Evolutionary couplings of amino acid residues reveal structure and function of bacterial signaling proteins

The genomic era along with major advances in high‐throughput sequencing technology has led to a rapid expansion of the genomic and consequently the protein sequence space. Bacterial extracytoplasmic function sigma factors have emerged as an important group of signaling proteins in bacteria involved in many regulatory decisions, most notably the adaptation to cell envelope stress. Their wide prevalence and amplification among bacterial genomes has led to sub‐group classification and the realization of diverse signaling mechanisms. Mathematical frameworks have been developed to utilize extensive protein sequence alignments to extract co‐evolutionary signals of interaction. This has proven useful in a number of different biological fields, including de novo structure prediction, protein–protein partner identification and the elucidation of alternative protein conformations for signal proteins, to name a few. The mathematical tools, commonly referred to under the name ‘Direct Coupling Analysis’ have now been applied to deduce molecular mechanisms of activation for sub‐groups of extracytoplasmic sigma factors adding to previous successes on bacterial two‐component signaling proteins. The amplification of signal transduction protein genes in bacterial genomes made them the first to be amenable to this approach but the sequences are available now to aid the molecular microbiologist, no matter their protein pathway of interest.     

SuperSegger: robust image segmentation,analysis and lineage tracking of bacterial cells

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame‐to‐frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB‐based image processing package well‐suited to quantitative analysis of high‐throughput live‐cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine‐learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame‐to‐frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell‐cycle dynamics in bacteria as well as cell‐contact mediated phenomena. This package has a range of built‐in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution.     

Resources and transgenesis techniques for functional genomics in Xenopus

Recent developments in genomic resources and high‐throughput transgenesis techniques have allowed Xenopus to ‘metamorphose’ from a classic model for embryology to a leading‐edge experimental system for functional genomics. This process has incorporated the fast‐breeding diploid frog, Xenopus tropicalis, as a new model‐system for vertebrate genomics and genetics. Sequencing of the X. tropicalis genome is nearly complete, and its comparison with mammalian sequences offers a reliable guide for the genome‐wide prediction of cis‐regulatory elements. Unique cDNA sets have been generated for both X. tropicalis and X. laevis, which have facilitated non‐redundant, systematic gene expression screening and comprehensive gene expression analysis. A variety of transgenesis techniques are available for both X. laevis and X. tropicalis, and the appropriate procedure may be chosen depending on the purpose for which it is required. Effective use of these resources and techniques will help to reveal the overall picture of the complex wiring of gene regulatory networks that control vertebrate development.     

Anomalies of the anaerobic tricarboxylic acid cycle in Shewanella oneidensis revealed by Tn‐seq

The availability of increasingly inexpensive sequencing combined with an ever‐expanding molecular biology toolbox has transported classical bacterial genetics into the 21st century. Whole genome genetic fitness analysis using transposon mutagenesis combined with next‐generation high‐throughput sequencing (Tn‐seq) promises to revolutionize systems level analysis of microbial metabolism. Tn‐seq measures the frequency of actual members of a heterogeneous mutant pool undergoing purifying selection to determine the contribution of every non‐essential gene in the genome to the fitness of an organism under a given condition. Here we use Tn‐seq to assess gene function in the Gram negative γ‐proteobacterium Shewanella oneidensis strain MR‐1. In addition to being a model environmental organism, there is considerable interest in using S. oneidensis as a platform organism for bioremediation and biotechnology, necessitating a complete understanding of the metabolic pathways that may be utilized. Our analysis reveals unique aspects of S. oneidensis metabolism overlooked by over 30 years of classical genetic and systems level analysis. We report the utilization of an alternative citrate synthase and describe a dynamic branching of the S. oneidensis anaerobic tricarboxylic acid cycle, unreported in any other organism, which may be a widespread strategy for microbes adept at dissipating reducing equivalents via anaerobic respiration.     

Small RNA interactome of pathogenic E. coli revealed through crosslinking of RNase E

RNA sequencing studies have identified hundreds of non‐coding RNAs in bacteria, including regulatory small RNA (sRNA). However, our understanding of sRNA function has lagged behind their identification due to a lack of tools for the high‐throughput analysis of RNA–RNA interactions in bacteria. Here we demonstrate that in vivo sRNA–mRNA duplexes can be recovered using UV‐crosslinking, ligation and sequencing of hybrids (CLASH). Many sRNAs recruit the endoribonuclease, RNase E, to facilitate processing of mRNAs. We were able to recover base‐paired sRNA–mRNA duplexes in association with RNase E, allowing proximity‐dependent ligation and sequencing of cognate sRNA–mRNA pairs as chimeric reads. We verified that this approach captures bona fide sRNA–mRNA interactions. Clustering analyses identified novel sRNA seed regions and sets of potentially co‐regulated target mRNAs. We identified multiple mRNA targets for the pathotype‐specific sRNA Esr41, which was shown to regulate colicin sensitivity and iron transport in E. coli. Numerous sRNA interactions were also identified with non‐coding RNAs, including sRNAs and tRNAs, demonstrating the high complexity of the sRNA interactome.     

Rickettsial evolution in the light of comparative genomics

Rickettsia are best known as strictly intracellular vector‐borne bacteria that cause mild to severe diseases in humans and other animals. Recent advances in molecular tools and biological experiments have unveiled a wide diversity of Rickettsia spp. that include species with a broad host range and some species that act as endosymbiotic associates. Molecular phylogenies of Rickettsia spp. contain some ambiguities, such as the position of R. canadensis and relationships within the spotted fever group. In the modern era of genomics, with an ever‐increasing number of sequenced genomes, there is enhanced interest in the use of whole‐genome sequences to understand pathogenesis and assess evolutionary relationships among rickettsial species. Rickettsia have small genomes (1.1–1.5 Mb) as a result of reductive evolution. These genomes contain split genes, gene remnants and pseudogenes that, owing to the colinearity of some rickettsial genomes, may represent different steps of the genome degradation process. Genomics reveal extreme genome reduction and massive gene loss in highly vertebrate‐pathogenic Rickettsia compared to less virulent or endosymbiotic species. Information gleaned from rickettsial genomics challenges traditional concepts of pathogenesis that focused primarily on the acquisition of virulence factors. Another intriguing phenomenon about the reduced rickettsial genomes concerns the large fraction of non‐coding DNA and possible functionality of these “non‐coding” sequences, because of the high conservation of these regions. Despite genome streamlining, Rickettsia spp. contain gene families, selfish DNA, repeat palindromic elements and genes encoding eukaryotic‐like motifs. These features participate in sequence and functional diversity and may play a crucial role in adaptation to the host cell and pathogenesis. Genome analyses have identified a large fraction of mobile genetic elements, including plasmids, suggesting the possibility of lateral gene transfer in these intracellular bacteria. Phylogenetic analyses have identified several candidates for horizontal gene acquisition among Rickettsia spp. including tra, pat2, and genes encoding for the type IV secretion system and ATP/ADP translocase that may have been acquired from bacteria living in amoebae. Gene loss, gene duplication, DNA repeats and lateral gene transfer all have shaped rickettsial genome evolution. A comprehensive analysis of the entire genome, including genes and non‐coding DNA, will help to unlock the mysteries of rickettsial evolution and pathogenesis.