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Life sciences · Journal article
PLOS Neglected Tropical Diseases · September 1, 2026
Early or partial results. Treat as a signal, not a conclusion.
This is a descriptive feasibility study of a novel offline metagenomic sequencing workflow for point-of-care pathogen detection deployed in three Burundian settings during suspected cholera cases. The work demonstrates that the technology can be operationalised in resource-limited settings and reveals that syndromic cholera diagnosis captures multiple bacterial causes, primarily Escherichia coli alongside Vibrio cholerae; however, the lack of a formal diagnostic accuracy framework, sample size reporting, and independent verification limits the strength of inference about clinical utility.
Uncontrolled diagnostic technology feasibility study. Patients with suspected cholera presenting at a health centre, district hospital, and refugee transit camp in Burundi. Intervention: Mobile, offline metagenomic sequencing workflow using long-read ONT sequencing with rapid taxonomic and antimicrobial resistance screening. Three sites in Burundi: a health centre, a district hospital, and a refugee transit camp.
V. cholerae signals detected in only a subset of suspected cholera cases, with many samples dominated by alternative bacterial taxa, most frequently Escherichia coli V. cholerae abundance correlated strongly with detection of the cholera toxin phage CTXφ, supporting differentiation between toxigenic signal and background exposure AMR genes detected across samples, providing early situational insight into resistance determinants among gastrointestinal bacteria
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This exploratory study suggests that metagenomics can improve aetiological differentiation in diarrhoeal outbreaks and reduce false-positive syndromic cholera diagnosis. However, the lack of diagnostic accuracy metrics (sensitivity, specificity, positive predictive value) and clinical outcome data means the findings should inform pilot validation studies rather than immediate deployment decisions.
A single-site deployment of a novel diagnostic technology in three Burundian settings showing feasibility and descriptive pathogen findings, lacking a formal clinical or diagnostic accuracy comparison to establish performance.
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This exploratory study suggests that metagenomics can improve aetiological differentiation in diarrhoeal outbreaks and reduce false-positive syndromic cholera diagnosis. However, the lack of diagnostic accuracy metrics (sensitivity, specificity, positive predictive value) and clinical outcome data means the findings should inform pilot validation studies rather than immediate deployment decisions.
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Abstract Background Cholera outbreaks remain a major public-health challenge in sub-Saharan Africa, where diagnostic capacity is limited and clinical case definitions are non-specific and reply heavily on syndromic diagnosis. Rapid identification of Vibrio cholerae is critical, yet cholera-suspected diarrhoea can have multiple infectious causes not captured by targeted diagnostics. Methods We evaluated a mobile, culture-independent metagenomic sequencing workflow for on-site detection of gastrointestinal pathogens directly from faecal samples in Burundi. The offline workflow combined long-read ONT sequencing with rapid, laptop-based taxonomic and antimicrobial resistance (AMR) screening and was deployed across a health centre, a district hospital, and a refugee transit camp. The frontline and real-time results were verified using both conventional culturing and in-depth bioinformatic analyses. Results V. cholerae signals were only detected in a subset of suspected cholera cases, while many samples were dominated by alternative bacterial taxa, most frequently Escherichia coli. V. cholerae abundance correlated strongly with detection of the cholera toxin phage CTXφ, supporting differentiation between toxigenic signal and background exposure. AMR genes were detected across samples, providing early situational insight into resistance determinants among gastrointestinal bacteria. Conclusions Mobile, offline metagenomic sequencing enables rapid frontline characterization of gastrointestinal disease, especially cholera-suspected, in resource-limited settings and complements existing diagnostics by improving etiological resolution and outbreak response. Author Summary Cholera remains a major cause of severe diarrhoeal disease in many low-resource settings, where diagnosis often relies on symptoms and limited laboratory testing. However, patients suspected of cholera can be infected by a wide range of other pathogens that are not detected by standard diagnostics. In this study, we evaluated a portable, sequencing-based approach that allows direct identification of pathogens from stool samples at the point of care, without the need for laboratory infrastructure, internet access, or culture. Using this approach in multiple settings in Burundi, including a health centre, hospital, and refugee camp, we found a subset of suspected cholera cases were associated with Vibrio cholerae. Other cases were also dominated by other bacteria, particularly Escherichia coli. We also detected antimicrobial resistance genes across samples, providing additional information relevant for treatment and surveillance. Our findings demonstrate that mobile metagenomic sequencing can improve the identification of disease causes directly in outbreak settings and help distinguish true cholera cases from other gastrointestinal infections. This approach has the potential to strengthen outbreak response, improve patient management, and support more accurate disease surveillance in resource-limited environments.
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