Olga O. Bochkareva

How functional protein sequences are distributed in sequence space is fundamentally important for evolutionary theory and protein design, particularly if a large diversity of protein functions are hidden in evolutionarily unexplored areas of the sequence space. However, this question is understudied in part because experimental and computational studies use extant sequences as a starting point to study sequence space. Here, we study whether extant sequences are representative of the entire functional sequence space. Across thousands of protein families from vertebrates and bacteria we calculate the dimensionality and the volume of sequence space occupied by extant homologs. We find that the observed dimensionality and volume of extant sequence space are minuscule, many orders of magnitude smaller than what we estimated using a model of protein evolution. Simulating sequence evolution we then quantify the impact of phylogeny, selection, and epistasis on restricting the evolutionary exploration of sequence space. We find that sequence evolution from a single common ancestor, or a single point of origin in sequence space, is by far the largest limiting factor that reduces the dimensionality and volume of extant sequence space. These results indicate that there are vast areas of functional sequence space that have not been explored in evolution because of the excessive restrictions on natural exploration of the protein sequence space imposed by the point of origin effect. We suggest that protein design methods that rely on extant sequences may be limited in their ability to discover truly novel functions.

Gut microorganisms inhabit a highly dynamic environment characterized by fluctuating nutrients, phage predation, and host immune pressure. To cope with such unpredictability, bacteria often rely on phase variation – the rapid generation of phenotypic heterogeneity via reversible DNA inversions. While the presence of multiple inversions, so called shufflons, in polysaccharide utilization loci was reported in several bacterial gut species, their role in gene expression regulation is poorly understood. Here we report and characterize an intra genus conserved phase variation system in Bacteroidaceae, a dominant group of the mammalian gut microbiota. This system consists of a cassette of silent susCD transmembrane transporter genes and an invertase that drives the rapid positioning of individual inactive genes into a single active expression site. Consequently, individual bacteria within a colony express different transporters, while collectively maintaining expression of the full gene repertoire. The composition of the transporter cassette is dynamic and evolves through horizontal gene transfer across the genus while preserving a conserved architecture. This shufflon system generates persistent genetic and phenotypic diversity, enabling Bacteroidaceae populations to adapt rapidly to the fluctuating conditions in the mammalian gut.

Active regulation of gene expression, orchestrated by complex interactions of activators and repressors at promoters, controls the fate of organisms. In contrast, basal expression at uninduced promoters is considered to be a dynamically inert mode of nonfunctional “promoter leakiness,” merely a byproduct of transcriptional regulation. Here, we investigate the basal expression mode of the mar operon, the main regulator of intrinsic multiple antibiotic resistance in Escherichia coli , and link its dynamic properties to the noncanonical, yet highly conserved start codon of marR across Enterobacteriaceae . Real-time, single-cell measurements across tens of generations reveal that basal expression consists of rare stochastic gene expression pulses, which maximize variability in wildtype and, surprisingly, transiently accelerate cellular elongation rates. Competition experiments show that basal expression confers fitness advantages to wildtype across several transitions between exponential and stationary growth by shortening lag times. The dynamically rich basal expression of the mar operon has likely been evolutionarily maintained for its role in growth homeostasis of Enterobacteria within the gut environment, thereby allowing other ancillary gene regulatory roles to evolve, e.g., control of costly-to-induce multidrug efflux pumps. Understanding the complex selection forces governing genetic systems involved in intrinsic multidrug resistance is crucial for effective public health measures.

Introduction: Genus Wolbachia comprises endosymbionts infecting many arthropods and nematodes; it is a model for studying symbiosis as its members feature numerous, diverse mutualistic and parasitic adaptations to different hosts. In contrast to nematode-infecting Wolbachia, genomes of arthropod-infecting strains contain a high fraction of repetitive elements creating possibilities for multiple recombination events and causing genome rearrangements. The mechanisms and role of these features are still not fully understood. Results: Transposons cover up to 18% of an arthropod-infecting Wolbachia genome and drive numerous genome rearrangements including inversions and segmental amplifications. ANK (ankyrin-repeat domain family) genes are also often found at the breakpoints of rearrangements, while less than 7% of them were found within locally collinear blocks (LCBs). We observed a strong correlation between the number of ANK genes and the genome size as well as significant overrepresentation of transposons adjacent to these genes. We also revealed numerous cases of integration of transposases to the ANK genes affecting the sequences and putative products of the latter. Our results uncover the role of mobile elements in the amplification and diversification of ANK genes. Conclusions: Evolution of arthropod-infecting Wolbachia was accompanied by diverse genome rearrangements driving the evolution of ANK genes important for bacteria-host interactions. This study demonstrates the effectiveness of our LCB-based approach to the Wolbachia genomics and provides a framework for understanding the impact of genome rearrangements on their rapid host adaptation.

Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) approaches have emerged as powerful tools for analyzing large-scale bacterial AMR data. However, ML methods often ignore evolutionary relationships among bacterial strains, which can greatly impact performance of the ML methods, especially if resistance-associated features are attempted to be detected. Genomewide association studies (GWAS) methods like linear mixed models accounts for the evolutionary relationships in bacteria, but they uncover only highly significant variants which have already been reported in literature. In this work, we introduce a novel phylogeny-related parallelism score (PRPS), which measures whether a certain feature is correlated with the population structure of a set of samples. We demonstrate that PRPS can be used, in combination with SVM- and random forest-based models, to reduce the number of features in the analysis, while simultaneously increasing models’ performance. We applied our pipeline to publicly available AMR data from PATRIC database for Mycobacterium tuberculosis against six common antibiotics. Using our pipeline, we re-discovered known resistance-associated mutations as well as new candidate mutations which can be related to resistance and not previously reported in the literature.

Until recently, Shigella and enteroinvasive Escherichia coli were thought to be primate-restricted pathogens. The base of their pathogenicity is the type 3 secretion system (T3SS) encoded by the pINV virulence plasmid, which facilitates host cell invasion and subsequent proliferation. A large family of T3SS effectors, E3 ubiquitin-ligases encoded by the ipaH genes, have a key role in the Shigella pathogenicity through the modulation of cellular ubiquitination that degrades host proteins. However, recent genomic studies identified ipaH genes in the genomes of Escherichia marmotae, a potential marmot pathogen, and an E. coli extracted from fecal samples of bovine calves, suggesting that non-human hosts may also be infected by these strains, potentially pathogenic to humans. We performed a comparative genomic study of the functional repertoires in the ipaH gene family in Shigella and enteroinvasive Escherichia from human and predicted non-human hosts. We found that fewer than half of Shigella genomes had a complete set of ipaH genes, with frequent gene losses and duplications that were not consistent with the species tree and nomenclature. Non-human host IpaH proteins had a diverse set of substrate-binding domains and, in contrast to the Shigella proteins, two variants of the NEL C-terminal domain. Inconsistencies between strains phylogeny and composition of effectors indicate horizontal gene transfer between E. coli adapted to different hosts. These results provide a framework for understanding of ipaH-mediated host-pathogens interactions and suggest a need for a genomic study of fecal samples from diseased animals.

Until recently, Shigella and enteroinvasive Escherichia coli were thought to be primate-restricted pathogens. The base of their pathogenicity is the type 3 secretion system (T3SS) encoded by the pINV virulence plasmid, which facilitates host cell invasion and subsequent proliferation. A large family of T3SS effectors, E3 ubiquitin-ligases encoded by the ipaH genes, have a key role in the Shigella pathogenicity through the modulation of cellular ubiquitination that degrades host proteins. However, recent genomic studies identified ipaH genes in the genomes of Escherichia marmotae, a potential marmot pathogen, and an E. coli extracted from fecal samples of bovine calves, suggesting that non-human hosts may also be infected by these strains, potentially pathogenic to humans. We performed a comparative genomic study of the functional repertoires in the ipaH gene family in Shigella and enteroinvasive Escherichia from human and predicted non-human hosts. We found that fewer than half of Shigella genomes had a complete set of ipaH genes, with frequent gene losses and duplications that were not consistent with the species tree and nomenclature. Non-human host IpaH proteins had a diverse set of substrate-binding domains and, in contrast to the Shigella proteins, two different types of the NEL C-terminal domain. Only the ipaH9.8 gene was found in Escherichia derived from both human and non-human hosts. These results provide a framework for understanding of ipaH -mediated host-pathogens interactions and suggest a need for a genomic study of fecal samples from diseased animals.

High plasticity of bacterial genomes is provided by numerous mechanisms including horizontal gene transfer and recombination via numerous flanking repeats. Genome rearrangements such as inversions, deletions, insertions and duplications may independently occur in different strains, providing parallel adaptation or phenotypic diversity. Specifically, such rearrangements might be responsible for virulence, antibiotic resistance and antigenic variation. However, identification of such events requires laborious manual inspection and verification of phyletic pattern consistency. Here, we define the term ‘parallel rearrangements’ as events that occur independently in phylogenetically distant bacterial strains and present a formalization of the problem of parallel rearrangements calling. We implement an algorithmic solution for the identification of parallel rearrangements in bacterial populations as a tool PaReBrick. The tool takes a collection of strains represented as a sequence of oriented synteny blocks and a phylogenetic tree as input data. It identifies rearrangements, tests them for consistency with a tree, and sorts the events by their parallelism score. The tool provides diagrams of the neighbors for each block of interest, allowing the detection of horizontally transferred blocks or their extra copies and the inversions in which copied blocks are involved. We demonstrated PaReBrick’s efficiency and accuracy and showed its potential to detect genome rearrangements responsible for pathogenicity and adaptation in bacterial genomes. PaReBrick is written in Python and is available on GitHub: https://github.com/ctlab/parallel-rearrangements. Supplementary data are available at Bioinformatics online.

Shigellaare pathogens originating within theEscherichialineage but frequently classified as a separate genus.Shigellagenomes contain numerous insertion sequences (ISs) that lead to pseudogenisation of affected genes and an increase of non-homologous recombination. Here, we study 414 genomes ofE. coliandShigellastrains to assess the contribution of genomic rearrangements toShigellaevolution. We found thatShigellaexperienced exceptionally high rates of intragenomic rearrangements and had a decreased rate of homologous recombination compared to pathogenic and non-pathogenicE. coli. The high rearrangement rate resulted in independent disruption of syntenic regions and parallel rearrangements in differentShigellalineages. Specifically, we identified two types of chromosomally encoded E3 ubiquitin-protein ligases acquired independently by allShigellastrains that also showed a high level of sequence conservation in the promoter and further in the 5′-intergenic region. In the only available enteroinvasiveE. coli(EIEC) strain, which is a pathogenicE. coliwith a phenotype intermediate betweenShigellaand non-pathogenicE. coli, we found a rate of genome rearrangements comparable to those in otherE. coliand no functional copies of the twoShigella-specific E3 ubiquitin ligases. These data indicate that the accumulation of ISs influenced many aspects of genome evolution and played an important role in the evolution of intracellular pathogens. Our research demonstrates the power of comparative genomics-based on synteny block composition and an important role of non-coding regions in the evolution of genomic islands.

A mesophilic methanogenic culture, designated JL01, was isolated from Holocene permafrost in the Russian Arctic. After long-term extensive cultivation at 15 °C, it turned out to be a tied binary culture of archaeal (JL01) and bacterial (Sphaerochaeta associata GLS2) strains. Strain JL01 was a strict anaerobe and grew on methanol, acetate, and methylamines as energy and carbon sources. Cells were irregular coccoid, non-motile, non-spore-forming, and Gram-stain-positive. Optimum conditions for growth were 24–28 °C, pH 6.8–7.3, and 0.075–0.1 M NaCl. Phylogenetic tree reconstructions based on 16S rRNA and concatenated alignment of broadly conserved protein-coding genes revealed 16S rRNA’s close relation to Methanosarcina mazei S-6^T (similarity 99.5%). The comparison of whole genomic sequences (ANI) of the isolate and the type strain of M. mazei was 98.5%, which is higher than the values recommended for new species. Thus, strain JL01 (=VKM B-2370 = JCM 31898) represents the first M. mazei isolated from permanently subzero Arctic sediments. The long-term co-cultivation of JL01 with S. associata GLS2^T showed the methane production without any additional carbon and energy sources. Genome analysis of S. associata GLS2^T revealed putative genes involved in methanochondroitin catabolism.