Biology subjects

Reuter, S.

Publications and source records attributed to Reuter, S..

18 recordsLinked to original sources

bioRxiv2026

Treg-derived IκBζ promotes their conversion into Th2-like effectors and drives type 2 inflammation via BATF

Regulatory T cells (Treg cells) maintain peripheral immune tolerance but display considerable plasticity in peripheral tissues. The molecular mechanisms governing their function and plasticity, particularly under inflammatory conditions, remain poorly defined. Here, we identify the NF-{kappa}B-associated transcriptional cofactor I{kappa}B{zeta} as a critical regulator of Treg cell plasticity and function. Enforced expression of I{kappa}B{zeta} in Treg cells triggered the excessive expansion of functionally impaired Treg cells, resulting in lymphadenopathy, splenomegaly, and systemic type 2 inflammation, most prominently in the lung. Mechanistically, I{kappa}B{zeta} modified BATF expression and function, thereby driving the cell-intrinsic production of Th2-associated cytokines by Treg cells. Conversely, Treg-specific deletion of I{kappa}B{zeta} constrained IL-33-mediated expansion of tissue Treg cells and surprisingly attenuated type 2 inflammation. Thus, I{kappa}B{zeta} functions as a molecular switch that reprograms regulatory T cells into Th2-like Treg cells, thereby perturbing peripheral immune tolerance. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/707402v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1ef0b17org.highwire.dtl.DTLVardef@c12eaaorg.highwire.dtl.DTLVardef@decc86org.highwire.dtl.DTLVardef@1458767_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Sub-Millivolt Voltage Imaging Reveals Gap Junction-Mediated Bioelectric Contact Inhibition

Sub-millivolt membrane potential (Vm) dynamics in multicellular non-excitable networks have remained largely invisible due to a lack of sufficiently sensitive imaging tools. Here, we introduce rEstus2s, a next-generation genetically encoded voltage indicator that overcomes this barrier by enabling high-resolution Vm imaging across the full physiological resting Vm range (-100 to 0 mV). Using rEstus2s, we uncover bioelectric contact inhibition (BCI), a fundamental biophysical principle where gap junction coupling acts as a passive noise filter to stabilize Vm. We demonstrate that the time-dependent variance of Vm (electrical volatility) relative to the number of cells (n) in a network follows a 1/n scaling law, reflecting a transition from stochastic single-cell behavior to collective electrical stability. While Ca2+-activated oncogenic ion channels, including ANO1 and KCa3.1, promote pronounced electrical volatility in isolated cells, BCI effectively attenuates volatility in electrically coupled networks. Disruption of gap junction coupling in cancer cells abolishes BCI and restores high electrical volatility. These findings establish a unifying biophysical framework for understanding how multicellularity maintains electrical homeostasis in health and disease. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/701308v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@120fcb9org.highwire.dtl.DTLVardef@affa2aorg.highwire.dtl.DTLVardef@150ffa7org.highwire.dtl.DTLVardef@c05392_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

WNT-driven immune evasion promotes malignant transformation of BRAF-mutant colorectal cancer

BRAF-mutant colorectal cancer (CRC) constitutes a molecularly and clinically distinct subtype with poor prognosis and resistance to standard therapies, representing a major unmet clinical need. Arising from the serrated pathway of colorectal carcinogenesis rather than the classical adenoma-carcinoma sequence, this subgroup remains relatively understudied yet displays a more aggressive disease course. To investigate the progression of serrated CRC, we generated multiple genetically engineered mouse models (GEMMs) of BRAF-mutant, microsatellite-stable (MSS) CRC that closely recapitulate human disease. Our findings demonstrate that WNT-pathway activation via APC- or CTNNB1-mutations, but not RNF43-loss, initiates serrated CRC by suppressing immune-mediated tumor surveillance. Mechanistically, WNT-signaling drives distinct alterations in T cell phenotypes within the tumor microenvironment, enabling tumor progression. Together, these data indicate that WNT-signaling mediates immune escape during the malignant transformation of BRAF-mutant CRC.

cancer biology↗

bioRxiv2025

Neighbour Typing Using Long Read Sequencing Provides Rapid Prediction of Sequence Type and Antimicrobial Susceptibility of Klebsiella pneumoniae

The rapid genome-based diagnostic approach of long read sequencing coupled with neighbor typing offers the potential to improve empiric treatment of infection. However, this approach is still in development, and clinical validation is needed to support its use. In this study, we present an assessment of a neighbour typing method (RASE - resistance associated sequence elements) to predict lineage or sequence type (ST) and antimicrobial susceptibility in real time for Klebsiella pneumoniae sensu lato. We analysed the initial reads generated during the early phase of long read sequencing from pure culture (n=99), mock communities (n=20) and metagenomic samples (n=20). RASE accurately identified 69.7% and 70% of STs in pure culture and metagenomes, respectively, and identified the STs of the isolates representing the highest proportion in mock communities. Regarding antimicrobial susceptibility prediction, the probability of susceptibility increased to 72% (95% CI 63%-80%) across all tested antibiotics, when RASE predicted susceptibility, and decreased probability of susceptibility to 8.9% (95% CI 6.4%-9.6%) when was indicative of a resistant phenotype. Our study confirmed that genomic neighbor typing in K. pneumoniae sensu lato is capable of providing informative predictions of ST and antibiotic susceptibility in less than ten minutes (after the start of sequencing) with 200-500 reads. IMPORTANCEThe growing burden of antimicrobial resistance is leading to high rates of mortality and morbidity worldwide. This situation has made the selection of empirical antibiotic therapy challenging, due to the risk of treatment failure and the overuse of last-resort antibiotics. The development of new sequencing technologies is helping to reduce the waiting time for a microbiological diagnosis, providing information in the early phase of bacterial infections, which could help improve clinical outcomes in a time of rising antimicrobial resistance. In this context, we assessed the performance of RASE (resistance associated sequence elements) in Klebsiella pneumoniae, an opportunistic pathogen frequently associated with nosocomial infections, which can rapidly acquire antibiotic resistance genes. Thus, in our study we provide insights that may aid in the validation of RASE for clinical use.

genomics↗

bioRxiv2025

BaGPipe: an automated, reproducible, and flexible pipeline for bacterial genome-wide association studies

Microbial genome-wide association study (GWAS) tools often require manual data processing steps, lack comprehensive workflows, and are limited by scalability issues, thus hindering the exploration of bacterial genetic traits. To address these challenges, we developed BaGPipe, an automated and flexible bacterial GWAS pipeline built using Nextflow and incorporating Pyseer for association analysis. BaGPipe integrates all essential components of a bacterial GWAS--spanning pre-processing, statistical analysis, and downstream visualisation--into a unified workflow that is reproducible and easy to deploy across diverse computational environments. BaGPipe was validated on a publicly available dataset of Streptococcus pneumoniae whole-genome sequences, and reproduced published findings with improved computational efficiency. BaGPipe was then applied to a dataset of Staphylococcus aureus whole-genome sequences, successfully identifying known and novel antibiotic resistance associations. By offering an accessible, efficient, and reproducible platform, BaGPipe accelerates bacterial GWAS and facilitates deeper exploration into the genetic underpinnings of phenotypic traits. Impact StatementThe increasing availability of bacterial genome sequences has created an opportunity for robust, reproducible tools to facilitate the discovery of novel genotype-phenotype associations. Despite the demonstrated utility of genome-wide association studies (GWAS) in identifying genetic determinants of disease, toxicity and antibiotic resistance, existing tools for bacterial GWAS often involve fragmented workflows requiring extensive manual intervention, limiting their adoption and reproducibility. Here, we introduce BaGPipe, a fully integrated bacterial GWAS pipeline that automates pre-processing, statistical analysis, and visualisation, thereby streamlining the entire workflow. With its flexibility, scalability, and ease of use, BaGPipe makes bacterial GWAS more accessible to researchers, enabling faster and more reliable insights into microbial genetics. This is an important step towards overcoming the computational and logistical barriers that have constrained bacterial GWAS, ultimately accelerating research into microbial evolution, resistance mechanisms, and the genetic basis of other key phenotypic traits. Data SummaryBaGPipe is freely available at https://github.com/sanger-pathogens/BaGPipe. The Streptococcus pneumoniae input dataset is available from the Pyseer tutorial (https://pyseer.readthedocs.io/en/master/tutorial.html#). The Staphylococcus aureus sequencing assemblies can be sourced from their ERS accession numbers provided in supplementary data. The reference assemblies, listed in the supplementary, can be sourced from NCBI.

bioinformatics↗

bioRxiv2024

Cold Atmospheric Plasma Selectively Disrupts Breast Cancer Growth in a Bioprinted 3D Tumor Microenvironment Model

Spine metastases are the most common bone site for breast cancer, with evolving surgery and multidisciplinary care improving outcomes. Current treatments, including chemotherapy and invasive surgery, may damage healthy tissue and may leave residual tumors that lead to recurrence. Cold atmospheric plasma (CAP) offers a non-invasive alternative by delivering reactive oxygen and nitrogen species (RONS) locally to tumor sites, selectively targeting cancer cells while sparing healthy tissue. To assess the impact and selectivity toward tumor cells adjacent to bone-like tissue, we develop a 3D bioprinted tumor-stroma model using a 1% alginate and 7% gelatin cell-laden hydrogel to mimic a bone-like microenvironment. The model co-cultures triple-negative MDA-MB-231 human breast cancer cells with primary human bone marrow mesenchymal stromal cells to simulate tumor-stroma interactions. The effects of CAP treatments are assessed through metabolic activity and viability assays over three days. Results show significant selectivity for cancer cells in both 2D and 3D cultures. CAP minimizes damage to healthy cells, offering the potential for localized treatment over systemic chemotherapies such as doxorubicin. Our novel bioprinted model, combined with a plasma source controlling RONS composition, enables detailed studies of redox-based cancer cell inactivation and highlights CAP as a personalized, non-invasive treatment for bone metastases.

bioengineering↗

bioRxiv2024

Identification and Mitigation of microbial contaminant reads from long-read metagenomic samples

Metagenomic sequencing of clinical samples has significantly enhanced our understanding of microbial communities. However, microbial contamination and host-derived DNA remain a major obstacle to accurate data interpretation. Here, we present a methodology called Stop-Check-Go for detecting and mitigating contaminants in metagenomic datasets obtained from neonatal patient samples (nasal and rectal swabs). This method incorporates laboratory and bioinformatics work combining a prevalence method, coverage estimation, and microbiological reports. We compared the Stop-Check-Go decontamination system with other published decontamination tools, and commonly found poor performance in decontaminating microbiologically negative patients (false positives). We emphasize that host DNA decreased by an average of 76% per sample using a lysis method and was further reduced during post-sequencing analysis. Microbial species were classified as putative contaminants and assigned to Stop in nearly 60% of the dataset. The Stop-Check-Go system was developed to address the specific need of decontaminating low-biomass samples, where existing tools primarily designed for short-read metagenomic data showed limited performance. Impact StatementMetagenomics has gained popularity due to its diverse applications in the multi-omics research field and the improvements in sequencing performance of technologies such as Nanopore. However, challenges in biological interpretation remain because of the complexity of the data structure and the potential of contamination occurring at multiple steps during sample processing, which can lead to incorrect conclusions. We aim to raise awareness of contamination, which can be host-associated, cross-contamination, or library-derived, any of which may be introduced at any stage from sample collection. Existing decontamination tools are largely designed for short-read sequencing and thus present limitations when applied to long-read datasets. We propose a direct comparison of species in samples with species in weekly negative controls that progressively accumulate both external and kit-reagent contaminants. Additionally, we recommend incorporating read-depth coverage and read-prevalence metrics, particularly in studies involving low-biomass or non-culturable microorganisms. Whenever possible, validation with microbiological reports is strongly advised. Our code is available on GitHub and can be executed locally in RStudio. It outputs species classifications labeled Stop, Check, or Go, as well as BIOM format files clean of identified contaminants, ready for downstream analysis with R packages such as phyloseq, vegan, or metagenomeSeq. Data summaryThe complete source code and documentation are available from GitHub (https://github.com/SAM81221/Stop-Check-Go_TAPIR). Metagenomic sequences including controls have been deposited in the ENA in project PRJEB82667; and isolate sequences of control samples in PRJEB95992. Information on samples and sequences can be found in Supplementary Table S1.

bioinformatics↗

bioRxiv2024

Assessing the performance of current strain resolution tools on long-read metagenomes

Recent advances in long-read sequencing-based methods have greatly enhanced genomics and public health applications. However, the challenge of effectively distinguishing strains within microbial communities from clinical samples using these technologies restricts their widespread use. We assessed the strain resolution capabilities of three currently available bioinformatics tools--TRACS, Strainy, and Strainberry--using both mock communities and authentic metagenomic datasets. Following sample preparation and long-read sequencing using the GridION sequencing platform, raw reads were processed using TRACS, aligning them to a custom reference database, while Strainberry and Strainy mapped reads to metagenome assemblies for strain resolution. Performance on mock microbial community was assessed by comparing predicted microbiota composition to the expected composition, and on both mock and authentic datasets by evaluating strain-resolved genome assemblies. Computational efficiency was measured in terms of task execution time, single-core CPU usage, and physical memory usage. TRACS demonstrated substantial agreement with the known composition, achieving a median score of 86.7% for Escherichia coli-dominant communities and 94.7% for Klebsiella pneumoniae-dominant communities. Strainberry and Strainy exhibited improved concordance after excluding strains with a genome size below 1 Mb, thus showcasing comparable performance metrics to TRACS. In mock and real metagenomic datasets, TRACS demonstrated the highest haplotype completeness compared to the other two tools, while Strainy demonstrated the highest haplotype accuracy. All tools were able to allocate strains to their respective transmission clusters (< 20 SNPs), albeit with varying degrees of success. Except for single core CPU usage, TRACS outperformed Strainy and Strainberry in terms of speed and computational efficiency. Our study underscores the utility of TRACS, Strainy, and Strainberry in resolving strains within microbial communities from clinical samples. TRACS stands out for its better haplotype completeness and computational efficiency, suggesting its potential to streamline advanced genomic analyses and public health initiatives.

bioinformatics↗

bioRxiv2024

TRACKING CLONAL AND PLASMID TRANSMISSION IN COLISTIN AND CARBAPENEM RESISTANT KLEBSIELLA PNEUMONIAE

The surveillance of mobile genetic elements facilitating the spread of antimicrobial resistance genes has been challenging. Here, we tracked both clonal and plasmid transmission in colistin- and carbapenem-resistant K. pneumoniae using short and long read sequencing technologies. We observed three clonal transmissions, all containing IncL plasmids and blaNDM-1, although not co-located on the same plasmid. One IncL-blaNDM-1 plasmid had been transferred between ST392 and ST15, and the promiscuous IncL-blaOXA-48 plasmid was likely shared between a singleton and a clonal transmission of ST392. Plasmids within clonal outbreaks and between clusters and STs had 0-2 SNP differences, showing high stability upon transfer to same or different STs. The simplest explanation of a single common IncL-blaNDM-1 plasmid spreading was in fact false, and we found blaNDM-1 in the context of five different plasmids, emphasizing the need to investigate plasmid-mediated transmission for effective containment of outbreaks. IMPORTANCEAntimicrobial resistance occupies a central stage in global public health emergencies. Recently, efforts to track the genetic elements that facilitate the spread of resistance genes to determine so-called plasmid outbreaks have been described, however, such short read sequencing hinders full knowledge about plasmid structure and makes this approach very challenging to implement. In this study we used both short and long read sequencing in clinical Klebsiella pneumoniae from University Hospital Centre Zagreb, Croatia which were resistant to both last resort antibiotics colistin and carbapenem. Our results show complex transmission networks and sharing of plasmids, emphasizing multiple transmissions of plasmids harbouring carbapenem and/or colistin resistance genes between and within K. pneumoniae clones. Only full length sequencing plus a novel way of determining plasmid clusters resulted in the full picture, showing how future active monitoring of plasmids as a vital tool for infection prevention and control could be implemented.

microbiology↗

bioRxiv2024

Experts fail to reliably detect AI-generated histological data

AI-based methods to generate images have seen unprecedented advances in recent years challenging both image forensic and human perceptual capabilities. Accordingly, they are expected to play an increasingly important role in the fraudulent fabrication of data. This includes images with complicated intrinsic structures like histological tissue samples, which are harder to forge manually. We use stable diffusion, one of the most recent generative algorithms, to create such a set of artificial histological samples and in a large study with over 800 participants, we study the ability of human subjects to discriminate between such artificial and genuine histological images. Although they perform better than naive participants, we find that even experts fail to reliably identify fabricated data. While participant performance depends on the amount of training data used, even low quantities result in convincing images, necessitating methods to detect fabricated data and technical standards such as C2PA to secure data integrity.

scientific communication and education↗

bioRxiv2023

Long-term dynamics of the 'Serratia marcescens complex' in the hospital-built environment

Serratia marcescens is an opportunistic pathogen historically associated with abrupt, unpredictable, and severe outbreaks in hospital intensive care units (ICUs) and, more recently, with the spread of acquired genes encoding carbapenem resistance. However, the population biology and ecology of S. marcescens in the hospital ecosystem is still poorly understood. Here, we combine epidemiological information of 1417 Serratia isolates collected from the sinks of a large ICU ward that underwent significant demographic and operational changes (2019-2020) and 99 non-redundant outbreak/non-outbreak isolates from the same hospital (2003-2019), with genomic data of 165 isolates. We first report hospital sinks as reservoirs of heterogeneous and coexistent populations of the S. marcescens complex (SMC). A novel SMC clade congruent with the recently described Serratia nevei species is predominant, exhibiting chromosomal AmpC {beta}-lactamase with an unusual basal expression in contrast to one of the major features of S. marcescens. Persistent Serratia sink strains are identical to those involved in clonal and polyclonal outbreaks of VIM-1 and OXA-48 producers since at least 2017. The "source-sink" dynamics of SMC populations able to acquire the highly conserved plasmids such as IncL carrying blaVIM-1 or blaOXA-48 offer novel insights that might improve interventions to control outbreaks and treat Serratia infections in high-risk hospital areas.

microbiology↗

bioRxiv2023

International and regional spread of carbapenem-resistant Klebsiella pneumoniae in Europe

Klebsiella pneumoniae, an opportunistic pathogen able to cause hospital- and community-acquired infections, is of particular concern due to the active spread of antibiotic resistance genes associated with mobile genetic elements such as plasmids and transposons. Carbapenem-resistant K. pneumoniae (CRKP) exhibit a higher mortality rate than carbapenem-susceptible K. pneumoniae infections. In this COMBACTE-EURECA study, we present genomic data of 687 carbapenem-resistant strains recovered among clinical samples from 41 hospitals in nine Southern European countries (2016-2018) and compared these with the previous EuSCAPE collection (2013-2014). All isolates were resistant (EUCAST criteria) to at least one carbapenem antibiotic. We identified 11 clonal complexes (CCs), with most isolates belonging to the high-risk clones CC258, CC101, CC11, and CC307. blaKPC-like was the most prevalent carbapenemase-encoding gene (45%), along with the dominance of the CC258 lineage. Equally, blaOXA-48 had a wide-ranging spread (39%), and blaNDM was present in half of the ST11 isolates representing a particular lineage circulating in Greece. Two carbapenemase genes were found in 38 isolates (5.5%). Through the combination of both EURECA and EuSCAPE collections, we elucidated the evolution of K. pneumoniae high-risk clones circulating in Europe. Dominating clones and their associated carbapenemase genes exhibit relevant regional differences, namely CC258 in Greece, Italy, and Spain, CC101 present in Serbia and Romania and CC14 in Turkiye. Due to the wide expansion of CRKP, genomic surveillance across Europe with projects such as EURECA provides crucial insights for risk mapping at geo-temporal scales and informs necessary adaptions to the local settings for implementation of control strategies.

microbiology↗

bioRxiv2023

Monitoring oligomerization dynamics of individual human neurotensin receptors 1 in living cells and in SMALP nanodiscs

The human neurotensin receptor 1 (NTSR1) is a G protein-coupled receptor. The receptor is activated by a small peptide ligand neurotensin. NTSR1 can be expressed in HEK cells by stable transfection. Previously we used the fluorescent protein markers mRuby3 or mNeonGreen fused to NTSR1 for EMCCD-based structured illumination microscopy (SIM) in living HEK cells. Ligand binding induced conformational changes in NTSR1 which triggered the intracellular signaling processes. Recent single-molecule studies revealed a dynamic monomer/dimer equilibrium of this receptor in artificial lipid bilayers. Here we report on the oligomerization state of human NTSR1 from living cells by trapping them into lipid nanodiscs. Briefly, SMALPs (styrene-maleic acid copolymer lipid nanoparticles) were produced directly from the plasma membranes of living HEK293T FlpIn cells. SMALPs with a diameter of 15 nm were soluble and stable. NTSR1 in SMALPs were analyzed by single-molecule intensity measurements one membrane patch at a time using a custom-built confocal anti-Brownian electrokinetic trap (ABEL trap) microscope. We found oligomerization changes before and after stimulation of the receptor with its ligand neurotensin.

biophysics↗

bioRxiv2021

Toll-like receptor 5 as a novel receptor for fungal zymosan

Microbial pathogens carry specific structural patterns which were termed pathogen-associated molecular patterns (PAMPs). Toll-like receptors (TLRs) as key elements for the recognition of microbial pathogens are necessary for the activation of innate immune pathways. TLRs are activated by binding PAMPs of bacteria, viruses and fungi and initiate a signaling pathway resulting in the activation of transcription factors which modulate the production of various proinflammatory cytokines. It is not fully clear in detail which microbial pattern is recognized by which TLR. Here we show for the first time that TLR5 is a strong receptor for the yeast particle zymosan. We have generated stable human cell lines with combinations of TLR2 and TLR5 knock in/knock out together with stable nuclear factor kappaB (NF-{kappa}B) luciferase reporters. We found that both receptors TLR5 and TLR2 lead to an independent activation of the NF-{kappa}B pathway when simulated with zymosan. Our results demonstrate that TLR5 is a receptor for the fungal particle zymosan in addition to bacterial fragments like flagellin. Distinct cytokine patterns might suggest that TLR5 is potentially important for the differentiation in the recognition of the specific type of the foreign microorganisms and in the specific host defense response.

immunology↗

bioRxiv2020

Genomic basis of drought resistance in Fagus sylvatica

In the course of global climate change, central Europe is experiencing more frequent and prolonged periods of drought. The drought years 2018 and 2019 affected European beeches (Fagus sylvatica L.) differently: even in the same stand, drought damaged trees neighboured healthy trees, suggesting that the genotype rather than the environment was responsible for this conspicuous pattern. We used this natural experiment to study the genomic basis of drought resistance with Pool-GWAS. Contrasting the extreme phenotypes identified 106 significantly associated SNPs throughout the genome. Most annotated genes with associated SNPs (>70%) were previously implicated in the drought reaction of plants. Non-synonymous substitutions led either to a functional amino acid exchange or premature termination. A SNP-assay with 70 loci allowed predicting drought phenotype in 98.6% of a validation sample of 92 trees. Drought resistance in European beech is a moderately polygenic trait that should respond well to natural selection, selective management, and breeding. Impact StatementEuropean beech harbours substantial genetic variation at genomic loci associated with drought resistance and the loci identified in this study can help to accelerate and monitor adaptation to climate change.

plant biology↗

bioRxiv2019

Genomic analysis of carbapenemase-encoding plasmids from Klebsiella pneumoniae across Europe highlights three major patterns of dissemination

The incidence of Klebsiella pneumoniae infections that are resistant to carbapenems, a last-line class of antibiotics, has been rapidly increasing. The primary mechanism of carbapenem resistance is production of carbapenemase enzymes, which are most frequently encoded on plasmids by blaOXA-48-like, blaVIM, blaNDM and blaKPC genes. Using short-read sequence data, we previously analysed genomes of 1717 isolates from the K. pneumoniae species complex submitted during the European survey of carbapenemase-producing Enterobacteriaceae (EuSCAPE). Here, we investigated the diversity, prevalence and transmission dynamics of carbapenemase-encoding plasmids using long-read sequencing of representative isolates (n=79) from this collection in combination with short-read data from all isolates. We highlight three major patterns by which carbapenemase genes have disseminated via plasmids. First, blaOXA-48-like genes have spread across diverse lineages primarily via a highly conserved, epidemic pOXA-48-like plasmid. Second, blaVIM and blaNDM genes have spread via transient associations of diverse plasmids with numerous lineages. Third, blaKPC genes have transmitted predominantly by stable association with one clonal lineage (ST258/512) despite frequent mobilisation between pre-existing yet diverse plasmids within the lineage. Despite contrasts in these three modes of carbapenemase gene spread, which can be summarised as using one plasmid/multiple lineages, multiple plasmids/multiple lineages, and multiple plasmids/one lineage, all are underpinned by significant propagation along high-risk clonal lineages.

microbiology↗

bioRxiv2019

Contrasting approaches to genome-wide association studies impact the detection of resistance mechanisms in Staphylococcus aureus

Rapid detection of antibiotic resistance using whole-genome sequencing (WGS) could improve clinical outcomes and limit the spread of resistance. For this to succeed, we need an accurate way of linking genotype to phenotype, that identifies new resistance mechanisms as they appear. To assess how close we are to this goal, we characterized antimicrobial resistance determinants in >4,000 Staphylococcus aureus genomes of isolates associated with bloodstream infection in the United Kingdom and Ireland. We sought to answer three questions: 1) how well did known resistance mechanisms explain phenotypic resistance in our collection, 2) how many previously identified resistance mechanisms appeared in our collection, and 3) how many of these were detectable using four contrasting genome-wide association study (GWAS) methods. Resistance prediction based on the detection of known resistance determinants was 98.8% accurate. We identified challenges in correcting for population structure, clustering orthologous genes, and identifying causal mechanisms in rare or common phenotypes, which reduced the recovery of known mechanisms. Limited sensitivity and specificity of these methods made prediction using GWAS-discovered hits alone less accurate than using literature-derived genetic determinants. However, GWAS methods identified novel mutations associated with resistance, including five mutations in rpsJ, which improved tetracycline resistance prediction for 28 isolates, and a T118I substitution in fusA which resulted in better fusidic acid resistance prediction for 5 isolates. Thus, GWAS approaches in conjunction with phenotypic testing data can support the development of comprehensive databases to enable real-time use of WGS for patient management.

bioinformatics↗

bioRxiv2018

More than 16,000 effectors in the Legionella genus genome provide multiple, independent combinations for replication in human cells

SignificanceLegionella pneumophila is a bacterial pathogen causing outbreaks of a lethal pneumonia. The genus Legionella comprises 65 species for which aquatic amoebae are the natural reservoirs. Using functional and comparative genomics to deconstruct the entire bacterial genus we reveal the surprising parallel evolutionary trajectories that have led to the emergence of human pathogenic Legionella. An unexpectedly large and unique repository of secreted proteins (>16,000) containing eukaryotic-like proteins acquired from all domains of life (plant, animal, fungal, archaea) is contrasting with a highly conserved type 4 secretion system. This study reveals an unprecedented environmental reservoir of bacterial virulence factors, and provides a new understanding of how reshuffling and gene-acquisition from environmental eukaryotic hosts, may allow for the emergence of human pathogens.\n\nAbstractThe bacterial genus Legionella comprises 65 species among, which Legionella pneumophila is a human pathogen causing severe pneumonia. To understand the evolution of an environmental to an accidental human pathogen, we have functionally analyzed 80 Legionella genomes spanning 58 species. Uniquely, an immense repository of 16,000 secreted proteins encoding 137 different eukaryotic-like domains and more than 200 eukaryotic-like proteins is paired with a highly conserved T4SS. Specifically, we show that eukaryotic Rho and Rab GTPase domains are found nearly exclusively in eukaryotes and Legionella species. Translocation assays for selected Rab-GTPase proteins revealed that they are indeed T4SS secreted substrates. Furthermore, F/U-box and SET domains were present in >70% of all species suggesting that manipulation of host signal transduction, protein turnover and chromatin modification pathways, respectively are fundamental intracellular replication strategies for Legionellae. In contrast, the Sec-7 domain was restricted to L. pneumophila and seven other species, indicating effector repertoire tailoring within different amoebae. Functional screening of 47 species revealed 60% were competent for intracellular replication in THP-1 cells, but interestingly this phenotype was associated with diverse effector assemblages. These data, combined with evolutionary analysis indicate that the capacity to infect eukaryotic cells has been acquired independently many times within the genus and that a highly conserved yet versatile T4SS secretes an exceptional number of different proteins shaped by inter-domain gene transfer. Furthermore we revealed the surprising extent to which legionellae have co-opted genes and thus cellular functions from their eukaryotic hosts and provides a new understanding of how dynamic reshuffling and gene-acquisition has led to the emergence of major human pathogens.

genomics↗