SEARCH · Search bioRxiv

Results for “Epidemiology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16Linked to original sources

bioRxiv2024

Understanding the epidemiology and pathogenesis of Mycobacterium tuberculosis with non-redundant pangenome and population genetics

Tuberculosis is a major public health threat demanding more than one million lives every year. Many challenges exist to defeat this deadly infectious disease which address the importance of a thorough understanding of the biology of the causative agent Mycobacterium tuberculosis (MTB). We generated a non-redundant pangenome of 420 epidemic MTB strains from China. We estimate that MTB strains have a pangenome of 4,278 genes encoding 4,183 proteins, of which 3,438 of which are core genes. However, due to 99,694 interruptions in 2,447 coding genes, only 1,651 may be translated in all samples, which dramatically reduces the number of active core genes. Of these interruptions, 67,315 (67.52%) could be classified by various genetic variations detected by currently available tools, and more than half of them are due to structure variations, mostly small indels. We further describe differential evolutionary patterns of genes under the influences of selective pressure, population structure and background selection. While selective pressure is ubiquitous among these coding genes, evolutionary adaptations primarily occur in 1,313 genes. Genes located in the cell wall and membrane region are under the strongest selective pressure, while biological processes including regulation of transcription, translation and regulation of growth are under strongest background selection in MTB. The metabolism of fatty acids may be an outstanding example of evolutionary adaption for MTB under current selective pressure. This study provides a comprehensive view on the genetic diversity and evolution patterns of coding genes in MTB which may deepen our understanding of its epidemiology and pathogenicity.

microbiology↗

bioRxiv2024

Improving Accuracy of Somatic Mutation Profiling in Large Epidemiologic Studies: Addressing Cases without Matched Normal Samples

Ideally, detection of somatic mutations in a tumor is accomplished using a patient-matched sample of normal cells as the benchmark. In this way somatic mutations can be distinguished from rare germline mutations. In large retrospective studies, archival tissue collection can pose challenges in obtaining samples of normal DNA. In this article we propose a protocol that improves somatic mutation analysis in the absence of a matched normal sample. The method was motivated by the InterMEL study, a large-scale epidemiologic investigation involving multiomic, multi-institutional genomic profiling of 1000 primary melanoma samples. The key insight for accomplishing improved mutation calling is the fact that germline mutations should produce a variant allele frequency (VAF) of around 50%. While a similar VAF of 50% would also be expected for somatic mutations in pure tumor samples, typically the tumor purity is much less than 50%, resulting in a considerably lower VAF. Making use of a technique that can simultaneously estimate both tumor purity and VAF from tumor-only samples we have developed a method for better distinguishing somatic versus germline variants. Based on 137 melanomas from the InterMEL Study with matched normal tissue to provide a gold standard we show that the conventional pipeline using a panel of (unmatched) normal samples has a false positive rate of 15.6% and a false negative rate of 3.5%. Our new technique improves these error rates to 6.4% and 2.1%, respectively.

genomics↗

bioRxiv2024

Genomic epidemiology of emerging terbinafine-resistant Trichophyton indotineae

Dermatophyte skin infections affect around a quarter of the worlds population and are a growing public health concern due to increasing incidence of novel species causing severe infections that are resistant to antifungal treatments. Trichophyton species cause the greatest burden of dermatophytosis worldwide, with the T. mentagrophytes species complex being particularly associated with the emergence of new aggressive infections. One emerging species, T. indotineae (originally T. mentagrophytes genotype VIII) is notable for the extensive nature of the often inflammatory infection, its clinical resistance to terbinafine antifungal treatment, and its rapid global spread. To better understand the epidemiology of this disease, we sourced isolates from severe cases of dermatophytosis in the United Kingdom, Ireland, France, Canada and India for the period 2018-2023, including the type strain from Japan. We used whole-genome sequencing to confirm 90 isolates were T. indotineae, and antifungal susceptibility testing indicated that over half of these (62%) were resistant to terbinafine (MIC [≥]1 mg/L). Pairwise genetic distances showed very high identity with only 147 (1-414) SNPs separating isolates that were nested within a monophyletic phylogeny, supporting a single evolutionary origin of T. indotineae. That no clear geographic clustering of isolates was observed confirms the rapid transcontinental spread of T. indotineae from its likely centre of diversity in Asia. Genome-wide analyses identified multiple non-synonymous SNPs in SQLE (ERG1), the squalene epoxidase target of terbinafine, that were associated with terbinafine in vitro resistance [≥]1 mg/L. However, five isolates exhibited high MIC values without SQLE mutations, suggesting the presence of alternative resistance mechanisms. Our findings highlight the importance of better genomic surveillance to understand and manage this severe and rapidly emerging terbinafine-resistant dermatophyte.

genomics↗

bioRxiv2024

Guidance for the design and analysis of cell-type specific epigenetic epidemiology studies.

Recent studies on the role of epigenetics in disease have focused on DNA methylation profiled in bulk tissues limiting the detection of the cell-type affected by disease related changes. Advances in isolating homogeneous populations of cells now make it possible to identify DNA methylation differences associated with disease in specific cell-types. Critically, these datasets will require a bespoke analytical framework that can characterise whether the difference affects multiple or is specific to a particular cell-type. We take advantage of a large set of DNA methylation profiles (n = 751) obtained from five different purified cell populations isolated from human prefrontal cortex samples and evaluate the effects on study design, data preprocessing and statistical analysis for cell-specific studies, particularly for scenarios where multiple cell types are included. We describe novel quality control metrics that confirm successful isolation of purified cell populations, which when included in standard preprocessing pipelines provide confidence in the dataset. Our power calculations show substantial gains in detecting differentially methylated positions for some purified cell populations compared to bulk tissue analyses, countering concerns regarding the feasibility of generating large enough sample sizes for informative epidemiological studies. In a simulation study, we evaluated different regression models finding that this choice impacts on the robustness of the results. These findings informed our proposed two-stage framework for association analyses. Overall, our results provide guidance for cell-specific EWAS, establishing standards for study design and analysis, while showcasing the potential of cell-specific DNA methylation analyses to reveal links between epigenetic dysregulation and disease.

bioinformatics↗

bioRxiv2024

Integrated population clustering and genomic epidemiology with PopPIPE

Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations, and as an additional source of information when detecting possible transmission events. Due to their variable gene content and order, reference-free methods offer more sensitive detection of genetic differences, especially among closely related samples found in outbreaks. However, across longer genetic distances, frequent recombination can make calculation and interpretation of these differences more challenging, requiring significant bioinformatic expertise and manual intervention during the analysis process. Here we present a Population analysis PIPEline (PopPIPE) which combines rapid reference-free genome analysis methods to analyse bacterial genomes across these two scales, splitting whole populations into subclusters and detecting plausible transmission events within closely related clusters. We use k-mer sketching to split populations into strains, followed by split k-mer analysis and recombination removal to create alignments and subclusters within these strains. We first show that this approach creates high quality subclusters on a population-wide dataset of Streptococcus pneumoniae. When applied to nosocomial vancomycin resistant Enterococcus faecium samples, PopPIPE finds transmission clusters which are more epidemiologically plausible than core genome or MLST-based approaches. Our pipeline is rapid and reproducible, creates interactive visualisations, and can easily be reconfigured and re-run on new datasets. Therefore PopPIPE provides a user-friendly pipeline for analyses spanning species-wide clustering to outbreak investigations. Impact statementAs time passes, bacterial genomes accumulate small changes in their sequence due to mutations, or larger changes in their content due to horizontal gene transfer. Using their genome sequences, it is possible to use phylogenetics to work out the most likely order in which these changes happened, and how long they took to happen. Then, one can estimate the time that separates any two bacterial samples - if it is short then they may have been directly transmitted or acquired from the same source; but if it is long they must have been acquired separately. This information can be used to determine transmission chains, in conjunction with dates and locations of infections. Understanding transmission chains enables targeted infection control measures. However, correctly calculating the genetic evidence for transmission is made difficult by correctly distinguishing different types of sequence changes, dealing with large amounts of genome data, and the need to use multiple complex bioinformatic tools. We addressed this gap by creating a computational workflow, PopPIPE, which automates the process of detecting possible transmissions using genome sequences. PopPIPE applies state-of-the-art tools and is fast and easy to run - making this technology will be available to a wider audience of researchers. Data summaryThe code for this pipeline is available at https://github.com/bacpop/PopPIPE and as a docker image https://hub.docker.com/r/poppunk/poppipe. Raw sequencing reads for Enterococcus faecium isolates have been deposited at the NCBI under BioProject accession number PRJNA997588.

bioinformatics↗

bioRxiv2024

Molecular epidemiology of Ascaris lumbricoides following multiple rounds of community-wide treatment: who infects whom?

Control and elimination of the parasite Ascaris lumbricoides relies on mass administration using a limited number of anti-helminthics. Whilst these programs have reduced the infection intensity and prevalence within many endemic regions transmission is poorly understood, with reinfection commonly occurring following cessation of treatment. Here, we utilise genomic data to understand parasite transmission within and between households in a community and the genomic impact of repeated MDA. We sequenced 54 whole-genomes from individuals in a longitudinal cohort epidemiological study of transmission and drug treatment extending over 6 years. We found that fine-scale population structure exists in spatially distinct clusters of infected individuals with reinfection occurring within or between geographically close households. This observation helps inform the policy of future control in low prevalence settings suggesting more targeted treatment of infection hotspots We found evidence of positive selection acting on members of gene families previously implicated in reduced drug efficacy but detect no high frequency of impactful variants. As efforts to eliminate A. lumbricoides intensify, our study provides a foundation for genomic surveillance to help identify both who infects whom and the impact of repeated drug treatment.

genomics↗

bioRxiv2025

Decay and Solid-Liquid Partitioning of Mpox and Vaccinia Viruses in Primary Influent and Settled Solids to Guide Wastewater-Based Epidemiology Practices

Wastewater-based epidemiology (WBE) has proven to be a powerful tool for tracking the spread of viral pathogens, such as SARS-CoV-2, but as WBE has expanded to include new pathogens, such as mpox virus, more data is needed to guide practitioners on how to design WBE campaigns. Here, we investigated the decay rates of heat-inactivated mpox (HI-MPXV) and attenuated vaccinia virus (VV) in primary influent and settled solids collected from a local POTW at 4{degrees}C, 22{degrees}C, or 35{degrees}C using digital PCR. Subsequently, we studied the solid-liquid partitioning of the viruses in primary influent. Over the 30-day study period, we observed no significant difference in log-linear decay rates between viruses (p=0.5258), with significantly higher decay rates in primary influent (0.109-0.144/day) compared to settled solids (0.019-0.040/day) at both 22{degrees}C (p=0.0030) and 35{degrees}C (p=0.0166). Furthermore, as part of the partitioning experiment, we found that HI-MPXV and VV adsorb to the solids fraction of primary influent at higher intensities than previously studied enveloped viruses (KF = 1,000-31,800 mL/g, n = 1.01-1.41). Likewise, it was determined in the partitioning experiment that a concentration of greater than 103 gc/mL in raw influent was needed for the viable quantification of mpox and vaccinia viruses in the clarified liquid fraction of raw primarily influent. Our study provides essential insights into informative sample collection and storage conditions for the analysis of wastewater and for transport modeling studies. Due to the slow decay observed in settled solids at all tested temperatures in the persistence experiment, this matrix may be most suitable for retrospective analyses of community infection of the mpox virus.

microbiology↗

bioRxiv2025

Etiology and epidemiology of branch dieback and fruit blight and necrosis of English walnut in France

English walnut (Juglans regia L.) is an economically-important fruit crop worldwide, particularly in France, where it is the second most important fruit crop after apples in terms of cultivated area. Walnut orchards are targeted by numerous diseases, but new symptoms have been widely observed since 2015 in France, consisting in typical branch dieback and fruit blight and necrosis. Herein, both symptomatic and asymptomatic twigs and husks were collected from 12 commercial French walnut orchards from the two main production areas located in the South of France from 2020 to 2022. Overall, Botryosphaeriaceae, Colletotrichum, Diaporthe, and Fusarium species were consistently isolated from symptomatic husks and twigs. Among these taxa, B. dothidea and C. godetiae were significantly more associated with symptomatic husks, contrary to D. eres and F. juglandicola, more frequently isolated from symptomatic twigs, as also confirmed by ITS2 metabarcoding sequencing. Tissue type was the primary factor significantly impacting the composition of the fungal communities (R{superscript 2} = 16.6%), followed by sampling campaign and production area (R{superscript 2} = 11.6% and 4.6%, respectively). We also found that Neofusicoccum and Diaporthe were significantly more associated with warm and dry years, unlike Colletotrichum. Pathogenicity tests revealed that only Botryosphaeriaceae and Diaporthe species were pathogenic on walnut fruits and twigs, with B. dothidea and N. parvum being the most aggressive species. Several significant positive and negative correlations were identified based on SparCC co-occurrence networks and correlograms based on prevalence data. In particular, the positive correlation between Colletotrichum and Fusarium species on symptomatic twigs was highlighted by both methods. This work is the first comprehensive etiological and epidemiological study of branch dieback and fruit blight and necrosis of English walnut in France. Author SummaryEnglish walnut is an economically important crop, mainly produced in China, in the United States and in Turkey while in Europe, France is one of the biggest producers. Although widespread in nut orchards abroad, new symptoms, including fruit necroses and branch dieback, were observed for the first time in 2015 in France. We then conducted sampling campaigns between 2020 and 2022 to collect walnut husks and twigs in the two main French production areas. Exploration of the associated microbiota revealed the presence of six predominant fungal species, even in samples without symptoms. We then investigated the capacity of these species to cause lesions on twigs and fruits. Among all species, Neofusicoccum parvum was the most aggressive on both organs while other species were mainly aggressive on only twigs or husks. In addition, we evidenced that the presence of some species was favored by warm and dry weather or inversely cold and wet weather. We also found negative correlations between certain species (in particular between N. parvum and Diaporthe eres), suggesting that some species probably prevented the other from further colonization. Overall, we identified the species specifically associated with the disease in France and the factors influencing the disease risk. This work will enable us to better identify the best strategies to combat this disease.

microbiology↗

bioRxiv2025

Managing populations after a disease outbreak: exploration of epidemiological consequences of managed host reintroduction following disease-driven host decline

Disease outbreaks in wild populations around the globe can lead to widespread mortality within populations, where recovery of individuals can be rare. An example of this population is the sunflower sea star Pyc-nopodia helianthioides in the Northeastern Pacific coast. The populations of this species, as well as many other sea star populations, have experienced massive mortality events due to an unidentified disease called Sea Star Wasting Disease (SSWD). Pycnopodia play a key role in providing top-down control of kelp grazers in rocky reefs across the Northeastern Pacific coast. This, combined with the massive declines in kelp coverage observed during the 2015-2016 marine heat wave observed in the Northeastern Pacific, has sparked an interest in reintroducing Pycnopodia individuals in the coast to potentially assist in recovery of the populations. However, the epidemiological implications of reintroducing healthy sea stars into the wild populations is an under-explored question. This work explores this question using a dynamical population model of Pycnopodia. We use this model to estimate the impacts of reintroducing healthy individuals into a wild sea star population. This analysis will provide valuable information for managers interested in restoring Pycnopodia populations.

ecology↗

bioRxiv2025

Genetic heterogeneity in Taenia solium cysticerci among naturally infected pigs revealed by microsatellite markers and associated epidemiological risk factors.

BackgroundThe tapeworm, Taenia solium, also called as pork tapeworm is acquired by human on consumption of raw or undercooked pork infested with intermediate larval stage. The parasite is known to establish an obligatory cyclozoonoses with human serving as the only definitive host for the organism. India is endemic for the presence of T. solium infection particularly for cysticercosis both in human and pig population. Material methodA total of 389 pigs were screened from Ludhiana, Amritsar, Bathinda, Jalandhar, Patiala and in union territory, Chandigarh were screened for T. solium. The collected samples were analyzed in relation to different epidemiological variables - Location, age, sex, breed, and management system and to conduct a PCR targeting valine t-RNA and NADH subunit-2. Against molecular confirmed T. solium, genetic polymorphism was asses for seven microsatellite satellite markers. FindingsA prevalence rate 5.14% on post mortem examination as well as molecular confirmation of suspected samples (PCR-targeting NADH subunit-2 gene). Highest prevalence rate was observed in Patiala (15%) with lowest in Bathinda (0.00%), due to low participation of the pig farmers of that region. We also observed genetic variability for seven microsatellite markers with TSSR_09 (26/200) and TSSR_01 (14/200) were the 2 microsatellites showing highest variability. ConclusionT. solium cysticercosis is a neglected tropical disease with significant public health hazard. Measures should be taken to prevent transmission of pathogen as well as sale of infected pork.

molecular biology↗

bioRxiv2025

Extensive endemic transmission of multidrug resistant Mycobacterium tuberculosis in Bhutan: A retrospective genomic-epidemiological study

Despite decreasing overall tuberculosis notifications, the proportion of multidrug-resistant tuberculosis (MDR-TB) cases are increasing in Bhutan. While most MDR-TB cases are diagnosed among patients in the bordering districts and the capital, current diagnostic tests are limited in their ability to differentiate between the recurrent introductions and local transmission. For the first time, we conducted a retrospective genomic-epidemiological study to provide insights into the population structure, genotypic resistance patterns, and explore recent transmission of drug-resistant TB in Bhutan. Whole genome sequencing was performed on randomly selected drug-resistant and drug-sensitive TB isolates from Bhutan, collected between 2018-2022 at Microbiological Diagnostic Unit Public Health Laboratory in Melbourne, Australia. We investigated drug resistance mutations, and genomic clustering of cases using different single nucleotide polymorphisms (SNPs) thresholds. Of the 203 sequences that passed the quality control, 126 (62.1%) were MDR-TB and 15 (7.4%) were isoniazid-resistant TB. There were four different circulating lineages, with most sequences belonging to lineage 2 (86.2%). Using a SNP-threshold of [≤]12 SNPs, 71% of sequences formed 12 genomic clusters. Surprisingly, the largest cluster included of 88% of all MDR-TB sequences and spanned the entire study period. These cases were highly clonal (mean pairwise SNP-distance of 10, range 0-25). Phylogenetic analysis with publicly available international sequence data showed that this MDR-TB cluster formed a distinct clade. The major burden of MDR-TB in Bhutan appears to be due to recent local transmission of cases resulting in a large, single endemic cluster. This information will be critical for TB control program in Bhutan to tackle the major burden of MDR-TB through enhanced contact tracing of this MDR-TB clade. Additionally, this genomic data will be valuable to regional neighbours to monitor for dissemination of the strain. This study highlights the significant value of investing in TB genomics in resource limited settings globally to gain actionable insights into transmission dynamics.

genomics↗

bioRxiv2025

Predicting Risk of Transfusion-Induced Red Blood Cell Alloimmunization Using Statistical and Machine Learning Approaches in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Database

Red blood cell (RBC) alloimmunization is a common complication from blood transfusion, often resulting in accelerated donor RBC destruction. Patients show substantial variation in their predisposition to RBC alloimmunization. Previous studies have identified several risk factors, but to our knowledge, there have been no studies that predict risk of RBC alloimmunization by modeling multiple potential risk factors simultaneously. Here, our study represents the first attempt to build prediction models for RBC alloimmunization using the large sample size and rich set of potential risk factors available in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) recipient database. To develop the prediction models, we applied a range of approaches, including traditional statistical models (logistic regression), and modern machine learning (including gradient boosting, random forest, and XGBoost), deep learning (the multilayer perceptron method), and large language models (LLM). XGBoost demonstrates the overall best performance among models providing uncertainty quantification (F1= 0.672 and area under the ROC curve [AUC-ROC]=0.752). LLMs show promising results with the best F1 scores (0.677-0.687), though they are limited by their inability to provide uncertainty estimates, they hold the potential for use as an interactive chatbot for patients. Although there is ample room for performance improvement, limiting the analysis to patients predicted with >80% confidence by XGBoost resulted in a substantially improved AUC-ROC of 0.919, which can be of potential clinical significance.

immunology↗

bioRxiv2025

Streptococcus pneumoniae vaccine serotype persistence following 13-valent pneumococcal conjugate vaccine introduction in Mongolia: investigating changes in epidemiology, immunology and virulence

BackgroundStreptococcus pneumoniae is a leading cause of pneumonia globally. Vaccine serotypes can persist despite pneumococcal conjugate vaccine (PCV) introduction. To examine serotype persistence, we leveraged 6,545 nasopharyngeal swabs collected from children hospitalised with pneumonia before and after PCV13 introduction in Mongolia and undertook molecular, epidemiological and experimental analyses. MethodsSerotype, genetic lineage and antimicrobial resistance genes were inferred from DNA microarray. Patients carrying lineages that were predominant pre- and post-PCV introduction were examined for differences in disease severity. We also compared the pre- and post-PCV lineages by bacterial adhesion to hydrocarbon (BATH) and enzyme-linked immunosorbent (ELISA) assays. Capsule gene expression was measured by quantitative reverse transcription polymerase chain reaction (qRT-PCR), capsule thickness by transmission electron microscopy, and virulence using an infant mouse model. FindingsChanges in lineage composition were observed within serotypes 6A, 6B, 14, 19F and 23F over the six-year surveillance period. Children carrying pre-PCV lineages were more likely to have severe pneumonia than those carrying post-PCV lineages (serotypes 6B, 14 and 19F). Pre-PCV lineages were more likely to be multi-drug resistant than post-PCV lineages (serotypes 6A, 6B and 23F). For serotype 6B the post-PCV lineage had higher cell surface hydrophobicity, lower IgG, lower expression of capsule genes and evidence of thinner capsule than the pre-PCV lineage. Notably, the post-PCV 6B lineage was also less virulent in mice than the pre-PCV 6B lineage. InterpretationDespite persistence of vaccine serotypes in highly vaccinated populations, vaccination may select for lineages with differences in capsule and antibody binding and that are less virulent. When evaluating the true value of vaccination, it is important to consider factors beyond serotype alone. FundingNational Health and Medical Research Council, Murdoch Childrens Research Institute, GAVI, the Vaccine Alliance.

microbiology↗

bioRxiv2025

Parameterisation of epidemiological models from small field experiments: a case study of banana bunchy top virus transmission

Accurate estimation of epidemiological parameters from limited field data remains a major challenge in plant disease modeling. We present a novel data-augmented adaptive multiple importance sampling (DA-AMIS) framework that integrates Bayesian inference with stochastic epidemic modeling to estimate key transmission parameters from small field experiments. Using detailed individual-level observations from a 24-plant experiment on the natural spread of banana bunchy top virus (BBTV) in Benin, we jointly inferred infection timing, dispersal characteristics, and transmission rates for both primary and secondary infections. Model validation against independent datasets from BBTV field trials in Burundi and Malawi showed close correspondence between simulated and observed prevalence dynamics, confirming the generality of parameter estimates across regions. The inferred 12% infection rate of replanting suckers underscores the risk of disease introduction through planting material, while simulations identified April as the period of peak infection, providing actionable insights for surveillance timing.

plant biology↗

bioRxiv2018

Microbiomes of North American Triatominae: the grounds for Chagas disease epidemiology

AbstarctInsect microbiomes influence many fundamental host traits, including functions of practical significance such as their capacity as vectors to transmit parasites and pathogens. The knowledge on the diversity and development of the gut microbiomes in various blood feeding insects is thus crucial not only for theoretical purposes, but also for the development of better disease control strategies. In Triatominae (Heteroptera: Reduviidae), the blood feeding vectors of Chagas disease in South America and parts of North America, the investigation of the microbiomes is in its infancy. The few studies done on microbiomes of South American Triatominae species indicate a relatively low taxonomic diversity and a high host specificity. We designed a comparative survey to serve several purposes: I) to obtain a better insight into the overall microbiome diversity in different species, II) to check the long term stability of the interspecific differences, III) to describe the ontogenetic changes of the microbiome, and IV) to determine the potential correlation between microbiome composition and presence in the vector gut of Trypanosoma cruzi, the causative agent of Chagas disease. Using 16S amplicons of two abundant species from the southern US, and four laboratory reared colonies, we showed that the microbiome composition is determined by host species, rather than locality or environment. The OTUs (Operational Taxonomic Units) determination confirms a low microbiome diversity, with 12-17 main OTUs detected in wild populations of T. sanguisuga and T. protracta. Among the dominant bacterial taxa are Acinetobacter and Proteiniphilum but also the symbiotic bacterium Arsenophonus triatominarum, previously believed to only live intracellularly. The possibility of ontogenic microbiome changes was evaluated in all six developmental stages and faeces of the laboratory reared model Rhodnius prolixus. We detected considerable changes along the hosts ontogeny, including clear trends in the abundance variation of the three dominant bacteria, namely Enterococcus, Acinetobacter and Arsenophonus. Finally, we screened the samples for the presence of T. cruzi. Comparing the parasite presence with the microbiome composition, we assessed the possible significance of the latter in the epidemiology of the disease. Particularly, we found a trend towards more diverse microbiomes in T. cruzi positive T. protracta specimens.

microbiology↗

bioRxiv2018

Epidemiology, Microbiology and Therapeutic Consequences of Chronic Osteomyelitis in Northern China: A Retrospective Analysis of 255 Patients

The study aimed to explore the epidemiology and clinical characteristics of chronic osteomyelitis observed in a northern China hospital. Clinical data of 255 patients with chronic osteomyelitis from January 2007 to January 2014 were collected and analyzed, including general information, disease data, treatment and follow-up data. Chronic osteomyelitis is more common in males and in the age group from 41-50 years of age. Common infection sites are the femur, tibiofibular, and hip joint. More g+ than g- bacterial infections were observed, with S. aureus the most commonly observed pathogenic organism. The positive detection rate from debridement bacterial culture is 75.6%. The detection rate when five samples are sent for bacterial culture is 90.6%, with pathogenic bacteria identified in 82.8% of cases. The two-stage debridement method (87.0%) has higher first curative rate than the one-stage debridement method (71.2%). To improve detection rate using bacterial culture, at least five samples are recommended. Treatment of chronic osteomyelitis with two-stage debridement, plus antibiotic-loaded polymethylmethacrylate (PMMA) beads provided good clinical results in this study and is therefore recommended.

microbiology↗

bioRxiv2018

Mutators as drivers of adaptation in pathogenic bacteria and a risk factor for host jumps and vaccine escape: insights into evolutionary epidemiology of the global aquatic pathogen Streptococcus iniae

Pathogens continuously adapt to changing host environments where variation in their virulence and antigenicity is critical to their long-term evolutionary success. The emergence of novel variants is accelerated in microbial mutator strains (mutators) deficient in DNA repair genes, most often from mismatch repair and oxidised-guanine repair systems (MMR and OG respectively). Bacterial MMR/OG mutants are abundant in clinical samples and show increased adaptive potential in experimental infection models, yet the role of mutators in the epidemiology and evolution of infectious disease is not well understood. Here we investigated the role of mutation rate dynamics in the evolution of a broad host range pathogen, Streptococcus iniae, using a set of 80 strains isolated globally over 40 years. We have resolved phylogenetic relationships using non-recombinant core genome variants, measured in vivo mutation rates by fluctuation analysis, identified variation in major MMR/OG genes and their regulatory regions, and phenotyped the major traits determining virulence in streptococci. We found that both mutation rate and MMR/OG genotype are remarkably conserved within phylogenetic clades but significantly differ between major phylogenetic lineages. Further, variation in MMR/OG loci correlates with occurrence of atypical virulence-associated phenotypes, infection in atypical hosts (mammals), and atypical tissue of a vaccinated primary hosts (barramundi bone). These findings suggest that mutators are likely to facilitate adaptations preceding major diversification events, and may promote emergence of variation permitting colonisation of a novel host tissue, novel host taxa (host jumps), and immune-escape in the vaccinated host.

microbiology↗

bioRxiv2018

Fast and flexible bacterial genomic epidemiology with PopPUNK

The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology.\n\nHowever, current whole-genome clustering and multi-locus typing approaches do not fully exploit core and accessory genomic variation, and cannot both automatically identify, and subsequently expand, clusters of significantly-similar isolates in large datasets and across species.\n\nHere we describe PopPUNK (Population Partitioning Using Nucleotide K-mers; https://poppunk.readthedocs.io/en/latest/). software implementing scalable and expandable annotation- and alignment-free methods for population analysis and clustering.\n\nVariable-length k-mer comparisons are used to distinguish isolates divergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using both simulated data and real datasets from ten taxonomically-widespread species. Connections between closely-related isolates of the same strain are robustly identified, despite variation in the discontinuous pairwise distance distributions that reflects species diverse evolutionary patterns. PopPUNK can process 103-104 genomes as single batch, with minimal memory use and runtimes up to 200-fold faster than existing methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to re-analyse all genomes de novo.\n\nThis facilitates real-time surveillance with stable cluster naming and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualisation and online publication is streamlined through automatic output of results to multiple platforms.\n\nPopPUNK has been designed as a flexible platform that addresses important issues with currently used whole-genome clustering and typing methods, and has potential uses across bacterial genetics and public health research.

genomics↗