Integrating responders' mental health into the Ebola outbreak response.
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Letter↗
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Results for “outbreak response”
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The return of measles: a dangerous comeback.
PURPOSE OF REVIEW: Measles has reemerged as a significant global public health threat, with increasing morbidity and mortality associated with declining vaccination rates. This review summarizes current global outbreaks, history of measles, vaccination and elimination status, vaccine hesitancy, and outbreak response and lessons learned highlighting different novel digital epidemiological tools. RECENT FINDINGS: Measles continues to surge worldwide with an estimated 11 million infections in 2024, which is more than prepandemic levels. Developing and developed countries are both facing measles outbreaks, with the United States at risk of losing measles elimination status. Recent studies have showed that worldwide percentages of two-dose measles vaccination were lower than 95% that is required to interrupt measles transmission in all WHO regions. Novel epidemiological tools such as interactive simulators, real-time use of dynamic models, serosurveillance, and others are transforming measles outbreak response and enable earlier outbreak detection, tracking, and targeted public health interventions. SUMMARY: Vaccine hesitancy is one of the top global health threats and developing a tailored evidence-based approach is necessary to establish and maintain measles elimination.
Humans↗
Evaluation of amplicon-based nanopore sequencing for foot-and-mouth disease viruses in clinical and environmental samples.
Foot-and-mouth disease (FMD) causes severe global economic loss, necessitating rapid viral characterization. Nanopore sequencing provides a simple, real-time workflow suitable for on-site outbreak response, addressing the limitations of conventional methods. In this study, we optimized a previously published amplicon-based protocol and used this method to characterize a diverse range of samples (vesicular fluid, epithelium, serum, nasal/oral swabs, and environmental samples) collected during FMD outbreaks in 2025 in the Republic of Korea. Of the 129 samples collected, we successfully recovered complete genomes from 37 samples and VP1 sequences from 85 samples. Amplifying the S-fragment in isolation and separately barcoding each pool of PCR amplicons markedly improved sequence recovery. Furthermore, sequencing success depended on viral load and sample type. Based on comparisons with real-time RT-PCR results, whole-genome sequence (WGS) recovery exceeded 77.3% at cycle threshold (Ct) values ≤25 across all clinical samples. In the Ct > 30 category, serum samples yielded the highest WGS recovery rates (44.4%). This rate was markedly higher than the success rates observed for epithelium (20.0%) and nasal swabs (9.1%), whereas oral swabs and environmental samples failed to yield any sequences (0%). However, VP1 recovery from environmental samples reached 80% at Ct ≤ 30 (8/10), providing an approach to enable non-invasive monitoring. These findings demonstrate that amplicon-based nanopore sequencing is a practical method for the rapid generation of genomic data during FMD outbreaks.IMPORTANCEAlthough rapid detection and genomic data analysis are crucial for effective foot-and-mouth disease (FMD) control, the collection of these data can be challenging for certain sample types and impacted by reduced viral loads that result from nationwide FMD vaccination. This study provides a practical solution through large-scale evaluation of an optimized amplicon-based nanopore sequencing protocol to enhance the sequencing success rates for both clinical and environmental samples. Using a modified protocol to enhance genome recovery, we demonstrated that sequence data could be retrieved from diverse sample types (even with high real-time RT-PCR cycle threshold values). We identified serum as the most suitable sample, with environmental sample sequencing allowing for non-invasive monitoring during outbreaks. These results support the use of nanopore sequencing for rapid genomic analysis, particularly in outbreak responses, such as rapid surveillance, emergency vaccine selection, and epidemiological monitoring.
Foot-and-Mouth Disease↗
ScITree: Scalable Bayesian inference of transmission tree from epidemiological and genomic data.
Phylodynamic models capture joint epidemiological-evolutionary dynamics during an outbreak, providing a powerful tool to enhance understanding and management of disease transmission. Existing phylodynamic approaches, however, mostly rely on various non-mechanistic or semi-mechanistic approximations of the underlying epidemiological-evolutionary process. Previous work by Lau and colleagues has shown that full Bayesian mechanistic models, without relying on these approximations, can enable highly accurate joint inference of the epidemiological-evolutionary dynamics including the unobserved transmission tree. However, the Lau method faces major computational bottlenecks. As the volume of genomic data collected during outbreaks continues to grow, it is crucial to develop scalable yet accurate phylodynamic methods. Here we propose a new Bayesian phylodynamic model, overcoming the major scalability issue in the previous method and enabling a readily deployable, yet accurate, phylodynamic modeling framework. Specifically, we develop a scalable spatio-temporal phylodynamic framework for inferring the transmission tree (ScITree) and other key epidemiological parameters considering the infinite sites assumption in modeling mutation on the sequence level, in contrast to the Lau method in which mutation was modeled explicitly on the nucleotide level. Our approach features full Bayesian implementation utilizing an exact likelihood to mechanistically integrate epidemiological and evolutionary processes. We develop a computationally-efficient data-augmentation Markov Chain Monte Carlo algorithm, inferring key model parameters and unobserved dynamics including the transmission tree. We assess performance of our method using multiple simulated outbreak datasets. Our results indicate that our method can achieve high inference accuracy, comparable to the performance of the Lau method. Additionally, our method scales significantly more efficiently for large outbreaks, with computing time increasing linearly with outbreak size, compared to the exponential scaling of the Lau method. We also demonstrate our method's utility by applying our validated modeling framework to a dataset describing a foot-and-mouth disease outbreak in the UK. Our results show that our method is able to generate estimates of the transmission dynamics consistent with those from the prior method, further demonstrating the robustness of our new approach. In summary, our method provides a computationally-efficient, highly scalable, accurate modeling framework for inferring the joint spatio-temporal dynamics of epidemiological and evolutionary processes, facilitating timely and effective outbreak responses in space and time. Our method is implemented in our R package ScITree.
Bayes Theorem↗
Saliva versus lesion swabs for PCR diagnosis of acute-phase clade Ib mpox in Uganda: a prospective matched hospital cohort study.
BACKGROUND: As clade Ib mpox expands through HIV-affected populations in east and central Africa, diagnostic specimen selection should balance accuracy, accessibility, and operational feasibility in outbreak settings. Here, we aimed to compare the diagnostic performance of matched plasma, saliva, genital, anal, and skin specimens during the acute rash phase of clade Ib mpox to identify clinically practical and high-yield sampling approaches for outbreak response and clinical care. METHODS: We conducted a prospective cohort study of 155 adults (median age 30 years, IQR 25-36) hospitalised at Uganda's national mpox referral hospital. The specimens were collected between March 3 and April 10, 2025, during the clade Ib outbreak. All participants were admitted with suspected mpox and were subsequently confirmed by MPXV PCR. We collected 836 clinical specimens (acid citrate dextrose plasma, saliva, genital swabs, anal swabs, and skin swabs) during the acute phase (visit 1; 14 days [SD 2] after systemic symptom onset) and at approximately 3 months (visit 2). A matched acute-phase subset (n=80) provided concurrent plasma, saliva, genital, and skin specimens for within-participant comparisons. MPXV DNA was quantified by F3L real-time quantitative PCR, and cycle threshold (Ct) values were compared using paired Wilcoxon signed-rank tests. Whole-genome sequencing of selected acute specimens confirmed clade assignment. FINDINGS: In the matched subset at visit 1, PCR positivity was high in saliva (78 [98%] of 80), skin swabs (78 [98%] of 80), and genital swabs (77 [96%] of 80). Results for the saliva closely mirrored genital and skin swab results, supporting saliva as a high-yield alternative when lesion sampling is painful, operationally difficult, or unacceptable. Plasma had substantially lower sensitivity (34 [43%] of 80) and showed poor agreement with mucocutaneous compartments. At 3 months, persistent MPXV DNA was rare (ten [9%] of 109) and clustered among people with HIV, including the only two participants with persistent plasma positivity. All sequenced genomes clustered within clade Ib. INTERPRETATION: During the established rash phase (14 days [SD 2] after onset), saliva provides diagnostic yield similar to that provided by lesion swabs for clade Ib mpox in this hospitalised cohort. These findings are restricted to this sampling window; further studies are needed to define performance in prodromal, pre-rash, and asymptomatic infection. FUNDING: CEPI through its Centralised Laboratory Network.
Adult↗
Applicability of Nanopore-only whole-genome sequencing for Pseudomonas aeruginosa outbreak investigation in the ICU setting: a multicentric study.
UNLABELLED: Pseudomonas aeruginosa outbreaks frequently occur in intensive care units (ICUs). In particular, ICU patients requiring mechanical ventilation are vulnerable to P. aeruginosa ventilator-associated pneumonia, which is associated with high morbidity and mortality. Fast and accurate genotyping during the early stage is crucial to document and manage P. aeruginosa outbreaks at the ICU. In this study, we have evaluated the applicability of Oxford Nanopore whole-genome sequencing (WGS) for outbreak investigation and antimicrobial resistance (AMR) prediction. To evaluate whether a Nanopore-only WGS workflow was able to reproduce Illumina-confirmed transmission clusters, 19 P. aeruginosa isolates from ICUs at UZ Brussels (Belgium) that were previously sequenced with Illumina were sequenced using a Nanopore-only workflow based on the latest V14 chemistry, followed by bioinformatic analysis via BugSeq and MBioSEQ Ridom Typer. Although both bioinformatic platforms showed high concordance between Illumina and Nanopore data, MBioSEQ Ridom Typer yielded the lowest allelic distance (maximum one cgMLST allele), confirming all outbreak clusters. When applying the Nanopore-only workflow to longitudinally collected isolates, low genetic heterogeneity (maximum three cgMLST alleles) was observed between isolates from the same patient. WGS and subsequent outbreak analysis of 65 respiratory P. aeruginosa isolates collected from 38 different ICU patients across six Belgian hospitals during a 9-month period showed no intra- or inter-hospital transmission. When the Nanopore-only WGS data were used to predict AMR, there was high categorical agreement (95%) between AMR genotype and phenotype. These findings highlight the potential of Nanopore WGS as a rapid and accurate tool for outbreak investigation of P. aeruginosa. IMPORTANCE: In recent years, Nanopore sequencing has found its way to clinical laboratories because of its affordability, scalability, and, most importantly, its ability to obtain sequencing results in near-real time. However, despite improved raw read accuracies with the latest generation R10.4.1 flow cells, the question remains whether the achieved accuracy is sufficient for accurate bacterial outbreak investigation, particularly in high-risk settings such as intensive care units (ICUs). In this study, we show that Nanopore-only whole-genome sequencing (WGS) is able to match Illumina-only WGS in terms of accuracy for Pseudomonas aeruginosa outbreak investigation in the ICU setting, although important sequence type-dependent and even strain-specific methylation issues need to be resolved in order to guarantee this accuracy. By providing a fast and accurate workflow for reliable P. aeruginosa outbreak investigation, this study could pave the way for large-scale implementation of Nanopore-only WGS, leading to faster outbreak response times.
Humans↗
Nucleic acid amplification testing and genome sequencing for WHO priority viruses in Africa: a scoping review.
Emerging viruses continue to pose serious public health threats across Africa, with recurrent outbreaks exposing gaps in diagnostics and surveillance systems. Nucleic acid amplification tests (NAATs) and genome sequencing are increasingly important for diagnostics and outbreak responses; however, their routine implementation is fragmented. This scoping review examines NAATs and genome sequencing technologies for viral detection and surveillance in Africa from 2019 to 2024, mapped to the 2024 updated WHO R&D Blueprint for Epidemics pathogen priority list. We identified 117 studies from 34 African countries reporting applications across 20 virus families, including ten designated as priorities by WHO. PCR-based assays were the most frequently reported NAATs. Illumina platforms predominated sequencing, and Oxford Nanopore Technologies were commonly used in outbreak investigations. Genome sequencing applied to priority viruses was largely reactive. NAAT-capable mobile laboratories were reported in 13 countries. Our findings underscore the need for proactive integration of NAATs into diagnostic and surveillance systems to strengthen decentralised testing, sustain genomic surveillance beyond outbreak periods, and improve early detection and preparedness for viral threats.
Journal Article↗
Investigation of a Mycobacterium fortuitum prosthetic joint infection outbreak at two ambulatory surgery centers in Tennessee.
OBJECTIVE: This study outlines the investigation into an outbreak of Mycobacterium fortuitum infections involving 17 cases undergoing hip or knee surgeries at two ambulatory surgery centers (ASCs) in Tennessee from January 2023 to November 2024. Notably, the outbreak could not be attributed to contaminated water sources, which are typically associated with non-tuberculous mycobacteria (NTM) outbreaks, presenting a unique challenge. METHODS: Outbreak investigation steps included Infection Prevention (IP) assessments, case-control study, environmental sampling, whole genome sequencing, and a healthcare personnel (HCP) exposure questionnaire. RESULTS: IP assessment highlighted several concerns, including no formal facility water management program (WMP), a lack of dedicated IP personnel and certified sterile processing staff, the absence of a formalized system for tracking surgical site infections, and a notable gap in understanding the requirements for reporting diseases. The case-control findings revealed a significant association between the presence of a surgical technologist in the operating room during the procedures and the occurrence of NTM infections, indicated by an odds ratio of 55.77 (95% CI [3.16-985.44]; P = 0.0097). Thirteen clinical isolates collected at one ASC and three additional isolates collected at a second ASC were highly related by whole genome sequencing. CONCLUSION: The study further elucidates valuable insights gained from the outbreak response, including the gaps in surveillance within the ambulatory surgical setting and systematic collection of cultures from environmental sources. It emphasizes the importance of thorough vetting, onboarding, continuing education, and practice monitoring for HCP.
Humans↗
Nosocomial Outbreak of Lassa Fever in Conakry, Guinea, 2022.
BACKGROUND: Lassa fever is endemic in Guinea, with high seroprevalence in the forest region. However, clinical cases have been only anecdotally reported. In August 2022, a nosocomial outbreak occurred at a private clinic in the capital, Conakry, an area previously considered low risk. METHODS: Suspected cases were confirmed by real-time reverse-transcription polymerase chain reaction within 24 hours. Viremia was monitored during hospitalization, and whole-genome sequencing was performed in-country within 13 days of outbreak detection. Outbreak investigation involved rodent testing in the home village of the suspected primary case. RESULTS: Six cases were laboratory-confirmed, 5 of which were healthcare workers of the clinic. The case fatality rate was 16.7%. Viral RNA remained detectable in blood of survivors for a median of 26 days (interquartile range, 24-41 days) post-disease onset. Epidemiological investigations identified a suspected primary case, who had died of a febrile disease compatible with Lassa fever, had contact with all secondary cases, and had a travel history from Kissidougou area. Three near-complete and 1 partial Lassa virus genomes were recovered from the secondary cases, which phylogenetically clustered with genomes from central Guinea. Consistent with a common transmission source, the 4 genomes were almost identical. Rodent testing revealed a new reservoir area in eastern-central Guinea. CONCLUSIONS: This outbreak highlights the vulnerability of healthcare settings in low-prevalence areas of West Africa to nosocomial Lassa virus transmission due to human mobility. Facilitated by capacity-building programs for viral hemorrhagic fevers, rapid diagnosis, genomic analysis, and ecological assessment enabled an efficient outbreak response and control.
Lassa Fever↗
Advancing One Health genomics in Africa: opportunities and challenges for outbreak and antimicrobial resistance control.
SUMMARYAfrica's ongoing struggles with emerging epidemics and antimicrobial resistance (AMR) underscore the urgency of integrating pathogen genomics and surveillance systems into the continent's One Health strategy, particularly given the existing limitations in preparedness and technological resources. This review brings together current evidence on the growth of sequencing infrastructure, the development of regional genomic hubs, and the establishment of governance frameworks, while identifying critical challenges in data integration, bioinformatics capacity, and sustainable financing. Special focus is placed on the lack of African-based genomic data, with our analysis showing that only 1.82% of the global total is available. Case studies illustrate the immense potential and importance of pathogen genomics, giving policymakers a tangible sense of its impact. These examples demonstrate how genomic technologies integrated with artificial intelligence (AI) are transforming outbreak response, AMR surveillance, and stewardship programs by enabling early detection of zoonotic threats, mapping transmission pathways, and guiding vaccine development. However, to fully realize this scientific intel, it is essential to embed One Health pathogen surveillance within strong policy and system frameworks to ensure the translation of technical progress into lasting institutional capacity and sustainable impact. Long-term implementation depends on coordinated investment and advocacy across four interdependent pillars: data architecture, governance and sovereignty, human capital, and technical capacity.
Humans↗
Global Genomic Surveillance.
Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.
Humans↗
Nanopore Sequencing for Chikungunya Virus: Principles and Application.
Nanopore sequencing is transforming viral genomics through real-time, portable, long-read analysis of RNA and DNA. Unlike traditional short-read platforms, it detects nucleotide sequences by measuring ionic current changes as nucleic acids pass through nanoscale pores, enabling direct single-molecule sequencing and base modification detection. Its simplicity, flexibility, and capacity for ultra-long reads make it ideal for resolving complex genomic regions, structural variants, and full viral genomes. These advantages have accelerated its use in pathogen surveillance and outbreak response, especially in resource-limited settings. For chikungunya virus (CHIKV), nanopore sequencing allows rapid, culture-independent recovery of complete genomes from clinical and vector samples, enabling real-time tracking of viral diversity, evolution, and spread. Experiences from Ebola, Zika, and COVID-19 have demonstrated the power of portable sequencing, now applied to CHIKV monitoring. Advances in tools such as Guppy, Dorado, Minimap2, and Medaka enhance read quality, consensus accuracy, and downstream analyses. Despite challenges in basecalling and error correction, robust quality control pipelines ensure reliable results. Ongoing improvements in chemistry, flow cell design, and machine learning will further enhance fidelity and throughput, establishing nanopore sequencing as a cornerstone of CHIKV genomic surveillance and epidemic preparedness.
Chikungunya virus↗
Evaluation of one-step amplicon-based targeted enrichment for SARS-CoV-2 whole-genome sequencing using the Midnight amplicon scheme.
Genomic surveillance proved invaluable during the COVID-19 pandemic for tracking SARS-CoV-2 variants and guiding outbreak responses, underscoring the ongoing need to reduce whole-genome sequencing (WGS) costs and improve workflow efficiency to ensure accessibility in resource limited settings. Here, we evaluated a one-step reverse transcription polymerase chain reaction (RT-PCR) approach using the Midnight V2 primer scheme for targeted amplification of the SARS-CoV-2 genome, assessed its compatibility with Illumina sequencing, and compared its performance to a well-established two-step method. Initially, we determined optimal RT-PCR reaction conditions using the Midnight V2 primer panel for the one-step RT-PCR kit and scaled reaction volumes for both RT-PCR and library preparation. Clinical specimens (n = 53) that had undergone routine WGS for surveillance purposes using the established two-step RT-PCR method were compared using the one-step RT-PCR assay. For samples with genome completeness greater than 70%, both methods gave comparable results with similar sequence coverage and 100% concordance for lineage assignment. Further investigation revealed a higher percentage of reads aligning to the SARS-CoV-2 genome with a greater depth of coverage using the one-step method compared to the two-step method. Finally, analysis of scaled one-step and library reaction volumes revealed significant cost savings for samples undergoing WGS. Overall, the results presented here verify the accuracy and reproducibility of one-step targeted amplification and offer an efficient and cost-effective workflow for routine SARS-CoV-2 genomic surveillance.
Humans↗
Scalable near-real-time Bayesian phylogenetics for outbreaks with Delphy.
Pathogen genomic analysis is central to tracking, understanding and containing outbreaks1-13, but the complexity and cost of state-of-the-art phylogenetic tools limit global access and impact. Here we introduce Delphy, an exact reformulation of Bayesian phylogenetics14-17 designed to transform its speed, scalability and accessibility while retaining Bayesian state-of-the-art accuracy. Delphy's central data structure, an explicit mutation-annotated tree, takes advantage of the high sequence similarity of large-scale epidemic datasets18-20 for efficient tree exploration and convergence. By reproducing key analyses from recent major epidemics, including Ebola1,21, Zika2, SARS-CoV-2 (ref. 22), mpox3,4 and H5N1 (refs. 23,24), we demonstrate state-of-the-art accuracy with up to 2-3 orders of magnitude improvements in speed. Assessing Delphy's scalability, we show that a simulated dataset of 100,000 sequences can be analysed within a day. We distribute Delphy as a client-side web application that enables local, interactive analysis of raw data on the user's machine. Delphy automatically identifies key viral lineages and mutations, as well as their emergence and prevalence through time, with quantified uncertainties grounded in Bayesian theory. Delphy establishes Bayesian phylogenetics as a fast, accessible frontline tool for future outbreak response.
Journal Article↗
A smartphone-integrated plasmonic biosensor for amplification-free detection of African swine fever virus.
African Swine Fever Virus (ASFV) poses a catastrophic threat to global swine production, with recent outbreaks across Europe, Asia, and the Caribbean, significantly elevating the biosecurity risk to the United States' billion-dollar pork industry. Current diagnostic gold standards are laboratory-dependent and introduce critical delays in outbreak response. To address this gap, a plasmonic biosensor based on functionalized gold nanoparticles (GNPs) was developed for the rapid, amplification-free detection of ASFV. GNPs were surface-functionalized with 11-mercaptoundecanoic acid (MUDA) and combined in situ with ASFV-specific oligonucleotide probes targeting a conserved region of the p72 (B646L) gene. The detection mechanism relies on acid-induced aggregation: hybridization of target ASFV DNA to the probe generates a rigid duplex that shields the nanoparticles from acid-induced destabilization, maintaining a ruby-red color, whereas in the absence of target DNA the GNPs aggregate, producing a visible red-to-blue color shift. The optimized plasmonic biosensor demonstrated 100% analytical specificity, with no cross-reactivity against a panel of 19 non-target bacterial genomic DNA samples representative of the swine environment. Detection limits determined by the IUPAC 3σ criterion were 285 copies per reaction for Probe 1 and 402 copies per reaction for Probe 2, within the same order of magnitude as the qPCR reference assay run on the same dilution series (approximately 312 copies per reaction) under the experimental conditions used here. A smartphone-based Bio-Analytics App employing an RGB color-conversion algorithm served as a quantitative reader, yielding signal-to-noise ratios (S/N) that strongly correlated with benchtop spectrophotometric readings (A520/A620 ratio, R2 = 0.96) and achieved diagnostic concordance with qPCR binary calls. This platform offers a robust and low-cost (∼$2 per test), amplification-free approach to ASFV screening with potential for point-of-need deployment, subject to future validation in clinical specimens.
Journal Article↗
Parallel algorithms for phylogenetic inference under a structured coalescent approximation.
While advances in molecular epidemiology and computational modeling have enhanced our capacity to track pathogen evolution, the accurate reconstruction of spatiotemporal transmission dynamics remains essential for developing epidemic preparedness frameworks and implementing outbreak response measures. Structured coalescent models offer a phylogeographic framework by restricting lineage coalescence events to geographically proximate host populations. Although the Bayesian structured coalescent approximation (BASTA) provides a tractable approach, contemporary phylogeographic analyses involving dozens of geographic localities and hundreds to thousands of viral genomes substantially exceed the computational capacity of existing implementations. The BASTA likelihood scales cubically with deme count and quadratically with sequence count due to matrix exponentiation and pairwise coalescent probability calculations. Here, we introduce a comprehensive algorithmic restructuring of the structured coalescent likelihood that eliminates redundancies, optimizes memory access, and exposes parallelization opportunities. Our approach reorganizes computations along three dimensions: (i) independent calculation of deme-transition probability matrices across time intervals; (ii) simultaneous evaluation of partial likelihood vectors within temporal slices; and (iii) concurrent aggregation of coalescent probabilities. Algorithmic restructuring cuts average coalescent likelihood computation by 7-8 fold, and parallelization further boosts performance to 10-26 fold, enabling joint phylogeographic analyses of dengue virus across 10 South American countries and H5N1 avian influenza across 20 Eurasian regions to finish in a fraction of prior time. This computational efficiency also enables comparison between backward-in-time structured coalescent approximations and forward-in-time phylogeographic methods, revealing that the former provides appropriately conservative posterior estimates, particularly at intermediate phylogenetic depths. We integrate our implementation into the popular BEAST X and BEAGLE software packages, with an accompanying interface in BEAUti X to easily set up the analyses, providing researchers with an accessible and scalable tool for real-time phylogeographic surveillance of rapidly evolving pathogens.
Journal Article↗
Whole-genome sequencing-based pathogen characterization for streptococcal infection directly from positive blood culture samples.
Clinical laboratories are increasingly using diagnostic tests directly on positive blood cultures, which may lead to fewer attempts to recover bacterial isolates. Consequently, public health laboratories can benefit from assays that directly process blood culture samples without requiring submission of clinical isolates to determine additional pathogen features not identified by clinical tests, such as vaccine serotype and bacterial genomic relatedness, for surveillance and outbreak response purposes. In partnership with the Minnesota Active Bacterial Core surveillance (ABCs) site, we identified blood culture samples positive for ABCs streptococcal pathogens and characterized them by a direct whole-genome sequencing from blood culture (dWGS) assay. The dWGS results were compared with the results of a reference method (WGS of isolates from the same cultures) to evaluate concordance in pathogen features and genome assemblies. Of the 97 eligible blood culture samples, 83 (86%) passed dWGS quality control criteria and were subjected to a total of 655 dWGS-based tests, which yielded 651 (99.3%) evaluable results. The percent agreement with reference results was 100% (83/83) for M protein gene (emm)/capsular types and 100% (81/81) for multilocus sequencing types. For genotypic antimicrobial susceptibility testing prediction, the percent prediction agreement was 100% (487/487), false resistant prediction rate was 0% (0/417), and the false susceptible prediction rate was 0% (0/66). Assemblies of pathogen genomes from the same patient differed by 1.08 ± 1.68 (mean ± SD) sites per genome. The dWGS assay can extract high-quality, important streptococcal strain characteristics directly from positive blood culture samples to support evolving public health needs.IMPORTANCEWhole-genome sequencing (WGS) technologies have emerged as a transformative toolkit used by public health microbiology laboratories to detect and characterize pathogens. The surveillance of bacterial diseases often relies on clinical laboratories to submit pathogen isolates to regional or national public health laboratories, which have the capacity to routinely conduct WGS-based strain characterization. Clinical laboratories are increasingly using diagnostic tests directly on positive blood cultures, which may lead to fewer attempts to recover bacterial isolates. The study evaluated a direct whole-genome sequencing from blood culture (dWGS) assay that directly processes blood culture samples. The dWGS assay recovered high quality, important streptococcal strain characteristics, including vaccine serotypes and whole-genome assemblies, without requiring submission of clinical isolates. Thus, the dWGS assay represents a promising tool for addressing the evolving needs of public health laboratories in the metagenomics era.
Humans↗
Syndromic cholera diagnosis masks diverse causes of diarrhoeal disease in Burundi revealed by portable metagenomics.
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 re ly 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 Oxford Nanopore Technologies (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 C holera T oxin P hage 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.
Humans↗