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Importance: Staphylococcus aureus frequently colonizes the skin and nose of patients with atopic dermatitis (AD), a disease associated with skin barrier dysfunction and chronic cutaneous inflammation. Published genomic studies on AD-associated S. aureus in pediatric populations in sub-Saharan Africa are limited. Objectives: To investigate the phenotypic and genomic diversity of S. aureus in children with and without AD during early childhood. Data setting and participants: A cross-sectional study of 220 children (aged 9-38 months) with AD (cases) and without AD (controls) from Cape Town and Umtata, South Africa. Main outcomes and measures: S. aureus phenotypic and genomic diversity were investigated using whole-genome sequencing, antibiotic susceptibility testing and biofilm microtiter assay. Results: Of the 124 S. aureus isolates recovered from 220 children, 96 isolates (79 cases and 17 controls) with high-quality sequences were analyzed. Isolates from cases showed greater phenotypic resistance to gentamicin (10%), rifampicin (4%), chloramphenicol (4%), and exhibited multidrug resistance (9%) than in controls. Furthermore, the isolates from cases formed stronger biofilms than those from controls (76% vs. 35%, p = 0.001), but showed no dominance of any virulence factor gene or mobile genetic elements. There was no significant difference in the distribution of immune evasion cluster types between cases and controls. However, IEC type G was identified only among cases. Conclusion and relevance: AD-associated S. aureus has phenotypic and genetic features that are important for successful pathogenic colonization and survival. Further studies are needed to assess the pathological implications of colonization of various S. aureus lineages in vivo to elucidate their pathological contribution to AD pathogenesis and pathophysiology.
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BACKGROUND: The Salmonella enterica serovar Newport red onion outbreak of 2020 was the largest foodborne outbreak of Salmonella in over a decade. The epidemiological investigation suggested two farms as the likely source of contamination. However, single nucleotide polymorphism (SNP) analysis of the whole genome sequencing data showed that none of the Salmonella isolates collected from the farm regions were linked to the clinical isolates-preventing the use of phylogenetics in source identification. Here, we explored an alternative method for analyzing the whole genome sequencing data driven by the hypothesis that if the outbreak strain had come from the farm regions, then the clinical isolates would disproportionately contain plasmids found in isolates from the farm regions due to horizontal transfer. RESULTS: SNP analysis confirmed that the clinical isolates formed a single, nearly-clonal clade with evidence for ancestry in California going back a decade. The clinical clade had a large core genome (4,399 genes) and a large and sparsely distributed accessory genome (2,577 genes, at least 64% on plasmids). At least 20 plasmid types occurred in the clinical clade, more than were found in the literature for Salmonella Newport. A small number of plasmids, 14 from 13 clinical isolates and 17 from 8 farm isolates, were found to be highly similar (> 95% identical)-indicating they might be related by horizontal transfer. Phylogenetic analysis was unable to determine the geographic origin, isolation source, or time of transfer of the plasmids, likely due to their promiscuous and transient nature. However, our resampling analysis suggested that observing a similar number and combination of highly similar plasmids in random samples of environmental Salmonella enterica within the NCBI Pathogen Detection database was unlikely, supporting a connection between the outbreak strain and the farms implicated by the epidemiological investigation. CONCLUSION: Horizontally transferred plasmids provided evidence for a connection between clinical isolates and the farms implicated as the source of the outbreak. Our case study suggests that such analyses might add a new dimension to source tracking investigations, but highlights the need for detailed and accurate metadata, more extensive environmental sampling, and a better understanding of plasmid molecular evolution.
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Salmonella enterica , Sorogrupo , Cebolas/genética , Fazendas , Filogenia , Plasmídeos/genética , Surtos de DoençasRESUMO
MOTIVATION: Scientists seeking to understand the genomic basis of bacterial phenotypes, such as antibiotic resistance, today have access to an unprecedented number of complete and nearly complete genomes. Making sense of these data requires computational tools able to perform multiple-genome comparisons efficiently, yet currently available tools cannot scale beyond several tens of genomes. RESULTS: We describe PRAWNS, an efficient and scalable tool for multiple-genome analysis. PRAWNS defines a concise set of genomic features (metablocks), as well as pairwise relationships between them, which can be used as a basis for large-scale genotype-phenotype association studies. We demonstrate the effectiveness of PRAWNS by identifying genomic regions associated with antibiotic resistance in Acinetobacter baumannii. AVAILABILITY AND IMPLEMENTATION: PRAWNS is implemented in C++ and Python3, licensed under the GPLv3 license, and freely downloadable from GitHub (https://github.com/KiranJavkar/PRAWNS.git). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Metagenômica , Software , Genômica , Genoma , BactériasRESUMO
Carbapenems-one of the important last-line antibiotics for the treatment of gram-negative infections-are becoming ineffective for treating Acinetobacter baumannii infections. Studies have identified multiple genes (and mechanisms) responsible for carbapenem resistance. In some A. baumannii strains, the presence/absence of putative resistance genes is not consistent with their resistance phenotype-indicating the genomic factors underlying carbapenem resistance in A. baumannii are not fully understood. Here, we describe a large-scale whole-genome genotype-phenotype association study with 349 A. baumannii isolates that extends beyond the presence/absence of individual antimicrobial resistance genes and includes the genomic positions and pairwise interactions of genes. Ten known resistance genes exhibited statistically significant associations with resistance to imipenem, a type of carbapenem: blaOXA-23, qacEdelta1, sul1, mphE, msrE, ant(3")-II, aacC1, yafP, aphA6, and xerD. A review of the strains without any of these 10 genes uncovered a clade of isolates with diverse imipenem resistance phenotypes. Finer resolution evaluation of this clade revealed the presence of a 38.6 kbp conserved chromosomal region found exclusively in imipenem-susceptible isolates. This region appears to host several HTH-type DNA binding transcriptional regulators and transporter genes. Imipenem-susceptible isolates from this clade also carried two mutually exclusive plasmids that contain genes previously known to be specific to imipenem-susceptible isolates. Our analysis demonstrates the utility of using whole genomes for genotype-phenotype correlations in the context of antibiotic resistance and provides several new hypotheses for future research.
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BACKGROUND: Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. RESULTS: We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. CONCLUSION: The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.
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Listeria monocytogenes , Nanoporos , Genômica , Sequenciamento de Nucleotídeos em Larga Escala , Listeria monocytogenes/genética , Análise de Sequência de DNA , Sequenciamento Completo do GenomaRESUMO
Multidrug-resistant (MDR) Shigella infections have been identified globally among men who have sex with men (MSM). The highly drug-resistant phenotype often confounds initial antimicrobial therapy, placing patients at risk for adverse outcomes, the development of more drug-resistant strains, and additional treatment failures. New macrolide-resistant Shigella strains complicate treatment further as azithromycin is a next-in-line antibiotic for MDR strains, and an antibiotic-strain combination confounded by gaps in validated clinical breakpoints for clinical laboratories to interpret macrolide resistance in Shigella We present the first high-resolution genomic analyses of 2,097 U.S. Shigella isolates, including those from MDR outbreaks. A sentinel shigellosis case in an MSM patient revealed a strain carrying 12 plasmids, of which two carried known resistance genes, the pKSR100-related plasmid pMHMC-004 and spA-related plasmid pMHMC-012. Genomic-epidemiologic analyses of isolates revealed high carriage rates of pMHMC-004 predominantly in U.S. isolates from men and not in other demographic groups. Isolates genetically related to the sentinel case further harbored elevated numbers of unique replicons, showing the receptivity of this Shigella lineage to plasmid acquisition. Findings from integrated genomic-epidemiologic analyses were leveraged to direct targeted clinical actions to improve rapid diagnosis and patient care and for public health efforts to further reduce spread.IMPORTANCE Multidrug-resistant Shigella isolates with resistance to macrolides are an emerging public health threat. We define a plasmid/pathogen complex behind infections seen in the United States and globally in vulnerable patient populations and identify multiple outbreaks in the United States and evidence of intercontinental transmission. Using new tools and sequence information, we experimentally identify the drivers of antibiotic resistance that complicate patient treatment to facilitate improvements to clinical microbiologic testing for their detection. We illustrate the use of these methods to support multiagency efforts to combat multidrug-resistant Shigella using publicly available tools, existing genomic data, and resources in clinical microbiology and public health laboratories to inform credible actions to reduce spread.
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Antibacterianos/farmacologia , Farmacorresistência Bacteriana Múltipla/genética , Genoma Bacteriano , Shigella/efeitos dos fármacos , Shigella/genética , Disenteria Bacilar/epidemiologia , Disenteria Bacilar/microbiologia , Feminino , Homossexualidade Masculina , Humanos , Internacionalidade , Masculino , Testes de Sensibilidade Microbiana , Pessoa de Meia-Idade , Plasmídeos/genética , Estados Unidos/epidemiologiaRESUMO
Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus-host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE.
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Biologia Computacional , Bases de Dados Genéticas , Metagenômica/métodos , Vírus/genética , Biologia Computacional/métodos , Variação Genética , Genoma Viral , Interações Hospedeiro-Patógeno , Humanos , Interface Usuário-Computador , Proteínas Virais/genética , Proteínas Virais/metabolismo , Vírus/metabolismo , NavegadorRESUMO
The Mid-Atlantic Microbiome Meet-up (M3) organization brings together academic, government, and industry groups to share ideas and develop best practices for microbiome research. In January of 2018, M3 held its fourth meeting, which focused on recent advances in biodefense, specifically those relating to infectious disease, and the use of metagenomic methods for pathogen detection. Presentations highlighted the utility of next-generation sequencing technologies for identifying and tracking microbial community members across space and time. However, they also stressed the current limitations of genomic approaches for biodefense, including insufficient sensitivity to detect low-abundance pathogens and the inability to quantify viable organisms. Participants discussed ways in which the community can improve software usability and shared new computational tools for metagenomic processing, assembly, annotation, and visualization. Looking to the future, they identified the need for better bioinformatics toolkits for longitudinal analyses, improved sample processing approaches for characterizing viruses and fungi, and more consistent maintenance of database resources. Finally, they addressed the necessity of improving data standards to incentivize data sharing. Here, we summarize the presentations and discussions from the meeting, identifying the areas where microbiome analyses have improved our ability to detect and manage biological threats and infectious disease, as well as gaps of knowledge in the field that require future funding and focus.