RESUMO
The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded ß-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts.
Assuntos
Curadoria de Dados , Bases de Dados Factuais , Resistência Microbiana a Medicamentos , Aprendizado de Máquina , Antibacterianos/farmacologia , Genes Bacterianos , Funções Verossimilhança , Software , Anotação de Sequência MolecularRESUMO
The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.
Assuntos
Bases de Dados Genéticas , Farmacorresistência Bacteriana , Genes Bacterianos , Software , Bactérias/efeitos dos fármacos , Bactérias/genética , Proteínas de Bactérias/química , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismoRESUMO
Since its emergence in Wuhan, China, in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected ≈6 million persons worldwide. As SARS-CoV-2 spreads across the planet, we explored the range of human cells that can be infected by this virus. We isolated SARS-CoV-2 from 2 infected patients in Toronto, Canada; determined the genomic sequences; and identified single-nucleotide changes in representative populations of our virus stocks. We also tested a wide range of human immune cells for productive infection with SARS-CoV-2. We confirm that human primary peripheral blood mononuclear cells are not permissive for SARS-CoV-2. As SARS-CoV-2 continues to spread globally, it is essential to monitor single-nucleotide polymorphisms in the virus and to continue to isolate circulating viruses to determine viral genotype and phenotype by using in vitro and in vivo infection models.
Assuntos
Betacoronavirus , Infecções por Coronavirus/virologia , Leucócitos Mononucleares/virologia , Pneumonia Viral/virologia , Replicação Viral/genética , Betacoronavirus/genética , Betacoronavirus/isolamento & purificação , Betacoronavirus/fisiologia , COVID-19 , DNA Viral/genética , DNA Viral/isolamento & purificação , Genótipo , Humanos , Cinética , Pandemias , Polimorfismo de Nucleotídeo Único , SARS-CoV-2 , Sequenciamento Completo do GenomaRESUMO
Identification of the nucleotide sequences encoding antibiotic resistance elements and determination of their association with antibiotic resistance are critical to improve surveillance and monitor trends in antibiotic resistance. Current methods to study antibiotic resistance in various environments rely on extensive deep sequencing or laborious culturing of fastidious organisms, both of which are heavily time-consuming operations. An accurate and sensitive method to identify both rare and common resistance elements in complex metagenomic samples is needed. Referencing the sequences in the Comprehensive Antibiotic Resistance Database, we designed a set of 37,826 probes to specifically target over 2,000 nucleotide sequences associated with antibiotic resistance in clinically relevant bacteria. Testing of this probe set on DNA libraries generated from multidrug-resistant bacteria to selectively capture resistance genes reproducibly produced higher numbers of reads on target at a greater length of coverage than shotgun sequencing. We also identified additional resistance gene sequences from human gut microbiome samples that sequencing alone was not able to detect. Our method to capture the resistome enables a sensitive means of gene detection in diverse environments where genes encoding antibiotic resistance represent less than 0.1% of the metagenome.
Assuntos
Farmacorresistência Bacteriana/genética , Metagenoma , Bactérias/efeitos dos fármacos , Bactérias/genética , Bactérias/isolamento & purificação , Sondas de DNA/genética , Bases de Dados Genéticas , Farmacorresistência Bacteriana Múltipla/genética , Fezes/microbiologia , Microbioma Gastrointestinal/efeitos dos fármacos , Microbioma Gastrointestinal/genética , Genoma Bacteriano , Humanos , Metagenômica/métodos , Microbiota/efeitos dos fármacos , Microbiota/genética , Sequenciamento Completo do GenomaRESUMO
The Comprehensive Antibiotic Resistance Database (CARD; http://arpcard.mcmaster.ca) is a manually curated resource containing high quality reference data on the molecular basis of antimicrobial resistance (AMR), with an emphasis on the genes, proteins and mutations involved in AMR. CARD is ontologically structured, model centric, and spans the breadth of AMR drug classes and resistance mechanisms, including intrinsic, mutation-driven and acquired resistance. It is built upon the Antibiotic Resistance Ontology (ARO), a custom built, interconnected and hierarchical controlled vocabulary allowing advanced data sharing and organization. Its design allows the development of novel genome analysis tools, such as the Resistance Gene Identifier (RGI) for resistome prediction from raw genome sequence. Recent improvements include extensive curation of additional reference sequences and mutations, development of a unique Model Ontology and accompanying AMR detection models to power sequence analysis, new visualization tools, and expansion of the RGI for detection of emergent AMR threats. CARD curation is updated monthly based on an interplay of manual literature curation, computational text mining, and genome analysis.
Assuntos
Biologia Computacional/métodos , Bases de Dados Genéticas , Resistência Microbiana a Medicamentos , Microbiologia , Ontologias Biológicas , Curadoria de Dados , NavegadorRESUMO
Type III Secretion Systems (T3SSs) are structurally conserved nanomachines that span the inner and outer bacterial membranes, and via a protruding needle complex contact host cell membranes and deliver type III effector proteins. T3SS are phylogenetically divided into several families based on structural basal body components. Here we have studied the evolutionary and functional conservation of four T3SS proteins from the Inv/Mxi-Spa family: a cytosolic chaperone, two hydrophobic translocators that form a plasma membrane-integral pore, and the hydrophilic 'tip complex' translocator that connects the T3SS needle to the translocon pore. Salmonella enterica serovar Typhimurium (S. Typhimurium), a common cause of food-borne gastroenteritis, possesses two T3SSs, one belonging to the Inv/Mxi-Spa family. We used invasion-deficient S. Typhimurium mutants as surrogates for expression of translocator orthologs identified from an extensive phylogenetic analysis, and type III effector translocation and host cell invasion as a readout for complementation efficiency, and identified several Inv/Mxi-Spa orthologs that can functionally substitute for the S. Typhimurium chaperone and translocator proteins. Functional complementation correlates with amino acid sequence identity between orthologs, but varies considerably between the four proteins. This is the first in-depth survey of the functional interchangeability of Inv/Mxi-Spa T3SS proteins acting directly at the host-pathogen interface.
Assuntos
Proteínas de Transporte/metabolismo , Membrana Celular/metabolismo , Chaperonas Moleculares/metabolismo , Salmonella typhimurium/metabolismo , Sistemas de Secreção Tipo III/metabolismo , Sequência de Aminoácidos , Antígenos de Bactérias/genética , Antígenos de Bactérias/metabolismo , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismo , Proteínas de Transporte/genética , Linhagem Celular Tumoral , Regulação Bacteriana da Expressão Gênica , Células HeLa , Humanos , Proteínas de Membrana/genética , Proteínas de Membrana/metabolismo , Chaperonas Moleculares/genética , Sistemas de Secreção Tipo III/genéticaRESUMO
Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the CZ ID AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.
RESUMO
As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.
Assuntos
Biologia Computacional , Saúde Pública , Controle de Qualidade , Humanos , Biologia Computacional/métodos , Disseminação de Informação/métodos , Reprodutibilidade dos Testes , Anotação de Sequência Molecular/métodos , Genômica/métodos , SoftwareRESUMO
Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.
RESUMO
IMPORTANCE: While increasing rates of antimicrobial resistance undermine our current arsenal of antibiotics, resistance-modifying agents (RMAs) hold promise to extend the lifetime of these important molecules. We here provide a standardized nomenclature for RMAs within the Comprehensive Antibiotic Resistance Database in aid of RMA discovery, data curation, and genome mining.
Assuntos
Antibacterianos , Antibacterianos/farmacologia , Resistência Microbiana a Medicamentos/genéticaRESUMO
Atherosclerotic cardiovascular disease is characterized by both chronic low-grade inflammation and dyslipidemia. The AMP-activated protein kinase (AMPK) inhibits cholesterol synthesis and dampens inflammation but whether pharmacological activation reduces atherosclerosis is equivocal. In the current study, we found that the orally bioavailable and highly selective activator of AMPKß1 complexes, PF-06409577, reduced atherosclerosis in two mouse models in a myeloid-derived AMPKß1 dependent manner, suggesting a critical role for macrophages. In bone marrow-derived macrophages (BMDMs), PF-06409577 dose dependently activated AMPK as indicated by increased phosphorylation of downstream substrates ULK1 and acetyl-CoA carboxylase (ACC), which are important for autophagy and fatty acid oxidation/de novo lipogenesis, respectively. Treatment of BMDMs with PF-06409577 suppressed fatty acid and cholesterol synthesis and transcripts related to the inflammatory response while increasing transcripts important for autophagy through AMPKß1. These data indicate that pharmacologically targeting macrophage AMPKß1 may be a promising strategy for reducing atherosclerosis.
RESUMO
Fast, efficient public health actions require well-organized and coordinated systems that can supply timely and accurate knowledge. Public databases of pathogen genomic data, such as the International Nucleotide Sequence Database Collaboration (INSDC), have become essential tools for efficient public health decisions. However, these international resources began primarily for academic purposes, rather than for surveillance or interventions. Now, queries need to access not only the whole genomes of multiple pathogens but also make connections using robust contextual metadata to identify issues of public health relevance. Databases that over time developed a patchwork of submission formats and requirements need to be consistently organized and coordinated internationally to allow effective searches.To help resolve these issues, we propose a common pathogen data structure called the Pathogen Data Object Model (DOM) that will formalize the minimum pieces of sequence data and contextual data necessary for general public health uses, while recognizing that submitters will likely withhold a wide range of non-public contextual data. Further, we propose contributors use the Pathogen DOM for all pathogen submissions (bacterial, viral, fungal, and parasites), which will simplify data submissions and provide a consistent and transparent data structure for downstream data analyses. We also highlight how improved submission tools can support the Pathogen DOM, offering users additional easy-to-use methods to ensure this structure is followed.
Assuntos
Nucleotídeos , Saúde Pública , Sequência de Bases , Genômica/métodos , Bases de Dados de Ácidos NucleicosRESUMO
Whole genome sequencing (WGS) is a key tool in identifying and characterising disease-associated bacteria across clinical, agricultural, and environmental contexts. One increasingly common use of genomic and metagenomic sequencing is in identifying the type and range of antimicrobial resistance (AMR) genes present in bacterial isolates in order to make predictions regarding their AMR phenotype. However, there are a large number of alternative bioinformatics software and pipelines available, which can lead to dissimilar results. It is, therefore, vital that researchers carefully evaluate their genomic and metagenomic AMR analysis methods using a common dataset. To this end, as part of the Microbial Bioinformatics Hackathon and Workshop 2021, a 'gold standard' reference genomic and simulated metagenomic dataset was generated containing raw sequence reads mapped against their corresponding reference genome from a range of 174 potentially pathogenic bacteria. These datasets and their accompanying metadata are freely available for use in benchmarking studies of bacteria and their antimicrobial resistance genes and will help improve tool development for the identification of AMR genes in complex samples.
Assuntos
Antibacterianos , Bactérias , Antibacterianos/farmacologia , Bactérias/genética , Benchmarking , Farmacorresistência Bacteriana/genética , Genoma Bacteriano , Testes de Sensibilidade Microbiana , Sequenciamento Completo do GenomaRESUMO
Short-read sequencing can provide detection of multiple genomic determinants of antimicrobial resistance from single bacterial genomes and metagenomic samples. Despite its increasing application in human, animal, and environmental microbiology, including human clinical trials, the performance of short-read Illumina sequencing for antimicrobial resistance gene (ARG) detection, including resistance-conferring single nucleotide polymorphisms (SNPs), has not been systematically characterized. Using paired-end 2 × 150 bp (base pair) Illumina sequencing and an assembly-based method for ARG prediction, we determined sensitivity, positive predictive value (PPV), and sequencing depths required for ARG detection in an Escherichia coli isolate of sequence type (ST) 38 spiked into a synthetic microbial community at varying abundances. Approximately 300,000 reads or 15× genome coverage was sufficient to detect ARGs in E. coli ST38, with comparable sensitivity and PPV to ~100× genome coverage. Using metagenome assembly of mixed microbial communities, ARG detection at E. coli relative abundances of 1% would require assembly of approximately 30 million reads to achieve 15× target coverage. The minimum sequencing depths were validated using public data sets of 948 E. coli genomes and 10 metagenomic rectal swab samples. A read-based approach using k-mer alignment (KMA) for ARG prediction did not substantially improve minimum sequencing depths for ARG detection compared to assembly of the E. coli ST38 genome or the combined metagenomic samples. Analysis of sequencing depths from recent studies assessing ARG content in metagenomic samples demonstrated that sequencing depths had a median estimated detection frequency of 84% (interquartile range: 30%-92%) for a relative abundance of 1%. IMPORTANCE Systematically determining Illumina sequencing performance characteristics for detection of ARGs in metagenomic samples is essential to inform study design and appraisal of human, animal, and environmental metagenomic antimicrobial resistance studies. In this study, we quantified the performance characteristics of ARG detection in E. coli genomes and metagenomes and established a benchmark of ~15× coverage for ARG detection for E. coli in metagenomes. We demonstrate that for low relative abundances, sequencing depths of ~30 million reads or more may be required for adequate sensitivity for many applications.
Assuntos
Antibacterianos , Metagenoma , Animais , Humanos , Antibacterianos/farmacologia , Farmacorresistência Bacteriana/genética , Escherichia coli/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Metagenoma/genética , Genoma BacterianoRESUMO
BACKGROUND: Probiotic use in preterm infants can mitigate the impact of antibiotic exposure and reduce rates of certain illnesses; however, the benefit on the gut resistome, the collection of antibiotic resistance genes, requires further investigation. We hypothesized that probiotic supplementation of early preterm infants (born < 32-week gestation) while in hospital reduces the prevalence of antibiotic resistance genes associated with pathogenic bacteria in the gut. We used a targeted capture approach to compare the resistome from stool samples collected at the term corrected age of 40 weeks for two groups of preterm infants (those that routinely received a multi-strain probiotic during hospitalization and those that did not) with samples from full-term infants at 10 days of age to identify if preterm birth or probiotic supplementation impacted the resistome. We also compared the two groups of preterm infants up to 5 months of age to identify persistent antibiotic resistance genes. RESULTS: At the term corrected age, or 10 days of age for the full-term infants, we found over 80 antibiotic resistance genes in the preterm infants that did not receive probiotics that were not identified in either the full-term or probiotic-supplemented preterm infants. More genes associated with antibiotic inactivation mechanisms were identified in preterm infants unexposed to probiotics at this collection time-point compared to the other infants. We further linked these genes to mobile genetic elements and Enterobacteriaceae, which were also abundant in their gut microbiomes. Various genes associated with aminoglycoside and beta-lactam resistance, commonly found in pathogenic bacteria, were retained for up to 5 months in the preterm infants that did not receive probiotics. CONCLUSIONS: This pilot survey of preterm infants shows that probiotics administered after preterm birth during hospitalization reduced the diversity and prevented persistence of antibiotic resistance genes in the gut microbiome. The benefits of probiotic use on the microbiome and the resistome should be further explored in larger groups of infants. Due to its high sensitivity and lower sequencing cost, our targeted capture approach can facilitate these surveys to further address the implications of resistance genes persisting into infancy without the need for large-scale metagenomic sequencing. Video Abstract.
Assuntos
Nascimento Prematuro , Probióticos , Antibacterianos/farmacologia , Antibacterianos/uso terapêutico , Bactérias/genética , Suplementos Nutricionais , Feminino , Humanos , Lactente , Recém-Nascido , Recém-Nascido PrematuroRESUMO
Outbreaks of virulent and/or drug-resistant bacteria have a significant impact on human health and major economic consequences. Genomic islands (GIs; defined as clusters of genes of probable horizontal origin) are of high interest because they disproportionately encode virulence factors, some antimicrobial-resistance (AMR) genes, and other adaptations of medical or environmental interest. While microbial genome sequencing has become rapid and inexpensive, current computational methods for GI analysis are not amenable for rapid, accurate, user-friendly and scalable comparative analysis of sets of related genomes. To help fill this gap, we have developed IslandCompare, an open-source computational pipeline for GI prediction and comparison across several to hundreds of bacterial genomes. A dynamic and interactive visualization strategy displays a bacterial core-genome phylogeny, with bacterial genomes linearly displayed at the phylogenetic tree leaves. Genomes are overlaid with GI predictions and AMR determinants from the Comprehensive Antibiotic Resistance Database (CARD), and regions of similarity between the genomes are also displayed. GI predictions are performed using Sigi-HMM and IslandPath-DIMOB, the two most precise GI prediction tools based on nucleotide composition biases, as well as a novel blast-based consistency step to improve cross-genome prediction consistency. GIs across genomes sharing sequence similarity are grouped into clusters, further aiding comparative analysis and visualization of acquisition and loss of mobile GIs in specific sub-clades. IslandCompare is an open-source software that is containerized for local use, plus available via a user-friendly, web-based interface to allow direct use by bioinformaticians, biologists and clinicians (at https://islandcompare.ca).
Assuntos
Genoma Bacteriano , Ilhas Genômicas , Bactérias/genética , Surtos de Doenças , Ilhas Genômicas/genética , Humanos , FilogeniaRESUMO
Enterococcus faecium is a ubiquitous opportunistic pathogen that is exhibiting increasing levels of antimicrobial resistance (AMR). Many of the genes that confer resistance and pathogenic functions are localized on mobile genetic elements (MGEs), which facilitate their transfer between lineages. Here, features including resistance determinants, virulence factors and MGEs were profiled in a set of 1273 E. faecium genomes from two disparate geographic locations (in the UK and Canada) from a range of agricultural, clinical and associated habitats. Neither lineages of E. faecium, type A and B, nor MGEs are constrained by geographic proximity, but our results show evidence of a strong association of many profiled genes and MGEs with habitat. Many features were associated with a group of clinical and municipal wastewater genomes that are likely forming a new human-associated ecotype within type A. The evolutionary dynamics of E. faecium make it a highly versatile emerging pathogen, and its ability to acquire, transmit and lose features presents a high risk for the emergence of new pathogenic variants and novel resistance combinations. This study provides a workflow for MGE-centric surveillance of AMR in Enterococcus that can be adapted to other pathogens.
Assuntos
Anti-Infecciosos , Enterococcus faecium , Saúde Única , Enterococcus faecium/genética , Humanos , Fatores de Virulência/genética , Águas ResiduáriasRESUMO
BACKGROUND: The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. RESULTS: As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. CONCLUSIONS: Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI's BioSample database.
Assuntos
COVID-19 , SARS-CoV-2 , Genômica , Humanos , Metadados , Saúde Pública , Reprodutibilidade dos TestesRESUMO
BACKGROUND/PURPOSE: Type 2 diabetes and obesity increase the risk of developing colorectal cancer. Metformin may reduce colorectal cancer but the mechanisms mediating this effect remain unclear. In mice and humans, a high-fat diet (HFD), obesity and metformin are known to alter the gut microbiome but whether this is important for influencing tumor growth is not known. METHODS: Mice with syngeneic MC38 colon adenocarcinomas were treated with metformin or feces obtained from control or metformin treated mice. RESULTS: We find that compared to chow-fed controls, tumor growth is increased when mice are fed a HFD and that this acceleration of tumor growth can be partially recapitulated through transfer of the fecal microbiome or in vitro treatment of cells with fecal filtrates from HFD-fed animals. Treatment of HFD-fed mice with orally ingested, but not intraperitoneally injected, metformin suppresses tumor growth and increases the expression of short-chain fatty acid (SCFA)-producing microbes Alistipes, Lachnospiraceae and Ruminococcaceae. The transfer of the gut microbiome from mice treated orally with metformin to drug naïve, conventionalized HFD-fed mice increases circulating propionate and butyrate, reduces tumor proliferation, and suppresses the expression of sterol response element binding protein (SREBP) gene targets in the tumor. CONCLUSION: These data indicate that in obese mice fed a HFD, metformin reduces tumor burden through changes in the gut microbiome.
Assuntos
Neoplasias Colorretais , Diabetes Mellitus Tipo 2 , Microbioma Gastrointestinal , Metformina , Animais , Dieta Hiperlipídica/efeitos adversos , Microbioma Gastrointestinal/fisiologia , Metformina/farmacologia , Metformina/uso terapêutico , Camundongos , Camundongos Endogâmicos C57BL , Obesidade/tratamento farmacológicoRESUMO
Obesity results from a caloric imbalance between energy intake, absorption and expenditure. In both rodents and humans, diet-induced thermogenesis contributes to energy expenditure and involves the activation of brown adipose tissue (BAT). We hypothesize that environmental toxicants commonly used as food additives or pesticides might reduce BAT thermogenesis through suppression of uncoupling protein 1 (UCP1) and this may contribute to the development of obesity. Using a step-wise screening approach, we discover that the organophosphate insecticide chlorpyrifos suppresses UCP1 and mitochondrial respiration in BAT at concentrations as low as 1 pM. In mice housed at thermoneutrality and fed a high-fat diet, chlorpyrifos impairs BAT mitochondrial function and diet-induced thermogenesis, promoting greater obesity, non-alcoholic fatty liver disease (NAFLD) and insulin resistance. This is associated with reductions in cAMP; activation of p38MAPK and AMPK; protein kinases critical for maintaining UCP1 and mitophagy, respectively in BAT. These data indicate that the commonly used pesticide chlorpyrifos, suppresses diet-induced thermogenesis and the activation of BAT, suggesting its use may contribute to the obesity epidemic.