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Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI) screens can provide insights into the biological role(s) of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems. [ABSTRACT FROM AUTHOR]

Group I chaperonins are a highly conserved family of essential proteins that self-assemble into molecular nanoboxes that mediate the folding of cytoplasmic proteins in bacteria and organelles. GroEL, the chaperonin of Escherichia coli, is the archetype of the family. Protein folding-independent functions have been described for numerous chaperonins, including HtpB, the chaperonin of the bacterial pathogen Legionella pneumophila. Several protein folding-independent functions attributed to HtpB are not shared by GroEL, suggesting that differences in the amino acid (aa) sequence between these two proteins could correlate with functional differences. GroEL and HtpB differ in 137 scattered aa positions. Using the Evolutionary Trace (ET) bioinformatics method, site-directed mutagenesis, and a functional reporter test based upon a yeast-two-hybrid interaction with the eukaryotic protein ECM29, it was determined that out of those 137 aa, ten (M68, M212, S236, K298, N507 and the cluster AEHKD in positions 471-475) were involved in the interaction of HtpB with ECM29. GroEL was completely unable to interact with ECM29, but when GroEL was modified at those 10 aa positions, to display the HtpB aa, it acquired a weak ability to interact with ECM29. This constitutes proof of concept that the unique functional abilities of HtpB can be mapped to specific aa positions. [ABSTRACT FROM AUTHOR]

Phylogenetic profiles (PPs) are one of the most promising methods for predicting functional relationships by genomic context. The idea behind PPs is that if the products of two genes have a functional interdependence, the genes should both be either present or absent across genomes. One of the main problems with PPs is that evolutionarily close organisms tend to share a higher number of genes resulting in the overscoring of PP-relatedness. The proper measure of the overscoring effect of evolutionary redundancy requires examples of both functionally related genes (positive gold standards) and functionally unrelated genes (negative gold standards). Since experimentally verified functional interactions are only available for a few model organisms, there is a need for an alternative to gold standards. The presence of operons (polycistronic transcription units formed of functionally related genes) in prokaryotic genomes offers such an alternative. Genes in operons are located next to each other in the same DNA strand, and thus their presence should result in a higher proportion of predicted functional interactions among adjacent genes in the same strand than among adjacent genes in opposite strands. Under the preceding principle, we present a confidence value (CV) designed for evaluating predictions of functional interactions obtained using PPs. We first show that the CV corresponds to a positive predictive value calculated using experimentally known operons and further validate operon predictions based on this CV in other organisms using available microarray data. Then, we use a fixed CV of 0.90 as a reference to compare PP predictions obtained using different nonredundant genome datasets filtered at varying thresholds of genomic similarity. Our results demonstrate that nonredundant genome datasets increase the number of high-quality predictions by an average of 20%. Confidence values as those presented here should help compare other strategies and scoring systems to use phylogenetic profiles and other genomic context methods for predicting functional interactions. Proteins 2008. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI) screens can provide insights into the biological role(s) of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems. [ABSTRACT FROM AUTHOR]

Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. In this work, we propose a hybrid model to identify transcription factors (TFs) among prokaryotic and eukaryotic protein sequences, named Deep Regulation (DeepReg) model. Two architectures were used in the DL model: a convolutional neural network (CNN), and a bidirectional long-short-term memory (BiLSTM). DeepReg reached a precision of 0.99, a recall of 0.97, and an F1-score of 0.98. The quality of our predictions, the bias-variance trade-off approach, and the characterization of new TF predictions were evaluated and compared against those produced by DeepTFactor, as well as against experimental data from three model organisms. Predictions based on our DLM tended to exhibit less variance and bias than those from DeepTFactor, thus increasing reliability and decreasing overfitting., (© 2024. The Author(s).)

The analysis and comparison of gene neighborhoods is a powerful approach for exploring microbial genome structure, function, and evolution. Although numerous tools exist for genome visualization and comparison, genome exploration across large genomic databases or user-generated datasets remains a challenge. Here, we introduce AnnoView, a web server designed for interactive exploration of gene neighborhoods across the bacterial and archaeal tree of life. Our server offers users the ability to identify, compare, and visualize gene neighborhoods of interest from 30 238 bacterial genomes and 1672 archaeal genomes, through integration with the comprehensive Genome Taxonomy Database and AnnoTree databases. Identified gene neighborhoods can be visualized using pre-computed functional annotations from different sources such as KEGG, Pfam and TIGRFAM, or clustered based on similarity. Alternatively, users can upload and explore their own custom genomic datasets in GBK, GFF or CSV format, or use AnnoView as a genome browser for relatively small genomes (e.g. viruses and plasmids). Ultimately, we anticipate that AnnoView will catalyze biological discovery by enabling user-friendly search, comparison, and visualization of genomic data. AnnoView is available at http://annoview.uwaterloo.ca., (© The Author(s) 2024. Published by Oxford University Press.)

Cytokinin is a major phytohormone that has been used in agriculture as a plant-growth stimulating compound since its initial discovery in the 1960s. Isopentenyl transferase (IPT) is a rate-limiting enzyme for cytokinin biosynthesis, which is produced by plants as well as bacteria including both plant pathogenic species and plant growth-promoting bacteria (PGPB). It has been hypothesized that there may be differences in IPT function between plant pathogens and PGPB. However, a comprehensive comparison of IPT genes between plant pathogenic and PGPB species has not been performed. Here, we performed a global comparison of IPT genes across bacteria, analyzing their DNA sequences, codon usage, phyletic distribution, promoter structure and genomic context. We found that adenylate type IPT genes are highly specific to plant-associated bacteria and subdivide into two major clades: clade A, largely composed of proteobacterial plant pathogens; and clade B, largely composed of actinomycete PGPB species. Besides these phylogenetic differences, we identified several genomic features that suggest differences in IPT regulation between pathogens and PGPB. Pathogen-associated IPT s tended to occur in predicted virulence loci, whereas PGPB-associated IPT s tended to co-occur with other genes involved in cytokinin metabolism and degradation. Pathogen-associated IPTs also showed elevated gene copy numbers, significant deviation in codon usage patterns, and extended promoters, suggesting differences in regulation and activity levels. Our results are consistent with the hypothesis that differences in IPT regulation and activity exist between plant pathogens and PGPB, which determine their effect on plant host phenotypes through the control of cytokinin levels., Competing Interests: The authors declare no conflict of interest., (© 2023 The Author(s).)

Background: A substantial fraction of genes identified within bacterial genomes encode proteins of unknown function. Identifying which of these proteins represent potential virulence factors, and mapping their key virulence determinants, is a challenging but important goal., Results: To facilitate virulence factor discovery, we performed a comprehensive analysis of 17,929 protein domain families within the Pfam database, and scored them based on their overrepresentation in pathogenic versus non-pathogenic species, taxonomic distribution, relative abundance in metagenomic datasets, and other factors., Conclusions: We identify pathogen-associated domain families, candidate virulence factors in the human gut, and eukaryotic-like mimicry domains with likely roles in virulence. Furthermore, we provide an interactive database called PathFams to allow users to explore pathogen-associated domains as well as identify pathogen-associated domains and domain architectures in user-uploaded sequences of interest. PathFams is freely available at https://pathfams.uwaterloo.ca ., (© 2021. The Author(s).)

Bacteria have developed different intra- and inter-specific communication mechanisms that involve the production, release, and detection of signaling molecules, because these molecules serve as the autoinducers involved in "quorum sensing" systems. Other communication mechanisms employ volatile signaling molecules that regulate different bacterial processes. The Arthrobacter agilis strain UMCV2 is a plant growth promoting actinobacterium, which induces plant growth and inhibits phytopathogenic fungi by emitting the dimethylhexadecylamine (DMHDA). However, little is known about the effect of this volatile compound on A. agilis UMCV2 itself, as well as on other bacteria. By exposing A. agilis UMCV2 and bacteria of the genus Bacillus and Pseudomonas to different concentrations of DMHDA, this study showed the dose-dependent effects of DMHDA on A. agilis UMCV2 growth, cellular viability, swarming motility, and expression of marker genes of the flagellar apparatus of bacteria. DMHDA was found to also modulate swarming motility of Bacillus sp. ZAP018 and P. fluorescens UM270, but not that of P. aeruginosa PA01. These data indicate that DMHDA is involved in both intra- and inter-specific bacterial interaction.

Our laboratory has developed bioinformatic strategies for identifying distant phylogenetic relationships and characterizing families and superfamilies of transport proteins. Results using these tools suggest that the Anoctamin Superfamily of cation and anion channels, as well as lipid scramblases, includes three functionally characterized families: the Anoctamin (ANO), Transmembrane Channel (TMC) and Ca2+-permeable Stress-gated Cation Channel (CSC) families; as well as four families of functionally uncharacterized proteins, which we refer to as the Anoctamin-like (ANO-L), Transmembrane Channel-like (TMC-L), and CSC-like (CSC-L1 and CSC-L2) families. We have constructed protein clusters and trees showing the relative relationships among the seven families. Topological analyses suggest that the members of these families have essentially the same topologies. Comparative examination of these homologous families provides insight into possible mechanisms of action, indicates the currently recognized organismal distributions of these proteins, and suggests drug design potential for the disease-related channel proteins.

The membrane attack complex/perforin (MACPF) superfamily consists of a diverse group of proteins involved in bacterial pathogenesis and sporulation as well as eukaryotic immunity, embryonic development, neural migration and fruiting body formation. The present work shows that the evolutionary relationships between the members of the superfamily, previously suggested by comparison of their tertiary structures, can also be supported by analyses of their primary structures. The superfamily includes the MACPF family (TC 1.C.39), the cholesterol-dependent cytolysin (CDC) family (TC 1.C.12.1 and 1.C.12.2) and the pleurotolysin pore-forming (pleurotolysin B) family (TC 1.C.97.1), as revealed by expansion of each family by comparison against a large protein database, and by the comparisons of their hidden Markov models. Clustering analyses demonstrated grouping of the CDC homologues separately from the 12 MACPF subfamilies, which also grouped separately from the pleurotolysin B family. Members of the MACPF superfamily revealed a remarkably diverse range of proteins spanning eukaryotic, bacterial, and archaeal taxonomic domains, with notable variations in protein domain architectures. Our strategy should also be helpful in putting together other highly divergent protein families., (© 2017 S. Karger AG, Basel.)

Predicting functional associations using the Gene Neighbor Method depends on the simple idea that if genes are conserved next to each other in evolutionarily distant prokaryotes they might belong to a polycistronic transcription unit. The procedure presented in this chapter starts with the organization of the genes within genomes into pairs of adjacent genes. Then, the pairs of adjacent genes in a genome of interest are mapped to their corresponding orthologs in other, informative, genomes. The final step is to verify if the mapped orthologs are also pairs of adjacent genes in the informative genomes.

The Transporter Classification Database (TCDB; http://www.tcdb.org) is a freely accessible reference database for transport protein research, which provides structural, functional, mechanistic, evolutionary and disease/medical information about transporters from organisms of all types. TCDB is the only transport protein classification database adopted by the International Union of Biochemistry and Molecular Biology (IUBMB). It consists of more than 10,000 non-redundant transport systems with more than 11 000 reference citations, classified into over 1000 transporter families. Transporters in TCDB can be single or multi-component systems, categorized in a functional/phylogenetic hierarchical system of classes, subclasses, families, subfamilies and transport systems. TCDB also includes updated software designed to analyze the distinctive features of transport proteins, extending its usefulness. Here we present a comprehensive update of the database contents and features and summarize recent discoveries recorded in TCDB., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

We have designed a freely accessible program, PhyST, which allows the automated characterization of any family of homologous proteins within the Transporter Classification Database. The program performs an NCBI-PSI-BLAST search and reports (1) the average protein sequence length with standard deviations, (2) the average predicted number of transmembrane segments, (3) the total number of homologues retrieved, (4) a quantitative list of all source phyla, and (5) potential fusion proteins of sizes considerably exceeding the average size of the proteins retrieved. We have applied this program to 58 families of holins, and the results are presented. The results show that holins are very rarely fused to other protein domains, suggesting that holins form transmembrane pores as homooligomers without the participation of other proteins or protein domains., (© 2016 S. Karger AG, Basel.)

Pseudomonas syringae pv. tomato DC3000 is a model pathogen of tomato and Arabidopsis that uses a hypersensitive response and pathogenicity (Hrp) type III secretion system (T3SS) to deliver virulence effector proteins into host cells. Expression of the Hrp system and many effector genes is activated by the HrpL alternative sigma factor. Here, an open reading frame-specific whole-genome microarray was constructed for DC3000 and used to comprehensively identify genes that are differentially expressed in wild-type and deltahrpL strains. Among the genes whose differential regulation was statistically significant, 119 were upregulated and 76 were downregulated in the wild-type compared with the deltahrpL strain. Hierarchical clustering revealed a subset of eight genes that were upregulated particularly rapidly. Gibbs sampling of regions upstream of HrpL-activated operons revealed the Hrp promoter as the only identifiable regulatory motif and supported an iterative refinement involving real-time polymerase chain reaction testing of additional HrpL-activated genes and refinements in a hidden Markov model that can be used to predict Hrp promoters in P. syringae strains. This iterative bioinformatic-experimental approach to a comprehensive analysis of the HrpL regulon revealed a mix of genes controlled by HrpL, including those encoding most type III effectors, twin-arginine transport (TAT) substrates, other regulatory proteins, and proteins involved in the synthesis or metabolism of phytohormones, phytotoxins, and myo-inositol. This analysis provides an extensively verified, robust method for predicting Hrp promoters in P. syringae genomes, and it supports subsequent identification of effectors and other factors that likely are important to the host-specific virulence of P. syringae.

We have previously demonstrated that genes within experimentally characterized operons of Escherichia coli are conserved together in other genomes more frequently than genes at the borders of transcription units. Here we expand the analyses and show that, as the phylogenetic distance of the genomes compared increases, the genes remaining together must belong to genes associated into operons in other prokaryotes regardless of the operon organization of the corresponding orthologous gene pair of E. coli. At the same time, we show that the observed tendencies of genes within operons to keep very short inter-genic distances in E. coli, is the same in any other prokaryote whose genome is currently available. We also show the relationship between our analyses of conservation and the inference of functional relationships from genomic context.