resistance (including duplications and deletions), and CSP and potential vaccine targets. The panel can also detect non-falciparum Plasmodium species. MAD4HatTeR successfully generated data from low-parasite-density dried blood spot and mosquito midgut samples and detected minor alleles at within-sample allele frequencies as low as 1% with high specificity in high-parasite-density dried blood spot samples. Gene deletions and duplications were reliably detected in mono- and polyclonal controls. Data generated by MAD4HatTeR were highly reproducible across multiple laboratories. The successful implementation of MAD4HatTeR in five laboratories, including three in malaria-endemic African countries, showcases its feasibility and reproducibility in diverse settings. MAD4HatTeR is thus a powerful tool for research and a robust resource for malaria public health surveillance and control.

Performance of Molecular Inversion Probe DR23K and Paragon MAD4HatTeR Amplicon Sequencing Panels for Detection of Plasmodium falciparum Mutations Associated with Antimalarial Drug Resistance

Background

Molecular surveillance of drug-resistant Plasmodium falciparum is crucial for malaria control in endemic regions. Two targeted-resequencing tools, the Molecular Inversion Probe (MIP) drug resistance panel DR23K and the Multiplexed Amplicons for Drugs, Diagnostics, Diversity, and Differentiation using High-Throughput Targeted Resequencing (MAD4HatTeR) panel, are widely used to detect resistance genotypes. However, comparisons of their performance for genotyping drug resistance polymorphisms in malaria parasites and their comparative utility for other use cases is lacking.

Methods

To compare the performance of DR23K and MAD4HatTeR in terms of sequencing depth, sensitivity to minor alleles, and precision, each platform was used to evaluate SNP alleles and microhaplotypes in double- and triple-strain mixtures of well-characterized laboratory parasites at densities of 10, 100, 1,000, and 10,000 parasites/μL. In addition, 67 Ugandan field samples collected in 2022 were genotyped using each platform to assess performance and concordance.

Results

Across the four parasite densities, MAD4HatTeR exhibited superior sequencing depth (mean reads per locus: 144, 992, 1,153, and 1,300) compared to DR23K (mean unique molecular identifiers [UMIs] per locus: 1, 4, 49, and 364). For SNP detection, MAD4HatTeR achieved 100% sensitivity at 2% within-sample allele frequency (WSAF) at 1,000 and 10,000 parasites/μL, whereas DR23K achieved 100% sensitivity at 40% and 5% WSAF at these densities, respectively. Microhaplotype sensitivity was lower for both assays; MAD4HatTeR reached 69% sensitivity at 10 parasites/μL when WSAF was ≥ 10%, increasing to 100% sensitivity at 2% WSAF and 100 parasites/μL. DR23K had < 50% sensitivity at 10 and 100 parasites/μL. In field samples, which commonly contain polyclonal infections, high concordance was observed between the two methods for all SNPs (94%, 1,848/1,969) and polymorphic SNPs (88%, 898/1,019). All discrepancies were attributed to varied detection of minority alleles in mixed genotype infections.

Conclusions

MAD4HatTeR demonstrated higher sensitivity than DR23K, particularly at low parasite densities. Both assays showed strong concordance for genotyping key resistance mutations in field samples, supporting their reliability. These findings suggest MAD4HatTeR as the preferred assay for low-density parasite studies and microhaplotype analysis, while DR23K may be appropriate for specific applications with high-parasite density samples, where detection of minority alleles is not prioritized, or when more comprehensive genome coverage is required.

Development of a clinical metagenomics workflow for the diagnosis of wound infections

BACKGROUND

Wound infections are a common complication of injuries negatively impacting the patient's recovery, causing tissue damage, delaying wound healing, and possibly leading to the spread of the infection beyond the wound site. The current gold-standard diagnostic methods based on microbiological testing are not optimal for use in austere medical treatment facilities due to the need for large equipment and the turnaround time. Clinical metagenomics (CMg) has the potential to provide an alternative to current diagnostic tests enabling rapid, untargeted identification of the causative pathogen and the provision of additional clinically relevant information using equipment with a reduced logistical and operative burden.

METHODS

This study presents the development and demonstration of a CMg workflow for wound swab samples. This workflow was applied to samples prospectively collected from patients with a suspected wound infection and the results were compared to routine microbiology and real-time quantitative polymerase chain reaction (qPCR).

RESULTS

Wound swab samples were prepared for nanopore-based DNA sequencing in approximately 4 h and achieved sensitivity and specificity values of 83.82% and 66.64% respectively, when compared to routine microbiology testing and species-specific qPCR. CMg also enabled the provision of additional information including the identification of fungal species, anaerobic bacteria, antimicrobial resistance (AMR) genes and microbial species diversity.

CONCLUSIONS

This study demonstrates that CMg has the potential to provide an alternative diagnostic method for wound infections suitable for use in austere medical treatment facilities. Future optimisation should focus on increased method automation and an improved understanding of the interpretation of CMg outputs, including robust reporting thresholds to confirm the presence of pathogen species and AMR gene identifications.

Genomic identification of Oryctes rhinoceros nudivirus isolates, a biocontrol agent for coconut rhinoceros beetle

The coconut rhinoceros beetle (Oryctes rhinoceros, CRB) is a serious pest of coconut and oil palms. It is native to South and Southeast Asia and was inadvertently introduced to Samoa in 1909. It has invaded many other Pacific countries throughout the last century. Oryctes rhinoceros nudivirus (OrNV), a natural pathogen of CRB in its native range, was successfully introduced as a classical biocontrol agent and has effectively suppressed invasive CRB populations for decades. However, resurgence of CRB has been recorded, with new invasions detected in several Pacific Island Countries and Territories. Additionally, new populations of CRB are emerging in some invaded areas that have a degree of resistance to the virus isolates commonly released for CRB biocontrol. Here, we designed a fast and reliable tool for distinguishing between different OrNV isolates that can help with the selection process to identify effective isolates for management of new CRB invasions. A comparison of 13 gene/gene region sequences within the OrNV genome of 16 OrNV isolates from native and invaded ranges allowed us to identify unique Single Nucleotide Polymorphisms (SNPs). With these SNPs, we developed an assay using multiplex PCR-amplicon-based nanopore sequencing to distinguish between OrNV isolates. We found that as few as four gene fragments were sufficient to identify 15 out of 20 OrNV isolates. This method can be used as a tool to monitor the establishment and distribution of OrNV isolates selected for release as biocontrol agents in CRB-infected areas.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline

Background

Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources.

Methods

We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment.

Results

Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime.

Conclusions

The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.