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bioRxiv2020

Mutational dynamics and transmission properties of SARS-CoV-2 superspreading events in Austria

Superspreading events shape the COVID-19 pandemic. Here we provide a national-scale analysis of SARS-CoV-2 outbreaks in Austria, a country that played a major role for virus transmission across Europe and beyond. Capitalizing on a national epidemiological surveillance system, we performed deep whole-genome sequencing of virus isolates from 576 samples to cover major Austrian SARS-CoV-2 clusters. Our data chart a map of early viral spreading in Europe, including the path from low-frequency mutations to fixation. Detailed epidemiological surveys enabled us to calculate the effective SARS-CoV-2 population bottlenecks during transmission and unveil time-resolved intra-patient viral quasispecies dynamics. This study demonstrates the power of integrating deep viral genome sequencing and epidemiological data to better understand how SARS-CoV-2 spreads through populations. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

microbiology↗

bioRxiv2020

Origin and evolutionary dynamics of multi-drug resistant and highly virulent community-associated methicillin-resistant Staphylococcus aureus ST772-SCCmec V lineage

BackgroundCommunity-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) are increasing in prevalence across the world. However, studies on the molecular epidemiology and the genomic investigation of MRSA are limited in India. ObjectivesTo understand the molecular epidemiology of MRSA and to reconstruct the origin and evolution of S. aureus belonged to the sequence type (ST772). MethodsA total of 233 non-repetitive MRSA isolates were screened for the presence staphylococcal cassette chromosome (SCCmec) types, multi-locus sequence types (MLST) and staphylococcal protein A (spa) types. Whole genome sequence data of ST772-SCCmec V (n=32) isolates were generated and analysed along with the publically available ST772-SCCmec V (n=273) genome. ResultsST772 (27%), ST22 (19%) and ST239 (16%) were found as the predominant STs. Analysis of the core SNPs using Bayesian time scaled phylogenetic analysis showed ST772-SCCmec V was emerged on the Indian subcontinent in 1960s. The acquisition of integrated resistance plasmid (IRP) in the ST772-SCCmec V lineage during 1990s, fixation of SCCmec V (5C2) and the double serine mutations (S84L, S80Y) appears to have played a key role in the successful expansion. The IRP carries the loci for multiple antibiotic resistant genes: beta-lactam (blaZ), aminoglycosides (aphA3-sat-aadE), macrolide (mphC), macrolide-lincosamide-streptogramin B (msrA) and bacitracin (bacA, bacB). ConclusionThe Panton Valentine Leukocidin (PVL) positive ST772 and ST22 MRSA lineages are observed in the hospital settings. ST772-SCCmec V has the multi-drug resistance trait of hospital-associated (HA) MRSA and the epidemiological characteristics of CA-MRSA. The antimicrobial use pattern may have driven the spread and survival of ST772 MRSA in hospitals.

microbiology↗

bioRxiv2020

Validation of a novel multiplex real-time PCR assay for Trypanosoma cruzi detection and quantification in acai pulp

In Brazil, orally acquired T. cruzi infection has become the most relevant transmission mechanisms from public health perspective. Around 70% of new Chagas disease cases have been associated with consumption of contaminated food or beverages. Acai (Euterpe oleracea and Euterpe precatoria) is currently one of the most commercialized Amazonian fruits in the Brazilian and international markets. Therefore, it has become important to incorporate in the production process some procedures to measure out effective hygiene and product quality control required by global market. Molecular methods have been developed for rapid detection and quantification of T. cruzi DNA in several biological samples, including food matrices, for epidemiological investigation of Chagas disease and food quality control. However, a high-performance molecular methodology since DNA extraction until detection and quantification of T. cruzi DNA in acai berry pulp is still needed. Herein, a simple DNA extraction methodology was standardized from the supernatant of acai berry pulp stabilized in a Lysis buffer. In addition, a multiplex real time qPCR assay, targeting T. cruzi DNA and an Exogenous Internal Positive Control was developed and validated, using reference from all T. cruzi DTUs and commercial samples of acai pulp, from an endemic municipality with previous history of oral Chagas disease outbreak. Thus, a high-sensitivity qPCR assay, that could detect up to 0.01 parasite equivalents/mL in acai, was reached. As of the 45 commercial samples analyzed, 9 (20%) were positive for T. cruzi. This high-sensitive, fast and easy-to-use molecular assay is compatible with most of the laboratories involved in the investigations of oral Chagas disease outbreaks, representing an important tool to the epidemiology, control and surveillance of Chagas disease. Author SummaryOral transmission of Chagas disease has acquired an increasingly importance on the disease epidemiology. Most of the orally acquired Chagas Disease cases are related to the consumption of fresh foods or drinks, as sugar cane juice, acai berry pulp and bacaba wine, contaminated with triatomines or its feces. In Brazil, it has recently caused numerous outbreaks and has been linked to unusually severe acute infections. So far, the evaluation of the potential for oral transmission of Chagas disease through the consumption of acai-based products is mostly determined by clinical or parasitological methods. Despite the recent advances, a highly sensitive, reproductible and properly validated real time PCR assay for the molecular diagnostic of T. cruzi in acai pulp samples is still missing. Herein, a simple and reproducible multiplex real-time PCR assay was developed to the detection and quantification of T. cruzi DNA in acai pulp samples. This methodology, that includes a simple step for sample stabilization and DNA extraction based on silica-membrane spin columns, can be useful for analyzing orally transmitted acute Chagas disease outbreaks.

microbiology↗

bioRxiv2020

Novel SARS-CoV-2 Whole-genome sequencing technique using Reverse Complement PCR enables fast and accurate outbreak analysis

BackgroundCurrent transmission rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still increasing and many countries are facing second waves of infections. Rapid SARS-CoV-2 whole-genome sequencing (WGS) is often unavailable but could support public health organizations and hospitals in monitoring and determining transmission links. Here we report the use of reverse complement polymerase chain reaction (RC-PCR), a novel technology for WGS of SARS-CoV-2 enabling library preparation in a single PCR saving time, resources and enables high throughput screening. Additionally, we show SARS-CoV-2 diversity and possible transmission within the Radboud university medical center (Radboudumc) during September 2020 using RC-PCR WGS. MethodsA total of 173 samples tested positive for SARS-CoV-2 between March and September 2020 were selected for whole-genome sequencing. Ct values of the samples ranged from 16 to 42. They were collected from 83 healthcare workers and three patients at the Radboudumc, in addition to 64 people living in the area around the hospital and tested by the local health services. For validation purposes, nineteen of the included samples were previously sequenced using Oxford Nanopore Technologies and compared to RC-PCR WGS results. The applicability of RC-PCR WGS in outbreak analysis for public health service and hospitals was tested on six suspected clusters containing samples of healthcare workers and patients with an epidemiological link. FindingsRC-PCR resulted in sequencing data for 146 samples. It showed a genome coverage of up to 98,2% for samples with a maximum Ct value of 32. Comparison to Oxford Nanopore technologies gives a near-perfect agreement on 95% of the samples (18 out of 19). Three out of six clusters with a suspected epidemiological link were fully confirmed, in the others, four healthcare workers were not associated. In the public health service samples, a previously unknown chain of transmission was confirmed. Significance statementSAR-CoV-2 whole-genome sequencing using RC-PCR is a reliable technique and applicable for use in outbreak analysis and surveillance. Its ease of use, high-trough screening capacity and wide applicability makes it a valuable addition or replacement during this ongoing SARS-CoV-2 pandemic. FundingNone Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAt present whole genome sequencing techniques for SARS-CoV-2 have a large turnover time and are not widely available. Only a few laboratories are currently able to perform large scale SARS-CoV-2 sequencing. This restricts the use of sequencing to aid hospital and community infection prevention. Added value of this studyHere we present clinical and technical data on a novel Whole Genome Sequencing technology, implementing reverse-complement PCR. It is able to obtain high genome coverage of SARS-CoV-2 and confirm and exclude epidemiological links in 173 healthcare workers and patients. The RC-PCR technology simplifies the workflow thereby reducing hands on time. It combines targeted PCR and sequence library construction in a single PCR, which normally takes several steps. Additionally, this technology can be used in concordance with the widely available range of Illumina sequencers. Implications of all the available evidenceRC-PCR whole genome sequencing technology enables rapid and targeted surveillance and response to an ongoing outbreak that has great impact on public health and society. Increased use of sequencing technologies in local laboratories can help prevent increase of SARS-CoV-2 spreading by better understanding modes of transmission.

microbiology↗

bioRxiv2020

Phylodynamic analysis of an emergent Mycobacterium bovis outbreak in an area with no previously known wildlife infections

Understanding how an emergent pathogen successfully establishes itself and persists in a previously unaffected population is a crucial problem in disease ecology. In multi-host pathogen systems this problem is particularly difficult, as the importance of each host species to transmission is often poorly characterised, and the epidemiology of the disease is complex. Opportunities to observe and analyse such emergent scenarios are few. Here, we exploit a unique dataset combining densely-collected data on the epidemiological and evolutionary characteristics of an outbreak of Mycobacterium bovis (M. bovis, the causative agent of bovine tuberculosis, bTB) in a population of cattle and badgers in an area considered low-risk for bTB, that has no previous record of either persistent infection in cattle, or of any infection in wildlife. We analyse the outbreak dynamics using a combination of mathematical modelling, machine learning and Bayesian evolutionary analyses. Comparison to M. bovis whole-genome sequences from Northern Ireland confirmed this to be a single introduction of the pathogen from the latter region, with evolutionary analysis supporting an introduction directly into the local cattle population at least six years prior to its first discovery in badgers. Once introduced, the evidence supports M. bovis epidemiological dynamics passing through two phases, the first dominated by cattle-to-cattle transmission before becoming established in the local badger population. These findings emphasise the importance of disease surveillance for early containment of outbreaks, in particular for pathogens not causing immediately evident symptoms in the infected host, and highlight the utility of combining dynamic modelling and phylogenetic analyses for understanding the often complex infection dynamics associated with emergent outbreaks.

ecology↗

bioRxiv2021

Large scale genomic and evolutionary study reveals SARS-CoV-2 virus isolates from Bangladesh strongly correlate with European origin and not with China.

RationaleThe global public health is in serious crisis due to emergence of SARS-CoV-2 virus. Studies are ongoing to reveal the genomic variants of the virus circulating in various parts of the world. However, data generated from low- and middle-income countries are scarce due to resource limitation. This study was focused to perform whole genome sequencing of 151 SARS-CoV-2 isolates from COVID-19 positive Bangladeshi patients. The goal of this study was to identify the genomic variants among the SARS-CoV-2 virus isolates in Bangladesh, to determine the molecular epidemiology and to develop a relationship between host clinical trait with the virus genomic variants. MethodSuspected patients were tested for COVID-19 using one step commercial qPCR kit for SARS-CoV-2 Virus. Viral RNA was extracted from positive patients, converted to cDNA which was amplified using Ion AmpliSeq SARS-CoV-2 Research Panel. Massive parallel sequencing was carried out using Ion AmpliSeq Library Kit Plus. Assembly of raw data is done by aligning the reads to a pre-defined reference genome (NC_045512.2) while retaining the unique variations of the input raw data by creating a consensus genome. A random forest-based association analysis was carried out to correlate the viral genomic variants with the clinical traits present in the host. ResultAmong the 151 viral isolates, we observed the 413 unique variants. Among these 8 variants occurred in more than 80 % of cases which include 241C to T, 1163A to T, 3037C to T,14408C to T, 23403A to G, 28881G to A, 28882 G to A, and finally the 28883G to C. Phylogenetic analysis revealed a predominance of variants belonging to GR clade, which have a strong geographical presence in Europe, indicating possible introduction of the SARS-CoV-2 virus into Bangladesh through a European channel. However, other possibilities like a route of entry from China cannot be ruled out as viral isolate belonging to L clade with a close relationship to Wuhan reference genome was also detected. We observed a total of 37 genomic variants to be strongly associated with clinical symptoms such as fever, sore throat, overall symptomatic status, etc. (Fishers Exact Test p-value<0.05). The most mention-worthy among those were the 3916CtoT (associated with causing sore throat, p-value 0.0005), the 14408C to T (associated with protection from developing cough, p-value= 0.027), and the 28881G to A, 28882G to A, and 28883G to C variant (associated with causing chest pain, p-value 0.025). ConclusionTo our knowledge, this study is the first large scale phylogenomic studies of SARS-CoV-2 virus circulating in Bangladesh. The observed epidemiological and genomic features may inform future research platform for disease management, vaccine development and epidemiological study.

genetics↗

bioRxiv2021

PulseNet international: the missing link between PFGE and WGS

IntroductionDNA-based surveillance of bacterial diseases has been using pulsed field gel electrophoresis (PFGE) since 1996. Currently, the international surveillance network (PulseNet international) is turning toward whole genome sequencing (WGS). ATCGs of WGS are compared using several sequence alignment methods. While patterns of horizontal lines of PFGE profiles are being compared using relative positioning of bands within a range of tolerance. A recently suggested image analysis algorithm and a deployed database (geltowgs.uofk.edu) collectively invented a promising method for comparing PFGE to in-silico obtained digestion models (DMs) derived from WGS. The database requires a parameter that determines PFGE resolution. Here, the author suggests a new method for calculating this factor. Epidemiological and molecular conclusions returned by the database are evaluated. Methodologytwo PFGE profiles representing XbaI digests of E. coli and Salmonella enterica analyzed by the suggested image analysis algorithm were submitted to the database after calculating resolution of PFGE using Dice percentage of difference between the closest PFGE bands in length. E. coli and Salmonella enterica test subjects were compared to 489 and 401 DMs respectively. The three data sets returned were analyzed. Results and conclusionsaccording to modified PFGE evaluation criteria; a single DM is possibly related to E. coli test subject. It belonged to the same serovar. No epidemiologically related DM was shown for S. enterica test subject. Conclusions mentioned earlier could never be made ignoring co-migration. Standardization of both; suggested image analysis and database algorithms will deepen our understanding of bacterial epidemiology by means of possible qualitative approach built upon identification of fragment sequences and their locations within chromosomes.

bioinformatics↗

bioRxiv2021

phastSim: efficient simulation of sequence evolution for pandemic-scale datasets

Sequence simulators are fundamental tools in bioinformatics, as they allow us to test data processing and inference tools, as well as being part of some inference methods. The ongoing surge in available sequence data is however testing the limits of our bioinformatics software. One example is the large number of SARS-CoV-2 genomes available, which are beyond the processing power of many methods, and simulating such large datasets is also proving difficult. Here we present a new algorithm and software for efficiently simulating sequence evolution along extremely large trees (e.g. < 100, 000 tips) when the branches of the tree are short, as is typical in genomic epidemiology. Our algorithm is based on the Gillespie approach, and implements an efficient multi-layered search tree structure that provides high computational efficiency by taking advantage of the fact that only a small proportion of the genome is likely to mutate at each branch of the considered phylogeny. Our open source software is available from https://github.com/NicolaDM/phastSim and allows easy integration with other Python packages as well as a variety of evolutionary models, including indel models and new hypermutatability models that we developed to more realistically represent SARS-CoV-2 genome evolution. Author summaryOne of the most influential responses to the SARS-CoV-2 pandemic has been the widespread adoption of genome sequencing to keep track of viral spread and evolution. This has resulted in vast availability of genomic sequence data, that, while extremely useful and promising, is also increasingly hard to store and process efficiently. An important task in the processing of this genetic data is simulation, that is, recreating potential histories of past and future virus evolution, to benchmark data analysis methods and make statistical inference. Here, we address the problem of efficiently simulating large numbers of closely related genomes, similar to those sequenced during SARS-CoV-2 pandemic, or indeed to most scenarios in genomic epidemiology. We develop a new algorithm to perform this task, that provides not only computational efficiency, but also extreme flexibility in terms of possible evolutionary models, allowing variation in mutation rates, non-stationary evolution, and indels; all phenomena that play an important role in SARS-CoV-2 evolution, as well as many other real-life epidemiological scenarios.

bioinformatics↗

bioRxiv2021

Whole-genome-based Helicobacter pylori geographic surveillance: a visualized and expandable webtool

Helicobacter pylori exhibits specific geographic distributions that related to the clinical outcomes. Despite the high infection rate of H. pylori throughout the world, the genetic epidemiology surveillance of H. pylori still needs to be improved. Here, we used single nucleotide polymorphisms (SNPs) profiling approach based on whole genome sequencing (WGS) that facilitates genomic population analyses of H. pylori and encourages the dissemination of microbial genotyping strategies worldwide. A total number of 1,211 public H. pylori genomes were downloaded and used to construct the typing tool, named as HPTT (H. pylori Typing Tool). Combined with the metadata, we developed two levels of genomic typing, including a continent scale and a country scale that nested in the continent scale. Results showed that Asia was the largest isolates source in our dataset, while isolates from Europe and Oceania were comparatively more widespread. More specifically, Switzerland and Australia are the main source of widespread isolates in their corresponding continents. To integrate all the typing information and enable researchers to compare their own dataset against the existing global database in an easy and rapid way, a user-friendly website (https://db.cngb.org/HPTT/) was developed with both genomic typing tool and visualization tool. To further confirm the validity of the website, ten newly assembled genomes were downloaded and tested precisely located on the branch as we expected. In summary, H. pylori typing tool (HPTT) is a novel genomic epidemiological tool that can achieve high resolution analysis of genomic typing and visualizing simultaneously, providing insights into the genetic population structure analysis, evolution analysis and epidemiological surveillance of H. pylori.

genomics↗

bioRxiv2021

The quantitative genetics of the endemic prevalence of infectious diseases: Indirect Genetic Effects dominate heritable variation and response to selection

Infectious diseases have profound effects on life, both in nature and agriculture. Despite the availability of well-established epidemiological theory, however, a quantitative genetic theory of the host population for the endemic prevalence of infectious diseases is almost entirely lacking. While several studies have demonstrated the relevance of the transmission dynamics of infectious diseases for heritable variation and response to selection of the host population, our current theoretical framework of quantitative genetics excludes these dynamics. As a consequence, we do not know which genetic effects of the host population determine the prevalence of an infection, and have no concepts of breeding value and heritable variation for endemic prevalence. Here we integrate quantitative genetics and epidemiology, and propose a quantitative genetic theory for R0 and for the endemic prevalence of an infectious disease. We first identify the genetic factors that determine the prevalence of an infection, using an approach founded in epidemiological theory. Subsequently we investigate the population level consequences of individual genetic variation, both for R0 and for the endemic prevalence. Next, we present expressions for the breeding value and heritable variation, for both prevalence and individual binary disease status, and show that these parameters depend strongly on the level of the prevalence. Results show that heritable variation for endemic prevalence is substantially greater than currently believed, and increases when prevalence approaches zero, while heritability of individual disease status goes to zero. As a consequence, response of prevalence to selection accelerates considerably when prevalence goes down, in contrast to predictions from classical theory. Finally, we show that most of the heritable variation for the endemic prevalence of an infection is hidden due to indirect genetic effects, suggesting a key role for kin-group selection both in the evolutionary history of current populations and for genetic improvement strategies in animals and plants.

genetics↗

bioRxiv2021

Exploration of clinical breakpoint of Danofloxacin for Glaesserella parasuis in plasma and in PELF

BackgroundTo establish the clinical breakpoint (CBP) of danofloxacin to G. parasuis, three cutoff values, including epidemiological cutoff value (ECV), pharmacodynamic cutoff value (COPD) and clinical cutoff value (COCL), was obtained in the present study. MethodsThe ECV was calculated using ECOFFinder base on MIC distribution of 347 G. parasuis collected from disease pigs. The COPD was established base on in vivo and ex vivo pharmacokinetic (PK) - pharmacodynamic (PD) modeling of danofloxacin both in plasma and pulmonary epithelial lining fluid (PELF) using Hill formula and Monte Carlo analysis. The COCL was established based on the relationship between possibility of cure (POC) and MIC in the clinical trials using "WindoW" approach, nonlinear regression and CART analysis. ResultsThe MIC50 and MIC90 of danofloxacin against 347 G. parasuis were 2 g/mL and 8 g/mL, respectively. The ECV value was set up as 8 g/mL using ECOFFinder. Concentration-time curve of danofloxacin indicated a two-compartment model for PK analysis. The PK parameters of the maximum concentration (Cmax) and area under concentration-time curve (AUC) in PELF were 3.67 {+/-} 0.25 g/mL and 24.28 {+/-} 2.70 h{middle dot}g/mL, higher than those in plasma (0.67 {+/-} 0.01g/mL and 4.47 {+/-} 0.51 h{middle dot}g/mL). The peak time (Tmax) in plasma was 0.23 {+/-} 0.07 h, shorter than that in PELF (1.61 {+/-} 0.15 h). The COPD in plasma and PELF were 0.125 g/mL and 0.5 g/mL, respectively. The COCL calculated by WindoW approach, nonlinear regression and CART analysis were 0.125[~]4 g/mL, 0.428 g/mL and 0.56 g/mL, respectively. The 0.5 g/mL was selected as eligible COCL. The ECV is much higher than the COPD and COCL, and the clinical breakpoint based on data in plasma was large different with that of in PELF. ConclusionsOur study firstly established three cutoff values of danofloxacin against G. parasuis. It suggested that epidemiological danofloxacin-resistant G. parasuis may lead to the ineffective treatment by danofloxacin. ImportanceG. parasuis, a gram-negative respiratory pathogen, can colonize in the upper respiratory tract in swine and cause Glassers disease. As the abuse of antibiotics, antimicrobial resistant G. parasuis emerged in different degrees, which brought serious threat to global economy and public health. Danofloxacin in quinolones are one of the best choices for treatment of G. parasuis infection, because of their strong bactericidal activity and good absorption into blood and great distribution in the lung. However, the clinical breakpoint (CBP) for danofloxacin against G. parasuis had not yet been established by clinical laboratory of standard Institute (CLSI) and European Commission of antimicrobial susceptibility testing (EUCAST). Our study firstly established three cutoff values of danofloxacin against G. parasuis. It suggested that epidemiological danofloxacin-resistant G. parasuis may lead to the ineffective treatment by danofloxacin.

microbiology↗

bioRxiv2021

Disentangling how multiple traits drive 2 strain frequencies in SIS dynamics with coinfection

A general theory for competitive dynamics among many strains at the epidemiological level is required to understand polymorphisms in virulence, transmissibility, antibiotic resistance and other biological traits of infectious agents. Mathematical coinfection models have addressed specific systems, focusing on the criteria leading to stable coexistence or competitive exclusion, however, due to their complexity and nonlinearity, analytical solutions in coinfection models remain rare. Here we study a 2-strain SIS compartmental model with co-infection/co-colonization, incorporating multiple fitness dimensions under the same framework: variation in transmissibility, duration of carriage, pairwise susceptibilities to coinfection, coinfection duration, and transmission priority effects from mixed coinfection. Taking advantage of a singular perturbation approach, under the assumption of strain similarity, we expose how strain dynamics on a slow timescale are explicitly governed by a replicator equation which encapsulates all traits and their interplay. This allows us to predict explicitly not only the final epidemiological outcome of a given 2-player competition, but moreover, their entire frequency dynamics as a direct function of their relative variation and of strain-transcending global parameters. Based on mutual invasion fitnesses, we analyze and report rigorous results on transition phenomena in the 2-strain system, strongly mediated via coinfection prevalence. We show that coinfection is not always a promoter of coexistence; instead, its effect to favour or prevent polymorphism is non-monotonic and depends on the type and level of phenotypic differentiation between strains. This framework offers a deeper analytical understanding of 2-strain competitive games in coinfection, with theoretical and practical applications in epidemiology, ecology and evolution.

ecology↗

bioRxiv2021

Genome Sequencing Identifies Previously Unrecognized Klebsiella pneumoniae Outbreaks in Neonatal Intensive Care Units in the Philippines

BackgroundKlebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least two classes of antibiotics, yet mechanisms and spread of its resistance are not well studied. MethodsA retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam- and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015-2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic and genome-derived data. ResultsPrevalent AMR mechanisms detected include blaCTX-M-15 (76.8%) and blaNDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying blaNDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (ST). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs, K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged <1. ConclusionWGS provided an in-depth understanding of the epidemiology of AMR in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of three previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs. summaryWhole genome sequencing identified three distinct previously unrecognized local outbreaks in a retrospective study in the Philippines, along with an epidemic plasmid carrying antimicrobial resistance genes, highlighting its importance in antimicrobial resistance surveillance, outbreak detection and infection control.

genomics↗

bioRxiv2021

Development and Validation of a High-throughput Short Sequence Typing Scheme for Serratia marcescens Pure Culture and Environmental DNA

Molecular typing methods are used to characterize the relatedness between bacterial isolates involved in infections. These approaches rely mostly on discrete loci or whole genome sequences (WGS) analyses of pure cultures. On the other hand, their application to environmental DNA profiling to evaluate epidemiological relatedness amongst patients and environments has received less attention. We developed a specific, high-throughput short sequence typing (HiSST) method for the opportunistic human pathogen Serratia marcescens. Genes displaying the highest polymorphism were retrieved from the core genome of 60 S. marcescens strains. Bioinformatics analyses showed that use of only three loci (within bssA, gabR and dhaM) distinguished strains with the same level of efficiency than average nucleotide identity scores of whole genomes. This HiSST scheme was applied to an epidemiological survey of S. marcescens in a neonatal intensive care unit (NICU). In a first case study, a strain responsible for an outbreak in the NICU was found in a sink drain of this unit, by using HiSST scheme and confirmed by WGS. The HiSST scheme was also applied to environmental DNA extracted from sink-environment samples. Diversity of S. marcescens was modest, with 11, 6 and 4 different sequence types (ST) of gabR, bssA and dhaM loci amongst 19 sink drains, respectively. Epidemiological relationships amongst sinks were inferred on the basis of pairwise comparisons of ST profiles. Further research aimed at relating ST distribution patterns to environmental features encompassing sink location, utilization and microbial diversity is needed to improve the surveillance and management of opportunistic pathogens.

molecular biology↗

bioRxiv2021

Global evolutionary dynamics and resistome analysis of Clostridioides difficile ribotype 017

Clostridioides difficile PCR ribotype (RT) 017 ranks among the most successful strains of C. difficile in the world. In the past three decades, it has caused outbreaks on four continents, more than other "epidemic" strains, however, our understanding of the genomic epidemiology underpinning the spread of C. difficile RT 017 is limited. Here, we performed high-resolution phylogenomic and Bayesian evolutionary analyses on an updated and more representative dataset of 282 non-clonal C. difficile RT 017 isolates collected worldwide between 1981 and 2019. These analyses place an estimated time of global dissemination between 1953 and 1983 and identified the acquisition of the ermB-positive transposon Tn6194 as a key factor behind global emergence. This coincided with the introduction of clindamycin, a key inciter of C. difficile infection, into clinical practice in the 1960s. Based on the genomic data alone, the origin of C. difficile RT 017 could not be determined, however, geographical data and records of population movement suggest that C. difficile RT 017 had been moving between Asia and Europe since the Middle Ages and was later transported to North America around 1860 (95% CI: 1622 - 1954). A focused epidemiological study of 45 clinical C. difficile RT 017 genomes from a cluster in a tertiary hospital in Thailand revealed that the population consisted of two groups of multidrug-resistant (MDR) C. difficile RT 017 and a group of early, non-MDR C. difficile RT 017. The significant genomic diversity within each MDR group suggests that although they were all isolated from hospitalised patients, there was likely a reservoir of C. difficile RT 017 in the community that contributed to the spread of this pathogen. Impact statementThis study utilises genomic sequence data from 282 non-clonal C. difficile ribotype (RT) 017 isolates collected from around the world to delineate the origin and spread of this epidemic lineage, as well as explore possible factors that have driven its success. It also reports a focused epidemiological investigation of a cluster of C. difficile RT 017 in a tertiary hospital in Thailand to identify possible sources of transmission in this specific setting. Data summaryAll new WGS data generated in this study has been submitted to the European Nucleotide Archive under the BioProject PRJEB44406 (sample accession ERS6268756 - ERS6268798). The complete genome of C. difficile MAR286 was submitted to GenBank under BioProject PRJNA679085 (accession CP072118). Details of all genomes included in the final analyses are available in the Supplementary Document, available at 10.6084/m9.figshare.14544792.

microbiology↗

bioRxiv2021

Bats host the most virulent--but not the most dangerous--zoonotic viruses

Identifying virus characteristics associated with the largest public health impacts on human populations is critical to informing zoonotic risk assessments and surveillance strategies. Efforts to assess "zoonotic risk" often use trait-based analyses to identify which viral and reservoir host groups are most likely to source zoonoses but have not fully addressed how and why the impacts of zoonotic viruses vary in terms of disease severity ( virulence), capacity to spread within human populations ( transmissibility), or total human mortality ( death burden). We analyzed trends in human case fatality rates, transmission capacities, and total death burdens across a comprehensive dataset of mammalian and avian zoonotic viruses. Bats harbor the most virulent zoonotic viruses even when compared to birds, which alongside bats, have been hypothesized to be "special" zoonotic reservoirs due to molecular adaptations that support the physiology of flight. Reservoir host groups more closely related to humans--in particular, Primates--harbor less virulent, but more highly transmissible viruses. Importantly, disproportionately high human death burden, arguably the most important metric of zoonotic risk, is not associated with any animal reservoir, including bats. Our data demonstrate that mechanisms driving death burdens are diverse and often contradict trait-based predictions. Ultimately, total human mortality is dependent on context-specific epidemiological dynamics, which are shaped by a combination of viral traits and conditions in the animal host population and across and beyond the human-animal interface. Understanding the conditions that predict high zoonotic burden in humans will require longitudinal studies of epidemiological dynamics in wildlife and human populations. Significance statementThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective burden on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

ecology↗

bioRxiv2021

Ruminant-associated Listeria monocytogenes isolates belong preferentially to dairy-related hypervirulent clones: a longitudinal study in 19 farms

The increasing prevalence of Listeria monocytogenes infections is a public health issue. Although studies have shown that ruminants constitute reservoirs of this foodborne pathogen, little is known about its epidemiology and genetic diversity within ruminant farms. Here we conducted a large-scale genomic and epidemiologic longitudinal study of Listeria spp. in dairy ruminants and their environments, comprising 19 farms monitored for three consecutive seasons (N=3251 samples). L. innocua was the most prevalent Listeria spp, followed by L. monocytogenes. L. monocytogenes was detected in 52.6% of farms (prevalence in feces samples 3.8%, in farm environment samples 2.5%) and more frequently in cattle (4.1%) and sheep (4.5%) than in goat farms (0.2%). Lineage I accounted for 69% of L. monocytogenes isolates. Among animal samples, the most prevalent sublineages (SL) and clonal complexes (CC) were SL1/CC1, SL219/CC4, SL26/CC26 and SL87/CC87, whereas SL666/CC666 was prevalent in environmental samples. 61 different L. monocytogenes CTs (cgMLST sequence types) were found, 17 of them (27.9%) common to different animals and/or surfaces within the same farms. L. monocytogenes prevalence was not affected by farm hygiene but by season: the overall prevalence of L. monocytogenes in cattle farms was higher during winter, and in sheep farms was higher during winter and spring. Cows in their second lactation had a higher probability of L. monocytogenes fecal shedding than other lactating cows. This study highlights that dairy farms constitute a reservoir for hypervirulent L. monocytogenes and the importance of continuous animal surveillance to reduce the burden of human listeriosis. IMPORTANCEListeria monocytogenes is a bacterial pathogen responsible for listeriosis, the foodborne disease with the highest hospitalization and case-fatality rate. Despite increasing evidence that dairy products and ruminant farms are important reservoirs of L. monocytogenes, little is known about the epidemiology and genetic diversity of Listeria spp. within dairy ruminant farms. We report the largest Listeria spp. longitudinal study in individual domestic animals, and the first using whole-genome sequencing for a deep isolate characterization. Here, we show that domestic ruminants can be asymptomatic carriers of pathogenic Listeria, that L. monocytogenes fecal shedding is often intermittent, and that hypervirulent L. monocytogenes clones are overrepresented in dairy farms. Moreover, we uncover the effect of seasons and lactation number on the prevalence of L. monocytogenes in ruminants. Our study highlights the need for Listeria spp. monitoring in farm animals to control the spread of hypervirulent L. monocytogenes and reduce the burden of human listeriosis.

microbiology↗

bioRxiv2021

Carbapenem-Resistant Acinetobacter baumannii in US hospitals: diversification of circulating lineages and antimicrobial resistance

Carbapenem-resistant Acinetobacter baumannii (CRAb) are a major cause of healthcare-associated infections. CRAb are typically multidrug-resistant and infection is difficult to treat. Despite the urgent threat that CRAb pose, few systematic studies of CRAb clinical and molecular epidemiology have been conducted. The Study Network of Acinetobacter as a Carbapenem-Resistant Pathogen (SNAP) is designed to investigate the clinical characteristics and contemporary population structure of CRAb circulating in US hospital systems using whole genome sequencing (WGS). Analysis of the initial 120 SNAP patients from four US centers revealed that CRAb remain a significant threat to hospitalized patients, affecting the most vulnerable patients and resulting in 24% all-cause 30-day mortality. The majority of currently circulating isolates belonged to ST2Pas, a part of Clonal Complex 2 (CC2), which is the dominant drug-resistant lineage in the United States and Europe. We identified three distinct sub-lineages within CC2, which differed in their antibiotic resistance phenotypes and geographic distribution. Most concerning, colistin resistance (38%) and cefiderocol (10%) resistance were common within CC2 sub-lineage C (CC2C), where the majority of isolates belonged to ST2Pas/ST281Ox. Additionally, we identified a newly emergent lineage, ST499Pas that was the most common non-CC2 lineage in our study and had a more favorable drug susceptibility profile compared to CC2. Our findings suggest a shift within the CRAb population in the US during the past 10 years, and emphasize the importance of real-time surveillance and molecular epidemiology in studying CRAb dissemination and clinical impact. ImportanceCarbapenem-resistant Acinetobacter baumannii (CRAb) constitute a major threat to public health. To elucidate the molecular and clinical epidemiology of CRAb in the US, clinical CRAb isolates were collected along with data on patient characteristics and outcomes and bacterial isolates underwent whole genome sequencing and antibiotic susceptibility phenotyping. Key findings included emergence of new sub-lineages within the globally predominant clonal complex (CC) 2, increased colistin and cefiderocol resistance within one of the CC2 sub-lineages, and the emergence of ST499Pas as a previously unrecognized CRAb lineage in US hospitals.

microbiology↗