CSBFinder: discovery of colinear syntenic blocks across thousands of prokaryotic genomes

Genetic structure and diversity of the rfb locus of pathogenic species of the genus Leptospira

Leptospirosis is caused by pathogenic strains of the genus Leptospira and is considered the most widespread zoonotic bacterial disease. The genus is characterized by the large number of serology variants, which challenges developing effective serotyping methods and vaccines with a broad spectrum. Because knowledge on the genetic basis of the serological diversity among leptospires is still limited, we aimed to explore the genetic structure and patterns of the rfb locus, which is involved in the biosynthesis of lipopolysaccharides, the major surface antigen that defines the serovar in leptospires. Here, we used genomic data of 722 pathogenic samples and compared the gene composition of their rfb locus by hierarchical clustering. Clustering analysis showed that the rfb locus gene composition is species-independent and strongly associated with the serological classification. The samples were grouped into four well-defined classes, which cluster together samples either belonging to the same serogroup or from different serogroups but sharing serological affinity. Our findings can assist in the development of new strategies based on molecular methods, which can lead to better tools for serological identification in this zoonosis.

Identification and Structural Modeling of the RNA Polymerase Omega Subunits in Chlamydiae and Other Obligate Intracellular Bacteria

Gene transcription in bacteria is carried out by the multisubunit RNA polymerase (RNAP), which is composed of a catalytic core enzyme and a promoter-recognizing σ factor. The core enzyme comprises two α subunits, one β subunit, one β' subunit, and one ω subunit. The ω subunit plays critical roles in the assembly of the core enzyme and other cellular functions, including the regulation of bacterial growth, the stress response, and biofilm formation. However, the identity of an ω subunit for the obligate intracellular bacterium Chlamydia has not previously been determined. Here, we report the identification of the hypothetical protein CTL0286 as the probable chlamydial ω subunit based on sequence, synteny, and AlphaFold and AlphaFold-Multimer three-dimensional-structure predictions. Our findings indicate that CTL0286 functions as the missing ω subunit of chlamydial RNAP. Our extended analysis also indicates that all obligate intracellular bacteria have ω orthologs. IMPORTANCE Chlamydiae are obligate intracellular bacteria that replicate only inside eukaryotic cells. Previously, it has not been possible to identify a candidate gene encoding the chlamydial RNA polymerase ω subunit, and it has been hypothesized that the chlamydial RNA polymerase ω subunit was lost in the evolutionary process through which Chlamydiae reduced their genome size and proteome sizes to adapt to an obligate intracellular lifestyle. Here, we report the identification of the chlamydial RNA polymerase ω subunit, based on conserved sequence, conserved synteny, AlphaFold-predicted conserved three-dimensional structure, and AlfaFold-Multimer-predicted conserved interactions. Our identification of the previously elusive chlamydial RNA polymerase ω subunit sets the stage for investigation of its roles in regulation of gene expression during chlamydial growth, development, and stress responses, and sets the stage for preparation and study of the intact chlamydial RNA polymerase and its interactions with inhibitors.

HMS-S-S: a tool for the identification of sulfur metabolism-related genes and analysis of operon structures in genome and metagenome assemblies

Sulfur compounds are used in a variety of biological processes including respiration and photosynthesis. Sulfide and sulfur compounds of intermediary oxidation state can serve as electron donors for lithotrophic growth while sulfate, thiosulfate and sulfur are used as electron acceptors in anaerobic respiration. The biochemistry underlying the manifold transformations of inorganic sulfur compounds occurring in sulfur metabolizing prokaryotes is astonishingly complex and knowledge about it has immensely increased over the last years. The advent of next-generation sequencing approaches as well as the significant increase of data availability in public databases has driven focus of environmental microbiology to probing the metabolic capacity of microbial communities by analysis of this sequence data. To facilitate these analyses, we created HMS-S-S, a comprehensive equivalogous hidden Markov model (HMM)-supported tool. Protein sequences related to sulfur compound oxidation, reduction, transport and intracellular transfer are efficiently detected and related enzymes involved in dissimilatory sulfur oxidation as opposed to sulfur compound reduction can be confidently distinguished. HMM search results are coupled to corresponding genes, which allows analysis of co-occurrence, synteny and genomic neighborhood. The HMMs were validated on an annotated test dataset and by cross-validation. We also proved its performance by exploring meta-assembled genomes isolated from samples from environments with active sulfur cycling, including members of the cable bacteria, novel Acidobacteria and assemblies from a sulfur-rich glacier, and were able to replicate and extend previous reports.

Density-based binning of gene clusters to infer function or evolutionary history using GeneGrouper

MOTIVATION

Identifying variant forms of gene clusters of interest in phylogenetically proximate and distant taxa can help to infer their evolutionary histories and functions. Conserved gene clusters may differ by only a few genes, but these small differences can in turn induce substantial phenotypes, such as by the formation of pseudogenes or insertions interrupting regulation. Particularly as microbial genomes and metagenomic assemblies become increasingly abundant, unsupervised grouping of similar, but not necessarily identical, gene clusters into consistent bins can provide a population-level understanding of their gene content variation and functional homology.

RESULTS

We developed GeneGrouper, a command-line tool that uses a density-based clustering method to group gene clusters into bins. GeneGrouper demonstrated high recall and precision in benchmarks for the detection of the 23-gene Salmonella enterica LT2 Pdu gene cluster and four-gene Pseudomonas aeruginosa PAO1 Mex gene cluster among 435 genomes spanning mixed taxa. In a subsequent application investigating the diversity and impact of gene-complete and -incomplete LT2 Pdu gene clusters in 1130 S.enterica genomes, GeneGrouper identified a novel, frequently occurring pduN pseudogene. When investigated in vivo, introduction of the pduN pseudogene negatively impacted microcompartment formation. We next demonstrated the versatility of GeneGrouper by clustering distant homologous gene clusters and variable gene clusters found in integrative and conjugative elements.

AVAILABILITY AND IMPLEMENTATION

GeneGrouper software and code are publicly available at https://pypi.org/project/GeneGrouper/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal

Due to major breakthroughs in sequencing technologies throughout the last decades, the time and cost per sequencing experiment have reduced drastically, overcoming the data generation barrier during the early genomic era. Such a shift has encouraged the scientific community to develop new computational methods that are able to compare large genomic sequences, thus enabling large-scale studies of genome evolution. The field of comparative genomics has proven itself invaluable for studying the evolutionary mechanisms and the forces driving genome evolution. In this line, a full genome comparison study between 2 species requires a quadratic number of comparisons in terms of the number of sequences (around 400 chromosome comparisons in the case of mammalian genomes); however, when studying conserved syntenies or evolutionary rearrangements, many sequence comparisons can be skipped for not all will contain significant signals. Subsequently, the scientific community has developed fast heuristics to perform multiple pairwise comparisons between large sequences to determine whether significant sets of conserved similarities exist. The data generation problem is no longer an issue, yet the limitations have shifted toward the analysis of such massive data. Therefore, we present XCout, a Web-based visual analytics application for multiple genome comparisons designed to improve the analysis of large-scale evolutionary studies using novel techniques in Web visualization. XCout enables to work on hundreds of comparisons at once, thus reducing the time of the analysis by identifying significant signals between chromosomes across multiple species. Among others, XCout introduces several techniques to aid in the analysis of large-scale genome rearrangements, particularly (1) an interactive heatmap interface to display comparisons using automatic color scales based on similarity thresholds to ease detection at first sight, (2) an overlay system to detect individual signal contributions between chromosomes, (3) a tracking tool to trace conserved blocks across different species to perform evolutionary studies, and (4) a search engine to search annotations throughout different species.

Discovery of multi-operon colinear syntenic blocks in microbial genomes

MOTIVATION

An important task in comparative genomics is to detect functional units by analyzing gene-context patterns. Colinear syntenic blocks (CSBs) are groups of genes that are consistently encoded in the same neighborhood and in the same order across a wide range of taxa. Such CSBs are likely essential for the regulation of gene expression in prokaryotes. Recent results indicate that colinearity can be conserved across multiple operons, thus motivating the discovery of multi-operon CSBs. This computational task raises scalability challenges in large datasets.

RESULTS

We propose an efficient algorithm for the discovery of cross-strand multi-operon CSBs in large genomic datasets. The proposed algorithm uses match-point arithmetic, which is scalable for large datasets of microbial genomes in terms of running time and space requirements. The algorithm is implemented and incorporated into a tool with a graphical user interface, called CSBFinder-S. We applied CSBFinder-S to data mine 1485 prokaryotic genomes and analyzed the identified cross-strand CSBs. Our results indicate that most of the syntenic blocks are exclusively colinear. Additional results indicate that transcriptional regulation by overlapping transcriptional genes is abundant in bacteria. We demonstrate the utility of CSBFinder-S to identify common function of the gene-pair PulEF in multiple contexts, including Type 2 Secretion System, Type 4 Pilus System and DNA uptake machinery.

AVAILABILITY AND IMPLEMENTATION

CSBFinder-S software and code are publicly available at https://github.com/dinasv/CSBFinder.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.