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bioRxiv2022

COVID-MVP: an interactive visualization for tracking SARS-CoV-2 mutations, variants, and prevalence, enabled by curated functional annotations and portable genomics workflow

The SARS-CoV-2 pandemic has reemphasized the importance of genomic epidemiology to track the evolution of the virus, dynamics of epidemics, geographic origins, and the emerging variants. It is vital in understanding the epidemiological spread of the virus on global, national, and local scales. Several analytical (bioinformatics) resources have been developed for molecular surveillance. However, a resource that combines genetic mutations and functional annotations on the impact of these mutations has been lacking in SARS-CoV-2 genomics surveillance. COVID-MVP provides an interactive visualization application that summarizes the mutations and their prevalence in SARS-CoV-2 viral lineages and provides functional annotations from the literature curated in an ongoing effort, Pokay. COVID-MVP is a tool that can be used for routine surveillance including spatio-temporal analyses. We have powered the visualization through a scalable and reproducible genomic analysis workflow nf-ncov-voc wrapped in Nextflow. COVID-MVP allows users to interactively explore data and download summarized surveillance reports. COVID-MVP, Pokay, and nf-ncov-voc are open-source tools available under the Massachusetts Institute of Technology (MIT) and GPL-3.0 licenses. COVID-MVP source code is available at https://github.com/cidgoh/COVID-MVP and an instance is hosted at https://covidmvp.cidgoh.ca.

bioinformatics↗

bioRxiv2022

A genomic platform for surveillance and antigen discovery in Plasmodium spp. using long-read amplicon sequencing

Many vaccine candidate proteins are under strong selective pressure to diversify in terms of antigenicity. We present a sequencing and data analysis platform for epidemiological surveillance and discovery of indel-rich vaccine antigens by long-read circular consensus sequencing (CCS) in multiclonal pathogen isolates. Our platform uses 40 PCR primers to asymmetrically barcode and identify multiclonal infections in pools of up to 384 samples. We validated the method using 235 mock infections combining 10 synthetic variants of the indel-rich gene merozoite surface protein 2 of Plasmodium falciparum at different concentrations and infection complexities, as well as 95 isolates from P. falciparum-infected residents of Nyamisati, Tanzania. We also constructed a fully automated analysis pipeline that streamlines the processing and interpretation of epidemiological and antigenic diversity data from demultiplexed FASTQ files. This platform can be easily adapted to other polymorphic antigens of interest in Plasmodium and other human pathogens.

genomics↗

bioRxiv2022

Antigenic escape accelerated by the presence of immunocompromised hosts

The repeated emergence of SARS-CoV-2 escape mutants from host immunity has obstructed the containment of the current pandemic and poses a serious threat to humanity. Prolonged infection in immunocompromised patients has received increasing attention as a driver of immune escape, and accumulating evidence suggests that viral genomic diversity and emergence of immune-escape mutants are promoted in immunocompromised patients. However, because immunocompromised patients comprise a small proportion of the host population, whether they have a significant impact on antigenic evolution at the population level is unknown. We used an evolutionary epidemiological model combining antigenic evolution and epidemiological dynamics in host populations with heterogeneity in immune competency to determine the impact of immunocompromised patients on the pathogen evolutionary dynamics of antigenic escape from host immunity. We derived analytical formulae of the speed of antigenic evolution in heterogeneous host populations and found that even a small number of immunocompromised hosts in the population significantly accelerates antigenic evolution. Our results demonstrate that immunocompromised hosts play a key role in viral adaptation at the population level and emphasize the importance of critical care and surveillance of immunocompromised hosts.

evolutionary biology↗

bioRxiv2022

Large retrospective WGS study describes three major sequence types of S. aureus in India and reveals two novel multi-drug resistant sub-lineages of S. aureus Clonal Complex 22

BackgroundS. aureus is a major pathogen in India, causing nosocomial infections, but little is known about its molecular epidemiology and mechanisms of resistance in hospital settings. Here, we use WGS to characterize 508 S. aureus clinical isolates collected across India and analyze them in a global context. MethodsWhole-genome sequencing was performed on 508 clinical isolates of S. aureus collected from 17 sentinel sites across India between 2014 and 2019 with the Illumina platform. AMR genotypes were predicted using Staphopia. Isolates carrying novel SCCmec cassettes were further characterized using long-read sequencing. A temporal analysis of clonal complex (CC) 22 global isolates from 14 different studies was performed using BactDating. ResultsSequencing results confirmed 478 isolates as S. aureus. ST22, ST772 & ST239 were the major clones identified. An in-depth analysis of the 175 CC22 Indian isolates identifies two novel ST22 MRSA clones, PVL+ and one harboring the tsst-1 gene. Temporal analysis showed that these two ST22 clusters shared a common ancestor in the 1980s and they became widespread after the year 2000 in India. Analyzing these in a global context, we found evidence of transmission of the two Indian clones to other parts of the world. ConclusionOur study describes a large retrospective S. aureus sampled from India. By comparing the Indian isolates globally we show the evidence of the international transmission of ST22 Indian isolates. Even though the two of the major dominant clones (ST772 and ST239) using WGS have been reported, this is the first study that describes the third dominant clone (ST22) in India. Impact statementStaphylococcus aureus is an opportunistic pathogen listed as a high-priority pathogen by WHO. It is a leading cause of nosocomial infections in India and worldwide. Our study is the first study to describe the epidemiology of S. aureus in India with a large sample set of 478. Here we describe a collection of 478 S. aureus genomes, isolated from 17 sentinel sites in India, between 2014 and 2019. With the focus on understanding sequence types, AMR profiles, SCCmec types, and spa types and discuss these in the context of previous molecular studies on S. aureus conducted in India. We also conducted an in-depth analysis of the Clonal Complex 22 Indian isolates and we identified two novel ST22 MRSA clones, both PVL+ and one harboring the tsst-1 gene. Temporal analysis shows that these two ST22 clusters originated around 2010 in India. Analyzing these in a global context, we found evidence of transmission of the two Indian clones in other parts of the world. Analysis of a cluster of 33 isolates belonging to ST239 from a single hospital in Bangalore indicates an outbreak that persisted over the period of three years from a single contamination source. The novel SCCmec types identified in our study are characterized using long reads to understand their genetic structure. Data SummaryO_LIIllumina read files of the strains used in the study have been deposited in European Nucleotide Archive, BioProject PRJEB29740 (https://www.ebi.ac.uk/ena/browser/view/PRJEB29740?show=reads). A full list of accession numbers for all sequence read files is provided in Supplementary table 2. C_LIO_LINanopore reads are submitted to ENA under the BioProject PRJEB50484. C_LIO_LIMetadata and other related information on the strains are provided in the microreact project with different views in this link microreact.org/s.aureus_ghru_analysis. C_LIO_LIStrain information for the ST22 samples used from other studies is provided in microreact at this link: https://microreact.org/project/2xDvKQhriNveJ4kiVYsmSQ-s-aureus-wgs-study. The authors confirm all supporting data, code and protocols have been provided within the article or the supporting data repository. C_LI

genomics↗

bioRxiv2022

Culture-Independent Detection and Identification of Leptospira Serovars

Pathogenic Leptospira, the causative agents of leptospirosis, comprise >200 serotypes (called serovars). Most have a restricted reservoir-host range, and some, e.g., serovar Copenhageni, are cosmopolitan and of public health importance owing to their propensity to produce severe, fatal disease in humans. Available serotyping approaches--such as multi-locus sequence typing, core genome sequence typing, pulsed-field gel electrophoresis, and the cross-agglutination absorption test--are tedious and expensive, and require isolation of the organisms in culture media--a protracted and incredibly inefficient process-- precluding their use in prospective studies or outbreak investigations. The unavailability of culture-independent assays capable of distinguishing Leptospira serotypes remains a crucial gap in the field. Here, we have developed a simple yet specific real-time qPCR assay--targeting a Leptospira-unique gene encoding a putative polysaccharide flippase--that provides intra-species, serotype-defining (i.e., epidemiologically useful) information, and improves upon the sensitivity of preferred lipL32-based qPCR-based diagnostic tests. The assay, dubbed RAgI ("rage one"), is rapid and affordable, and reliably and specifically detects group I pathogenic Leptospira in culture, serum and urine, with no detectable off-target amplification--even of the genetically related but low virulence group II pathogenic (formerly "intermediate") or non-pathogenic Leptospira. It retained 100% diagnostic specificity when tested against difficult sample types, including field-collected dog urine-samples and environmental samples containing varied and complex microbial species-consortia. And holds considerable promise in the clinical setting, and for routine epidemiological and environmental surveillance studies.

microbiology↗

bioRxiv2022

Mosquito metabolism shapes life-cycle strategies of Plasmodium parasites

The life-history of multicellular organisms is a collection of traits determining fitness described by growth, survival, and reproduction. Within-host survival and between-host transmission are key life-history traits of single-celled malaria parasites. Therefore, understanding the evolutionary forces that shape these components is crucial to predict malaria epidemiology, drug resistance, and virulence. The evolutionary strategies of Plasmodium parasites have been largely investigated in the vertebrate host. In contrast, very little is known about their adaptation strategies in the mosquito vector, possibly due to the experimental challenges encountered while studying vector-parasite interactions. Mathematical models offer a unique tool to study such complex biological systems, and have been extensively employed in malaria epidemiology. However, all models developed so far do not consider mosquito physiology. Here, we examine the life-history evolution of Plasmodium parasites with a novel individual-based model of malaria transmission that includes mosquito metabolism. Specifically, we model the metabolic cascade of resource allocation induced by blood-feeding, as well as the influence of multiple blood meals on parasite development. Our model shows that successful vector-to-human transmission events are rare, and are caused by long-lived mosquitoes. Interestingly, we observe that the life-history strategies of malaria parasites depend on the mosquito metabolic status. In our model, additional resources provided by multiple blood meals benefit selection for parasites with slow or intermediate developmental time. These results challenge the current concept that evolution selects for fast developing parasites to maximize their chances to complete their within-mosquito life cycle. We propose that the long sporogonic cycle observed for Plasmodium is not a constraint but rather an adaptation to increase transmission potential.

evolutionary biology↗

bioRxiv2022

Genetic diversity and spread dynamics of SARS-CoV-2 variants present in African populations

The dynamics of COVID-19 disease have been extensively researched in many settings around the world, but little is known about these patterns in Africa. 6139 complete nucleotide genomes from 51 African nations were obtained and analyzed from the National Center for Biotechnology Information (NCBI) and Global Initiative on Sharing Influenza Data (GISAID) databases to examine genetic diversity and spread dynamics of SARS-CoV-2 lineages circulating in Africa. We investigated their diversity using several clade and lineage nomenclature systems, and used maximum parsimony inference methods to recreate their evolutionary divergence and history. According to this study, only 193 of the 2050 Pango lineages discovered worldwide circulated in Africa after two years of the COVID-19 pandemic outbreak, with five different lineages dominating at various points during the outbreak. We identified South Africa, Kenya, and Nigeria as key sources of viral transmissions between Sub-Saharan African nations because they had the most SARS-CoV-2 genomes sampled and sequenced. These results shed light on the evolutionary dynamics of the circulating viral strains in Africa. Genomic surveillance is one of the important techniques in the pandemic preparedness toolbox and to better understand the molecular, evolutionary, epidemiological, and spatiotemporal dynamics of the COVID-19 pandemic in Africa, genomic surveillance activities across the continent must be expanded. The effectiveness of molecular surveillance as a method for tracking pandemics strongly depends on continuous and reliable sampling, speedy virus genome sequencing, and prompt reporting and we have to improve in all these aspects in Africa. Additionally, the pandemic breakout revealed that current land-border regulations aimed at limiting viruss international transmission are ineffective and a lot needs to be done to implement and improve our African land-borders as far as epidemiology is concerned in order to contain such outbreaks in the future.

bioinformatics↗

bioRxiv2022

Comparative seasonal abundance and diversity of populations of the Pseudomonas syringae and Soft Rot Pectobacteriaceae species complexes throughout the Durance River catchment from its French Alps sources to its delta

Rivers, creeks, streams are integrators of biological, chemical and physical processes occurring in a catchment linking land cover from the headwaters to the outlet. The dynamics of human and animal pathogens in catchments have been widely studied in a large variety of contexts allowing the optimization of disease risk reduction. In parallel, there is an emerging awareness that crop pathogens might also be disseminated via surface waters especially when they are used for irrigation. However, there are no studies on the extent to which potential plant pathogens are present - nor about their dynamics - along the full course of a catchment. Here we have compared the seasonal dynamics of populations of the Pseudomonas syringae (Psy) and the Soft Rot Pectobacteriaceae (SRP) species complexes along a 270 km stretch of the Durance River from the upstream alpine reaches to the downstream agricultural production areas at the confluence with the Rhone River at Avignon. Among 168 samples collected at 21 sites in fall, winter, spring and summer of 2016 and 2017, Psy strains were detected at all sampling sites and in 156 of the samples at population densities up to 105 bacteria L-1. In contrast, SRP strains were detected in 98 of the samples, mostly from the southern part of the river, at population densities that did not exceed 3 x 104 bacteria L-1. Among the biological and chemical parameters that were characterized at each sampling site, temperature was the only factor that explained a significant amount of the variability in population size for both species complexes. Psy densities decreased with increasing temperature whereas SRP densities increased with increasing temperature. River-borne populations of SRP were composed mainly of Pectobacterium versatile and P. aquaticum that have little known epidemiological importance. Only a few strains of Pectobacterium and Dickeya species reputed for their epidemiological impact were observed. In contrast, Psy populations at all sites were dominated by a genetic lineage of phylogroup 2 known from other studies for its broad host range and its geographic and habitat ubiquity. Our observations suggest that surveillance of river water for SRP could be leveraged to signal diagnostic and management reactions to avoid disease outbreaks. In contrast, the constant presence of Psy throughout the catchment in absence of regular and widespread disease outbreaks due to this group of bacteria suggests that surveillance should focus on future changes in land use, river water conditions and agronomic practices that could destabilize the mechanisms currently holding Psy outbreaks in check.

ecology↗

bioRxiv2022

A climate-driven compartmental model for fungal diseases in fruit orchards: The impacts of climate change on a brown rot-peach system

As a well-known driving force of diseases in crops, climate change is likely to impact future crop yields. In the present work, we account for climate-related influences on the key parameters of a SIR-type epidemiological model for fungal diseases in stone fruit aimed at simulating different observed epidemic patterns, and, eventually, evaluating the possible impacts of climate change on the disease-induced yield loss. Brown rot disease in peach orchards is used here as a study system. We contrasted simulation results with epidemiological measures collected from an experimental orchard in Avignon (southern France) in two consecutive years, characterized by dissimilar brown rot outbreaks. The capacity of our climate-driven model to adequately reproduce the observed disease patterns suggests temperature and precipitation as key drivers of brown rot epidemics. Overall, the model predicts a potential decrease of brown rot severity under warmer and drier climatic conditions. To comprehensively understand the effect of future climate change on peach yield, alterations of crop phenology must also be accounted for. We thus build a model that considers the synergism between the two factors: vulnerability to the pathogen and varying phenology. Using plausible climate change scenarios, we find that the peach yield in the considered Mediterranean region will be considerably impaired: although brown rot-related yield losses are expected to decrease in warmer and drier climatic conditions, climate change will hinder fruit blooming and consequently the yield because milder winters will impede the achievement of dormancy. By deepening our understanding of climatic impacts on crop fungal infections, the present study may serve as a useful tool to plan and implement suitable adaptation strategies for peach cultivation.

plant biology↗

bioRxiv2022

Heme-induced genes facilitate endosymbiont (Sodalis glossinidius) colonization of the tsetse fly (Glossina morsitans) midgut

Tsetse flies (Glossina spp.) feed exclusively on vertebrate blood. After a blood meal, the enteric endosymbiont Sodalis glossinidius is exposed to various environmental stressors including high levels of heme. To investigate how S. glossinidius morsitans (Sgm, the Sodalis subspecies that resides within the gut of G. morsitans) tolerates the heme-induced oxidative environment of tsetses midgut, we used RNAseq to identify bacterial genes that are differentially expressed in cells cultured in high versus lower heme environments. Our analysis identified 436 genes that were significantly differentially expressed (> or < 2-fold) in the presence of high heme [219 heme-induced genes (HIGs) and 217 heme-repressed genes (HRGs)]. HIGs were enriched in Gene Ontology (GO) terms related to regulation of a variety of biological functions, including gene expression and metabolic processes. We observed that 11 out of 13 Sgm genes that were heme regulated in vitro were similarly regulated in bacteria that resided within tsetses midgut 24 hr (high heme environment) and 96 hr (low heme environment) after the flies had consumed a blood meal. We used intron mutagenesis to make insertion mutations in 12 Sgm HIGs and observed no significant change in growth in vitro in any of the mutant strains in high versus low heme conditions. However, Sgm strains that carried mutations in genes encoding a putative undefined phosphotransferase sugar (PTS) system component (SG2427), fucose transporter (SG0182), bacterioferritin (SG2280), and a DNA-binding protein (SGP1-0002) presented growth and/or survival defects in tsetse midguts as compared to normal Sgm. These findings suggest that the uptake up of sugars and storage of iron represent strategies that Sgm employs to successfully reside within the high heme environment of its tsetse hosts midgut. Our results are of epidemiological relevance, as many hematophagous arthropods house gut-associated bacteria that mediate their hosts competency as a vector of disease-causing pathogens. Author summaryTsetse flies feed exclusively on vertebrate blood. This nutrient source contains large quantities of heme, which can be toxic to the flys associated microorganisms. We investigated the genetic mechanisms that underlie the ability of the bacterial endosymbiont, Sodalis glossinidius, to successfully reside within tsetses heme-rich midgut. Exposure of cultured S. glossinidius to high levels of heme induced changes in the expression of genes that encode proteins involved in transcription, replication and repair of DNA, inorganic ion transport, and carbohydrate transport and metabolism processes. Changes in the expression of several of these same S. glossinidius genes also occurred within tsetses midgut following exposure to a blood meal. S. glossinidius genetically engineered to present mutations in several of these heme regulated genes were unable to successfully colonize tsetses gut. Our results provide insight into how bacteria that live in the gut of blood feeding arthropods mitigate the toxic effects of excessive heme. This information is of epidemiological relevance, as many of these bacteria influence their hosts ability to transmit disease pathogens that cause disease in humans and domesticated animals.

microbiology↗

bioRxiv2022

Incipient parallel evolution of SARS-CoV-2 Deltacron variant in South Brazil

With the coexistence of multiple lineages and increased international travel, recombination and gene flow are likely to become increasingly important in the adaptive evolution of SARS-CoV-2. This could result in the incipient parallel evolution of multiple recombinant lineages. However, identifying recombinant lineages is challenging, and the true extent of recombinant evolution in SARS-CoV-2 may be underestimated. This study describes the first SARS-CoV-2 Deltacron recombinant case identified in Brazil. We demonstrate that the recombination breakpoint is at the beginning of Spike gene (S). The 5' genome portion (circa 22 kb) resembles the AY.101 lineage (VOC Delta), and the 3' genome portion (circa 8 kb nucleotides) is most similar to the BA.1.1 lineage (VOC Omicron). Furthermore, evolutionary genomic analyses indicate that the new strain emerged after a single recombination event between lineages of diverse geographical locations in December 2021 in South Brazil. This Deltacron, named AYBA-RS, is one out of almost 30 recombinants described this year. The submission of only four sequences in the GISAID database suggests that this Brazilian lineage had a minor epidemiological impact. On the other hand, the recent emergence of this and various other Deltacron recombinant lineages (i.e., XD, XF, and XS) suggests that gene flow and recombination may play an increasingly important role in the COVID-19 pandemic. We explain the evolutionary and population genetic theory that support this assertion, and we conclude that this stresses the need for continued genomic and epidemiological surveillance. This is particularly important for countries where multiple variants are present, as well as for countries that receive significant inbound international travel.

evolutionary biology↗

bioRxiv2022

Beyond consensus sequence: a quantitative scheme for inferring transmission using deep sequencing in a bacterial transmission model

Genomic surveillance provides a data source complementary to contact tracing to resolve putative transmission chains. However, the role of within-host diversity in transmission is understudied due to a lack of experimental and clinical datasets that capture within-host diversity in both donors and recipients. Here, we assess the utility of deep-sequenced genomic surveillance within a mouse transmission model where the gastrointestinal pathogen Citrobacter rodentium was controllably spread during co-housing of infected and naive animals. We observed that within-host variants were maintained over multiple transmission steps until fixation or elimination. We present a model for inferring the likelihood that a given pair of samples are linked by transmission, by comparing the allelic frequency at variant genomic loci. Our data affirm that within-host single nucleotide variants (iSNVs) can repeatedly pass from donor to recipient along the transmission chain, and the mere sharing of iSNVs between different transmission pairs offers limited confidence in identifying a transmission pair. Beyond the presence and absence of within-host variants, we show that differences arising in the relative abundance of iSNVs can infer transmission pairs with high precision. An important component of our approach is that the inference is based solely on sequence data, without incorporating epidemiological or demographic data for context. Our model, which substantially reduces the number of comparisons a contact tracer needs to consider, may enhance the accuracy of contact tracing and other epidemiological processes, including early detection of emerging transmission clusters.

genomics↗

bioRxiv2022

Regional epidemic dynamics and Delta variant diversity resulted in varying rates of spread of Omicron-BA.1 in Mexico

The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In Mexico, this subvariant began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in the country. Unlike previous SARS-CoV-2 variants, BA.1 did not acquire local substitutions nor exhibited a geographically distinct circulation pattern in Mexico. However, a regional difference in the speed of the replacement of the Delta variant was observed, as some northern states showed persistence of Delta lineages well into February 2022. Mexican states were divided into four regions (North, Central North, Central South, and Southeast) based on the lineage circulation before the dominance of BA.1 to study possible causes for this difference. For each region, the time to fixation of BA.1, the diversity of Delta sublineages in the weeks preceding BA.1 entry, the population density, and the level of virus circulation during the inter-wave interval were determined. An association between a faster Omicron spread and lower Delta diversity, as well as fewer COVID-19 cases during the Delta-BA.1.x inter-wave period, was observed. For example, the North region exhibited the slowest spread but had the highest diversity of Delta sublineages and the greatest number of inter-wave cases relative to the maximum amount of the virus circulating in the region, whereas the Southeast region showed the opposite. Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics. Nonetheless, if there is a significant difference in the fitness of the variants or the time allowed for the competition is sufficient, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico. Impact statementThe surveillance of lineage circulation of SARS-CoV-2 has helped identify variants that have a transmission advantage and are of concern to public health and to track the virus dispersion accurately. However, many factors contributing to differences in lineage spread dynamics beyond the acquisition of specific mutations remain poorly understood. In this work, a description of BA.1 entry and dispersion within Mexico is presented, and which factors potentially affected the spread rates of the Omicron variant BA.1 among geographical regions in the country are analyzed, underlining the importance of population density, the proportion of active cases, and viral lineage diversity and identity before the entry of BA.1. Data summaryThis work was carried out using data shared through the GISAID initiative. All sequences and metadate are available through GISAID with the accession EPI_SET_220927gw, accession numbers and metadata are also reported in the supplemental material of this article. Epidemiological data was obtained though the Secretaria de Salud website (https://www.gob.mx/salud/documentos/datos-abiertos-152127),

microbiology↗

bioRxiv2022

ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics

Metagenomics can be used to monitor the spread of antibiotic resistance genes (ARGs). ARGs found in databases such as ResFinder and CARD primarily originate from culturable and pathogenic bacteria, while ARGs from non-culturable and non-pathogenic bacteria remain understudied. Functional metagenomics is based on phenotypic gene selection and can identify ARGs from non-culturable bacteria with a potentially low identity shared with known ARGs. In 2016, the ResFinderFG v1.0 database was created to collect ARGs from functional metagenomics studies. Here, we present the second version of the database, ResFinderFG v2.0, which is available on the Center of Genomic Epidemiology web server (https://cge.food.dtu.dk/services/ResFinderFG/). It comprises 3,913 ARGs identified by functional metagenomics from 50 carefully curated datasets. We assessed its potential to detect ARGs in comparison to other popular databases in gut, soil and water (marine + freshwater) Global Microbial Gene Catalogues (https://gmgc.embl.de). ResFinderFG v2.0 allowed for the detection of ARGs that were not detected using other databases. These included ARGs conferring resistance to beta-lactams, cycline, phenicol, glycopeptide/cycloserine and trimethoprim/sulfonamide. Thus, ResFinderFG v2.0 can be used to identify ARGs differing from those found in conventional databases and therefore improve the description of resistomes. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/512667v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1a16f6dorg.highwire.dtl.DTLVardef@19a7589org.highwire.dtl.DTLVardef@19a7d5forg.highwire.dtl.DTLVardef@19d1c16_HPS_FORMAT_FIGEXP M_FIG C_FIG Caption: Additional use of ResFinderFG v2.0 database (composed of antibiotic resistance genes obtained with functional metagenomics) on the Center of Genomic Epidemiology webserver (https://cge.food.dtu.dk/services/ResFinderFG/), allows for more exhaustive resistome descriptions.

microbiology↗

bioRxiv2022

Entomopathogen-host evolution and implications for biopesticide resistance management

Insecticide resistance evolution is becoming increasingly problematic globally. With chemical insecticides, attempts to combat resistance involves developing compounds with novel modes of action, or increasing rates to overcome partial resistance. While pests can develop resistance to pathogens used as biopesticides, these "pesticides" can be subjected to evolutionary selection pressure as well and may be able to adapt countermeasures to overcome pest resistance. Here, we consider two scenarios: 1) a single trait governs an arms race between pest and parasite, and 2) an epidemiological scenario where each, pathogen transmission and virulence, are governed by host and pathogen traits. Considering the single-trait parasite attack scenario, the evolving parasite is able to overcome resistance in the pest population and effectively suppress host population abundance. In this case, overcoming biopesticide resistance may be possible from parasite evolution to resistant hosts. In contrast, when transmission and abundance are allowed to vary independently in an epidemiological model, different pathogen traits promote different types of resistance development in the host - more contagious pathogens promote pathogen-tolerant (low mortality susceptibility) hosts, while less contagious pathogens promote pathogen-resistant (low transmission susceptibility) hosts. Pathogen-tolerant hosts are particularly detrimental to control programs, because they can quickly outcompete wild types by promoting infection in wild type populations. Furthermore, because evolution of pathogen-tolerance in pests can benefit pathogens through increasing infection prevalence, we do not expect pathogen evolution to improve control. Thus, the keys to biopesticide management depend on the virulence-transmission trade-off and whether hosts evolve to better prevent or survive infection.

evolutionary biology↗

bioRxiv2022

A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics

The bacterium Xylella fastidiosa (Xf) is mainly transmitted by the spittlebug, Philaenus spumarius, in Europe, where it has caused significant economic damage to olive and almond trees. Understanding the factors that determine disease dynamics in pathosystems that share similarities can help design control strategies focused on minimizing transmission chains. Here we introduce a compartmental model for Xf-caused diseases in Europe that accounts for the main relevant epidemiological processes, including the seasonal dynamics of P. spumarius. The model was confronted with epidemiological data from the two major outbreaks of Xf in Europe, the olive quick disease syndrome (OQDS) in Apulia, Italy, caused by the subspecies pauca, and the almond leaf scorch disease (ALSD) in Majorca, Spain, caused by subspecies multiplex and fastidiosa. Using a Bayesian inference framework, we show how the model successfully reproduces the general field data in both diseases. In a global sensitivity analysis, the vector-plant and plant-vector transmission rates, together with the vector removal rate, were the most influential parameters in determining the time of the infected host population peak, the incidence peak and the final number of dead hosts. We also used our model to check different vector-based control strategies, showing that a joint strategy focused on increasing the rate of vector removal while lowering the number of annual newborn vectors is optimal for disease control.

plant biology↗

bioRxiv2023

Multidrug resistance plasmids underlie clonal expansions and international spread of Salmonella enterica serotype 4,,12,i:- ST34 in Southeast Asia

Salmonella enterica serotype 4,[5],12,i:- (Typhimurium monophasic variant) of sequence type (ST) 34 has emerged as the predominant pandemic genotype in recent decades. Despite increasing reports of resistance to antimicrobials in Southeast Asia, Salmonella ST34 population structure and evolution remained understudied in the region. Here we performed detailed genomic investigations on 454 ST34 genomes collected from Vietnam and diverse geographical sources to elucidate the pathogens epidemiology, evolution and antimicrobial resistance. We showed that ST34 has been introduced into Vietnam in at least nine occasions since 2000, forming five co-circulating major clones responsible for paediatric diarrhoea and bloodstream infection. Most expansion events were associated with acquisitions of large multidrug resistance plasmids of IncHI2 or IncA/C2. Particularly, the self-conjugative IncA/C2 pST34VN2 (co-transferring blaCTX-M-55, mcr-3.1, and qnrS1) underlies local expansion and intercontinental spread in two separate ST34 clones. At the global scale, Southeast Asia was identified as a hotspot for the emergence and dissemination of multidrug resistant Salmonella ST34, and mutation analysis suggests of selection in antimicrobial responses and key virulence factors. Our work enriches the understanding on epidemiology and evolution of this variant in Southeast Asia, and determines that multidrug resistance plasmids have driven its local and potentially global success.

genomics↗

bioRxiv2023

Patterns of within-host spread of Chlamydia trachomatis between vagina, endocervix and rectum revealed by comparative genomic analysis

Chlamydia trachomatis, a gram-negative obligate intracellular bacterium, commonly causes sexually transmitted infections (STIs). Little is known about C. trachomatis transmission within the host, which is important for understanding disease epidemiology and progression. We used RNA-bait enrichment and whole-genome sequencing to compare rectal, vaginal and endocervical samples collected at the same time from 26 study participants who attended Fijian Ministry of Health and Medical Services clinics and tested positive for C. trachomatis at each anatomic site. The 78 C. trachomatis genomes from participants were from two major clades of the C. trachomatis phylogeny (the "prevalent urogenital and anorecta"l clade and "non-prevalent urogenital and anorectal" clade). For 21 participants, genome sequences were almost identical in each anatomic site. For the other five participants, two distinct C. trachomatis strains were present in different sites; in two cases, the vaginal sample was a mixture of strains. The absence of large numbers of fixed SNPs between C. trachomatis strains within many of the participants could indicate recent acquisition of infection prior to the clinic visit without sufficient time to accumulate significant variation in the different body sites. This model suggests that many C. trachomatis infections may be resolved relatively quickly in the Fijian population, possibly reflecting common prescription or over-the-counter antibiotics usage. ImportanceChlamydia trachomatis is a bacterial pathogen that causes millions of sexually transmitted infections (STIs) annually across the globe. Because C. trachomatis lives inside human cells, it has historically been hard to study. We know little about how the bacterium spreads between body sites. Here, samples from 26 study participants who had simultaneous infections in their vagina, rectum and endocervix were genetically analyzed using an improved method to extract C. trachomatis DNA directly from clinical samples for genome sequencing. By analyzing patterns of mutations in the genomes, we found that 21 participants shared very similar C. trachomatis strains in all three anatomic sites, suggesting recent infection and spread. For five participants two C. trachomatis strains were evident, indicating multiple infections. This study is significant in that improved enrichment methods for genome sequencing provides robust data to genetically trace patterns of C. trachomatis infection and transmission within an individual for epidemiologic and pathogenesis interrogations.

microbiology↗