A multiplex assay to detect mosquito species, bloodmeal host source and Plasmodium in malaria vectors using nanopore amplicon sequencing
Data files
Jan 23, 2026 version files 55.02 KB
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minION_Sequences_TB_Uploaded_gDNA_20252901.txt
5.89 KB
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minION_Sequences_TB_Uploaded_rRNA_Bloodmeal_20252101.txt
2.75 KB
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minION_Sequences_TB_Uploaded_rRNA_PLasmodium_20252101.txt
5.23 KB
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NanoPlot_QC.sh
2 KB
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ONTrack_pipeline.sh
2.06 KB
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PCR_Data_Table_Final.csv
32.36 KB
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README.md
4.74 KB
Abstract
Multiple species of Anopheles mosquitoes transmit malaria around the world. Molecular methods are often employed to confirm vector species, detect parasites, and determine bloodmeal host sources; these assays are often performed separately and can be time-consuming and expensive. However, in this study, we show that the Oxford Nanopore Technologies (ONT) MinION Sequencer offers a cost-effective and efficient alternative to accurately identify mosquito species, host bloodmeal sources, and detect parasites simultaneously in malaria vectors. We sequenced 150 insectary-reared mosquitoes representing nine species and 150 blood-fed mosquitoes with one of five vertebrate blood sources. We also analyzed the presence of Plasmodium falciparum in 40 mosquito samples. A final combined assay integrated all three previously optimized assays into a single sequencing run, demonstrating the high throughput capability of the Nanopore sequencing platform. This run included 32 samples for each targeted amplicon, totaling 96 samples. For comparison, we sequenced all samples using a standard Sanger sequencing protocol. Our results showed that the MinION sequencing platform accurately identified all 9 mosquito species, five different bloodmeal hosts from the blood-fed mosquitoes up to 48 hours post blood feed, and detected P. falciparum in the 40 positive controls. The sequencing results obtained using the MinION platform exhibited high concordance with those from standard Sanger sequencing, as demonstrated by comparable similarity scores and correct mosquito species identification. This demonstrates that our MinION sequencing and analysis protocol offers a novel, highly precise, cost-effective solution for mosquito species identification, bloodmeal analysis, and parasite detection.
Description of the data and file structure
The data were generated to support a multiplex amplicon sequencing assay designed to detect mosquito species, bloodmeal host source, and Plasmodium infection using Oxford Nanopore sequencing technology. Experimental efforts included the collection of 150 mosquito specimens representing nine species, DNA extraction, targeted amplification of species-specific, host-specific, and Plasmodium-specific loci, and sequencing on the Oxford Nanopore MinION platform.
The dataset includes processed consensus sequences for mosquito species identification, bloodmeal source determination, and pathogen detection, along with associated PCR results.
Description of the data and file structure
- Consensus Sequence Files (
.txt)
Files:minION_Sequences_TB_Uploaded_gDNA_20252901.txtminION_Sequences_TB_Uploaded_rRNA_Bloodmeal_20252101.txtminION_Sequences_TB_Uploaded_rRNA_PLasmodium_20252101.txt
These files contain consensus sequences generated from Nanopore reads using ONTrack and Geneious Prime. Users can perform BLAST searches on these sequences to identify mosquito species, bloodmeal hosts, and Plasmodium infection.
- PCR Results (
PCR_Data_Table_Final.csv)
This CSV file contains processed PCR results, including sample identifiers, target loci, and amplification outcomes.
Workflow Overview:
- Raw sequencing data were basecalled using Guppy to generate FASTQ files.
- Read quality and length distributions were visualized using NanoPlot.
- Consensus sequences were generated using ONTrack or Geneious Prime.
- Consensus sequences were compared to reference databases using BLASTn for species, host, and Plasmodium identification.
Access information
Other publicly accessible locations of the data:
- Consensus sequences generated in this study have been deposited in NCBI GenBank and are publicly accessible under their respective accession numbers
Data was derived from the following sources:
- Reference sequences used for mosquito species, bloodmeal host, and Plasmodium identification were obtained from publicly available NCBI GenBank records.
Code/software
All executable code associated with this dataset has been removed from the README and is provided as a separate script file to improve readability and reusability.
Scripts included in this repository:
ONTrack_pipeline.sh
NanoPlot_QC.sh
Script descriptions:
NanoPlot_QC.sh
This shell script generates read quality metrics and read length distribution plots from Oxford Nanopore FASTQ files using NanoPlot. The script was used to assess sequencing quality prior to downstream consensus sequence generation. Outputs include summary statistics and graphical visualizations of read length and quality.
ONTrack_pipeline.sh
This shell script implements the ONTrack pipeline for processing Oxford Nanopore MinION amplicon sequencing data. The script concatenates FASTQ files when multiple files per barcode are present, converts FASTQ files to FASTA format, prepares an input directory for ONTrack, activates a conda environment, and executes the ONTrack R-based workflow to generate consensus sequences and BLAST-based species identifications.
Workflow relationship:
NanoPlot quality control was performed prior to consensus sequence generation. FASTQ files passing quality assessment were subsequently processed using the ONTrack pipeline.
Key software and tools include:
- Oxford Nanopore MinKNOW (v22.12.5) – Used for raw sequencing data acquisition and basecalling.
- Guppy (v6.4.6) – Performed basecalling of raw FAST5 files to generate FASTQ reads.
- ONTrack (v1.2) – Used to generate consensus sequences from Nanopore reads.
- Geneious Prime (v2024.1.1) – Assisted with sequence assembly, alignment, and visualization of consensus sequences.
- NanoPlot (v1.41.0) – Visualized read length distributions and quality metrics.
- Python (v3.11) with packages:
pandas– Data handling and organizationmatplotlibandseaborn– Plotting and visualizationBiopython– Sequence manipulation and BLAST integration
The script assumes that barcode-specific FASTQ files produced by Oxford Nanopore MinION sequencing are present in the working directory. Input files are copied into an ONtrack_input/ directory prior to execution. File paths referencing local installations of ONTrack may require modification by the user. Relative file paths are recommended to ensure reproducibility across computing environments.