PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

Natural selection and recombination at host-interacting lipoprotein loci drive genome diversification of Lyme disease and related bacteria

Lyme disease, caused by spirochetes in the Borrelia burgdorferi sensu lato clade within the Borrelia genus, is transmitted by Ixodes ticks and is currently the most prevalent and rapidly expanding tick-borne disease in Europe and North America. We report complete genome sequences of 47 isolates that encompass all established species in this clade while highlighting the diversity of the widespread human pathogenic species B. burgdorferi. A similar set of plasmids has been maintained throughout Borrelia divergence, indicating that they are a key adaptive feature of this genus. Phylogenetic reconstruction of all sequenced Borrelia genomes revealed the original divergence of Eurasian and North American lineages and subsequent dispersals that introduced B. garinii, B. bavariensis, B. lusitaniae, B. valaisiana, and B. afzelii from East Asia to Europe and B. burgdorferi and B. finlandensis from North America to Europe. Molecular phylogenies of the universally present core replicons (chromosome and cp26 and lp54 plasmids) are highly consistent, revealing a strong clonal structure. Nonetheless, numerous inconsistencies between the genome and gene phylogenies indicate species dispersal, genetic exchanges, and rapid sequence evolution at plasmid-borne loci, including key host-interacting lipoprotein genes. While localized recombination occurs uniformly on the main chromosome at a rate comparable to mutation, lipoprotein-encoding loci are recombination hotspots on the plasmids, suggesting adaptive maintenance of recombinant alleles at loci directly interacting with the host. We conclude that within- and between-species recombination facilitates adaptive sequence evolution of host-interacting lipoprotein loci and contributes to human virulence despite a genome-wide clonal structure of its natural populations.

IMPORTANCE

Lyme disease (also called Lyme borreliosis in Europe), a condition caused by spirochete bacteria of the genus Borrelia, transmitted by hard-bodied Ixodes ticks, is currently the most prevalent and rapidly expanding tick-borne disease in the United States and Europe. Borrelia interspecies and intraspecies genome comparisons of Lyme disease-related bacteria are essential to reconstruct their evolutionary origins, track epidemiological spread, identify molecular mechanisms of human pathogenicity, and design molecular and ecological approaches to disease prevention, diagnosis, and treatment. These Lyme disease-associated bacteria harbor complex genomes that encode many genes that do not have homologs in other organisms and are distributed across multiple linear and circular plasmids. The functional significance of most of the plasmid-borne genes and the multipartite genome organization itself remains unknown. Here we sequenced, assembled, and analyzed whole genomes of 47 Borrelia isolates from around the world, including multiple isolates of the human pathogenic species. Our analysis elucidates the evolutionary origins, historical migration, and sources of genomic variability of these clinically important pathogens. We have developed web-based software tools (BorreliaBase.org) to facilitate dissemination and continued comparative analysis of Borrelia genomes to identify determinants of human pathogenicity.

Bacterial homologs of innate eukaryotic antiviral defenses with anti-phage activity highlight shared evolutionary roots of viral defenses

Prokaryotes have evolved a multitude of defense systems to protect against phage predation. Some of these resemble eukaryotic genes involved in antiviral responses. Here, we set out to systematically project the current knowledge of eukaryotic-like antiviral defense systems onto prokaryotic genomes, using Pseudomonas aeruginosa as a model organism. Searching for phage defense systems related to innate antiviral genes from vertebrates and plants, we uncovered over 450 candidates. We validated six of these phage defense systems, including factors preventing viral attachment, R-loop-acting enzymes, the inflammasome, ubiquitin pathway, and pathogen recognition signaling. Collectively, these defense systems support the concept of deep evolutionary links and shared antiviral mechanisms between prokaryotes and eukaryotes.

Efficient inference of large prokaryotic pangenomes with PanTA

Pangenome inference is an indispensable step in bacterial genomics, yet its scalability poses a challenge due to the rapid growth of genomic collections. This paper presents PanTA, a software package designed for constructing pangenomes of large bacterial datasets, showing unprecedented efficiency levels multiple times higher than existing tools. PanTA introduces a novel mechanism to construct the pangenome progressively without rebuilding the accumulated collection from scratch. The progressive mode is shown to consume orders of magnitude less computational resources than existing solutions in managing growing datasets. The software is open source and is publicly available at https://github.com/amromics/panta and at 10.6084/m9.figshare.23724705 .

Comprehensive blueprint of Salmonella genomic plasticity identifies hotspots for pathogenicity genes

Understanding the dynamic evolution of Salmonella is vital for effective bacterial infection management. This study explores the role of the flexible genome, organised in regions of genomic plasticity (RGP), in shaping the pathogenicity of Salmonella lineages. Through comprehensive genomic analysis of 12,244 Salmonella spp. genomes covering 2 species, 6 subspecies, and 46 serovars, we uncover distinct integration patterns of pathogenicity-related gene clusters into RGP, challenging traditional views of gene distribution. These RGP exhibit distinct preferences for specific genomic spots, and the presence or absence of such spots across Salmonella lineages profoundly shapes strain pathogenicity. RGP preferences are guided by conserved flanking genes surrounding integration spots, implicating their involvement in regulatory networks and functional synergies with integrated gene clusters. Additionally, we emphasise the multifaceted contributions of plasmids and prophages to the pathogenicity of diverse Salmonella lineages. Overall, this study provides a comprehensive blueprint of the pathogenicity potential of Salmonella. This unique insight identifies genomic spots in nonpathogenic lineages that hold the potential for harbouring pathogenicity genes, providing a foundation for predicting future adaptations and developing targeted strategies against emerging human pathogenic strains.

PanVA: Pangenomic Variant Analysis

Genomics researchers increasingly use multiple reference genomes to comprehensively explore genetic variants underlying differences in detectable characteristics between organisms. Pangenomes allow for an efficient data representation of multiple related genomes and their associated metadata. However, current visual analysis approaches for exploring these complex genotype-phenotype relationships are often based on single reference approaches or lack adequate support for interpreting the variants in the genomic context with heterogeneous (meta)data. This design study introduces PanVA, a visual analytics design for pangenomic variant analysis developed with the active participation of genomics researchers. The design uniquely combines tailored visual representations with interactions such as sorting, grouping, and aggregation, allowing users to navigate and explore different perspectives on complex genotype-phenotype relations. Through evaluation in the context of plants and pathogen research, we show that PanVA helps researchers explore variants in genes and generate hypotheses about their role in phenotypic variation.

Identification of mobile genetic elements with geNomad

Identifying and characterizing mobile genetic elements in sequencing data is essential for understanding their diversity, ecology, biotechnological applications and impact on public health. Here we introduce geNomad, a classification and annotation framework that combines information from gene content and a deep neural network to identify sequences of plasmids and viruses. geNomad uses a dataset of more than 200,000 marker protein profiles to provide functional gene annotation and taxonomic assignment of viral genomes. Using a conditional random field model, geNomad also detects proviruses integrated into host genomes with high precision. In benchmarks, geNomad achieved high classification performance for diverse plasmids and viruses (Matthews correlation coefficient of 77.8% and 95.3%, respectively), substantially outperforming other tools. Leveraging geNomad's speed and scalability, we processed over 2.7 trillion base pairs of sequencing data, leading to the discovery of millions of viruses and plasmids that are available through the IMG/VR and IMG/PR databases. geNomad is available at https://portal.nersc.gov/genomad .

Development and implementation of a core genome multilocus sequence typing scheme for Haemophilus influenzae

Haemophilus influenzae is part of the human nasopharyngeal microbiota and a pathogen causing invasive disease. The extensive genetic diversity observed in H. influenzae necessitates discriminatory analytical approaches to evaluate its population structure. This study developed a core genome multilocus sequence typing (cgMLST) scheme for H. influenzae using pangenome analysis tools and validated the cgMLST scheme using datasets consisting of complete reference genomes (N = 14) and high-quality draft H. influenzae genomes (N = 2297). The draft genome dataset was divided into a development dataset (N = 921) and a validation dataset (N = 1376). The development dataset was used to identify potential core genes, and the validation dataset was used to refine the final core gene list to ensure the reliability of the proposed cgMLST scheme. Functional classifications were made for all the resulting core genes. Phylogenetic analyses were performed using both allelic profiles and nucleotide sequence alignments of the core genome to test congruence, as assessed by Spearman's correlation and ordinary least square linear regression tests. Preliminary analyses using the development dataset identified 1067 core genes, which were refined to 1037 with the validation dataset. More than 70% of core genes were predicted to encode proteins essential for metabolism or genetic information processing. Phylogenetic and statistical analyses indicated that the core genome allelic profile accurately represented phylogenetic relatedness among the isolates (R 2 = 0.945). We used this cgMLST scheme to define a high-resolution population structure for H. influenzae, which enhances the genomic analysis of this clinically relevant human pathogen.

Genomic diversity in Paenibacillus polymyxa: unveiling distinct species groups and functional variability

BACKGROUND

Paenibacillus polymyxa is a bacterial species of high interest, as suggested by the increased number of publications on its functions in the past years. Accordingly, the number of described strains and sequenced genomes is also on the rise. While functional diversity of P. polymyxa has been suggested before, the available genomic data is now sufficient for robust comparative genomics analyses.

RESULTS

Using 157 genomes, we found significant disparities among strains currently affiliated to P. polymyxa. Multiple taxonomic groups were identified with conserved predicted functions putatively impacting their respective ecology. As strains of this species have been reported to exhibit considerable potential in agriculture, medicine, and bioremediation, it is preferable to clarify their taxonomic organization to facilitate reliable and durable approval as active ingredients.

CONCLUSIONS

Strains currently affiliated to P. polymyxa can be separated into two major species groups with differential potential in nitrogen fixation, plant interaction, secondary metabolism, and antimicrobial resistance, as inferred from genomic data.

Exploring gene content with pangene graphs

MOTIVATION

The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome.

RESULTS

We developed pangene, a computational tool to identify gene orientation, gene order and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph. It additionally finds subgraphs, which we call bibubbles, that capture gene content changes. Applied to the human pangenome, pangene identifies known gene-level variations and reveals complex haplotypes that are not well studied before. Pangene also works with high-quality bacterial pangenome and reports similar numbers of core and accessory genes in comparison to existing tools.

AVAILABILITY AND IMPLEMENTATION

Source code at https://github.com/lh3/pangene; pre-built pangene graphs can be downloaded from https://zenodo.org/records/8118576 and visualized at https://pangene.bioinweb.org.

Genome-resolved metagenomics: a game changer for microbiome medicine

Recent substantial evidence implicating commensal bacteria in human diseases has given rise to a new domain in biomedical research: microbiome medicine. This emerging field aims to understand and leverage the human microbiota and derivative molecules for disease prevention and treatment. Despite the complex and hierarchical organization of this ecosystem, most research over the years has relied on 16S amplicon sequencing, a legacy of bacterial phylogeny and taxonomy. Although advanced sequencing technologies have enabled cost-effective analysis of entire microbiota, translating the relatively short nucleotide information into the functional and taxonomic organization of the microbiome has posed challenges until recently. In the last decade, genome-resolved metagenomics, which aims to reconstruct microbial genomes directly from whole-metagenome sequencing data, has made significant strides and continues to unveil the mysteries of various human-associated microbial communities. There has been a rapid increase in the volume of whole metagenome sequencing data and in the compilation of novel metagenome-assembled genomes and protein sequences in public depositories. This review provides an overview of the capabilities and methods of genome-resolved metagenomics for studying the human microbiome, with a focus on investigating the prokaryotic microbiota of the human gut. Just as decoding the human genome and its variations marked the beginning of the genomic medicine era, unraveling the genomes of commensal microbes and their sequence variations is ushering us into the era of microbiome medicine. Genome-resolved metagenomics stands as a pivotal tool in this transition and can accelerate our journey toward achieving these scientific and medical milestones.

RIBAP: a comprehensive bacterial core genome annotation pipeline for pangenome calculation beyond the species level

Microbial pangenome analysis identifies present or absent genes in prokaryotic genomes. However, current tools are limited when analyzing species with higher sequence diversity or higher taxonomic orders such as genera or families. The Roary ILP Bacterial core Annotation Pipeline (RIBAP) uses an integer linear programming approach to refine gene clusters predicted by Roary for identifying core genes. RIBAP successfully handles the complexity and diversity of Chlamydia, Klebsiella, Brucella, and Enterococcus genomes, outperforming other established and recent pangenome tools for identifying all-encompassing core genes at the genus level. RIBAP is a freely available Nextflow pipeline at github.com/hoelzer-lab/ribap and zenodo.org/doi/10.5281/zenodo.10890871.

A pangenome analysis of ESKAPE bacteriophages: the underrepresentation may impact machine learning models

Bacteriophages are the most prevalent biological entities in the biosphere. However, limitations in both medical relevance and sequencing technologies have led to a systematic underestimation of the genetic diversity within phages. This underrepresentation not only creates a significant gap in our understanding of phage roles across diverse biosystems but also introduces biases in computational models reliant on these data for training and testing. In this study, we focused on publicly available genomes of bacteriophages infecting high-priority ESKAPE pathogens to show the extent and impact of this underrepresentation. First, we demonstrate a stark underrepresentation of ESKAPE phage genomes within the public genome and protein databases. Next, a pangenome analysis of these ESKAPE phages reveals extensive sharing of core genes among phages infecting the same host. Furthermore, genome analyses and clustering highlight close nucleotide-level relationships among the ESKAPE phages, raising concerns about the limited diversity within current public databases. Lastly, we uncover a scarcity of unique lytic phages and phage proteins with antimicrobial activities against ESKAPE pathogens. This comprehensive analysis of the ESKAPE phages underscores the severity of underrepresentation and its potential implications. This lack of diversity in phage genomes may restrict the resurgence of phage therapy and cause biased outcomes in data-driven computational models due to incomplete and unbalanced biological datasets.

From genome to evolution: investigating type II methylotrophs using a pangenomic analysis

A comprehensive pangenomic approach was employed to analyze the genomes of 75 type II methylotrophs spanning various genera. Our investigation revealed 256 exact core gene families shared by all 75 organisms, emphasizing their crucial role in the survival and adaptability of these organisms. Additionally, we predicted the functionality of 12 hypothetical proteins. The analysis unveiled a diverse array of genes associated with key metabolic pathways, including methane, serine, glyoxylate, and ethylmalonyl-CoA (EMC) metabolic pathways. While all selected organisms possessed essential genes for the serine pathway, Methylooceanibacter marginalis lacked serine hydroxymethyltransferase (SHMT), and Methylobacterium variabile exhibited both isozymes of SHMT, suggesting its potential to utilize a broader range of carbon sources. Notably, Methylobrevis sp. displayed a unique serine-glyoxylate transaminase isozyme not found in other organisms. Only nine organisms featured anaplerotic enzymes (isocitrate lyase and malate synthase) for the glyoxylate pathway, with the rest following the EMC pathway. Methylovirgula sp. 4MZ18 stood out by acquiring genes from both glyoxylate and EMC pathways, and Methylocapsa sp. S129 featured an A-form malate synthase, unlike the G-form found in the remaining organisms. Our findings also revealed distinct phylogenetic relationships and clustering patterns among type II methylotrophs, leading to the proposal of a separate genus for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129. This pangenomic study unveils remarkable metabolic diversity, unique gene characteristics, and distinct clustering patterns of type II methylotrophs, providing valuable insights for future carbon sequestration and biotechnological applications.

IMPORTANCE

Methylotrophs have played a significant role in methane-based product production for many years. However, a comprehensive investigation into the diverse genetic architectures across different genera of methylotrophs has been lacking. This study fills this knowledge gap by enhancing our understanding of core hypothetical proteins and unique enzymes involved in methane oxidation, serine, glyoxylate, and ethylmalonyl-CoA pathways. These findings provide a valuable reference for researchers working with other methylotrophic species. Furthermore, this study not only unveils distinctive gene characteristics and phylogenetic relationships but also suggests a reclassification for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129 into separate genera due to their unique attributes within their respective genus. Leveraging the synergies among various methylotrophic organisms, the scientific community can potentially optimize metabolite production, increasing the yield of desired end products and overall productivity.

Interactions between pili affect the outcome of bacterial competition driven by the type VI secretion system

The bacterial type VI secretion system (T6SS) is a widespread, kin-discriminatory weapon capable of shaping microbial communities. Due to the system's dependency on contact, cellular interactions can lead to either competition or kin protection. Cell-to-cell contact is often accomplished via surface-exposed type IV pili (T4Ps). In Vibrio cholerae, these T4Ps facilitate specific interactions when the bacteria colonize natural chitinous surfaces. However, it has remained unclear whether and, if so, how these interactions affect the bacterium's T6SS-mediated killing. In this study, we demonstrate that pilus-mediated interactions can be harnessed by T6SS-equipped V. cholerae to kill non-kin cells under liquid growth conditions. We also show that the naturally occurring diversity of pili determines the likelihood of cell-to-cell contact and, consequently, the extent of T6SS-mediated competition. To determine the factors that enable or hinder the T6SS's targeted reduction of competitors carrying pili, we developed a physics-grounded computational model for autoaggregation. Collectively, our research demonstrates that T4Ps involved in cell-to-cell contact can impose a selective burden when V. cholerae encounters non-kin cells that possess an active T6SS. Additionally, our study underscores the significance of T4P diversity in protecting closely related individuals from T6SS attacks through autoaggregation and spatial segregation.

Exploring gene content with pangene graphs

Motivation

The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome.

Results

We developed pangene, a computational tool to identify gene orientation, gene order and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph. It additionally finds subgraphs, which we call bibubbles, that capture gene content changes. Applied to the human pangenome, pangene identifies known gene-level variations and reveals complex haplotypes that are not well studied before. Pangene also works with high-quality bacterial pangenome and reports similar numbers of core and accessory genes in comparison to existing tools.

Availability and implementation

Source code at https://github.com/lh3/pangene; pre-built pangene graphs can be downloaded from https://zenodo.org/records/8118576 and visualized at https://pangene.bioinweb.org.

Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches

Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.

Antihyperalgesic properties of gut microbiota: Parabacteroides distasonis as a new probiotic strategy to alleviate chronic abdominal pain

ABSTRACT

The potential role of gut microbiota in pain modulation is arousing an emerging interest since recent years. This study investigated neuromodulatory properties of gut microbiota to identify next-generation probiotics to propose alternative therapies for visceral pain management. Neuromodulation ability of 10 bacterial strains isolated from a healthy donor was assessed both on ND7/23 immortalized cell line and primary neuronal cells from rat dorsal root ganglia. This screening highlighted the neuroinhibitory property of Parabacteroides distasonis (F1-2) strain, supported both by its intracellular content and membrane fraction, which was further investigated in visceral pain mouse models. Oral administration of F1-2 resulted in a significant decrease of colonic hypersensitivity (CHS) in dextran sulfate sodium (0.5%) model associated with low-grade inflammation and a significant decrease of CHS in Citrobacter rodentium postinfectious models. No effect of F1-2 oral administration on CHS was observed in a neonatal maternal separation stress model. Antihyperalgesic effect unlikely involved modulation of inflammatory processes or restoration of intestinal barrier. Exploration of direct dialogue mechanisms between this strain and nervous system, assessed by calcium imaging experiments, revealed that F1-2 interacts directly with nociceptors by reducing activation level on capsaicin, inflammatory soup, and bradykinin stimulations. Our study provides new insights about bacteria-host interaction and places P distasonis as a potential therapeutic strategy in the treatment of visceral pain observed in leaky gut-associated pathologies.

A distinct Fusobacterium nucleatum clade dominates the colorectal cancer niche

Fusobacterium nucleatum (Fn), a bacterium present in the human oral cavity and rarely found in the lower gastrointestinal tract of healthy individuals1, is enriched in human colorectal cancer (CRC) tumours2-5. High intratumoural Fn loads are associated with recurrence, metastases and poorer patient prognosis5-8. Here, to delineate Fn genetic factors facilitating tumour colonization, we generated closed genomes for 135 Fn strains; 80 oral strains from individuals without cancer and 55 unique cancer strains cultured from tumours from 51 patients with CRC. Pangenomic analyses identified 483 CRC-enriched genetic factors. Tumour-isolated strains predominantly belong to Fn subspecies animalis (Fna). However, genomic analyses reveal that Fna, considered a single subspecies, is instead composed of two distinct clades (Fna C1 and Fna C2). Of these, only Fna C2 dominates the CRC tumour niche. Inter-Fna analyses identified 195 Fna C2-associated genetic factors consistent with increased metabolic potential and colonization of the gastrointestinal tract. In support of this, Fna C2-treated mice had an increased number of intestinal adenomas and altered metabolites. Microbiome analysis of human tumour tissue from 116 patients with CRC demonstrated Fna C2 enrichment. Comparison of 62 paired specimens showed that only Fna C2 is tumour enriched compared to normal adjacent tissue. This was further supported by metagenomic analysis of stool samples from 627 patients with CRC and 619 healthy individuals. Collectively, our results identify the Fna clade bifurcation, show that specifically Fna C2 drives the reported Fn enrichment in human CRC and reveal the genetic underpinnings of pathoadaptation of Fna C2 to the CRC niche.

Genomic characterization of Pseudomonas syringae pv. syringae from Callery pear and the efficiency of associated phages in disease protection

The Pseudomonas syringae species complex is a heterogeneous group of plant pathogenic bacteria associated with a wide distribution of plant species. Advances in genomics are revealing the complex evolutionary history of this species complex and the wide array of genetic adaptations underpinning their diverse lifestyles. Here, we genomically characterize two P. syringae isolates collected from diseased Callery pears (Pyrus calleryana) in Berkeley, California in 2019 and 2022. We also isolated a lytic bacteriophage, which we characterized and evaluated for biocontrol efficiency. Using a multilocus sequence analysis and core genome alignment, we classified the P. syringae isolates as members of phylogroup 2, related to other strains previously isolated from Pyrus and Prunus. An analysis of effector proteins demonstrated an evolutionary conservation of effectoromes across isolates classified in PG2 and yet uncovered unique effector profiles for each, including the two newly identified isolates. Whole-genome sequencing of the associated phage uncovered a novel phage genus related to Pseudomonas syringae pv. actinidiae phage PHB09 and the Flaumdravirus genus. Finally, using in planta infection assays, we demonstrate that the phage was equally useful in symptom mitigation of immature pear fruit regardless of the Pss strain tested. Overall, this study demonstrates the diversity of P. syringae and their viruses associated with ornamental pear trees, posing spill-over risks to commercial pear trees and the possibility of using phages as biocontrol agents to reduce the impact of disease.IMPORTANCEGlobal change exacerbates the spread and impact of pathogens, especially in agricultural settings. There is a clear need to better monitor the spread and diversity of plant pathogens, including in potential spillover hosts, and for the development of novel and sustainable control strategies. In this study, we characterize the first described strains of Pseudomonas syringae pv. syringae isolated from Callery pear in Berkeley, California from diseased tissues in an urban environment. We show that these strains have divergent virulence profiles from previously described strains and that they can cause disease in commercial pears. Additionally, we describe a novel bacteriophage that is associated with these strains and explore its potential to act as a biocontrol agent. Together, the data presented here demonstrate that ornamental pear trees harbor novel P. syringae pv. syringae isolates that potentially pose a risk to local fruit production, or vice versa-but also provide us with novel associated phages, effective in disease mitigation.

Phylometagenomics of cycad coralloid roots reveals shared symbiotic signals

Cycads are known to host symbiotic cyanobacteria, including Nostocales species, as well as other sympatric bacterial taxa within their specialized coralloid roots. Yet, it is unknown if these bacteria share a phylogenetic origin and/or common genomic functions that allow them to engage in facultative symbiosis with cycad roots. To address this, we obtained metagenomic sequences from 39 coralloid roots sampled from diverse cycad species and origins in Australia and Mexico. Culture-independent shotgun metagenomic sequencing was used to validate sub-community co-cultures as an efficient approach for functional and taxonomic analysis. Our metanalysis shows a host-independent microbiome core consisting of seven bacterial orders with high species diversity within the identified taxa. Moreover, we recovered 43 cyanobacterial metagenome-assembled genomes, and in addition to Nostoc spp., symbiotic cyanobacteria of the genus Aulosira were identified for the first time. Using this robust dataset, we used phylometagenomic analysis to reveal three monophyletic cyanobiont clades, two host-generalist and one cycad-specific that includes Aulosira spp. Although the symbiotic clades have independently arisen, they are enriched in certain functional genes, such as those related to secondary metabolism. Furthermore, the taxonomic composition of associated sympatric bacterial taxa remained constant. Our research quadruples the number of cycad cyanobiont genomes and provides a robust framework to decipher cyanobacterial symbioses, with the potential of improving our understanding of symbiotic communities. This study lays a solid foundation to harness cyanobionts for agriculture and bioprospection, and assist in conservation of critically endangered cycads.

KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome

The microbes present in the human gastrointestinal tract are regularly linked to human health and disease outcomes. Thanks to technological and methodological advances in recent years, metagenomic sequencing data, and computational methods designed to analyze metagenomic data, have contributed to improved understanding of the link between the human gut microbiome and disease. However, while numerous methods have been recently developed to extract quantitative and qualitative results from host-associated microbiome data, improved computational tools are still needed to track microbiome dynamics with short-read sequencing data. Previously we have proposed KOMB as a de novo tool for identifying copy number variations in metagenomes for characterizing microbial genome dynamics in response to perturbations. In this work, we present KombOver (KO), which includes four key contributions with respect to our previous work: (i) it scales to large microbiome study cohorts, (ii) it includes both k-core and K-truss based analysis, (iii) we provide the foundation of a theoretical understanding of the relation between various graph-based metagenome representations, and (iv) we provide an improved user experience with easier-to-run code and more descriptive outputs/results. To highlight the aforementioned benefits, we applied KO to nearly 1000 human microbiome samples, requiring less than 10 minutes and 10 GB RAM per sample to process these data. Furthermore, we highlight how graph-based approaches such as k-core and K-truss can be informative for pinpointing microbial community dynamics within a myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) cohort. KO is open source and available for download/use at: https://github.com/treangenlab/komb.

Step-by-Step Bacterial Genome Comparison

Thanks to advancements in genome sequencing and bioinformatics, thousands of bacterial genome sequences are available in public databases. This presents an opportunity to study bacterial diversity in unprecedented detail. This chapter describes a complete bioinformatics workflow for comparative genomics of bacterial genomes, including genome annotation, pangenome reconstruction and visualization, phylogenetic analysis, and identification of sequences of interest such as antimicrobial-resistance genes, virulence factors, and phage sequences. The workflow uses state-of-the-art, open-source tools. The workflow is presented by means of a comparative analysis of Salmonella enterica serovar Typhimurium genomes. The workflow is based on Linux commands and scripts, and result visualization relies on the R environment. The chapter provides a step-by-step protocol that researchers with basic expertise in bioinformatics can easily follow to conduct investigations on their own genome datasets.

Influence of genomic variations on glanders serodiagnostic antigens using integrative genomic and transcriptomic approaches

Glanders is a highly contagious and life-threatening zoonotic disease caused by Burkholderia mallei (B. mallei). Without an effective vaccine or treatment, early diagnosis has been regarded as the most effective method to prevent glanders transmission. Currently, the diagnosis of glanders is heavily reliant on serological tests. However, given that markedly different host immune responses can be elicited by genetically different strains of the same bacterial species, infection by B. mallei, whose genome is unstable and plastic, may result in various immune responses. This variability can make the serodiagnosis of glanders challenging. Therefore, there is a need for a comprehensive understanding and assessment of how B. mallei genomic variations impact the appropriateness of specific target antigens for glanders serodiagnosis. In this study, we investigated how genomic variations in the B. mallei genome affect gene content (gene presence/absence) and expression, with a special focus on antigens used or potentially used in serodiagnosis. In all the genome sequences of B. mallei isolates available in NCBI's RefSeq database (accessed in July 2023) and in-house sequenced samples, extensive small and large variations were observed when compared to the type strain ATCC 23344. Further pan-genome analysis of those assemblies revealed variations of gene content among all available genomes of B. mallei. Specifically, differences in gene content ranging from 31 to 715 genes with an average of 334 gene presence-absence variations were found in strains with complete or chromosome-level genome assemblies, using the ATCC 23344 strain as a reference. The affected genes included some encoded proteins used as serodiagnostic antigens, which were lost due mainly to structural variations. Additionally, a transcriptomic analysis was performed using the type strain ATCC 23344 and strain Zagreb which has been widely utilized to produce glanders antigens. In total, 388 significant differentially expressed genes were identified between these two strains, including genes related to bacterial pathogenesis and virulence, some of which were associated with genomic variations, particularly structural variations. To our knowledge, this is the first comprehensive study to uncover the impacts of genetic variations of B. mallei on its gene content and expression. These differences would have significant impacts on host innate and adaptive immunity, including antibody production, during infection. This study provides novel insights into B. mallei genetic variants, knowledge which will help to improve glanders serodiagnosis.

The pan-genome of Mycobacterium avium subsp. paratuberculosis (Map) confirms ancestral lineage and reveals gene rearrangements within Map Type S

BACKGROUND

To date genomic studies on Map have concentrated on Type C strains with only a few Type S strains included for comparison. In this study the entire pan-genome of 261 Map genomes (205 Type C, 52 Type S and 4 Type B) and 7 Mycobacterium avium complex (Mac) genomes were analysed to identify genomic similarities and differences between the strains and provide more insight into the evolutionary relationship within this Mycobacterial species.

RESULTS

Our analysis of the core genome of all the Map isolates identified two distinct lineages, Type S and Type C Map that is consistent with previous phylogenetic studies of Map. Pan-genome analysis revealed that Map has a larger accessory genome than Mycobacterium avium subsp. avium (Maa) and Type C Map has a larger accessory genome than Type S Map. In addition, we found large rearrangements within Type S strains of Map and little to none in Type C and Type B strains. There were 50 core genes identified that were unique to Type S Map and there were no unique core genes identified between Type B and Type C Map strains. In Type C Map we identified an additional CE10 CAZyme class which was identified as an alpha/beta hydrolase and an additional polyketide and non-ribosomal peptide synthetase cluster. Consistent with previous analysis no plasmids and only incomplete prophages were identified in the genomes of Map. There were 45 hypothetical CRISPR elements identified with no associated cas genes.

CONCLUSION

This is the most comprehensive comparison of the genomic content of Map isolates to date and included the closing of eight Map genomes. The analysis revealed that there is greater variation in gene synteny within Type S strains when compared to Type C indicating that the Type C Map strain emerged after Type S. Further analysis of Type C and Type B genomes revealed that they are structurally similar with little to no genetic variation and that Type B Map may be a distinct clade within Type C Map and not a different strain type of Map. The evolutionary lineage of Maa and Map was confirmed as emerging after M. hominissuis.

Comparison of gene clustering criteria reveals intrinsic uncertainty in pangenome analyses

BACKGROUND

A key step for comparative genomics is to group open reading frames into functionally and evolutionarily meaningful gene clusters. Gene clustering is complicated by intraspecific duplications and horizontal gene transfers that are frequent in prokaryotes. In consequence, gene clustering methods must deal with a trade-off between identifying vertically transmitted representatives of multicopy gene families, which are recognizable by synteny conservation, and retrieving complete sets of species-level orthologs. We studied the implications of adopting homology, orthology, or synteny conservation as formal criteria for gene clustering by performing comparative analyses of 125 prokaryotic pangenomes.

RESULTS

Clustering criteria affect pangenome functional characterization, core genome inference, and reconstruction of ancestral gene content to different extents. Species-wise estimates of pangenome and core genome sizes change by the same factor when using different clustering criteria, allowing robust cross-species comparisons regardless of the clustering criterion. However, cross-species comparisons of genome plasticity and functional profiles are substantially affected by inconsistencies among clustering criteria. Such inconsistencies are driven not only by mobile genetic elements, but also by genes involved in defense, secondary metabolism, and other accessory functions. In some pangenome features, the variability attributed to methodological inconsistencies can even exceed the effect sizes of ecological and phylogenetic variables.

CONCLUSIONS

Choosing an appropriate criterion for gene clustering is critical to conduct unbiased pangenome analyses. We provide practical guidelines to choose the right method depending on the research goals and the quality of genome assemblies, and a benchmarking dataset to assess the robustness and reproducibility of future comparative studies.

Genomic and phenotypic comparison of two variants of multidrug-resistant Salmonella enterica serovar Heidelberg isolated during the 2015-2017 multi-state outbreak in cattle

Salmonella enterica subspecies enterica serovar Heidelberg (Salmonella Heidelberg) has caused several multistate foodborne outbreaks in the United States, largely associated with the consumption of poultry. However, a 2015-2017 multidrug-resistant (MDR) Salmonella Heidelberg outbreak was linked to contact with dairy beef calves. Traceback investigations revealed calves infected with outbreak strains of Salmonella Heidelberg exhibited symptoms of disease frequently followed by death from septicemia. To investigate virulence characteristics of Salmonella Heidelberg as a pathogen in bovine, two variants with distinct pulse-field gel electrophoresis (PFGE) patterns that differed in morbidity and mortality during the multistate outbreak were genotypically and phenotypically characterized and compared. Strain SX 245 with PFGE pattern JF6X01.0523 was identified as a dominant and highly pathogenic variant causing high morbidity and mortality in affected calves, whereas strain SX 244 with PFGE pattern JF6X01.0590 was classified as a low pathogenic variant causing less morbidity and mortality. Comparison of whole-genome sequences determined that SX 245 lacked ~200 genes present in SX 244, including genes associated with the IncI1 plasmid and phages; SX 244 lacked eight genes present in SX 245 including a second YdiV Anti-FlhC(2)FlhD(4) factor, a lysin motif domain containing protein, and a pentapeptide repeat protein. RNA-sequencing revealed fimbriae-related, flagella-related, and chemotaxis genes had increased expression in SX 245 compared to SX 244. Furthermore, SX 245 displayed higher invasion of human and bovine epithelial cells than SX 244. These data suggest that the presence and up-regulation of genes involved in type 1 fimbriae production, flagellar regulation and biogenesis, and chemotaxis may play a role in the increased pathogenicity and host range expansion of the Salmonella Heidelberg isolates involved in the bovine-related outbreak.

Exploring environmental intra-species diversity through non-redundant pangenome assemblies

At the genome level, microorganisms are highly adaptable both in terms of allele and gene composition. Such heritable traits emerge in response to different environmental niches and can have a profound influence on microbial community dynamics. As a consequence, any individual genome or population will contain merely a fraction of the total genetic diversity of any operationally defined "species", whose ecological potential can thus be only fully understood by studying all of their genomes and the genes therein. This concept, known as the pangenome, is valuable for studying microbial ecology and evolution, as it partitions genomes into core (present in all the genomes from a species, and responsible for housekeeping and species-level niche adaptation among others) and accessory regions (present only in some, and responsible for intra-species differentiation). Here we present SuperPang, an algorithm producing pangenome assemblies from a set of input genomes of varying quality, including metagenome-assembled genomes (MAGs). SuperPang runs in linear time and its results are complete, non-redundant, preserve gene ordering and contain both coding and non-coding regions. Our approach provides a modular view of the pangenome, identifying operons and genomic islands, and allowing to track their prevalence in different populations. We illustrate this by analysing intra-species diversity in Polynucleobacter, a bacterial genus ubiquitous in freshwater ecosystems, characterized by their streamlined genomes and their ecological versatility. We show how SuperPang facilitates the simultaneous analysis of allelic and gene content variation under different environmental pressures, allowing us to study the drivers of microbial diversification at unprecedented resolution.

De novo genome assembly resolving repetitive structures enables genomic analysis of 35 European Mycoplasmopsis bovis strains

Mycoplasmopsis (M.) bovis, the agent of mastitis, pneumonia, and arthritis in cattle, harbors a small genome of approximately 1 Mbp. Combining data from Illumina and Nanopore technologies, we sequenced and assembled the genomes of 35 European strains and isolate DL422_88 from Cuba. While the high proportion of repetitive structures in M. bovis genomes represent a particular challenge, implementation of our own pipeline Mycovista (available on GitHub www.github.com/sandraTriebel/mycovista ) in a hybrid approach enabled contiguous assembly of the genomes and, consequently, improved annotation rates considerably. To put our European strain panel in a global context, we analyzed the new genome sequences together with 175 genome assemblies from public databases. Construction of a phylogenetic tree based on core genes of these 219 strains revealed a clustering pattern according to geographical origin, with European isolates positioned on clades 4 and 5. Genomic data allowing assignment of strains to tissue specificity or certain disease manifestations could not be identified. Seven strains isolated from cattle with systemic circular condition (SCC), still a largely unknown manifestation of M. bovis disease, were located on both clades 4 and 5. Pairwise association analysis revealed 108 genomic elements associated with a particular clade of the phylogenetic tree. Further analyzing these hits, 25 genes are functionally annotated and could be linked to a M. bovis protein, e.g. various proteases and nucleases, as well as ten variable surface lipoproteins (Vsps) and other surface proteins. These clade-specific genes could serve as useful markers in epidemiological and clinical surveys.

Widespread Bradyrhizobium distribution of diverse Type III effectors that trigger legume nodulation in the absence of Nod factor

The establishment of the rhizobium-legume symbiosis is generally based on plant perception of Nod factors (NFs) synthesized by the bacteria. However, some Bradyrhizobium strains can nodulate certain legume species, such as Aeschynomene spp. or Glycine max, independently of NFs, and via two different processes that are distinguished by the necessity or not of a type III secretion system (T3SS). ErnA is the first known type III effector (T3E) triggering nodulation in Aeschynomene indica. In this study, a collection of 196 sequenced Bradyrhizobium strains was tested on A. indica. Only strains belonging to the photosynthetic supergroup can develop a NF-T3SS-independent symbiosis, while the ability to use a T3SS-dependent process is found in multiple supergroups. Of these, 14 strains lacking ernA were tested by mutagenesis to identify new T3Es triggering nodulation. We discovered a novel T3E, Sup3, a putative SUMO-protease without similarity to ErnA. Its mutation in Bradyrhizobium strains NAS96.2 and WSM1744 abolishes nodulation and its introduction in an ernA mutant of strain ORS3257 restores nodulation. Moreover, ectopic expression of sup3 in A. indica roots led to the formation of spontaneous nodules. We also report three other new T3Es, Ubi1, Ubi2 and Ubi3, which each contribute to the nodulation capacity of strain LMTR13. These T3Es have no homology to known proteins but share with ErnA three motifs necessary for ErnA activity. Together, our results highlight an unsuspected distribution and diversity of T3Es within the Bradyrhizobium genus that may contribute to their symbiotic efficiency by participating in triggering legume nodulation.

Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads

Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications.

Phages are unrecognized players in the ecology of the oral pathogen Porphyromonas gingivalis

BACKGROUND

Porphyromonas gingivalis (hereafter "Pg") is an oral pathogen that has been hypothesized to act as a keystone driver of inflammation and periodontal disease. Although Pg is most readily recovered from individuals with actively progressing periodontal disease, healthy individuals and those with stable non-progressing disease are also colonized by Pg. Insights into the factors shaping the striking strain-level variation in Pg, and its variable associations with disease, are needed to achieve a more mechanistic understanding of periodontal disease and its progression. One of the key forces often shaping strain-level diversity in microbial communities is infection of bacteria by their viral (phage) predators and symbionts. Surprisingly, although Pg has been the subject of study for over 40 years, essentially nothing is known of its phages, and the prevailing paradigm is that phages are not important in the ecology of Pg.

RESULTS

Here we systematically addressed the question of whether Pg are infected by phages-and we found that they are. We found that prophages are common in Pg, they are genomically diverse, and they encode genes that have the potential to alter Pg physiology and interactions. We found that phages represent unrecognized targets of the prevalent CRISPR-Cas defense systems in Pg, and that Pg strains encode numerous additional mechanistically diverse candidate anti-phage defense systems. We also found that phages and candidate anti-phage defense system elements together are major contributors to strain-level diversity and the species pangenome of this oral pathogen. Finally, we demonstrate that prophages harbored by a model Pg strain are active in culture, producing extracellular viral particles in broth cultures.

CONCLUSION

This work definitively establishes that phages are a major unrecognized force shaping the ecology and intra-species strain-level diversity of the well-studied oral pathogen Pg. The foundational phage sequence datasets and model systems that we establish here add to the rich context of all that is already known about Pg, and point to numerous avenues of future inquiry that promise to shed new light on fundamental features of phage impacts on human health and disease broadly. Video Abstract.

Roving methyltransferases generate a mosaic epigenetic landscape and influence evolution in Bacteroides fragilis group

Three types of DNA methyl modifications have been detected in bacterial genomes, and mechanistic studies have demonstrated roles for DNA methylation in physiological functions ranging from phage defense to transcriptional control of virulence and host-pathogen interactions. Despite the ubiquity of methyltransferases and the immense variety of possible methylation patterns, epigenomic diversity remains unexplored for most bacterial species. Members of the Bacteroides fragilis group (BFG) reside in the human gastrointestinal tract as key players in symbiotic communities but also can establish anaerobic infections that are increasingly multi-drug resistant. In this work, we utilize long-read sequencing technologies to perform pangenomic (n = 383) and panepigenomic (n = 268) analysis of clinical BFG isolates cultured from infections seen at the NIH Clinical Center over four decades. Our analysis reveals that single BFG species harbor hundreds of DNA methylation motifs, with most individual motif combinations occurring uniquely in single isolates, implying immense unsampled methylation diversity within BFG epigenomes. Mining of BFG genomes identified more than 6000 methyltransferase genes, approximately 1000 of which were associated with intact prophages. Network analysis revealed substantial gene flow among disparate phage genomes, implying a role for genetic exchange between BFG phages as one of the ultimate sources driving BFG epigenome diversity.

Arcobacteraceae comparative genome analysis demonstrates genome heterogeneity and reduction in species isolated from animals and associated with human illness

The Arcobacteraceae family groups Gram-negative bacterial species previously included in the family Campylobacteraceae. These species of which some are considered foodborne pathogens, have been isolated from different environmental niches and hosts. They have been isolated from various types of foods, though predominantly from food of animal origin, as well as from stool of humans with enteritis. Their different abilities to survive in different hosts and environments suggest an evolutionary pressure with consequent variation in their genome content. Moreover, their different physiological and genomic characteristics led to the recent proposal to create new genera within this family, which is however criticized due to the lack of discriminatory features and biological and clinical relevance. Aims of the present study were to assess the Arcobacteraceae pangenome, and to characterize existing similarities and differences in 20 validly described species. For this, analysis has been conducted on the genomes of the corresponding type strains obtained by Illumina sequencing, applying several bioinformatic tools. Results of the present study do not support the proposed division into different genera and revealed the presence of pangenome partitions with numbers comparable to other Gram-negative bacteria genera, such as Campylobacter. Different gene class compositions in animal and human-associated species are present, including a higher percentage of virulence-related gene classes such as cell motility genes. The adaptation to environmental and/or host conditions of some species was identified by the presence of specific genes. Furthermore, a division into pathogenic and non-pathogenic species is suggested, which can support future research on food safety and public health.

DNA modifications impact natural transformation of Acinetobacter baumannii

Acinetobacter baumannii is a dangerous nosocomial pathogen, especially due to its ability to rapidly acquire new genetic traits, including antibiotic resistance genes (ARG). In A. baumannii, natural competence for transformation, one of the primary modes of horizontal gene transfer (HGT), is thought to contribute to ARG acquisition and has therefore been intensively studied. However, knowledge regarding the potential role of epigenetic DNA modification(s) on this process remains lacking. Here, we demonstrate that the methylome pattern of diverse A. baumannii strains differs substantially and that these epigenetic marks influence the fate of transforming DNA. Specifically, we describe a methylome-dependent phenomenon that impacts intra- and inter-species DNA exchange by the competent A. baumannii strain A118. We go on to identify and characterize an A118-specific restriction-modification (RM) system that impairs transformation when the incoming DNA lacks a specific methylation signature. Collectively, our work contributes towards a more holistic understanding of HGT in this organism and may also aid future endeavors towards tackling the spread of novel ARGs. In particular, our results suggest that DNA exchanges between bacteria that share similar epigenomes are favored and could therefore guide future research into identifying the reservoir(s) of dangerous genetic traits for this multi-drug resistant pathogen.

Epistatic interactions between the high pathogenicity island and other iron uptake systems shape Escherichia coli extra-intestinal virulence

The intrinsic virulence of extra-intestinal pathogenic Escherichia coli is associated with numerous chromosomal and/or plasmid-borne genes, encoding diverse functions such as adhesins, toxins, and iron capture systems. However, the respective contribution to virulence of those genes seems to depend on the genetic background and is poorly understood. Here, we analyze genomes of 232 strains of sequence type complex STc58 and show that virulence (quantified in a mouse model of sepsis) emerged in a sub-group of STc58 due to the presence of the siderophore-encoding high-pathogenicity island (HPI). When extending our genome-wide association study to 370 Escherichia strains, we show that full virulence is associated with the presence of the aer or sit operons, in addition to the HPI. The prevalence of these operons, their co-occurrence and their genomic location depend on strain phylogeny. Thus, selection of lineage-dependent specific associations of virulence-associated genes argues for strong epistatic interactions shaping the emergence of virulence in E. coli.

Metabolic capabilities are highly conserved among human nasal-associated Corynebacterium species in pangenomic analyses

Corynebacterium species are globally ubiquitous in human nasal microbiota across the lifespan. Moreover, nasal microbiota profiles typified by higher relative abundances of Corynebacterium are often positively associated with health. Among the most common human nasal Corynebacterium species are C. propinquum, C. pseudodiphtheriticum, C. accolens, and C. tuberculostearicum. Based on the prevalence of these species, at least two likely coexist in the nasal microbiota of 82% of adults. To gain insight into the functions of these four species, we identified genomic, phylogenomic, and pangenomic properties and estimated the functional protein repertoire and metabolic capabilities of 87 distinct human nasal Corynebacterium strain genomes: 31 from Botswana and 56 from the U.S. C. pseudodiphtheriticum had geographically distinct clades consistent with localized strain circulation, whereas some strains from the other species had wide geographic distribution across Africa and North America. All four species had similar genomic and pangenomic structures. Gene clusters assigned to all COG metabolic categories were overrepresented in the persistent (core) compared to the accessory genome of each species indicating limited strain-level variability in metabolic capacity. Moreover, core metabolic capabilities were highly conserved among the four species indicating limited species-level metabolic variation. Strikingly, strains in the U.S. clade of C. pseudodiphtheriticum lacked genes for assimilatory sulfate reduction present in the Botswanan clade and in the other studied species, indicating a recent, geographically related loss of assimilatory sulfate reduction. Overall, the minimal species and strain variability in metabolic capacity implies coexisting strains might have limited ability to occupy distinct metabolic niches.

PanGraph: scalable bacterial pan-genome graph construction

The genomic diversity of microbes is commonly parameterized as SNPs relative to a reference genome of a well-characterized, but arbitrary, isolate. However, any reference genome contains only a fraction of the microbial pangenome, the total set of genes observed in a given species. Reference-based approaches are thus blind to the dynamics of the accessory genome, as well as variation within gene order and copy number. With the widespread usage of long-read sequencing, the number of high-quality, complete genome assemblies has increased dramatically. In addition to pangenomic approaches that focus on the variation in the sets of genes present in different genomes, complete assemblies allow investigations of the evolution of genome structure and gene order. This latter problem, however, is computationally demanding with few tools available that shed light on these dynamics. Here, we present PanGraph, a Julia-based library and command line interface for aligning whole genomes into a graph. Each genome is represented as a path along vertices, which in turn encapsulate homologous multiple sequence alignments. The resultant data structure succinctly summarizes population-level nucleotide and structural polymorphisms and can be exported into several common formats for either downstream analysis or immediate visualization.

Combination of whole genome sequencing and supervised machine learning provides unambiguous identification of eae-positive Shiga toxin-producing Escherichia coli

Introduction

The objective of this study was to develop, using a genome wide machine learning approach, an unambiguous model to predict the presence of highly pathogenic STEC in E. coli reads assemblies derived from complex samples containing potentially multiple E. coli strains. Our approach has taken into account the high genomic plasticity of E. coli and utilized the stratification of STEC and E. coli pathogroups classification based on the serotype and virulence factors to identify specific combinations of biomarkers for improved characterization of eae-positive STEC (also named EHEC for enterohemorrhagic E.coli) which are associated with bloody diarrhea and hemolytic uremic syndrome (HUS) in human.

Methods

The Machine Learning (ML) approach was used in this study on a large curated dataset composed of 1,493 E. coli genome sequences and 1,178 Coding Sequences (CDS). Feature selection has been performed using eight classification algorithms, resulting in a reduction of the number of CDS to six. From this reduced dataset, the eight ML models were trained with hyper-parameter tuning and cross-validation steps.

Results and discussion

It is remarkable that only using these six genes, EHEC can be clearly identified from E. coli read assemblies obtained from in silico mixtures and complex samples such as milk metagenomes. These various combinations of discriminative biomarkers can be implemented as novel marker genes for the unambiguous EHEC characterization from different E. coli strains mixtures as well as from raw milk metagenomes.

Comparative Genomics of Pseudomonas aeruginosa Strains Isolated from Different Ecological Niches

The Pseudomonas aeruginosa genome can change to adapt to different ecological niches. We compared four genomes from a Mexican hospital and 59 genomes from GenBank from different niches, such as urine, sputum, and environmental. The ST analysis showed that high-risk STs (ST235, ST773, and ST27) were present in the genomes of the three niches from GenBank, and the STs of Mexican genomes (ST167, ST2731, and ST549) differed from the GenBank genomes. Phylogenetic analysis showed that the genomes were clustering according to their ST and not their niche. When analyzing the genomic content, we observed that environmental genomes had genes involved in adapting to the environment not found in the clinics and that their mechanisms of resistance were mutations in antibiotic resistance-related genes. In contrast, clinical genomes from GenBank had resistance genes, in mobile/mobilizable genetic elements in the chromosome, except for the Mexican genomes that carried them mostly in plasmids. This was related to the presence of CRISPR-Cas and anti-CRISPR; however, Mexican strains only had plasmids and CRISPR-Cas. bla_OXA-488 (a variant of bla_OXA50) with higher activity against carbapenems was more prevalent in sputum genomes. The virulome analysis showed that exoS was most prevalent in the genomes of urinary samples and exoU and pldA in sputum samples. This study provides evidence regarding the genetic variability among P. aeruginosa isolated from different niches.

NGSEP 4: Efficient and accurate identification of orthogroups and whole-genome alignment

Whole-genome alignment allows researchers to understand the genomic structure and variation among genomes. Approaches based on direct pairwise comparisons of DNA sequences require large computational capacities. As a consequence, pipelines combining tools for orthologous gene identification and synteny have been developed. In this manuscript, we present the latest functionalities implemented in NGSEP 4, to identify orthogroups and perform whole genome alignments. NGSEP implements functionalities for identification of clusters of homologus genes, synteny analysis and whole genome alignment. Our results showed that the NGSEP algorithm for orthogroups identification has competitive accuracy and efficiency in comparison to commonly used tools. The implementation also includes a visualization of the whole genome alignment based on synteny of the orthogroups that were identified, and a reconstruction of the pangenome based on frequencies of the orthogroups among the genomes. NGSEP 4 also includes a new graphical user interface based on the JavaFX technology. We expect that these new developments will be very useful for several studies in evolutionary biology and population genomics.

Phylogroup-specific variation shapes the clustering of antimicrobial resistance genes and defence systems across regions of genome plasticity in Pseudomonas aeruginosa

BACKGROUND

Pseudomonas aeruginosa is an opportunistic pathogen consisting of three phylogroups (hereafter named A, B, and C). Here, we assessed phylogroup-specific evolutionary dynamics across available and also new P. aeruginosa genomes.

METHODS

In this genomic analysis, we first generated new genome assemblies for 18 strains of the major P. aeruginosa clone type (mPact) panel, comprising a phylogenetically diverse collection of clinical and environmental isolates for this species. Thereafter, we combined these new genomes with 1991 publicly available P. aeruginosa genomes for a phylogenomic and comparative analysis. We specifically explored to what extent antimicrobial resistance (AMR) genes, defence systems, and virulence genes vary in their distribution across regions of genome plasticity (RGPs) and "masked" (RGP-free) genomes, and to what extent this variation differs among the phylogroups.

FINDINGS

We found that members of phylogroup B possess larger genomes, contribute a comparatively larger number of pangenome families, and show lower abundance of CRISPR-Cas systems. Furthermore, AMR and defence systems are pervasive in RGPs and integrative and conjugative/mobilizable elements (ICEs/IMEs) from phylogroups A and B, and the abundance of these cargo genes is often significantly correlated. Moreover, inter- and intra-phylogroup interactions occur at the accessory genome level, suggesting frequent recombination events. Finally, we provide here the mPact panel of diverse P. aeruginosa strains that may serve as a valuable reference for functional analyses.

INTERPRETATION

Altogether, our results highlight distinct pangenome characteristics of the P. aeruginosa phylogroups, which are possibly influenced by variation in the abundance of CRISPR-Cas systems and are shaped by the differential distribution of other defence systems and AMR genes.

FUNDING

German Science Foundation, Max-Planck Society, Leibniz ScienceCampus Evolutionary Medicine of the Lung, BMBF program Medical Infection Genomics, Kiel Life Science Postdoc Award.

Pangenome Analysis of a Salmonella Enteritidis Population Links a Major Outbreak to a Gifsy-1-Like Prophage Containing Anti-Inflammatory Gene gogB

A major outbreak of the globally significant Salmonella Enteritidis foodborne pathogen was identified within a large clinical data set by a program of routine WGS of clinical presentations of salmonellosis in New South Wales, Australia. Pangenome analysis helped to quantify and isolate prophage content within the accessory partition of the pangenome. A prophage similar to Gifsy-1 (henceforth GF-1L) was found to occur in all isolates of the outbreak core SNP cluster, and in three other isolates. Further analysis revealed that the GF-1L prophage carried the gogB virulence factor. These observations suggest that GF-1L may be an important marker of virulence for S. Enteritidis population screening and, that anti-inflammatory, gogB-mediated virulence currently associated with Salmonella Typhimurium may also be displayed by S. Enteritidis. IMPORTANCE We examined 5 years of genomic and epidemiological data for the significant global foodborne pathogen, Salmonella enterica. Although Salmonella enterica subspecies enterica serovar Enteritidis (S. Enteritidis) is the leading cause of salmonellosis in the USA and Europe, prior to 2018 it was not endemic in the southern states of Australia. However, in 2018 a large outbreak led to the endemicity of S. Enteritidis in New South Wales, Australia, and a unique opportunity to study this phenomenon. Using pangenome analysis we uncovered that this clone contained a Gifsy-1-like prophage harboring the known virulence factor gogB. The prophage reported has not previously been described in S. Enteritidis isolates.

Cross-protection and cross-feeding between Klebsiella pneumoniae and Acinetobacter baumannii promotes their co-existence

Acinetobacter baumannii and Klebsiella pneumoniae are opportunistic pathogens frequently co-isolated from polymicrobial infections. The infections where these pathogens co-exist can be more severe and recalcitrant to therapy than infections caused by either species alone, however there is a lack of knowledge on their potential synergistic interactions. In this study we characterise the genomes of A. baumannii and K. pneumoniae strains co-isolated from a single human lung infection. We examine various aspects of their interactions through transcriptomic, phenomic and phenotypic assays that form a basis for understanding their effects on antimicrobial resistance and virulence during co-infection. Using co-culturing and analyses of secreted metabolites, we discover the ability of K. pneumoniae to cross-feed A. baumannii by-products of sugar fermentation. Minimum inhibitory concentration testing of mono- and co-cultures reveals the ability for A. baumannii to cross-protect K. pneumoniae against the cephalosporin, cefotaxime. Our study demonstrates distinct syntrophic interactions occur between A. baumannii and K. pneumoniae, helping to elucidate the basis for their co-existence in polymicrobial infections.

The ESKAPE mobilome contributes to the spread of antimicrobial resistance and CRISPR-mediated conflict between mobile genetic elements

Mobile genetic elements (MGEs) mediate the shuffling of genes among organisms. They contribute to the spread of virulence and antibiotic resistance (AMR) genes in human pathogens, such as the particularly problematic group of ESKAPE pathogens. Here, we performed the first systematic analysis of MGEs, including plasmids, prophages, and integrative and conjugative/mobilizable elements (ICEs/IMEs), across all ESKAPE pathogens. We found that different MGE types are asymmetrically distributed across these pathogens, and that most horizontal gene transfer (HGT) events are restricted by phylum or genus. We show that the MGEs proteome is involved in diverse functional processes and distinguish widespread proteins within the ESKAPE context. Moreover, anti-CRISPRs and AMR genes are overrepresented in the ESKAPE mobilome. Our results also underscore species-specific trends shaping the number of MGEs, AMR, and virulence genes across pairs of conspecific ESKAPE genomes with and without CRISPR-Cas systems. Finally, we observed that CRISPR spacers found on prophages, ICEs/IMEs, and plasmids have different targeting biases: while plasmid and prophage CRISPRs almost exclusively target other plasmids and prophages, respectively, ICEs/IMEs CRISPRs preferentially target prophages. Overall, our study highlights the general importance of the ESKAPE mobilome in contributing to the spread of AMR and mediating conflict among MGEs.

Text-Mining to Identify Gene Sets Involved in Biocorrosion by Sulfate-Reducing Bacteria: A Semi-Automated Workflow

A significant amount of literature is available on biocorrosion, which makes manual extraction of crucial information such as genes and proteins a laborious task. Despite the fast growth of biology related corrosion studies, there is a limited number of gene collections relating to the corrosion process (biocorrosion). Text mining offers a potential solution by automatically extracting the essential information from unstructured text. We present a text mining workflow that extracts biocorrosion associated genes/proteins in sulfate-reducing bacteria (SRB) from literature databases (e.g., PubMed and PMC). This semi-automatic workflow is built with the Named Entity Recognition (NER) method and Convolutional Neural Network (CNN) model. With PubMed and PMCID as inputs, the workflow identified 227 genes belonging to several Desulfovibrio species. To validate their functions, Gene Ontology (GO) enrichment and biological network analysis was performed using UniprotKB and STRING-DB, respectively. The GO analysis showed that metal ion binding, sulfur binding, and electron transport were among the principal molecular functions. Furthermore, the biological network analysis generated three interlinked clusters containing genes involved in metal ion binding, cellular respiration, and electron transfer, which suggests the involvement of the extracted gene set in biocorrosion. Finally, the dataset was validated through manual curation, yielding a similar set of genes as our workflow; among these, hysB and hydA, and sat and dsrB were identified as the metal ion binding and sulfur metabolism genes, respectively. The identified genes were mapped with the pangenome of 63 SRB genomes that yielded the distribution of these genes across 63 SRB based on the amino acid sequence similarity and were further categorized as core and accessory gene families. SRB's role in biocorrosion involves the transfer of electrons from the metal surface via a hydrogen medium to the sulfate reduction pathway. Therefore, genes encoding hydrogenases and cytochromes might be participating in removing hydrogen from the metals through electron transfer. Moreover, the production of corrosive sulfide from the sulfur metabolism indirectly contributes to the localized pitting of the metals. After the corroboration of text mining results with SRB biocorrosion mechanisms, we suggest that the text mining framework could be utilized for genes/proteins extraction and significantly reduce the manual curation time.

Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe

Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, sampling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several diverse bacterial genome data sets representing major human pathogens.

Comparative Genomics of the Genus Pseudomonas Reveals Host- and Environment-Specific Evolution

Each Earth ecosystem has unique microbial communities. Pseudomonas bacteria have evolved to occupy a plethora of different ecological niches, including living hosts, such as animals and plants. Many genes necessary for the Pseudomonas-niche interaction and their encoded functions remain unknown. Here, we describe a comparative genomic study of 3,274 genomes with 19,056,667 protein-coding sequences from Pseudomonas strains isolated from diverse environments. We detected functional divergence of Pseudomonas that depends on the niche. Each group of strains from a certain environment harbored a distinctive set of metabolic pathways or functions. The horizontal transfer of genes, which mainly proceeded between closely related taxa, was dependent on the isolation source. Finally, we detected thousands of undescribed proteins and functions associated with each Pseudomonas lifestyle. This research represents an effort to reveal the mechanisms underlying the ecology, pathogenicity, and evolution of Pseudomonas, and it will enable clinical, ecological, and biotechnological advances. IMPORTANCE Microbes play important roles in the health of living beings and in the environment. The knowledge of these functions may be useful for the development of new clinical and biotechnological applications and the restoration and preservation of natural ecosystems. However, most mechanisms implicated in the interaction of microbes with the environment remain poorly understood; thus, this field of research is very important. Here, we try to understand the mechanisms that facilitate the differential adaptation of Pseudomonas-a large and ubiquitous bacterial genus-to the environment. We analyzed more than 3,000 Pseudomonas genomes and searched for genetic patterns that can be related with their coevolution with different hosts (animals, plants, or fungi) and environments. Our results revealed that thousands of genes and genetic features are associated with each niche. Our data may be useful to develop new technical and theoretical advances in the fields of ecology, health, and industry.

IPGA: A handy integrated prokaryotes genome and pan-genome analysis web service

Pan-genomics is one of the most powerful means to study genomic variation and obtain a sketch of genes within a defined clade of species. Though there are a lot of computational tools to achieve this, an integrated framework to evaluate their performance and offer the best choice to users has never been achieved. To ease the process of large-scale prokaryotic genome analysis, we introduce Integrated Prokaryotes Genome and pan-genome Analysis (IPGA), a one-stop web service to analyze, compare, and visualize pan-genome as well as individual genomes, that rids users of installing any specific tools. IPGA features a scoring system that helps users to evaluate the reliability of pan-genome profiles generated by different packages. Thus, IPGA can help users ascertain the profiling method that is most suitable for their data set for the following analysis. In addition, IPGA integrates several downstream comparative analysis and genome analysis modules to make users achieve diverse targets.

Comparative genomics and genomic diversity of Pseudomonas syringae clade 2b-a in Australia

BACKGROUND

A zucchini disease outbreak with unusual symptoms associated with Pseudomonas syringae clade 2b was identified in Bundaberg, Australia during autumn 2016. To investigate the genetic diversity of the 11 Australian isolates obtained from the outbreak, the genomes were compared to the publicly available P. syringae strains in phylogroup 2.

RESULTS

Average nucleotide identity refined the P. syringae clade 2b-a into four clusters (Cluster A, B, C1 and C2), an expansion from the previously identified A, B and C. Australian isolates were in Cluster A, C1 and C2. Genomic analyses highlighted several key factors that may contribute to the virulence of these isolates. Six orthologous groups, including three virulence factors, were associated with P. syringae phylogroup 2 cucurbit-infecting strains. A region of genome plasticity analysis identified a type VI secretion system pathway in clade 2b-a strains which could also contribute to virulence. Pathogenicity assays on isolates KL004-k1, KFR003-1 and 77-4C, as representative isolates of Cluster A, C1 and C2, respectively, determined that all three isolates can infect pumpkin, squash, watermelon and zucchini var. Eva with different levels of disease severity. Subsequently, type III effectors were investigated and four type III effectors (avrRpt2, hopZ5, hopC1 and hopH1) were associated with host range. The hopZ effector family was also predicted to be associated with disease severity.

CONCLUSIONS

This study refined the taxonomy of the P. syringae clade 2b-a, supported the association between effector profile and pathogenicity in cucurbits established in a previous study and provides new insight into important genomic features of these strains. This study also provided a detailed and comprehensive resource for future genomic and functional studies of these strains.

The complete and closed genome of the facultative generalist Candidatus Endoriftia persephone from deep-sea hydrothermal vents

The mutualistic interactions between Riftia pachyptila and its endosymbiont Candidatus Endoriftia persephone (short Endoriftia) have been extensively researched. However, the closed Endoriftia genome is still lacking. Here, by employing single-molecule real-time sequencing we present the closed chromosomal sequence of Endoriftia. In contrast to theoretical predictions of enlarged and mobile genetic element-rich genomes related to facultative endosymbionts, the closed Endoriftia genome is streamlined with fewer than expected coding sequence regions, insertion-, prophage-sequences and transposase-coding sequences. Automated and manually curated functional analyses indicated that Endoriftia is more versatile regarding sulphur metabolism than previously reported. We identified the presence of two identical rRNA operons and two long CRISPR regions in the closed genome. Additionally, pangenome analyses revealed the presence of three types of secretion systems (II, IV and VI) in the different Endoriftia populations indicating lineage-specific adaptations. The in depth mobilome characterization identified the presence of shared genomic islands in the different Endoriftia drafts and in the closed genome, suggesting that the acquisition of foreign DNA predates the geographical dispersal of the different endosymbiont populations. Finally, we found no evidence of epigenetic regulation in Endoriftia, as revealed by gene screenings and absence of methylated modified base motifs in the genome. As a matter of fact, the restriction-modification system seems to be dysfunctional in Endoriftia, pointing to a higher importance of molecular memory-based immunity against phages via spacer incorporation into CRISPR system. The Endoriftia genome is the first closed tubeworm endosymbiont to date and will be valuable for future gene oriented and evolutionary comparative studies.