Genomic Pipeline for Analysis of Mutational Events in Bacteria.

Unveiling the strategies of bacterial adaptation to stress constitute a challenging area of research. The understanding of mechanisms governing emergence of resistance to antimicrobials is of particular importance regarding the increasing threat of antibiotic resistance on public health worldwide. In the last decades, the fast democratization of sequencing technologies along with the development of dedicated bioinformatical tools to process data offered new opportunities to characterize genomic variations underlying bacterial adaptation. Thereby, research teams have now the possibility to dive deeper in the deciphering of bacterial adaptive mechanisms through the identification of specific genetic targets mediating survival to stress. In this chapter, we proposed a step-by-step bioinformatical pipeline enabling the identification of mutational events underlying biocidal stress adaptation associated with antimicrobial resistance development using Escherichia marmotae as an illustrative model.

A Comprehensive Guide to Quality Assessment and Data Submission for Genomic Surveillance of Enteric Pathogens.

This document outlines the steps necessary to assemble and submit the standard data package required for contributing to the global genomic surveillance of enteric pathogens. Although targeted to GenomeTrakr laboratories and collaborators, these protocols are broadly applicable for enteric pathogens collected for different purposes. There are five protocols included in this chapter: (1) quality control (QC) assessment for the genome sequence data, (2) validation for the contextual data, (3) data submission for the standard pathogen package or Pathogen Data Object Model (DOM) to the public repository, (4) viewing and querying data at NCBI, and (5) data curation for maintaining relevance of public data. The data are available through one of the International Nucleotide Sequence Database Consortium (INSDC) members, with the National Center for Biotechnology Information (NCBI) being the primary focus of this document. NCBI Pathogen Detection is a custom dashboard at NCBI that provides easy access to pathogen data plus results for a standard suite of automated cluster and genotyping analyses important for informing public health and regulatory decision-making.

Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.

One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bacterial genomes contain signatures of natural evolution and adaptive markers that can be exploited to better understand the behavior of pathogen in the food industry. The monitoring of foodborne strains can therefore be facilitated by the use of these genomic markers capable of rapidly providing essential information on isolated strains, such as the source of contamination, risk of illness, potential for biofilm formation, and tolerance or resistance to biocides. The increasing availability of large genome datasets is enhancing the understanding of the genetic basis of complex traits such as host adaptation, virulence, and persistence. Genome-wide association studies have shown very promising results in the discovery of genomic markers that can be integrated into rapid detection tools. In addition, machine learning has successfully predicted phenotypes and classified important traits. Genome-wide association and machine learning tools have therefore the potential to support decision-making circuits intending at reducing the burden of foodborne diseases. The aim of this chapter review is to provide knowledge on the use of these two methods in food microbiology and to recommend their use in the field.

Hi-C/3C-seq Data Analysis for Prokaryotic Genomes with HiC-Pro.

Hi-C and 3C-seq are powerful tools to study the 3D genomes of bacteria and archaea, whose small cell sizes and growth conditions are often intractable to detailed microscopic analysis. However, the circularity of prokaryotic genomes requires a number of tricks for Hi-C/3C-seq data analysis. Here, I provide a practical guide to use the HiC-Pro pipeline for Hi-C/3C-seq data obtained from prokaryotes.

Specific amino acid changes correlate with pathogenic flavobacteria.

Flavobacterium is a genus of microorganisms living in a variety of hosts and habitats across the globe. Some species are found in fish organs, and only a few, such as Flavobacterium psychrophilum and Flavobacterium columnare, cause severe disease and losses in fish farms. The evolution of flavobacteria that are pathogenic to fish is unknown, and the protein changes accountable for the selection of their colonization to fish have yet to be determined. A phylogenetic tree was constructed with the complete genomic sequences of 208 species of the Flavobacterium genus using 861 softcore genes. This phylogenetic analysis revealed clade CII comprising nine species, including five pathogenic species, and containing the most species that colonize fish. Thirteen specific amino acid changes were found to be conserved across 11 proteins within the CII clade compared with other clades, and these proteins were enriched in functions related to replication, recombination, and repair. Several of these proteins are known to be involved in pathogenicity and fitness adaptation in other bacteria. Some of the observed amino acid changes can be explained by preferential selection for certain codons and tRNA frequency. These results could help explain how species belonging to the CII clade adapt to fish environments.

Feature sequence-based genome mining uncovers the hidden diversity of bacterial siderophore pathways.

Microbial secondary metabolites are a rich source for pharmaceutical discoveries and play crucial ecological functions. While tools exist to identify secondary metabolite clusters in genomes, precise sequence-to-function mapping remains challenging because neither function nor substrate specificity of biosynthesis enzymes can accurately be predicted. Here, we developed a knowledge-guided bioinformatic pipeline to solve these issues. We analyzed 1928 genomes of Pseudomonas bacteria and focused on iron-scavenging pyoverdines as model metabolites. Our pipeline predicted 188 chemically different pyoverdines with nearly 100% structural accuracy and the presence of 94 distinct receptor groups required for the uptake of iron-loaded pyoverdines. Our pipeline unveils an enormous yet overlooked diversity of siderophores (151 new structures) and receptors (91 new groups). Our approach, combining feature sequence with phylogenetic approaches, is extendable to other metabolites and microbial genera, and thus emerges as powerful tool to reconstruct bacterial secondary metabolism pathways based on sequence data.

Genomic evidence of two-staged transmission of the early seventh cholera pandemic.

The seventh cholera pandemic started in 1961 in Indonesia and spread across the world in three waves in the decades that followed. Here, we utilised genomic evidence to detail the first wave of the seventh pandemic. Genomes of 22 seventh pandemic Vibrio cholerae isolates from 1961 to 1979 were completely sequenced. Together with 152 publicly available genomes from the same period, they fell into seven phylogenetic clusters (CL1-CL7). By multilevel genome typing (MGT), all were assigned to MGT2 ST1 (Wave 1) except three isolates in CL7 which were typed as MGT2 ST2 (Wave 2). The Wave 1 seventh pandemic expanded in two stages, with Stage 1 (CL1-CL5) spread across Asia and Stage 2 (CL6 and CL7) spread to the Middle East and Africa. Three non-synonymous mutations, one each, in three regulatory genes, csrD (global regulator), acfB (chemotaxis), and luxO (quorum sensing) may have critically contributed to its pandemicity. The three MGT2 ST2 isolates in CL7 were the progenitors of Wave 2 and evolved from within Wave 1 with acquisition of a novel IncA/C plasmid. Our findings provide new insight into the evolution and transmission of the early seventh pandemic, which may aid future cholera prevention and control.

Pseudoalteromonas simplex sp. nov. Isolated from the Skin of Bandtail Puffer Fish (Sphoeroides spengleri).

A novel bacterial isolate A520T (A520T = CBAS 737T = CAIM 1944T) was obtained from the skin of bandtail puffer fish Sphoeroides spengleri (Tetraodontidae Family), collected in Arraial do Cabo (Rio de Janeiro, Brazil). A520T is Gram-stain-negative, flagellated and aerobic bacteria. Optimum growth occurs at 25-30 °C in the presence of 3% NaCl. The genome sequence of the novel isolate consisted of 4.5 Mb (4082 coding genes and G+C content of 41.1%). The closest phylogenetic neighbor was Pseudoalteromonas shioyasakiensis JCM 18891T (97.9% 16S rRNA sequence similarity, 94.8% Average Amino Acid Identity, 93% Average Nucleotide Identity and 51.8% similarity in Genome-to-Genome-Distance). Several in silico phenotypic features are useful to differentiate A520T from its closest phylogenetic neighbors, including trehalose, D-mannose, cellobiose, pyrrolidonyl-beta-naphthylamide, starch hydrolysis, D-xylose, lactose, tartrate utilization, sucrose, citrate, glycerol, mucate and acetate utilization, malonate, glucose oxidizer, gas from glucose, nitrite to gas, L-rhamnose, ornithine decarboxylase, lysine decarboxylase and yellow pigment. The genome of the novel species contains 3 gene clusters (~ 66.81 Kbp in total) coding for different types of bioactive compounds that could indicate ecological roles pertaining to the bandtail puffer fish host. Based on genome-based taxonomic approach, strain A520T (A520T = CBAS 737T = CAIM 1944T) is proposed as a new species, Pseudoalteromonas simplex sp. nov.

Chromobacterium indicum sp. nov., a Pigment-Producing Bacterium Isolated from Soil.

A purple colony, designated as TRC1.1.SA was isolated from a tea garden soil sample. It was a Gram-negative, rod-shaped, non-spore-forming and motile bacterium. The strain TRC1.1.SAT grew aerobically at temperatures 15-37 â„ƒ and pH levels 5.0-9.0. It showed both oxidase and catalase activity. The 16S rRNA gene sequence blast analysis revealed identity with the members of the genus Chromobacterium. The maximum identity was with the type strains of species Chromobacterium piscinae CCM 3329T (99.8%), C. vaccinii MWU205T (99.7%), and C. violaceum ATCC 12472T (98.7%). However, the average nucleotide identity (ANI) of the genome sequence showed less than 96% similarity with all species of the genus Chromobacterium. Further, digital DNA-DNA hybridization (dDDH) revealed the highest identity of 63.4% with its phylogenetic relative C. piscinae CCM 3329T. The G + C content of the strain was 63.9%. The major polar lipids identified were phosphatidylethanolamine (PE), diphosphatidylglycerol (DPG), and phosphoglyceraldehyde (PG). Fatty acid analysis showed C16:0, C16:1ω7c, C17:0 cyclo, and C18:1ω7c as the major fatty acids. RAST and antiSMASH analyses of the genome revealed the presence of a biosynthetic gene cluster (BGC) involved in the production of violacein pigment, as observed for type species C. violaceum ATCC 12472T. Considering the phenotypic differences and genomic identity, strain TRC1.1.SAT is assigned as a novel species of the genus Chromobacterium, for which the name Chromobacterium indicum is proposed. The type strain of prospective species is designated as TRC1.1.SAT (= MTCC 13391T; JCM 36723T; = KCTC 8324T).

Genome-wide sRNA and mRNA transcriptomic profiling insights into carbapenem-resistant Acinetobacter baumannii.

Introduction: Acinetobacter baumannii (AB) is rising as a human pathogen of critical priority worldwide as it is the leading cause of opportunistic infections in healthcare settings and carbapenem-resistant AB is listed as a "super bacterium" or "priority pathogen for drug resistance" by the World Health Organization. Methods: Clinical isolates of A. baumannii were collected and tested for antimicrobial susceptibility. Among them, carbapenem-resistant and carbapenem-sensitive A. baumannii were subjected to prokaryotic transcriptome sequencing. The change of sRNA and mRNA expression was analyzed by bioinformatics and validated by quantitative reverse transcription-PCR. Results: A total of 687 clinical isolates were collected, of which 336 strains of A. baumannii were resistant to carbapenem. Five hundred and six differentially expressed genes and nineteen differentially expressed sRNA candidates were discovered through transcriptomic profile analysis between carbapenem-resistant isolates and carbapenem-sensitive isolates. Possible binding sites were predicted through software for sRNA21 and adeK, sRNA27 and pgaC, sRNA29 and adeB, sRNA36 and katG, indicating a possible targeting relationship. A negative correlation was shown between sRNA21 and adeK (r = -0.581, P = 0.007), sRNA27 and pgaC (r = -0.612, P = 0.004), sRNA29 and adeB (r = -0.516, P = 0.020). Discussion: This study preliminarily screened differentially expressed mRNA and sRNA in carbapenem-resistant A. baumannii, and explored possible targeting relationships, which will help further reveal the resistance mechanism and provide a theoretical basis for the development of drugs targeting sRNA for the prevention and treatment of carbapenem-resistant A. baumannii infection.

Comparisons of genome assembly tools for characterization of Mycobacterium tuberculosis genomes using hybrid sequencing technologies.

Background: Next-generation sequencing of Mycobacterium tuberculosis, the infectious agent causing tuberculosis, is improving the understanding of genomic diversity of circulating lineages and strain-types, and informing knowledge of drug resistance mutations. An increasingly popular approach to characterizing M. tuberculosis genomes (size: 4.4 Mbp) and variants (e.g., single nucleotide polymorphisms (SNPs)) involves the de novo assembly of sequence data. Methods: We compared the performance of genome assembly tools (Unicycler, RagOut, and RagTag) on sequence data from nine drug resistant M. tuberculosis isolates (multi-drug (MDR) n = 1; pre-extensively-drug (pre-XDR) n = 8) generated using Illumina HiSeq, Oxford Nanopore Technology (ONT) PromethION, and PacBio platforms. Results: Our investigation found that Unicycler-based assemblies had significantly higher genome completeness (~98.7%; p values = 0.01) compared to other assembler tools (RagOut = 98.6%, and RagTag = 98.6%). The genome assembly sizes (bp) across isolates and sequencers based on RagOut was significantly longer (p values < 0.001) (4,418,574 ± 8,824 bp) than Unicycler and RagTag assemblies (Unicycler = 4,377,642 ± 55,257 bp, and RagTag = 4,380,711 ± 51,164 bp). RagOut-based assemblies had the fewest contigs (~32) and the longest genome size (4,418,574 bp; vs. H37Rv reference size 4,411,532 bp) and therefore were chosen for downstream analysis. Pan-genome analysis of Illumina and PacBio hybrid assemblies revealed the greatest number of detected genes (4,639 genes; H37Rv reference contains 3,976 genes), while Illumina and ONT hybrid assemblies produced the highest number of SNPs. The number of genes from hybrid assemblies with ONT and PacBio long-reads (mean: 4,620 genes) was greater than short-read assembly alone (4,478 genes). All nine RagOut hybrid genome assemblies detected known mutations in genes associated with MDR-TB and pre-XDR-TB. Conclusions: Unicycler software performed the best in terms of achieving contiguous genomes, whereas RagOut improved the quality of Unicycler's genome assemblies by providing a longer genome size. Overall, our approach has demonstrated that short-read and long-read hybrid assembly can provide a more complete genome assembly than short-read assembly alone by detecting pan-genomes and more genes, including IS6110, and SNPs.

Comparative genomics identifies key adaptive traits of sponge-associated microbial symbionts.

Sponge microbiomes are often highly diverse making it difficult to determine which lineages are important for maintaining host health and homeostasis. Characterising genomic traits associated with symbiosis can improve our knowledge of which lineages have adapted to their host and what functions they might provide. Here we examined five microbial families associated with sponges that have previously shown evidence of cophylogeny, including Endozoicomonadaceae, Nitrosopumilaceae, Spirochaetaceae, Microtrichaceae and Thermoanaerobaculaceae, to better understand the mechanisms behind their symbiosis. We compared sponge-associated genomes to genomes found in other environments and found that sponge-specific clades were enriched in genes encoding many known mechanisms for symbiont survival, such as avoiding phagocytosis and defence against foreign genetic elements. We expand on previous knowledge to show that glycosyl hydrolases with sulfatases and sulfotransferases likely form multienzyme degradation pathways to break and remodel sulfated polysaccharides and reveal an enrichment in superoxide dismutase that may prevent damage from free oxygen radicals produced by the host. Finally, we identified novel traits in sponge-associated symbionts, such as urea metabolism in Spirochaetaceae which was previously shown to be rare in the phylum Spirochaetota. These results identify putative mechanisms by which symbionts have adapted to living in association with sponges.

Actinomycetota Amycolatopsis nalaikhensis sp. nov. and Amycolatopsis carbonis sp. nov., two novel actinobacteria with antimicrobial activity isolated from a coal mining site in Mongolia.

Two-novel filamentous actinobacteria designated strains 2-2T and 2-15T were isolated from soil of a coal mining site in Mongolia, and their taxonomic positions were determined using a polyphasic approach. Phylogenetic analyses based on 16S rRNA gene sequences showed that each of the strains formed a distinct clade within the genus Amycolatopsis. The 16S rRNA gene sequence similarity analysis showed that both strains were mostly related to Amycolatopsis rhabdoformis NCIMB 14900T with 99.0 and 99.4% sequence similarity, respectively. The genome-based comparison indicated that strain 2-2T shared the highest digital DNA-DNA hybridization value of 35.6% and average nucleotide identity value of 86.9% with Amycolatopsis pretoriensis DSM 44654T, and strain 2-15T shared the corresponding values of 36.5 and 87.9% with A. rhabdoformis NCIMB 14900T, all of which being well below the thresholds for species delineation. The chemotaxonomic properties of both strains were typical of the genus Amycolatopsis. In silico prediction of chemotaxonomic markers was also carried out, and the results were consistent with the chemotaxonomic profiles of the genus. Genome mining for secondary metabolite production in strains 2-2T and 2-15T revealed the presence of 29 and 24 biosynthetic gene clusters involved in the production of polyketide synthase, non-ribosomal peptide synthetase, ribosomally synthesized and post-translationally modified peptides, lanthipeptide, terpenes, siderophore, and a number of other unknown type compounds. Both strains showed broad antifungal activity against several filamentous fungi and also antibacterial activity against methicillin-resistant Staphylococcus aureus and Acinetobacter baumannii. The phenotypic, biochemical, and chemotaxonomic properties indicated that both strains could be clearly distinguished from other species of Amycolatopsis, and thus the names Amycolatopsis nalaikhensis sp. nov. (type strain, 2-2T=KCTC 29695T=JCM 30462T) and Amycolatopsis carbonis (type strain, 2-15T=KCTC 39525T=JCM 30563T) are proposed accordingly.

Nocardiopsis codii sp. nov., and Rhodococcus chondri sp. nov., two novel actinomycetal species isolated from macroalgae collected in the northern Portuguese coast.

Two novel actinomycetal strains, designated CC-R113T and CC-R104T, were isolated from the tissues of two macroalgae collected on the northern Portuguese coast. Phylogenetic analyses based on the 16S rRNA gene showed that strain CT-R113T belongs to the genus Nocardiopsis, being closely related to Nocardiopsis umidischolae 66/93T and Nocardiopsis tropica VKM Ac-1457T, with 98.65 and 98.39 % sequence similarity, respectively. The clade formed between the three type strains was confirmed by phylogenomic analysis. The genome of strain CT-R113T was 7.27 Mb in size with a G+C content of 71.3 mol %, with average nucleotide identity (ANI) values of 89.59 and 90.14 % with strains 66/93T and VKM Ac-1457T, respectively. The major cellular fatty acids were identified as C18 : 1 ω9c, iso-C16 : 0 and anteiso-C17 : 0. Menaquinone 10 (MK-10) was the major respiratory quinone. Comparative analysis of 16S rRNA gene sequences showed that strain CC-R104T belongs to the genus Rhodococcus and is most closely related to Rhodococcus pyridinivorans DSM 44555T, with 98.24 % sequence similarity. However, phylogenomic analysis revealed that strain CC-R104T establishes a clade with Rhodococcus artemisae DSM 45380T, being more distant from Rhodococcus pyridinivorans DSM 44555T. The genome of strain CC-R104T was 5.34 Mb in size with a G+C content of 67.01 mol%. The ANI value between strains CC-R104T and DSM 45380T was 81.2 % and between strains CC-R104T and DSM 44555T was 81.5 %. The major cellular fatty acids were identified as C18 : 1 ω9c, C16 : 0 and summed feature 3. Menaquinone 8 (MK-8) was the only respiratory quinone. For both CC-R113T and CC-R104T, optimum growth was observed at pH 7.0, 28 °C and 0-5 % NaCl and whole-cell hydrolysates contained meso-diaminopimelic acid as the cell-wall diamino acid. On the basis of phenotypic, molecular and chemotaxonomic characteristics, strains CT-R113T and CC-R104T are considered to represent novel species, for which the names Nocardiopsis codii sp. nov. (type strain CT-R113T=LMG33234T=UCCCB172T) and Rhodococcus chondri sp. nov. (type strain CC-R104T=LMG33233T=UCCCB171T) are proposed.

Genetic diversity within diagnostic sputum samples is mirrored in the culture of Mycobacterium tuberculosis across different settings.

Culturing and genomic sequencing of Mycobacterium tuberculosis (MTB) from tuberculosis (TB) cases is the basis for many research and clinical applications. The alternative, culture-free sequencing from diagnostic samples, is promising but poses challenges to obtain and analyse the MTB genome. Paradoxically, culture is assumed to impose a diversity bottleneck, which, if true, would entail unexplored consequences. To unravel this paradox we generate high-quality genomes of sputum-culture pairs from two different settings after developing a workflow for sequencing from sputum and a tailored bioinformatics analysis. Careful downstream comparisons reveal sources of sputum-culture incongruences due to false positive/negative variation associated with factors like low input MTB DNA or variable genomic depths. After accounting for these factors, contrary to the bottleneck dogma, we identify a 97% variant agreement within sputum-culture pairs, with a high correlation also in the variants' frequency (0.98). The combined analysis from five different settings and more than 100 available samples shows that our results can be extrapolated to different TB epidemic scenarios, demonstrating that for the cases tested culture accurately mirrors clinical samples.

Genomic analysis of Vibrio cholerae O1 isolates from cholera cases, Europe, 2022.

BackgroundThe number of cholera cases reported to the World Health Organization (WHO) in 2022 was more than double that of 2021. Nine countries of the WHO European Region reported 51 cases of cholera in 2022 vs five reported cases in 2021.AimWe aimed to confirm that the Vibrio cholerae O1 isolates reported by WHO European Region countries in 2022 belonged to the seventh pandemic El Tor lineage (7PET). We also studied their virulence, antimicrobial resistance (AMR) determinants and phylogenetic relationships.MethodsWe used microbial genomics to study the 49 V. cholerae O1 isolates recovered from the 51 European cases. We also used > 1,450 publicly available 7PET genomes to provide a global phylogenetic context for these 49 isolates.ResultsAll 46 good-quality genomes obtained belonged to the 7PET lineage. All but two isolates belonged to genomic Wave 3 and were grouped within three sub-lineages, one of which, Pre-AFR15, predominated (34/44). This sub-lineage, corresponding to isolates from several countries in Southern Asia, the Middle East and Eastern or Southern Africa, was probably a major contributor to the global upsurge of cholera cases in 2022. No unusual AMR profiles were inferred from analysis of the AMR gene content of the 46 genomes.ConclusionReference laboratories in high-income countries should use whole genome sequencing to assign V. cholerae O1 isolates formally to the 7PET or non-epidemic lineages. Periodic collaborative genomic studies based on isolates from travellers can provide useful information on the circulating strains and their evolution, particularly as concerns AMR.

Interactive tools for functional annotation of bacterial genomes.

Automated annotations of protein functions are error-prone because of our lack of knowledge of protein functions. For example, it is often impossible to predict the correct substrate for an enzyme or a transporter. Furthermore, much of the knowledge that we do have about the functions of proteins is missing from the underlying databases. We discuss how to use interactive tools to quickly find different kinds of information relevant to a protein's function. Many of these tools are available via PaperBLAST (http://papers.genomics.lbl.gov). Combining these tools often allows us to infer a protein's function. Ideally, accurate annotations would allow us to predict a bacterium's capabilities from its genome sequence, but in practice, this remains challenging. We describe interactive tools that infer potential capabilities from a genome sequence or that search a genome to find proteins that might perform a specific function of interest. Database URL: http://papers.genomics.lbl.gov.

Population genomics of Streptococcus mitis in UK and Ireland bloodstream infection and infective endocarditis cases.

Streptococcus mitis is a leading cause of infective endocarditis (IE). However, our understanding of the genomic epidemiology and pathogenicity of IE-associated S. mitis is hampered by low IE incidence. Here we use whole genome sequencing of 129 S. mitis bloodstream infection (BSI) isolates collected between 2001-2016 from clinically diagnosed IE cases in the UK to investigate genetic diversity, antimicrobial resistance, and pathogenicity. We show high genetic diversity of IE-associated S. mitis with virtually all isolates belonging to distinct lineages indicating no predominance of specific lineages. Additionally, we find a highly variable distribution of known pneumococcal virulence genes among the isolates, some of which are overrepresented in disease when compared to carriage strains. Our findings suggest that S. mitis in patients with clinically diagnosed IE is not primarily caused by specific hypervirulent or antimicrobial resistant lineages, highlighting the accidental pathogenic nature of S. mitis in patients with clinically diagnosed IE.

Digital Microbe: a genome-informed data integration framework for team science on emerging model organisms.

The remarkable pace of genomic data generation is rapidly transforming our understanding of life at the micron scale. Yet this data stream also creates challenges for team science. A single microbe can have multiple versions of genome architecture, functional gene annotations, and gene identifiers; additionally, the lack of mechanisms for collating and preserving advances in this knowledge raises barriers to community coalescence around shared datasets. "Digital Microbes" are frameworks for interoperable and reproducible collaborative science through open source, community-curated data packages built on a (pan)genomic foundation. Housed within an integrative software environment, Digital Microbes ensure real-time alignment of research efforts for collaborative teams and facilitate novel scientific insights as new layers of data are added. Here we describe two Digital Microbes: 1) the heterotrophic marine bacterium Ruegeria pomeroyi DSS-3 with > 100 transcriptomic datasets from lab and field studies, and 2) the pangenome of the cosmopolitan marine heterotroph Alteromonas containing 339 genomes. Examples demonstrate how an integrated framework collating public (pan)genome-informed data can generate novel and reproducible findings.

Long-term persistence of diverse clones shapes the transmission landscape of invasive Listeria monocytogenes.

BACKGROUND: The foodborne bacterium Listeria monocytogenes (Lm) causes a range of diseases, from mild gastroenteritis to invasive infections that have high fatality rate in vulnerable individuals. Understanding the population genomic structure of invasive Lm is critical to informing public health interventions and infection control policies that will be most effective especially in local and regional communities. METHODS: We sequenced the whole draft genomes of 936 Lm isolates from human clinical samples obtained in a two-decade active surveillance program across 58 counties in New York State, USA. Samples came mostly from blood and cerebrospinal fluid. We characterized the phylogenetic relationships, population structure, antimicrobial resistance genes, virulence genes, and mobile genetic elements. RESULTS: The population is genetically heterogenous, consisting of lineages I-IV, 89 clonal complexes, 200 sequence types, and six known serogroups. In addition to intrinsic antimicrobial resistance genes (fosX, lin, norB, and sul), other resistance genes tetM, tetS, ermG, msrD, and mefA were sparsely distributed in the population. Within each lineage, we identified clusters of isolates with ≤ 20 single nucleotide polymorphisms in the core genome alignment. These clusters may represent isolates that share a most recent common ancestor, e.g., they are derived from the same contamination source or demonstrate evidence of transmission or outbreak. We identified 38 epidemiologically linked clusters of isolates, confirming eight previously reported disease outbreaks and the discovery of cryptic outbreaks and undetected chains of transmission, even in the rarely reported Lm lineage III (ST3171). The presence of animal-associated lineages III and IV may suggest a possible spillover of animal-restricted strains to humans. Many transmissible clones persisted over several years and traversed distant sites across the state. CONCLUSIONS: Our findings revealed the bacterial determinants of invasive listeriosis, driven mainly by the diversity of locally circulating lineages, intrinsic and mobile antimicrobial resistance and virulence genes, and persistence across geographical and temporal scales. Our findings will inform public health efforts to reduce the burden of invasive listeriosis, including the design of food safety measures, source traceback, and outbreak detection.