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bioRxiv2019

The human microbiota is associated with cardiometabolic risk across the epidemiologic transition

Oral and fecal microbial biomarkers have previously been associated with cardiometabolic (CM) risk, however, no comprehensive attempt has been made to explore this association in minority populations or across different geographic regions. We characterized gut- and oral-associated microbiota and CM risk in 655 participants of African-origin, aged 25-45, from Ghana, South Africa, Jamaica, and the United States (US). CM risk was classified using the CM risk cut-points for elevated waist circumference, elevated blood pressure and elevated fasted blood glucose, low high-density lipoprotein (HDL), and elevated triglycerides. Gut-associated bacterial alpha diversity negatively correlated with elevated blood pressure and elevated fasted blood glucose. Similarly, gut bacterial beta diversity was also significantly differentiated by waist circumference, blood pressure, triglyceridemia and HDL-cholesterolemia. Notably, differences in inter- and intra-personal gut microbial diversity were geographic-region specific. Participants meeting the cut-points for 3 out of the 5 CM risk factors were significantly more enriched with Lachnospiraceae, and were significantly depleted of Clostridiaceae, Peptostreptococcaceae, and Prevotella. The predicted relative proportions of the genes involved in the pathways for lipopolysaccharides (LPS) and butyrate synthesis were also significantly differentiated by the CM risk phenotype, whereby genes involved in the butyrate synthesis via lysine, glutarate and 4-aminobutyrate/succinate pathways and LPS synthesis pathway were enriched in participants with greater CM risk. Furthermore, inter-individual oral microbiota diversity was also significantly associated with the CM risk factors, and oral-associated Streptococcus, Prevotella, and Veillonella were enriched in participants with 3 out of the 5 CM risk factors. We demonstrate that in a diverse cohort of African-origin adults, CM risk is significantly associated with reduced microbial diversity, and the enrichment of specific bacterial taxa and predicted functional traits in both gut and oral environments. As well as providing new insights into the associations between the gut and oral microbiota and CM risk, this study also highlights the potential for novel therapeutic discoveries which target the oral and gut microbiota in CM risk.

microbiology↗

bioRxiv2019

Machine Learning based histology phenotyping to investigate epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral= 0.94, P < 2.2 x 10-16, R2subcutaneous= 0.91, P < 2.2 x 10-16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 x 10-69, {beta}subq = 0.45; Pvisc= 2.5 x 10-55, {beta}visc= 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta= 9.8 x 10-7). Lastly, we performed the largest GWAS and subsequent meta-analysis of adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations.

genomics↗

bioRxiv2019

Implicit versus explicit control strategies in models for vector-borne disease epidemiology

Throughout the vector-borne disease modeling literature, there exist two general frameworks for incorporating vector management strategies (e.g. area-wide adulticide spraying and larval source reduction campaigns) into vector population models, namely, the \"implicit\" and \"explicit\" control frameworks. The more simplistic \"implicit\" framework facilitates derivation of mathematically rigorous results on disease suppression and optimal control, but the biological connection of these results to realworld \"explicit\" control actions that could guide specific management actions is vague at best. Here, we formally define the biological and mathematical relationships between implicit and explicit control, and we provide detailed mathematical expressions relating the strength of implicit control to management-relevant properties of explicit control for four common intervention strategies. These expressions allow optimal control and sensitivity analysis results in existing implicit control studies to be interpreted in terms of real world actions. Our work reveals a previously unknown fact: implicit control is a meaningful approximation of explicit control only when resonance-like synergistic effects between multiple controls have a negligible effect on average population reduction. When non-negligible synergy exists, implicit control results, despite their mathematical tidiness, fail to provide accurate predictions regarding vector control and disease spread. The methodology we establish can be applied to study the interaction of phenological effects with control strategies, and we present a new technique for finding impulse control strategies that optimally reduce a vector population in the presence of seasonally oscillating model parameters. Collectively, these elements build an effective bridge between analytically interesting and mathematically tractable implicit control and the challenging, action-oriented explicit control.

ecology↗

bioRxiv2019

Modelling the epidemiology of residual Plasmodium vivax malaria in a heterogeneous host population: a case study in the Amazon Basin

The overall malaria burden in the Americas has decreased dramatically over the past two decades, but residual transmission pockets persist across the Amazon Basin, where Plasmodium vivax is the predominant infecting species. Current elimination efforts require a better quantitative understanding of malaria transmission dynamics for planning, monitoring, and evaluating interventions at the community level. This can be achieved with mathematical models that properly account for risk heterogeneity in communities approaching elimination, where few individuals disproportionately contribute to overall malaria prevalence, morbidity, and onwards transmission. Here we analyse demographic information combined with routinely collected malaria morbidity data from the town of Mancio Lima, the main urban transmission hotspot of Brazil. We estimate the proportion of high-risk subjects in the host population by fitting compartmental susceptible-infected-susceptible (SIS) transmission models simultaneously to age-stratified vivax malaria incidence densities and the frequency distribution of P. vivax malaria attacks experienced by each individual over 12 months. Simulations with the best-fitting SIS model indicate that 20% of the hosts contribute 86% of the overall vivax malaria burden. Despite the low overall force of infection typically found in the Amazon, about one order of magnitude lower than that in rural Africa, high-risk individuals gradually develop clinical immunity following repeated infections and eventually constitute a substantial infectious reservoir comprised of asymptomatic parasite carriers that is overlooked by routine surveillance but likely fuels onwards malaria transmission. High-risk individuals therefore represent a priority target for more intensive and effective interventions that may not be readily delivered to the entire community.

bioinformatics↗

bioRxiv2019

High-resolution micro-epidemiology of parasite spatial and temporal dynamics in a high malaria transmission setting in Kenya

Novel interventions that leverage the heterogeneity of parasite transmission are needed to push malaria further towards elimination. To better understand spatial and temporal dynamics of transmission, we applied amplicon NGS of two polymorphic gene regions (csp and ama1) to a cohort identified via reactive case detection in a high-transmission setting in western Kenya. From 4/2013-6/2014, we enrolled 442 symptomatic children with malaria, 442 matched controls, and all household members of both groups. We evaluated genetic similarity between infected individuals using three novel indices: sharing of parasite haplotypes on binary and proportional scales and the L1 norm. Symptomatic children more commonly shared haplotypes with their own household members. Furthermore, we identified robust temporal structuring of parasite genetic similarity that we exploited to identify the molecular signature of an outbreak. These findings of both micro- and macro-scale organization of parasite populations might be harnessed to inform next-generation malaria control measures.

microbiology↗

bioRxiv2019

Genomic epidemiology of vancomycin 1 resistant Enterococcus faecium (VREfm) in Latin America: Revisiting the global VRE population structure

The prevalence of vancomycin-resistant Enterococcus faecium varies across geographical regions yet little is known about its population structure in Latin America. Here, we provide a complete genomic characterization of 55 representative Latin American VREfm recovered from 1998-2015 in 5 countries. We found that VREfm population in the region is structured into two main clinical clades without geographical clustering. To place our regional findings in context, we reconstructed the global population structure of VREfm by including 285 genomes from 36 countries from 1946-2017. Our results differ from previous studies showing an early branching of animal related isolates and a further split of clinical isolates into two sub-clades, all within clade A. The overall phylogenomic structure was highly dependent on recombination (54% of the genome) and the split between clades A and B is estimated to have occurred more than 3585 years BP. Furthermore, while the branching of animal isolates and clinical clades was predicted to have occur [~]894 years BP, our molecular clock calculations suggest that the split within the clinical clade occurred around [~]371 years BP. By including isolates from Latin America, we present novel insights into the population structure of VREfm and revisit the evolution of this pathogen.

microbiology↗

bioRxiv2019

Molecular epidemiology of cefotaxime-resistant Escherichia coli from dairy farms in South West England identifies a dominant plasmid encoding CTX-M-32

Third-generation cephalosporin resistance (3GC-R) in Escherichia coli is a rising problem in human and farmed animal populations. We conducted whole genome sequencing analysis of 138 representative 3GC-R isolates previously collected from dairy farms in South West England and confirmed by PCR to carry acquired 3GC-R genes. This analysis identified blaCTX-M (131 isolates: encoding CTX-M-1, -14, -15, -32 and the novel variant, CTX-M-214), blaCMY-2 (6 isolates) and blaDHA-1 (one isolate). A highly conserved plasmid was identified in 73 isolates, representing 27 E. coli sequence types. This novel ~220 kb IncHI2 plasmid carrying blaCTX-M-32 was sequenced to closure and designated pMOO-32. It was found experimentally to be stable in cattle and human transconjugant E. coli even in the absence of selective pressure and was found by multiplex PCR to be present on 26 study farms representing a remarkable range of transmission over 1500 square kilometres. However, the plasmid was not found amongst human urinary E. coli we have recently characterised from people living in the same geographical location, collected in parallel with farm sampling. There were close relatives of two blaCTX-M plasmids circulating amongst eight human and two cattle isolates, and a closely related blaCMY-2 plasmid found in one cattle and one human isolate. However, phylogenetic evidence of recent sharing of 3GC-R strains between farms and humans in the same region was not found. ImportanceThird-generation cephalosporins (3GCs) are critically important antibacterials and 3GC-resistance (3GC-R) threatens human health, particularly in the context of opportunistic pathogens such as Escherichia coli. There is some evidence for zoonotic transmission of 3GC-R E. coli through food, but little work has been done examining possible transmission (e.g. via interaction of people with the local near-farm environment). We characterised acquired 3GC-R E. coli found on dairy farms in a geographically restricted region of the United Kingdom and compared these with E. coli from people living in the same region, collected in parallel. Whilst there is strong evidence for recent farm-to-farm transmission of 3GC-R strains and plasmids - including one epidemic plasmid that has a remarkable capacity to transmit - there was no evidence that 3GC-R found on study farms had a significant impact on circulating 3GC-R E. coli strains or plasmids in the local human population.

microbiology↗

bioRxiv2019

Expansion of a subset within C2 clade of Escherichia coli sequence type 131 (ST131) is driving the increasing rates of Aminoglycoside resistance: a molecular epidemiology report from Iran

The most important lineage of Escherichia coli, named sequence type 131 (ST131) is a pandemic clone which drives the increasing rates of antibiotic resistance. While the pervasiveness of ST131 clade C, especially subclades C2 and C1-M27 has been demonstrated in numerous global surveys, no report about the ST131 clades and its virotypes has been published from Iran, so far. So, in this study we investigated and compared the virotypes, antibiotic susceptibility patterns, resistance/virulence determinants and clonality of ST131 clades collected during one-year surveillance study. Most of isolates belonged to clade C2 (34/76 [44.7%]), with the highest virulence factor (VF) scores and resistance rates. The distinctive profiles of clade C2 virulence genes were revealed by "principle coordinates analysis" (PcoA) test. The distribution of hlyA/cnf1virulence genes among clade C2 was not uniform, so that positive strains showed significantly higher rates of resistance markers (blaCTX-M-15, blaOXA-1, aac6Ib/Ib-cr and aac3IIa) and ampicillin- sulbactam/gentamicin/tobramycin resistance. Virotype C as the most common virotype (48.7%) was predominant among clade C1 population, while almost all of virotypes E and F [(22/23), 95.6%] strains belonged to clade C2, with the highest VF scores and aminoglycoside resistance rates. "Multi locus variable Number tandem repeats analysis" (MLVA) clustered clades C1 and C2 together, while clades A and B strains were mostly identified as singletons. Appearance of virotypes E and F among clade C2 strains with higher rates of aminoglycoside resistance/virulence genes content demonstrate the shifting dynamics of this pandemic clone in response to antibiotic selection pressure by establishing the newly-emerged subsets.

microbiology↗

bioRxiv2025

Epidemiological Survey of Snail Intermediate Hosts of Schistosomiasis in Zaria, Northwest Nigeria and Molluscicidal Screening of Ficus exasperata Extracts

Schistosomiasis is a Snail-borne parasitic disease transmitted through water contact activities in endemic areas. It is associated with serious morbidities including anaemia, bladder cancer and infertility. Vector control efforts rely on the use of synthetic molluscicide (Niclosamide) which has been attributed to environmental toxicity. Snail intermediate hosts of schistosomiasis were obtained from water bodies and channels around Zaria, morphologically identified and screened for cercarial shedding. F. exasperata leaves and stem bark were obtained from natural habitat in Zaria, authenticated, dried under shade, ground into powder and subjected to extraction with distilled water, ethanol and methanol. The extracts were evaluated for phytochemical constituents, DPPH and FRAP radical scavenging activities and Molluscicidal efficacy against Bulinus spp. Higher percentage yield (8.62%) was obtained in Methanolic extract. Phytochemical analysis revealed the presence of compounds such as alkaloids, flavonoids, saponins, cardiac glycosides and steroids. Tannins and Phenolics have higher concentration compared to other phytochemicals detected in all the extracts. In vitro antioxidant analysis demonstrated moderate activity, with DPPH radical scavenging activity of 62%, 60% and 47% for methanolic, aqueous and ethanolic extracts, respectively. Molluscicidal screening of the extracts revealed dose dependent toxicity against Bulinus snails, with LC50 value of 23.59ppm, 28.96ppm, 31.51ppm for ethanolic, methanolic and aqueous extracts, respectively. These findings suggest that F. exasperata stem bark extracts could be exploited for development of eco-friendly botanical molluscicide. Further research is needed to identify the bioactive compounds responsible for Molluscicidal efficacy, elucidate the possible mechanisms of action, evaluate the efficacy in field trials and environmental impact.

pharmacology and toxicology↗

bioRxiv2026

Genomic epidemiology of Ukraine conflict-associated Klebsiella pneumoniae reveals the emergence of a high-risk clone with a hybrid virulence-resistance plasmid vulnerable to lytic phages

As antimicrobial resistance continues to rise and the development of new antimicrobials lags, we face an urgent threat where routine infections could become life-threatening. Armed conflicts, like Russias war on Ukraine, intensify this crisis by accelerating the emergence and spread of resistant organisms across regions and borders. Phage Support Ukraine (Phage Sp UKR) is a collaborative effort to provide phages targeting circulating pathogens in Ukraine for delivery of personalized phage therapies. Within this context, we received multidrug-resistant bacterial isolates belonging to a number of different species. We here focus on Klebsiella pneumoniae, the most concerning pathogen with regard to prevalence, virulence and antibiotic resistance. Among the K. pneumoniae isolates, we identified sequence types (ST) 39, 101, 147, 307 and 395, as well as a predominating clonal group--CG10146 (ST23 KL57), first detected in Moscow--carrying a hybrid virulence-resistance plasmid encoding NDM-1 and aerobactin. Over two years (2023-2025), this clonal group expanded and acquired pan-resistance. When tested in virulence assays, only one isolate (ST395) displayed hypervirulence in a Galleria mellonella though not in a mouse infection model. Several phages isolated from Ukrainian sewage were able to lyse these K. pneumoniae strains, including strains obtained from soldiers displaced in Belgium, Germany, and Latvia. Bacterial resistance was observed during in vitro testing. However, some phage-resistant isolates had mutations in virulence factors, including one that completely lost its hybrid plasmid, resulting in restored antibiotic susceptibility. Strategies like Phage Sp UKR are essential to prevent the selection, persistence, and global spread of these MDR clones.

microbiology↗

bioRxiv2026

A Comprehensive epidemiological and molecular study of gastrointestinal helminths of Companion Animals in Northeastern Bangladesh: A neglected zoonotic threat

BackgroundGastrointestinal helminths of companion animals are neglected sources of zoonotic infection in low and middle-income countries. In Bangladesh, close humananimal contact and large free-roaming dog and cat populations may facilitate parasite transmission, yet region-specific data remain limited. This study assessed the prevalence, species diversity, and zoonotic potential of gastrointestinal helminths in companion animals in northeastern Bangladesh. MethodsA cross-sectional study was conducted between January and December 2025 across urban and rural areas of the Sylhet Division. Fecal samples from 900 animals (600 dogs and 300 cats; owned and stray) were examined using standard coproscopic techniques. Molecular confirmation of selected positive samples was performed using PCR targeting ITS-2, 18S rRNA, and mitochondrial cox1 genes, followed by sequencing. Risk factors associated with infection were evaluated using multivariable logistic regression. ResultsOverall, 45.9% (95% CI: 42.6-49.2) of animals were infected with at least one gastrointestinal helminth, with mixed infections detected in 18.4%. Prevalence was similar in dogs (45.7%) and cats (46.3%) but significantly higher in stray animals (65.7%) than in owned animals (36.6%). Predominant zoonotic helminths included Ancylostoma spp., Toxocara canis, Toxocara cati, Dipylidium caninum, and Taenia/Echinococcus spp. Molecular analysis confirmed 93% of morphologically identified infections and revealed high genetic similarity to zoonotic reference strains. Stray status, lack of deworming, young age, and outdoor roaming were significant risk factors for infection (p < 0.05). ConclusionsCompanion dogs and cats in northeastern Bangladesh harbor a high burden of zoonotic gastrointestinal helminths and represent important reservoirs for human exposure. Strengthening One Health-based surveillance, routine deworming, and stray animal management is essential to reduce zoonotic transmission.

microbiology↗

bioRxiv2026

Towards a holistic epidemiology of Streptococcus agalactiae using the BakRep repository

Streptococcus agalactiae is a versatile multi-host pathogen that can cause major neonatal disease in humans, as well as mastitis in dairy animals. Its ability to infect a wide range of hosts is largely driven by its high genomic plasticity and the acquisition of distinct accessory genes. The global population of S. agalactiae is characterized by multiple of capsular serotypes and clonal complexes that differ in their propensity to cause invasive disease, including hypervirulent CC17 (often serotype III) associated with neonatal meningitis, whereas CC1/CC19/CC23 are more often colonizing lineages. Although widely studied, most research is limited to particular regions or single outbreak events, offering only fragmented snapshots instead of a comprehensive global picture. To move beyond region- or outbreak-limited studies, this work has analyzed 37970 S.agalactiae genomes from BakRep, integrating serotypes, MLST, AMR genes, lineage-specific genes, and descriptive metadata to map current trends and identify potential gaps in public data. The dataset largely matched the known population structure with serotype III, Ia and V most common and stable serotype/clonal complex lineages (e.g. III-2/CC17, Ia/CC23, CC1/V), while also rising serotype diversity. Lineages differed in their accessory-gene profiles, with III-2/CC17 being enriched for virulence and adhesion genes, while other groups showed either greater genomic plasticity (mobile/phage genes) or niche specialization. AMR was widespread with very high tetracycline resistance (>80%), frequent MLSB resistance determinants, and emerging aminoglycoside resistance in some genomes. But overall it became evident that the associated metadata contained substantial gaps. Missing or incomplete information limits biological interpretation, underscoring that rigorously curated, structured metadata is essential for maximizing the value of ongoing sequencing efforts.

genomics↗

bioRxiv2026

Long-read sequencing of Mycobacterial tuberculosis is comparable to short-read sequencing for antimicrobial resistance prediction and epidemiological studies.

BackgroundShort-read genetic sequencing technologies (mainly Illumina) have been extensively used for around a decade for Mycobacterium tuberculosis complex (MTBC) outbreak analysis and genomic drug susceptibility testing (gDST) with the result that Illumina has become the de facto gold standard. Long-read sequencing, as exemplified by Oxford Nanopore Technologies (ONT), offer the prospect of faster, simpler, and portable sequencing. In this work, we carry out the largest to date comparison of how well Illumina and ONT technologies sequence MTBC samples, making use of R10.4 ONT flowcells, updated basecalling models and deep-learning variant calling. MethodsA total of 508 samples were sequenced using both short and long-read platforms. All samples originated from South Africa or Vietnam and were over-selected for drug resistance and also included several local outbreaks and a range of lineages. The South African and Vietnamese samples had already been Illumina sequenced. Samples with [≥]50 read depth by Illumina were selected for sequencing by ONT using one of the GridION or PromethION platforms. Bioinformatics processing was done using a modified online cloud platform which included reference-based variant calling, catalogue-based gDST and identified related samples via SNP counting to inform outbreak detection. The lineages and gDST predictions obtained by short-and long-sequencing were compared for all samples as were all putative clusters identified via SNP counting. For convenience Illumina was used as the reference method. FindingsOf the 508 samples, 425 (83.7%) had sufficient read depths to permit comparison between the two sequencing technologies. The assigned lineages were identical for 407/425 (95.8%) samples and all discordances were due to mixed lineages being identified by one technology. Evidence of non-tuberculous mycobacterium (NTM) subpopulations were found in nine samples. Using Illumina as the reference method, the very major error (VME) rate of ONT for predicting resistance to all 15 drugs is 1.0% (0.6-1.5%) whilst the major error (ME) rate is 1.7% (1.3-2.2%) with an unclassified rate of 6.9% (6.3-7.5%). This is below the thresholds specified by the CLSI. Considering each of the 15 drugs individually they had VME and ME point estimates below [≤]3% in 29/30 cases; and most 25/30 below [≤]1.5%. Filtering out all samples containing mixtures left 382 isolates. By appropriate masking of the reference genome we were able to obtain a mean SNP distance between the two platforms of 0.13 (median of zero) for the same sample and for 376/382 samples (98.4%, CI:96.6-99.4%) the difference was [≤]1 SNPs. The high concordance in SNP identification ensured that few differences in the 43 putative clusters among 172 isolates were observed. InterpretationThe differences between the two sequencing platforms for the key clinical outputs is so small that it is now within the tolerances set by regulatory agencies. Provided the sequencing is of sufficient quality, we have therefore reached a threshold whereby sequencing data from long-and short-read platforms can be aggregated. This will enable large scale analyses by national and international public health agencies whilst allowing the MTBC community to take advantage of the portability and speed of long-read sequencing. FundingThe NIHR Health Protection Research Unit: Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford (NIHR200915), a partnership between the UK Health Security Agency (UKHSA) and the University of Oxford, the National Institute for Health and Care Research Biomedical Research Centre: Oxford (BRC) and the Ellison Institute of Technology, Oxford Ltd. The CRyPTIC project was funded by Wellcome [214560/Z/18/Z], a Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z); and the Bill & Melinda Gates Foundation Trust (OPP1133541). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe conducted a PubMed Central full text search for "tuberculosis" AND ("drug resistance prediction" OR "drug susceptibility prediction") AND ("genome" OR "genomic" OR "geno-typic") AND ("ont" OR "oxford nanopore") between 2022 and 2026 (conducted 1 April 2026). This returned 62 papers; of which, six used both Illumina and ONT sequencing. One of these, published in 2023, directly compared the performance of the two platforms on 151 M. tuberculosis isolates oversampled for resistance. The investigation yielded comparative results for the earlier generation ONT flow cell (R9{middle dot}4{middle dot}1) and base-caller (guppy version 5{middle dot}0{middle dot}16). Another, published in 2026, investigated a targeted next-generation sequencing panel of 20 amplicons using ONT sequencing on R10.4.1 flow cells with guppy 6{middle dot}4{middle dot}6. They compared the results on 71 isolates against phenotypic data and Illumina whole genome sequencing (for 53 isolates) but had low rates of resistance, with all drugs but isoniazid being limited to under five resistant isolates. Two other small studies (10 and 13 samples, respectively) conducted feasibility studies comparing ONT with Illumina, also using earlier generation flow cells and base-calling technology from ONT. Two further studies compared Illumina with ONT for direct sputum sequencing and did not investigate the comparative performance of the two platforms for variant call accuracy, resistance prediction, and outbreak detection. Illumina sequencing technology is widely used for genomic sequence analysis in research, and clinical and public health contexts. Consequently, it has become the de facto reference standard for generating whole genome sequence data. Whilst previous studies established the promise and limitations of long-read (ONT) sequencing as an alternative to short-read sequencing (mainly Illumina), the enhanced performance arising from newer flowcells (e.g. R10.4.1), V14 chemistry, and the latest basecallers (dorado v4.3.0/5.0.0) has not been analysed. Neither has any ONT analysis incorporating the new deep-learning variant callers been evaluated in a large-scale comparative study. Thus, it is currently unclear whether data generated by either platform can be used safely in aggregated analyses for research and clinical or public health service. Added value of this studyWe compared how well short-(Illumina) and long-read (ONT) sequencing platforms identify the genetic variants in M. tuberculosis, predict antituberculous drug resistance and recog-nise outbreaks. The long-reads were generated using the latest generation ONT R10.4.1 flows cells, V14 chemistry, super high accuracy basecalling (dorado v4.3.0/5.0.0) and a bioinformatics analysis pipeline built using the Clair3 deep-learning based variant caller. A total of 508 clinical samples were sequenced using both technologies, substantially more than previous studies. The sampling frame was much larger than previously investigations and included a large proportion of isolates with resistance to first-line and second-line antibiotics as well as bedaquiline. Thus, providing greater statistical power for resistance prediction than before. In particular, the inclusion of bedaquiline resistance provided evidence useful for predicting resistance to this newly deployed drug for treating multi-drug resistant (MDR) TB. We find that the differences between technologies are small meaning that either technology can be used alone safely, and services using both technologies can confidently aggregate the data for analysis. Implications of all the available evidenceThis will be a benefit to local, regional and international organisations, particularly public health agencies, which often have a mix of the two main sequencing technologies for characterising TB whole genome sequences. It also opens up the sequence based diagnostic market to greater competition, particularly if the observed performance can be replicated for other pathogen species.

microbiology↗

bioRxiv2026

Epidemiology and phylodynamic analysis of canine distemper virus circulating in Michigan, USA

Canine distemper virus (CDV) is a highly contagious generalist pathogen that can cause significant mortality in domestic dogs and wild mammals. Due to the fast-evolving nature of CDV and its global spread, epizootic events and the emergence of new strains have been frequently reported. In Michigan, CDV surveillance from 2008 to 2018 was previously reported. Here, we combine and extend these data through 2023 to bring together 16 years of CDV surveillance in wild mammals in Michigan. We also sequenced CDV strains originating from both wildlife and domestic dogs to examine viral evolution across host populations. To facilitate interpretation of these data in both local and global contexts, we developed a Nextstrain workflow for CDV, enabling interactive visualization of viral evolution over time and geographic space. Our data show persistence of CDV in Michigan mammals during the study period and point to temporal, geographic, and host factors associated with CDV occurrence. Phylogenetic analysis using the newly built Nextstrain workflow showed that three CDV lineages--America-3, America-5, and Canada-1--are currently circulating in both wild and domestic animals in Michigan. The Nextstrain workflow enables reproducible, scalable integration of genomic sequencing into local surveillance and provides an updateable platform for ongoing and future surveillance efforts. This study demonstrates the value of coupling wildlife surveillance and diagnostic testing with genomic sequencing to identify lineage turnover and anticipate changes in viral behavior.

microbiology↗

bioRxiv2026

neissflow: Streamlining Genomic Epidemiology of Neisseria gonorrhoeae with Nextflow

Antimicrobial-resistant Neisseria gonorrhoeae (Ng) poses a growing global public health threat. Existing tools available for Ng genome analysis carry notable limitations, including incomplete resistance marker coverage, absence of species identification, and lack of phylogenetic capability. We developed neiss-flow, a highly parallelized Nextflow pipeline for Ng genome analysis that integrates five subworkflows: read preprocessing, species identification, de novo assembly, antimicrobial resistance (AMR) profiling, and recombination-aware phylogenetic analysis with outbreak detection. neissflow performs extensive quality control on reads, assemblies, variant calls, and phylogenetic results. Validation was performed on two datasets: a mixed-species dataset (n=158; 105 Ng and 53 non-gonococcal species) for sensitivity/specificity assessment, and a reproducibility dataset (n=283 replicate sequences from 17 reference strains) for consistency and phylogenetic validation. neissflow achieved 100% sensitivity and specificity for Ng species identification compared with MALDI-TOF and PubMLST methods. All nine AMR and typing analytes demonstrated [≥]98.1% concordance with PubMLST genotype calls. Genotype-phenotype validation confirmed perfect concordance for key resistance determinants including gyrA mutations with ciprofloxacin resistance, 23S rRNA mutations with high-level azithromycin resistance, and tetM plasmid gene with high-level tetracycline resistance. Reproducibility analysis demonstrated 99.97% concordance across 3,093 analyte calls. Phylogenetic validation demonstrated 100% accuracy for both strain-level and intra-MLST clustering. neissflow is a robust, accessible, and standardized pipeline, positioning it as a valuable tool for public health laboratories engaged in Ng AMR monitoring and outbreak investigations. ImportanceNeisseria gonorrhoeae (Ng) is the second most common reported bacterial sexually transmitted infection and has developed resistance to all clinically relevant antibiotics. Surveillance of Ng resistance informs clinical recommendations for treatment of gonococcal infections. Whole genome sequencing (WGS) offers powerful insights into resistance mechanisms and transmission dynamics. However, many public health laboratories lack the resources needed to analyze these data effectively. We developed neissflow as an end-to-end, accessible Ng WGS analysis pipeline. neissflow demonstrated exceptional accuracy and reproducibility across diverse reference datasets. neissflow enables broader adoption of whole-genome sequencing-based surveillance and supports timely public health responses to emerging antimicrobial resistance in Ng by lowering technical barriers.

bioinformatics↗

bioRxiv2026

Genomic Epidemiology of Canine Distemper Virus (CDV) in Neotropical Primates in Brazil Reveals Multiple Spillover Events and Convergent Evolution at Hemagglutinin Residue 519

Canine distemper virus (CDV; Morbillivirus canis) is a multi-host paramyxovirus primarily maintained in the order Carnivora. However, recent outbreaks in Neotropical primates suggest recurrent cross-species spillover into non-human primates. Between May and July 2022, seven marmosets (Callithrix penicillata) were found dead in urban and peri-urban areas of Montes Claros, Minas Gerais, Brazil. Viral metagenomic sequencing recovered two near complete CDV genomes directly from liver samples. Maximum likelihood and Bayesian phylogenetic analyses placed these genomes within the South American CDV lineage and supported at least three independent zoonotic introductions into Callithrix populations. Domestic dogs (Canis lupus familiaris) were inferred as the most likely source and the crab-eating fox (Cerdocyon thous) as a probable bridge host. Ancestral-state reconstruction identified a substitution at position 519 of the hemagglutinin (H) protein (R519I in the two primate clades and R519G in a singleton primate sequence). In silico modelling of the marmoset signaling lymphocytic activation molecule (SLAM) complex was consistent with a modest reorganisation of the receptor-binding head in the 519-substituted variants (ipTM = 0.82), generating a testable hypothesis that this residue may contribute to adaptation at the primate SLAM receptor interface and is associated with altered predicted docking orientation for the receptor. Together, these findings suggest that residue 519 is a candidate marker of CDV adaptation to Neotropical primates and emphasise the importance of integrating genomic surveillance with domestic dog vaccination efforts under a One Health framework to reduce the threat of CDV spillover to vulnerable wildlife populations.

genomics↗

bioRxiv2026

Towards operational epidemiology of Pyricularia oryzae in sports turf: contribution of a multi-matrix molecular monitoring strategy at stadium scale

Gray leaf spot can cause severe turfgrass damage, particularly in intensively managed sports fields, while disease management remains challenging due to the rapid development of symptoms under favorable environmental conditions. Early detection of Pyricularia oryzae could therefore provide valuable information for anticipating disease development and supporting management decisions. This study aimed to develop a digital PCR (dPCR) molecular tool to support the monitoring and management of gray leaf spot disease in stadium turfgrass. The assay showed high sensitivity, consistently detecting P. oryzae when infected tissue represented only 0.05% of a mixture with healthy turfgrass, and enabled pathogen detection before symptom appearance under both controlled and field conditions. Different matrices were also investigated across 15 stadiums to identify the most relevant material for disease monitoring. Roots showed the highest prevalence of P. oryzae detection, including during asymptomatic periods, highlighting their potential as a relevant matrix for pathogen surveillance. In a stadium monitored several months after a gray leaf spot outbreak, P. oryzae DNA was still detected in roots from 27 of the 32 sampled zones despite the absence of visible symptoms. Overall, these results demonstrate the potential of dPCR for the early detection and monitoring of P. oryzae in stadium turfgrass, particularly through root sampling during periods when environmental conditions are not favorable for gray leaf spot development, and a spatio-temporal surveillance at stadium scale.

plant biology↗

bioRxiv2026

Epidemiological model selection unravels the molecular processes of antiviral resistance from experimental phytoplankton-virus dynamics

Phytoplankton-virus interactions are pivotal in understanding the intertwined dynamics of these key players of the global carbon cycle. Although antiviral resistance is the main hypothesis to solve the apparent paradox of their coexistence, identifying its molecular determinisms and mechanisms, as well as their dynamical consequences, remains challenging. By combining hypotheses about such determinisms and mechanisms, we designed 36 dynamical models and fitted them to experimental infection kinetics in a pioneering selection model approach. Through such a multiple hypotheses testing, we identified that resistance in the model species Ostreococcus tauri is most likely to be predominantly intracellular, to control lysis through budding, and to be acquired by phenotypic plasticity. We further showed that viral kinetics are strongly impacted by both the antiviral resistance's molecular determinants and virions' inactivation through attachment to lysis detritus, as the latter generates a key negative feedback loop during the 'bust' stage of the interaction dynamics.

ecology↗