Expression divergence between Escherichia coli and Salmonella enterica serovar Typhimurium reflects their lifestyles

RidA proteins contribute to fitness of S. enterica and E. coli by reducing 2AA stress and moderating flux to isoleucine biosynthesis

Defining the physiological role of a gene product relies on interpreting phenotypes caused by the lack, or alteration, of the respective gene product. Mutations in critical genes often lead to easily recognized phenotypes that can include changes in cellular growth, metabolism, structure etc. However, mutations in many important genes may fail to generate an obvious defect unless additional perturbations are caused by medium or genetic background. The latter scenario is exemplified by RidA proteins. In vitro RidA proteins deaminate numerous imine/enamines, including those generated by serine/threonine dehydratase IlvA (EC:4.3.1.19) from serine or threonine - 2-aminoacrylate (2AA) and 2-aminocrotonate (2AC), respectively. Despite this demonstrable biochemical activity, a lack of RidA has little to no effect on growth of E. coli or S. enterica without the application of additional metabolic perturbation. A cellular role of RidA is to prevent accumulation of 2AA which, if allowed to persist, can irreversibly damage pyridoxal 5'-phosphate (PLP)-dependent enzymes, causing global metabolic stress. Because the phenotypes caused by a lack of RidA are dependent on the unique structure of each metabolic network, the link between RidA function and 2AA stress is difficult to demonstrate in some organisms. The current study used coculture experiments to exacerbate differences in growth caused by the lack of RidA in S. enterica and E. coli. Results described here solidify the established role of RidA in removing 2AA, while also presenting evidence for a role of RidA in enhancing flux towards isoleucine biosynthesis in E. coli. Overall, these data emphasize that metabolic networks can generate distinct responses to perturbation, even when the individual components are conserved.

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

Absence of proline-peptide transporter YjiY in Salmonella Typhimurium leads to secretion of factors which inhibits intra-species biofilm formation

Salmonella is a genus of widely spread Gram negative, facultative anaerobic bacteria, which is known to cause ¼th of diarrheal morbidity and mortality globally. It causes typhoid fever and gastroenteritis by gaining access to the host gut through contaminated food and water. Salmonella utilizes its biofilm lifestyle to strongly resist antibiotics and persist in the host. Although biofilm removal or dispersal has been studied widely, the inhibition of the initiation of Salmonella Typhimurium (STM WT) biofilm remains elusive. This study demonstrates the anti-biofilm property of the cell-free supernatant obtained from a carbon-starvation induced proline peptide transporter mutant (STM ΔyjiY) strain. The STM ΔyjiY culture supernatant primarily inhibits biofilm initiation by regulating biofilm-associated transcriptional network that is reversed upon complementation (STM ΔyjiY:yjiY). We demonstrate that abundance of FlgM correlates with the absence of flagella in the STM ΔyjiY supernatant treated WT cells. NusG works synergistically with the global transcriptional regulator H-NS. Relatively low abundances of flavoredoxin, glutaredoxin, and thiol peroxidase might lead to accumulation of ROS within the biofilm, and subsequent toxicity in STM ΔyjiY supernatant. This work further suggests that targeting these oxidative stress relieving proteins might be a good choice to reduce Salmonella biofilm.

Modulators of a robust and efficient metabolism: Perspective and insights from the Rid superfamily of proteins

Metabolism is an integrated network of biochemical pathways that assemble to generate the robust, responsive physiologies of microorganisms. Despite decades of fundamental studies on metabolic processes and pathways, our understanding of the nuance and complexity of metabolism remains incomplete. The ability to predict and model metabolic network structure, and its influence on cellular fitness, is complicated by the persistence of genes of unknown function, even in the best-studied model organisms. This review describes the definition and continuing study of the Rid superfamily of proteins. These studies are presented with a perspective that illustrates how metabolic complexity can complicate the assignment of function to uncharacterized genes. The Rid superfamily of proteins has been divided into eight subfamilies, including the well-studied RidA subfamily. Aside from the RidA proteins, which are present in all domains of life and prevent metabolic stress, most members of the Rid superfamily have no demonstrated physiological role. Recent progress on functional assignment supports the hypothesis that, overall, proteins in the Rid superfamily modulate metabolic processes to ensure optimal organismal fitness.

Naegleria genus pangenome reveals new structural and functional insights into the versatility of these free-living amoebae

Introduction

Free-living amoebae of the Naegleria genus belong to the major protist clade Heterolobosea and are ubiquitously distributed in soil and freshwater habitats. Of the 47 Naegleria species described, N. fowleri is the only one being pathogenic to humans, causing a rare but fulminant primary amoebic meningoencephalitis. Some Naegleria genome sequences are publicly available, but the genetic basis for Naegleria diversity and ability to thrive in diverse environments (including human brain) remains unclear.

Methods

Herein, we constructed a high-quality Naegleria genus pangenome to obtain a comprehensive catalog of genes encoded by these amoebae. For this, we first sequenced, assembled, and annotated six new Naegleria genomes.

Results and Discussion

Genome architecture analyses revealed that Naegleria may use genome plasticity features such as ploidy/aneuploidy to modulate their behavior in different environments. When comparing 14 near-to-complete genome sequences, our results estimated the theoretical Naegleria pangenome as a closed genome, with 13,943 genes, including 3,563 core and 10,380 accessory genes. The functional annotations revealed that a large fraction of Naegleria genes show significant sequence similarity with those already described in other kingdoms, namely Animalia and Plantae. Comparative analyses highlighted a remarkable genomic heterogeneity, even for closely related strains and demonstrate that Naegleria harbors extensive genome variability, reflected in different metabolic repertoires. If Naegleria core genome was enriched in conserved genes essential for metabolic, regulatory and survival processes, the accessory genome revealed the presence of genes involved in stress response, macromolecule modifications, cell signaling and immune response. Commonly reported N. fowleri virulence-associated genes were present in both core and accessory genomes, suggesting that N. fowleri's ability to infect human brain could be related to its unique species-specific genes (mostly of unknown function) and/or to differential gene expression. The construction of Naegleria first pangenome allowed us to move away from a single reference genome (that does not necessarily represent each species as a whole) and to identify essential and dispensable genes in Naegleria evolution, diversity and biology, paving the way for further genomic and post-genomic studies.

A proposed framework for the identification of indicator genes for monitoring antibiotic resistance in wastewater: Insights from metagenomic sequencing

Antibiotic resistance is one of the greatest threats to global human and animal health of our time. Municipal wastewater has been identified as a hotspot of antibiotic resistance contamination to water bodies. However, there are numerous potential antibiotic resistant pathogens and their associated antibiotic resistance genes (ARGs), making it difficult to implement routine monitoring that addresses the breadth of the problem. The objective of this study was to identify candidate indicator ARGs for monitoring antibiotic resistance in wastewater and receiving water bodies. We developed a framework to identify indicator ARGs that incorporated clinical relevance, abundance in wastewater, geographic ubiquity, environmental relevance, ARG mobility, associations with mobile genetic elements, and the availability of quantitative analytical methods. To identify indicator ARGs, published metagenomic sequencing data from 191 wastewater samples originating from 64 countries across the world were obtained from online public repositories. Through ARG annotation and network analysis, this framework revealed 56 candidate indicator ARGs distributed across four modules of strongly correlated ARGs, with one ARG from each module (oqxA, ermB, sul1, and mexE) proposed as a minimally redundant monitoring target. The results of this study provide the basis for antibiotic resistance surveillance and monitoring framework in wastewater and contaminated waterways.

Curcumin Stimulates the Overexpression of Virulence Factors in Salmonella enterica Serovar Typhimurium: In Vitro and Animal Model Studies

Salmonella spp. is one of the most common food poisoning pathogens and the main cause of diarrheal diseases in humans in developing countries. The increased Salmonella resistance to antimicrobials has led to the search for new alternatives, including natural compounds such as curcumin, which has already demonstrated a bactericidal effect; however, in Gram-negatives, there is much controversy about this effect, as it is highly variable. In this study, we aimed to verify the antibacterial activity of curcumin against the Salmonella enterica serovar Typhimurium growth rate, virulence, and pathogenicity. The strain was exposed to 110, 220 or 330 µg/mL curcumin, and by complementary methods (spectrophotometric, pour plate and MTT assays), we determined its antibacterial activity. To elucidate whether curcumin regulates the expression of virulence genes, Salmonella invA, fliC and siiE genes were investigated by quantitative real-time reverse transcription (qRT-PCR). Furthermore, to explore the effect of curcumin on the pathogenesis process in vivo, a Caenorhabditis elegans infection model was employed. No antibacterial activity was observed, even at higher concentrations of curcumin. All concentrations of curcumin caused overgrowth (35−69%) and increased the pathogenicity of the bacterial strain through the overexpression of virulence factors. The latter coincided with a significant reduction in both the lifespan and survival time of C. elegans when fed with curcumin-treated bacteria. Our data provide relevant information that may support the selective antibacterial effects of curcumin to reconsider the indiscriminate use of this phytochemical, especially in outbreaks of pathogenic Gram-negative bacteria.

Ultrasound-controllable engineered bacteria for cancer immunotherapy

Rapid advances in synthetic biology are driving the development of genetically engineered microbes as therapeutic agents for a multitude of human diseases, including cancer. The immunosuppressive microenvironment of solid tumors, in particular, creates a favorable niche for systemically administered bacteria to engraft and release therapeutic payloads. However, such payloads can be harmful if released outside the tumor in healthy tissues where the bacteria also engraft in smaller numbers. To address this limitation, we engineer therapeutic bacteria to be controlled by focused ultrasound, a form of energy that can be applied noninvasively to specific anatomical sites such as solid tumors. This control is provided by a temperature-actuated genetic state switch that produces lasting therapeutic output in response to briefly applied focused ultrasound hyperthermia. Using a combination of rational design and high-throughput screening we optimize the switching circuits of engineered cells and connect their activity to the release of immune checkpoint inhibitors. In a clinically relevant cancer model, ultrasound-activated therapeutic microbes successfully turn on in situ and induce a marked suppression of tumor growth. This technology provides a critical tool for the spatiotemporal targeting of potent bacterial therapeutics in a variety of biological and clinical scenarios.

Environmental flexibility does not explain metabolic robustness

Cells show remarkable resilience against genetic and environmental perturbations. However, its evolutionary origin remains obscure. In order to leverage methods of systems biology for examining cellular robustness, a computationally accessible way of quantification is needed. Here, we present an unbiased metric of structural robustness in genome-scale metabolic models based on concepts prevalent in reliability engineering and fault analysis. The probability of failure (PoF) is defined as the (weighted) portion of all possible combinations of loss-of-function mutations that disable network functionality. It can be exactly determined if all essential reactions, synthetic lethal pairs of reactions, synthetic lethal triplets of reactions etc. are known. In theory, these minimal cut sets (MCSs) can be calculated for any network, but for large models the problem remains computationally intractable. Herein, we demonstrate that even at the genome scale only the lowest-cardinality MCSs are required to efficiently approximate the PoF with reasonable accuracy. Building on an improved theoretical understanding, we analysed the robustness of 489 E. coli, Shigella, Salmonella, and fungal genome-scale metabolic models (GSMMs). In contrast to the popular "congruence theory", which explains the origin of genetic robustness as a byproduct of selection for environmental flexibility, we found no correlation between network robustness and the diversity of growth-supporting environments. On the contrary, our analysis indicates that amino acid synthesis rather than carbon metabolism dominates metabolic robustness.

Prediction of Salmonella serovars isolated from clinical and food matrices in Lebanon and genomic-based investigation focusing on Enteritidis serovar

Salmonella enterica subsp. enterica serovars are considered major causes of food poisoning and we performed this study because Salmonella is a burden in Lebanon. The present study investigated the ability of genomic information to predict serovar using a collection of Salmonella isolates from infected humans (n = 24) and contaminated food (n = 63) in Lebanon. Further, the phylogenomic relationships of the serovar the predominated in Lebanon (i.e., S. Enteritidis; n = 25) were investigated in comparison with isolates from other countries (n = 130) based on coregenome single nucleotide polymorphisms (SNPs). Genetic elements, specifically Salmonella pathogenicity islands (SPIs), plasmid replicons, and antibiotic-resistance genes were screened in S. Enteritidis genomes (n = 155). Our results revealed that the Salmonella serovars identification by seroagglutination from the samples isolated in Lebanon (n = 87) was highly correlated with the genomic-based prediction of serovars (80.4-85.0% with SeqSero1 and 93.1-94.2% with SeqSero2). The Salmonella serovars isolated from human and food samples in Lebanon were mainly Enteritidis (28.7%) and Infantis (26%). To a rare extent, other serovars included Amager, Anatum, Bredeney, Chincol, Heidelberg, Hofit, Kentucky, Montevideo, Muenster, Newport, Schwarzengrund, Senftenberg and Typhimurium. In comparison with other countries, S. Enteritidis samples isolated in Lebanon (56 ± 27 intra-group pairwise SNP differences) presented a strong phylogenomic relativeness at the coregenome level with samples, as for example with samples isolated from Syria (65 ± 31 inter-group pairwise SNP differences). Most of the studied S. Enteritidis genomes encoded 10 SPIs involved in survival in immune cells (i.e. SPIs 1, 2, 3, 4, 5, 12, 13, 14, 16 and 17). The plasmid replicons IncFIB (S)_1 and IncFII (S)_1 encoding elements involved in virulence were identified in the majority of the S. Enteritidis genomes (94% and 96%, respectively), the majority exhibiting aminoglycosides (gene aac(6')-Iaa_1). The IncI_1_Alpha replicon responsible for ampicillin-resistance was only detected in 2 of 25 S. Enteritidis Lebanese strains. Genomic-based risk assessment of Salmonella serovars in Lebanon showed that food imported from Syria might be an origin of the S. Enteritidis human cases in Lebanon. The detection of several SPIs involved in the survival, plasmid replicons involved in virulence, and aminoglycoside-resistance genes, emphasizes that S. Enteritidis is of paramount importance for public health in Lebanon and other countries.

ICGEC: a comparative method for measuring epigenetic conservation of genes via the integrated signal from multiple histone modifications between cell types

Background

Histone post-translational modifications play crucial roles in epigenetic regulation of gene expression and are known to be associated with the phenotypic differences of different cell types. Therefore, it is of fundamental importance to dissect the genes and pathways involved in such a phenotypic variation at the level of epigenetics. However, the existing comparative approaches are largely based on the differences, especially the absolute difference in the levels of individual histone modifications of genes under contrasting conditions. Thus, a method for measuring the overall change in the epigenetic circumstance of each gene underpinned by multiple types of histone modifications between cell types is lacking.

Results

To address this challenge, we developed ICGEC, a new method for estimating the degree of epigenetic conservation of genes between two cell lines. Different from existing comparative methods, ICGEC provides a reliable score for measuring the relative change in the epigenetic context of corresponding gene between two conditions and simultaneously produces a score for each histone mark. The application of ICGEC to the human embryonic stem cell line H1 and four H1-derived cell lines with available epigenomic data for the same 16 types of histone modifications indicated high robustness and reliability of ICGEC. Furthermore, the analysis of the epigenetically dynamic and conserved genes which were defined based on the ICGEC output results demonstrated that ICGEC can deepen our understanding of the biological processes of cell differentiation to overcome the limitations of traditional expression analysis. Specifically, the ICGEC-derived differentiation-direction-specific genes were shown to have putative functions that are well-matched with cell identity. Additionally, H3K79me1 and H3K27ac were found to be the main histone marks accounting for whether an epigenetically dynamic gene was differentially expressed between two cell lines.

Conclusions

The use of ICGEC creates a convenient and robust way to measure the overall epigenetic conservation of individual genes and marks between two conditions. Thus, it provides a basis for exploring the epigenotype-phenotype relationship. ICGEC can be deemed a state-of-the-art method tailored for comparative epigenomic analysis of changes in cell dynamics.

Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale

BACKGROUND

Salmonella enterica subsp. enterica is a public health issue related to food safety, and its adaptation to animal sources remains poorly described at the pangenome scale. Firstly, serovars presenting potential mono- and multi-animal sources were selected from a curated and synthetized subset of Enterobase. The corresponding sequencing reads were downloaded from the European Nucleotide Archive (ENA) providing a balanced dataset of 440 Salmonella genomes in terms of serovars and sources (i). Secondly, the coregenome variants and accessory genes were detected (ii). Thirdly, single nucleotide polymorphisms and small insertions/deletions from the coregenome, as well as the accessory genes were associated to animal sources based on a microbial Genome Wide Association Study (GWAS) integrating an advanced correction of the population structure (iii). Lastly, a Gene Ontology Enrichment Analysis (GOEA) was applied to emphasize metabolic pathways mainly impacted by the pangenomic mutations associated to animal sources (iv).

RESULTS

Based on a genome dataset including Salmonella serovars from mono- and multi-animal sources (i), 19,130 accessory genes and 178,351 coregenome variants were identified (ii). Among these pangenomic mutations, 52 genomic signatures (iii) and 9 over-enriched metabolic signatures (iv) were associated to avian, bovine, swine and fish sources by GWAS and GOEA, respectively.

CONCLUSIONS

Our results suggest that the genetic and metabolic determinants of Salmonella adaptation to animal sources may have been driven by the natural feeding environment of the animal, distinct livestock diets modified by human, environmental stimuli, physiological properties of the animal itself, and work habits for health protection of livestock.

Bacteriophage-mediated identification of bacteria using photoacoustic flow cytometry

Infection with resistant bacteria has become an ever increasing problem in modern medical practice. Currently, broad spectrum antibiotics are prescribed until bacteria can be identified through blood cultures, a process that can take two to three days and is unable to provide quantitative information. To detect and quantify bacteria rapidly in blood samples, we designed a method using labeled bacteriophage in conjunction with photoacoustic flow cytometry (PAFC). PAFC is the generation of ultrasonic waves created by the absorption of laser light in particles under flow. Bacteriophage is a virus that infects bacteria and possesses the ability to discriminate bacterial surface antigens, allowing the bacteriophage to bind only to their target bacteria. Bacteria can be tagged with dyed phage and processed through a photoacoustic flow cytometer where they are detected by the acoustic response. We demonstrate that E. coli; can be detected and discriminated from Salmonella; using this method. Our goal is to develop a method to determine bacterial content in blood samples. We hope to develop this technology into future clinical use and decrease the time required to identify bacterial species from 3 to 4 days to less than 1 hour.

Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph

In this paper, we present a subgroup discovery method to find subgraphs in a graph that are associated with a given set of vertices. The association between a subgraph pattern and a set of vertices is defined by its significant enrichment based on a Bonferroni-corrected hypergeometric probability value. This interestingness measure requires a dedicated pruning procedure to limit the number of subgraph matches that must be calculated. The presented mining algorithm to find associated subgraph patterns in large graphs is therefore designed to efficiently traverse the search space. We demonstrate the operation of this method by applying it on three biological graph data sets and show that we can find associated subgraphs for a biologically relevant set of vertices and that the found subgraphs themselves are biologically interesting.

Vitamin B12 as a carrier of peptide nucleic acid (PNA) into bacterial cells

Short modified oligonucleotides targeted at bacterial DNA or RNA could serve as antibacterial agents provided that they are efficiently taken up by bacterial cells. However, the uptake of such oligonucleotides is hindered by the bacterial cell wall. To overcome this problem, oligomers have been attached to cell-penetrating peptides, but the efficiency of delivery remains poor. Thus, we have investigated the ability of vitamin B12 to transport peptide nucleic acid (PNA) oligomers into cells of Escherichia coli and Salmonella Typhimurium. Vitamin B12 was covalently linked to a PNA oligomer targeted at the mRNA of a reporter gene expressing Red Fluorescent Protein. Cu-catalyzed 1,3-dipolar cycloaddition was employed for the synthesis of PNA-vitamin B12 conjugates; namely the vitamin B12 azide was reacted with PNA possessing the terminal alkyne group. Different types of linkers and spacers between vitamin B12 and PNA were tested, including a disulfide bond. We found that vitamin B12 transports antisense PNA into E. coli cells more efficiently than the most widely used cell-penetrating peptide (KFF)3K. We also determined that the structure of the linker impacts the antisense effect. The results of this study provide the foundation for developing vitamin B12 as a carrier of PNA oligonucleotides into bacterial cells.

The Response to 2-Aminoacrylate Differs in Escherichia coli and Salmonella enterica, despite Shared Metabolic Components

The metabolic network of an organism includes the sum total of the biochemical reactions present. In microbes, this network has an impeccable ability to sense and respond to perturbations caused by internal or external stimuli. The metabolic potential (i.e., network structure) of an organism is often drawn from the genome sequence, based on the presence of enzymes deemed to indicate specific pathways. Escherichia coli and Salmonella enterica are members of the Enterobacteriaceae family of Gram-negative bacteria that share the majority of their metabolic components and regulatory machinery as the "core genome." In S. enterica, the ability of the enamine intermediate 2-aminoacrylate (2AA) to inactivate a number of pyridoxal 5'-phosphate (PLP)-dependent enzymes has been established in vivo In this study, 2AA metabolism and the consequences of its accumulation were investigated in E. coli The data showed that despite the conservation of all relevant enzymes, S. enterica and E. coli differed in both the generation and detrimental consequences of 2AA. In total, these findings suggest that the structure of the metabolic network surrounding the generation and response to endogenous 2AA stress differs between S. enterica and E. coliIMPORTANCE This work compared the metabolic networks surrounding the endogenous stressor 2-aminoacrylate in two closely related members of the Enterobacteriaceae The data showed that despite the conservation of all relevant enzymes in this metabolic node, the two closely related organisms diverged in their metabolic network structures. This work highlights how a set of conserved components can generate distinct network architectures and how this can impact the physiology of an organism. This work defines a model to expand our understanding of the 2-aminoacrylate stress response and the differences in metabolic structures and cellular milieus between S. enterica and E. coli.

Whole-genome comparative analysis of virulence genes unveils similarities and differences between endophytes and other symbiotic bacteria

Plant pathogens and endophytes co-exist and often interact with the host plant and within its microbial community. The outcome of these interactions may lead to healthy plants through beneficial interactions, or to disease through the inducible production of molecules known as virulence factors. Unravelling the role of virulence in endophytes may crucially improve our understanding of host-associated microbial communities and their correlation with host health. Virulence is the outcome of a complex network of interactions, and drawing the line between pathogens and endophytes has proven to be conflictive, as strain-level differences in niche overlapping, ecological interactions, state of the host's immune system and environmental factors are seldom taken into account. Defining genomic differences between endophytes and plant pathogens is decisive for understanding the boundaries between these two groups. Here we describe the major differences at the genomic level between seven grapevine endophytic test bacteria, and 12 reference strains. We describe the virulence factors detected in the genomes of the test group, as compared to endophytic and non-endophytic references, to better understand the distribution of these traits in endophytic genomes. To do this, we adopted a comparative whole-genome approach, encompassing BLAST-based searches through the GUI-based tools Mauve and BRIG as well as calculating the core and accessory genomes of three genera of enterobacteria. We outline divergences in metabolic pathways of these endophytes and reference strains, with the aid of the online platform RAST. We present a summary of the major differences that help in the drawing of the boundaries between harmless and harmful bacteria, in the spirit of contributing to a microbiological definition of endophyte.

Comparative analysis of gene expression: uncovering expression conservation and divergence between Salmonella enterica serovar Typhimurium strains LT2 and 14028S

Different strains of the same organism can share a large amount of their genetic material, the so called core pangenome. Nevertheless, these species can display different lifestyles and it is still not well known to what extent the core pangenome plays a role in the divergence of lifestyles between the two organisms. Here, we present a procedure for uncovering the conservation and divergence of gene expression by using large expression compendia. We will use data from two Salmonella enterica serovar Typhimurium strains as an example here, strain LT2 and strain 14028S, to assess if there are orthologous gene pairs with different expression domains related in both strains.

Genome-scale co-expression network comparison across Escherichia coli and Salmonella enterica serovar Typhimurium reveals significant conservation at the regulon level of local regulators despite their dissimilar lifestyles

Availability of genome-wide gene expression datasets provides the opportunity to study gene expression across different organisms under a plethora of experimental conditions. In our previous work, we developed an algorithm called COMODO (COnserved MODules across Organisms) that identifies conserved expression modules between two species. In the present study, we expanded COMODO to detect the co-expression conservation across three organisms by adapting the statistics behind it. We applied COMODO to study expression conservation/divergence between Escherichia coli, Salmonella enterica, and Bacillus subtilis. We observed that some parts of the regulatory interaction networks were conserved between E. coli and S. enterica especially in the regulon of local regulators. However, such conservation was not observed between the regulatory interaction networks of B. subtilis and the two other species. We found co-expression conservation on a number of genes involved in quorum sensing, but almost no conservation for genes involved in pathogenicity across E. coli and S. enterica which could partially explain their different lifestyles. We concluded that despite their different lifestyles, no significant rewiring have occurred at the level of local regulons involved for instance, and notable conservation can be detected in signaling pathways and stress sensing in the phylogenetically close species S. enterica and E. coli. Moreover, conservation of local regulons seems to depend on the evolutionary time of divergence across species disappearing at larger distances as shown by the comparison with B. subtilis. Global regulons follow a different trend and show major rewiring even at the limited evolutionary distance that separates E. coli and S. enterica.

The core proteome and pan proteome of Salmonella Paratyphi A epidemic strains

Comparative proteomics of the multiple strains within the same species can reveal the genetic variation and relationships among strains without the need to assess the genomic data. Similar to comparative genomics, core proteome and pan proteome can also be obtained within multiple strains under the same culture conditions. In this study we present the core proteome and pan proteome of four epidemic Salmonella Paratyphi A strains cultured under laboratory culture conditions. The proteomic information was obtained using a Two-dimensional gel electrophoresis (2-DE) technique. The expression profiles of these strains were conservative, similar to the monomorphic genome of S. Paratyphi A. Few strain-specific proteins were found in these strains. Interestingly, non-core proteins were found in similar categories as core proteins. However, significant fluctuations in the abundance of some core proteins were also observed, suggesting that there is elaborate regulation of core proteins in the different strains even when they are cultured in the same environment. Therefore, core proteome and pan proteome analysis of the multiple strains can demonstrate the core pathways of metabolism of the species under specific culture conditions, and further the specific responses and adaptations of the strains to the growth environment.

Structural properties of prokaryotic promoter regions correlate with functional features

The structural properties of the DNA molecule are known to play a critical role in transcription. In this paper, the structural profiles of promoter regions were studied within the context of their diversity and their function for eleven prokaryotic species; Escherichia coli, Klebsiella pneumoniae, Salmonella Typhimurium, Pseudomonas auroginosa, Geobacter sulfurreducens Helicobacter pylori, Chlamydophila pneumoniae, Synechocystis sp., Synechoccocus elongates, Bacillus anthracis, and the archaea Sulfolobus solfataricus. The main anchor point for these promoter regions were transcription start sites identified through high-throughput experiments or collected within large curated databases. Prokaryotic promoter regions were found to be less stable and less flexible than the genomic mean across all studied species. However, direct comparison between species revealed differences in their structural profiles that can not solely be explained by the difference in genomic GC content. In addition, comparison with functional data revealed that there are patterns in the promoter structural profiles that can be linked to specific functional loci, such as sigma factor regulation or transcription factor binding. Interestingly, a novel structural element clearly visible near the transcription start site was found in genes associated with essential cellular functions and growth in several species. Our analyses reveals the great diversity in promoter structural profiles both between and within prokaryotic species. We observed relationships between structural diversity and functional features that are interesting prospects for further research to yet uncharacterized functional loci defined by DNA structural properties.

COLOMBOS v2.0: an ever expanding collection of bacterial expression compendia

The COLOMBOS database (http://www.colombos.net) features comprehensive organism-specific cross-platform gene expression compendia of several bacterial model organisms and is supported by a fully interactive web portal and an extensive web API. COLOMBOS was originally published in PLoS One, and COLOMBOS v2.0 includes both an update of the expression data, by expanding the previously available compendia and by adding compendia for several new species, and an update of the surrounding functionality, with improved search and visualization options and novel tools for programmatic access to the database. The scope of the database has also been extended to incorporate RNA-seq data in our compendia by a dedicated analysis pipeline. We demonstrate the validity and robustness of this approach by comparing the same RNA samples measured in parallel using both microarrays and RNA-seq. As far as we know, COLOMBOS currently hosts the largest homogenized gene expression compendia available for seven bacterial model organisms.