OrtholugeDB: a bacterial and archaeal orthology resource for improved comparative genomic analysis

Transfer learning predicts species-specific drug interactions in emerging pathogens

Machine learning (ML) algorithms are necessary to efficiently identify potent drug combinations within a large candidate space to combat drug resistance. However, existing ML approaches cannot be applied to emerging and under-studied pathogens with limited training data. To address this, we developed a transfer learning and crowdsourcing framework (TACTIC) to train ML models on data from multiple bacteria. TACTIC was built using 2,965 drug interactions from 12 bacterial strains and outperformed traditional ML models in predicting drug interaction outcomes for species that lack training data. Top TACTIC model features revealed genetic and metabolic factors that influence cross-species and species-specific drug interaction outcomes. Upon analyzing ~600,000 predicted drug interactions across 9 metabolic environments and 18 bacterial strains, we identified a small set of drug interactions that are selectively synergistic against Gram-negative (e.g., A. baumannii) and non-tuberculous mycobacteria (NTM) pathogens. We experimentally validated synergistic drug combinations containing clarithromycin, ampicillin, and mecillinam against M. abscessus, an emerging pathogen with growing levels of antibiotic resistance. Lastly, we leveraged TACTIC to propose selectively synergistic drug combinations to treat bacterial eye infections (endophthalmitis).

Identifying magnetosome-associated genes in the extended CtrA regulon in Magnetospirillum magneticum AMB-1 using a combinational approach

Magnetotactic bacteria (MTB) are worth studying because of magnetosome biomineralization. Magnetosome biogenesis in MTB is controlled by multiple genes known as magnetosome-associated genes. Recent advances in bioinformatics provide a unique opportunity for studying functions of magnetosome-associated genes and networks that they are involved in. Furthermore, various types of bioinformatics analyses can also help identify genes associated with magnetosome biogenesis. To predict novel magnetosome-associated genes in the extended CtrA regulon, we analyzed expression data of Magnetospirillum magneticum AMB-1 in the GSE35625 dataset in NCBI GEO. We identified 10 potential magnetosome-associated genes using a combinational approach of differential expression analysis, Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analysis, protein-protein interaction network analysis and weighted gene co-expression network analysis. Meanwhile, we also discovered and compared two co-expression modules that most known magnetosome-associated genes belong to. Our comparison indicated the importance of energy on regulating co-expression module structures for magnetosome biogenesis. At the last stage of our research, we predicted at least four real magnetosome-associated genes out of 10 potential genes, based on a comparison of evolutionary trees between known and potential magnetosome-associated genes. Because of the discovery of common subtrees that the stressed species are enriched in, we proposed a hypothesis that multiple types of environmental stress can trigger magnetosome evolution in different waters, and therefore its evolution can recur at different times in various locations on earth. Overall, our research provides useful information for identifying new MTB species and understanding magnetosome biogenesis.

Time-Resolved Proteomics of Germinating Spores of Bacillus cereus

Bacillus cereus is a spore-forming human pathogen that is a burden to the food chain. Dormant spores are highly resistant to harsh environmental conditions, but lose resistance after germination. In this study, we investigate the B. cereus spore proteome upon spore germination and outgrowth so as to obtain new insights into the molecular mechanisms involved. We used mass spectrometry combined with co-expression network analysis and obtained a unique global proteome view of the germination and outgrowth processes of B. cereus spores by monitoring 2211 protein changeovers. We are the first to examine germination and outgrowth models of B. cereus spores experimentally by studying the dynamics of germinant receptors, other proteins involved in spore germination and resistance, and coat and exosporium proteins. Furthermore, through the co-expression analysis of 1175 proteins identified with high quality data, germination proteome data were clustered into eight modules (termed black, blue, brown, green, red, turquoise, grey, and yellow), whose associated functions and expression profiles were investigated. Germination related proteins were clustered into blue and brown modules, the abundances of which decreased after finishing germination. In the brown and blue we identified 124 proteins that could be vital during germination. These proteins will be very interesting to study in future genetic studies regarding their function in spore revival in B. cereus.

ProPan: a comprehensive database for profiling prokaryotic pan-genome dynamics

Compared with conventional comparative genomics, the recent studies in pan-genomics have provided further insights into species genomic dynamics, taxonomy and identification, pathogenicity and environmental adaptation. To better understand genome characteristics of species of interest and to fully excavate key metabolic and resistant genes and their conservations and variations, here we present ProPan (https://ngdc.cncb.ac.cn/propan), a public database covering 23 archaeal species and 1,481 bacterial species (in a total of 51,882 strains) for comprehensively profiling prokaryotic pan-genome dynamics. By analyzing and integrating these massive datasets, ProPan offers three major aspects for the pan-genome dynamics of the species of interest: 1) the evaluations of various species' characteristics and composition in pan-genome dynamics; 2) the visualization of map association, the functional annotation and presence/absence variation for all contained species' gene clusters; 3) the typical characteristics of the environmental adaptation, including resistance genes prediction of 126 substances (biocide, antimicrobial drug and metal) and evaluation of 31 metabolic cycle processes. Besides, ProPan develops a very user-friendly interface, flexible retrieval and multi-level real-time statistical visualization. Taken together, ProPan will serve as a weighty resource for the studies of prokaryotic pan-genome dynamics, taxonomy and identification as well as environmental adaptation.

Mycobacterium abscessus Mutants with a Compromised Functional Link between the Type VII ESX-3 System and an Iron Uptake Mechanism Reliant on an Unusual Mycobactin Siderophore

The opportunistic pathogen Mycobacterium abscessus subsp. abscessus (Mab) has become an emerging public health threat due to the increasing number of Mab-associated chronic pulmonary disease cases. Treatment requires multiple drug courses and is often combined with surgical resection. Cure rates are only ~50% due to treatment failure and comorbidities. Deeper understanding of the biology of Mab is required to illuminate potential avenues for the development of better therapeutics against Mab infections. The ESX-3 type VII protein secretion system of Mab has an important role in host inflammatory and pathological responses during infection. In this work, we demonstrate a functional link between ESX-3 and an iron uptake system based on an unusual mycobactin-type siderophore (designated MBT Ab) and exploit this link to implement a large screen for transposon mutants with an impaired ESX-3. Most mutants we identified carry insertions in genes encoding predicted ESX-3 secretion machinery components or potential ESX-3 substrates. The mutants overproduce MBT Ab, a trait consistent with an iron uptake defect. Our characterization of MBT Ab revealed structural features reminiscent of nocardial mycobactin-like compounds with cytotoxicity. This finding raises the possibility that MBT Ab may play roles in pathogenesis unlinked to iron homeostasis. The mutants generated herein will facilitate research to better understand the role of ESX-3 and its interplay with the siderophore system.

Identification and Characterization of an RRM-Containing, RNA Binding Protein in Acinetobacter baumannii

Acinetobacter baumannii is a Gram-negative pathogen, known to acquire resistance to antibiotics used in the clinic. The RNA-binding proteome of this bacterium is poorly characterized, in particular for what concerns the proteins containing RNA Recognition Motif (RRM). Here, we browsed the A. baumannii proteome for homologous proteins to the human HuR(ELAVL1), an RNA binding protein containing three RRMs. We identified a unique locus that we called AB-Elavl, coding for a protein with a single RRM with an average of 34% identity to the first HuR RRM. We also widen the research to the genomes of all the bacteria, finding 227 entries in 12 bacterial phyla. Notably we observed a partial evolutionary divergence between the RNP1 and RNP2 conserved regions present in the prokaryotes in comparison to the metazoan consensus sequence. We checked the expression at the transcript and protein level, cloned the gene and expressed the recombinant protein. The X-ray and NMR structural characterization of the recombinant AB-Elavl revealed that the protein maintained the typical β₁α₁β₂β₃α₂β₄ and three-dimensional organization of eukaryotic RRMs. The biochemical analyses showed that, although the RNP1 and RNP2 show differences, it can bind to AU-rich regions like the human HuR, but with less specificity and lower affinity. Therefore, we identified an RRM-containing RNA-binding protein actually expressed in A. baumannii.

Leveraging big data bioinformatics approaches to extract knowledge from Staphylococcus aureus public omics data

Staphylococcus aureus is a notorious pathogen posing challenges in the medical industry due to drug resistance and biofilm formation. The horizon of knowledge on S. aureus pathogenesis has expanded with the advancement of data-driven bioinformatics techniques. Mining information from sequenced genomes and their expression data is an economic approach that alleviates wastage of resources and redundancy in experiments. The current review covers how big data bioinformatics has been used in the analysis of S. aureus from publicly available -omics data to uncover mechanisms of infection and inhibition. Particularly, advances in the past two decades in biomarker discovery, host responses, phenotype identification, consolidation of information, and drug development are discussed highlighting the challenges and shortcomings. Overall, the review summarizes the diverse aspects of scrupulous re-analysis of S. aureus proteomic and transcriptomic expression datasets retrieved from public repositories in terms of the efforts taken, benefits offered, and follow-up actions. The detailed review thus serves as a reference and aid for (i) Computational biologists by briefing the approaches utilized for bacterial omics re-analysis concerning S. aureus and (ii) Experimental biologists by elucidating the potential of bioinformatics in biological research to generate reliable postulates in a prompt and economical manner.

Forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens

Experimental evolution with microbes is often highly repeatable under identical conditions, suggesting the possibility to predict short-term evolution. However, it is not clear to what degree evolutionary forecasts can be extended to related species in non-identical environments, which would allow testing of general predictive models and fundamental biological assumptions. To develop an extended model system for evolutionary forecasting, we used previous data and models of the genotype-to-phenotype map from the wrinkly spreader system in Pseudomonas fluorescens SBW25 to make predictions of evolutionary outcomes on different biological levels for Pseudomonas protegens Pf-5. In addition to sequence divergence (78% amino acid and 81% nucleotide identity) for the genes targeted by mutations, these species also differ in the inability of Pf-5 to make cellulose, which is the main structural basis for the adaptive phenotype in SBW25. The experimental conditions were changed compared to the SBW25 system to test if forecasts were extendable to a non-identical environment. Forty-three mutants with increased ability to colonize the air-liquid interface were isolated, and the majority had reduced motility and was partly dependent on the Pel exopolysaccharide as a structural component. Most (38/43) mutations are expected to disrupt negative regulation of the same three diguanylate cyclases as in SBW25, with a smaller number of mutations in promoter regions, including an uncharacterized polysaccharide synthase operon. A mathematical model developed for SBW25 predicted the order of the three main pathways and the genes targeted by mutations, but differences in fitness between mutants and mutational biases also appear to influence outcomes. Mutated regions in proteins could be predicted in most cases (16/22), but parallelism at the nucleotide level was low and mutational hot spot sites were not conserved. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations and provides testable predictions for evolutionary outcomes in other Pseudomonas species.

Halobacterium salinarum and Haloferax volcanii Comparative Transcriptomics Reveals Conserved Transcriptional Processing Sites

Post-transcriptional processing of messenger RNA is an important regulatory strategy that allows relatively fast responses to changes in environmental conditions. In halophile systems biology, the protein perspective of this problem (i.e., ribonucleases which implement the cleavages) is generally more studied than the RNA perspective (i.e., processing sites). In the present in silico work, we mapped genome-wide transcriptional processing sites (TPS) in two halophilic model organisms, Halobacterium salinarum NRC-1 and Haloferax volcanii DS2. TPS were established by reanalysis of publicly available differential RNA-seq (dRNA-seq) data, searching for non-primary (monophosphorylated RNAs) enrichment. We found 2093 TPS in 43% of H. salinarum genes and 3515 TPS in 49% of H. volcanii chromosomal genes. Of the 244 conserved TPS sites found, the majority were located around start and stop codons of orthologous genes. Specific genes are highlighted when discussing antisense, ribosome and insertion sequence associated TPS. Examples include the cell division gene ftsZ2, whose differential processing signal along growth was detected and correlated with post-transcriptional regulation, and biogenesis of sense overlapping transcripts associated with IS200/IS605. We hereby present the comparative, transcriptomics-based processing site maps with a companion browsing interface.

Evolutionary Genomics of Niche-Specific Adaptation to the Cystic Fibrosis Lung in Pseudomonas aeruginosa

The comparative genomics of the transition of the opportunistic pathogen Pseudomonas aeruginosa from a free-living environmental strain to one that causes chronic infection in the airways of cystic fibrosis (CF) patients remain poorly studied. Chronic infections are thought to originate from colonization by a single strain sampled from a diverse, globally distributed population, followed by adaptive evolution to the novel, stressful conditions of the CF lung. However, we do not know whether certain clades are more likely to form chronic infections than others and we lack a comprehensive view of the suite of genes under positive selection in the CF lung. We analyzed whole-genome sequence data from 1,000 P. aeruginosa strains with diverse ecological provenances including the CF lung. CF isolates were distributed across the phylogeny, indicating little genetic predisposition for any one clade to cause chronic infection. Isolates from the CF niche experienced stronger positive selection on core genes than those derived from environmental or acute infection sources, consistent with recent adaptation to the lung environment. Genes with the greatest differential positive selection in the CF niche include those involved in core cellular processes such as metabolism, energy production, and stress response as well as those linked to patho-adaptive processes such as antibiotic resistance, cell wall and membrane modification, quorum sensing, biofilms, mucoidy, motility, and iron homeostasis. Many genes under CF-specific differential positive selection had regulatory functions, consistent with the idea that regulatory mutations play an important role in rapid adaptation to novel environments.

A Mycobacterial Systems Resource for the Research Community

Functional characterization of bacterial proteins lags far behind the identification of new protein families. This is especially true for bacterial species that are more difficult to grow and genetically manipulate than model systems such as Escherichia coli and Bacillus subtilis To facilitate functional characterization of mycobacterial proteins, we have established a Mycobacterial Systems Resource (MSR) using the model organism Mycobacterium smegmatis This resource focuses specifically on 1,153 highly conserved core genes that are common to many mycobacterial species, including Mycobacterium tuberculosis, in order to provide the most relevant information and resources for the mycobacterial research community. The MSR includes both biological and bioinformatic resources. The biological resource includes (i) an expression plasmid library of 1,116 genes fused to a fluorescent protein for determining protein localization; (ii) a library of 569 precise deletions of nonessential genes; and (iii) a set of 843 CRISPR-interference (CRISPRi) plasmids specifically targeted to silence expression of essential core genes and genes for which a precise deletion was not obtained. The bioinformatic resource includes information about individual genes and a detailed assessment of protein localization. We anticipate that integration of these initial functional analyses and the availability of the biological resource will facilitate studies of these core proteins in many Mycobacterium species, including the less experimentally tractable pathogens M. abscessus, M. avium, M. kansasii, M. leprae, M. marinum, M. tuberculosis, and M. ulceransIMPORTANCE Diseases caused by mycobacterial species result in millions of deaths per year globally, and present a substantial health and economic burden, especially in immunocompromised patients. Difficulties inherent in working with mycobacterial pathogens have hampered the development and application of high-throughput genetics that can inform genome annotations and subsequent functional assays. To facilitate mycobacterial research, we have created a biological and bioinformatic resource (https://msrdb.org/) using Mycobacterium smegmatis as a model organism. The resource focuses specifically on 1,153 proteins that are highly conserved across the mycobacterial genus and, therefore, likely perform conserved mycobacterial core functions. Thus, functional insights from the MSR will apply to all mycobacterial species. We believe that the availability of this mycobacterial systems resource will accelerate research throughout the mycobacterial research community.

Paleogenomic insights into the red complex bacteria Tannerella forsythia in Pre-Hispanic and Colonial individuals from Mexico

The 'red complex' is an aggregate of three oral bacteria (Tannerella forsythia, Porphyromonas gingivalis and Treponema denticola) responsible for severe clinical manifestation of periodontal disease. Here, we report the first direct evidence of ancient T.forsythia DNA in dentin and dental calculus samples from archaeological skeletal remains that span from the Pre-Hispanic to the Colonial period in Mexico. We recovered twelve partial ancient T. forsythia genomes and observed a distinct phylogenetic placement of samples, suggesting that the strains present in Pre-Hispanic individuals likely arrived with the first human migrations to the Americas and that new strains were introduced with the arrival of European and African populations in the sixteenth century. We also identified instances of the differential presence of genes between periods in the T. forsythia ancient genomes, with certain genes present in Pre-Hispanic individuals and absent in Colonial individuals, and vice versa. This study highlights the potential for studying ancient T. forsythia genomes to unveil past social interactions through analysis of disease transmission. Our results illustrate the long-standing relationship between this oral pathogen and its human host, while also unveiling key evidence to understand its evolutionary history in Pre-Hispanic and Colonial Mexico. This article is part of the theme issue 'Insights into health and disease from ancient biomolecules'.

An Integrated Multi-Disciplinary Perspectivefor Addressing Challenges of the Human Gut Microbiome

Our understanding of the human gut microbiome has grown exponentially. Advances in genome sequencing technologies and metagenomics analysis have enabled researchers to study microbial communities and their potential function within the context of a range of human gut related diseases and disorders. However, up until recently, much of this research has focused on characterizing the gut microbiological community structure and understanding its potential through system wide (meta) genomic and transcriptomic-based studies. Thus far, the functional output of these microbiomes, in terms of protein and metabolite expression, and within the broader context of host-gut microbiome interactions, has been limited. Furthermore, these studies highlight our need to address the issues of individual variation, and of samples as proxies. Here we provide a perspective review of the recent literature that focuses on the challenges of exploring the human gut microbiome, with a strong focus on an integrated perspective applied to these themes. In doing so, we contextualize the experimental and technical challenges of undertaking such studies and provide a framework for capitalizing on the breadth of insight such approaches afford. An integrated perspective of the human gut microbiome and the linkages to human health will pave the way forward for delivering against the objectives of precision medicine, which is targeted to specific individuals and addresses the issues and mechanisms in situ.

IpdE1-IpdE2 Is a Heterotetrameric Acyl Coenzyme A Dehydrogenase That Is Widely Distributed in Steroid-Degrading Bacteria

Steroid-degrading bacteria, including Mycobacterium tuberculosis (Mtb), utilize an architecturally distinct subfamily of acyl coenzyme A dehydrogenases (ACADs) for steroid catabolism. These ACADs are α₂β₂ heterotetramers that are usually encoded by adjacent fadE-like genes. In mycobacteria, ipdE1 and ipdE2 (formerly fadE30 and fadE33) occur in divergently transcribed operons associated with the catabolism of 3aα-H-4α(3'-propanoate)-7aβ-methylhexahydro-1,5-indanedione (HIP), a steroid metabolite. In Mycobacterium smegmatis, ΔipdE1 and ΔipdE2 mutants had similar phenotypes, showing impaired growth on cholesterol and accumulating 5-OH HIP in the culture supernatant. Bioinformatic analyses revealed that IpdE1 and IpdE2 share many of the features of the α- and β-subunits, respectively, of heterotetrameric ACADs that are encoded by adjacent genes in many steroid-degrading proteobacteria. When coproduced in a rhodococcal strain, IpdE1 and IpdE2 of Mtb formed a complex that catalyzed the dehydrogenation of 5OH-HIP coenzyme A (5OH-HIP-CoA) to 5OH-3aα-H-4α(3'-prop-1-enoate)-7aβ-methylhexa-hydro-1,5-indanedione coenzyme A ((E)-5OH-HIPE-CoA). This corresponds to the initial step in the pathway that leads to degradation of steroid C and D rings via β-oxidation. Small-angle X-ray scattering revealed that the IpdE1-IpdE2 complex was an α₂β₂ heterotetramer typical of other ACADs involved in steroid catabolism. These results provide insight into an important class of steroid catabolic enzymes and a potential virulence determinant in Mtb.

Comparative Genomics and Evolutionary Analysis of RNA-Binding Proteins of Burkholderia cenocepacia J2315 and Other Members of the B. cepacia Complex

RNA-binding proteins (RBPs) are important regulators of cellular functions, playing critical roles on the survival of bacteria and in the case of pathogens, on their interaction with the host. RBPs are involved in transcriptional, post-transcriptional, and translational processes. However, except for model organisms like Escherichia coli, there is little information about the identification or characterization of RBPs in other bacteria, namely in members of the Burkholderia cepacia complex (Bcc). Bcc is a group of bacterial species associated with a poor clinical prognosis in cystic fibrosis patients. These species have some of the largest bacterial genomes, and except for the presence of two-distinct Hfq-like proteins, their RBP repertoire has not been analyzed so far. Using in silico approaches, we identified 186 conventional putative RBPs in Burkholderia cenocepacia J2315, an epidemic and multidrug resistant pathogen of cystic fibrosis patients. Here we describe the comparative genomics and phylogenetic analysis of RBPs present in multiple copies and predicted to play a role in transcription, protein synthesis, and RNA decay in Bcc bacteria. In addition to the two different Hfq chaperones, five cold shock proteins phylogenetically close to E. coli CspD protein and three distinct RhlE-like helicases could be found in the B. cenocepacia J2315 genome. No RhlB, SrmB, or DeaD helicases could be found in the genomes of these bacteria. These results, together with the multiple copies of other proteins generally involved in RNA degradation, suggest the existence, in B. cenocepacia and in other Bcc bacteria, of some extra and unexplored functions for the mentioned RBPs, as well as of alternative mechanisms involved in RNA regulation and metabolism in these bacteria.

Mimicking the human environment in mice reveals that inhibiting biotin biosynthesis is effective against antibiotic-resistant pathogens

To revitalize the antibiotic pipeline, it is critical to identify and validate new antimicrobial targets¹. In Mycobacteria tuberculosis and Francisella tularensis, biotin biosynthesis is a key fitness determinant during infection^2-5, making it a high-priority target. However, biotin biosynthesis has been overlooked for priority pathogens such as Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa. This can be attributed to the lack of attenuation observed for biotin biosynthesis genes during transposon mutagenesis studies in mouse infection models^6-9. Previous studies did not consider the 40-fold higher concentration of biotin in mouse plasma compared to human plasma. Here, we leveraged the unique affinity of streptavidin to develop a mouse infection model with human levels of biotin. Our model suggests that biotin biosynthesis is essential during infection with A. baumannii, K. pneumoniae and P. aeruginosa. Encouragingly, we establish the capacity of our model to uncover in vivo activity for the biotin biosynthesis inhibitor MAC13772. Our model addresses the disconnect in biotin levels between humans and mice, and explains the failure of potent biotin biosynthesis inhibitors in standard mouse infection models.

BINDER: computationally inferring a gene regulatory network for Mycobacterium abscessus

BACKGROUND

Although many of the genic features in Mycobacterium abscessus have been fully validated, a comprehensive understanding of the regulatory elements remains lacking. Moreover, there is little understanding of how the organism regulates its transcriptomic profile, enabling cells to survive in hostile environments. Here, to computationally infer the gene regulatory network for Mycobacterium abscessus we propose a novel statistical computational modelling approach: BayesIan gene regulatory Networks inferreD via gene coExpression and compaRative genomics (BINDER). In tandem with derived experimental coexpression data, the property of genomic conservation is exploited to probabilistically infer a gene regulatory network in Mycobacterium abscessus.Inference on regulatory interactions is conducted by combining 'primary' and 'auxiliary' data strata. The data forming the primary and auxiliary strata are derived from RNA-seq experiments and sequence information in the primary organism Mycobacterium abscessus as well as ChIP-seq data extracted from a related proxy organism Mycobacterium tuberculosis. The primary and auxiliary data are combined in a hierarchical Bayesian framework, informing the apposite bivariate likelihood function and prior distributions respectively. The inferred relationships provide insight to regulon groupings in Mycobacterium abscessus.

RESULTS

We implement BINDER on data relating to a collection of 167,280 regulator-target pairs resulting in the identification of 54 regulator-target pairs, across 5 transcription factors, for which there is strong probability of regulatory interaction.

CONCLUSIONS

The inferred regulatory interactions provide insight to, and a valuable resource for further studies of, transcriptional control in Mycobacterium abscessus, and in the family of Mycobacteriaceae more generally. Further, the developed BINDER framework has broad applicability, useable in settings where computational inference of a gene regulatory network requires integration of data sources derived from both the primary organism of interest and from related proxy organisms.

The LiaFSR and BsrXRS Systems Contribute to Bile Salt Resistance in Enterococcus faecium Isolates

Two-component systems (TCSs) are dominant regulating components in bacteria for responding to environmental stimuli. However, little information is available on how TCSs in Enterococcus faecium respond to bile salts - an important environmental stimulus for intestinal bacteria. In this study, the gene expression of 2 TCSs, BsrXRS and LiaFSR, was positively correlated with survival rates of different E. faecium isolates during exposure to ox gall. Moreover, gene disruptions of bsrR, bsrS, liaS, and liaR significantly reduced the survival rates of E. faecium in the presence of ox gall. Finally, EMSA results indicated that BsrR functioned as a transcription regulator for expression of its own gene as well as lipoate-protein ligase A (lplA). Additional 27 potential target genes by BsrR were revealed through in silico analyses. These findings suggest that BsrXRS and LiaFSR systems play important roles in bile salt resistance in E. faecium.

Pseudomonas aeruginosa Alters Its Transcriptome Related to Carbon Metabolism and Virulence as a Possible Survival Strategy in Blood from Trauma Patients

While a considerable body of knowledge regarding sepsis in trauma patients is available, the potential influence of trauma-induced changes in the blood of these patients on the pathogenesis of Pseudomonas aeruginosa is basically an unexplored area. Rather than using standard laboratory media, we grew P. aeruginosa in whole blood from either healthy volunteers or trauma patients. The specific changes in the P. aeruginosa transcriptome in response to growth in blood from trauma patients reflect the adaptation of this organism to the bloodstream environment. This knowledge is vital for understanding the strategies this pathogen uses to adapt and survive within the host during systemic infection. Such information will help researchers and clinicians to develop new approaches for treatment of sepsis caused by P. aeruginosa in trauma patients, especially in terms of recognizing the effects of specific therapies (e.g., iron, zinc, or mannitol) on the organism. Further, this information can most likely be extrapolated to all patients with P. aeruginosa septicemia.

Trauma patients (TPs) are highly susceptible to infections, which often lead to sepsis. Among the numerous causative agents, Pseudomonas aeruginosa is especially important, as P. aeruginosa sepsis is often fatal. Understanding the mechanism of its pathogenesis in bloodstream infections is imperative; however, this mechanism has not been previously described. To examine the effect of trauma-induced changes in blood on the expression of P. aeruginosa genes, we grew strain UCBPP-PA14 (PA14) in blood samples from eight TPs and seven healthy volunteers (HVs). Compared with its growth in blood from HVs, the growth of PA14 in blood from TPs significantly altered the expression of 285 genes. Genes whose expression was significantly increased were related to carbon metabolism, especially malonate utilization and mannitol uptake, and efflux of heavy metals. Genes whose expression was significantly reduced included genes of the type VI secretion system, genes related to uptake and metabolism of amino acids, and genes related to biosynthesis and transport of the siderophores pyoverdine and pyochelin. These results suggest that during systemic infection in trauma patients, and to adapt to the trauma-induced changes in blood, P. aeruginosa adjusts positively and negatively the expression of numerous genes related to carbon metabolism and virulence, respectively.

IMPORTANCE While a considerable body of knowledge regarding sepsis in trauma patients is available, the potential influence of trauma-induced changes in the blood of these patients on the pathogenesis of Pseudomonas aeruginosa is basically an unexplored area. Rather than using standard laboratory media, we grew P. aeruginosa in whole blood from either healthy volunteers or trauma patients. The specific changes in the P. aeruginosa transcriptome in response to growth in blood from trauma patients reflect the adaptation of this organism to the bloodstream environment. This knowledge is vital for understanding the strategies this pathogen uses to adapt and survive within the host during systemic infection. Such information will help researchers and clinicians to develop new approaches for treatment of sepsis caused by P. aeruginosa in trauma patients, especially in terms of recognizing the effects of specific therapies (e.g., iron, zinc, or mannitol) on the organism. Further, this information can most likely be extrapolated to all patients with P. aeruginosa septicemia.

Author Video: An author video summary of this article is available.

The Primary Antisense Transcriptome of Halobacterium salinarum NRC-1

Antisense RNAs (asRNAs) are present in diverse organisms and play important roles in gene regulation. In this work, we mapped the primary antisense transcriptome in the halophilic archaeon Halobacterium salinarum NRC-1. By reanalyzing publicly available data, we mapped antisense transcription start sites (aTSSs) and inferred the probable 3′ ends of these transcripts. We analyzed the resulting asRNAs according to the size, location, function of genes on the opposite strand, expression levels and conservation. We show that at least 21% of the genes contain asRNAs in H. salinarum. Most of these asRNAs are expressed at low levels. They are located antisense to genes related to distinctive characteristics of H. salinarum, such as bacteriorhodopsin, gas vesicles, transposases and other important biological processes such as translation. We provide evidence to support asRNAs in type II toxin–antitoxin systems in archaea. We also analyzed public Ribosome profiling (Ribo-seq) data and found that ~10% of the asRNAs are ribosome-associated non-coding RNAs (rancRNAs), with asRNAs from transposases overrepresented. Using a comparative transcriptomics approach, we found that ~19% of the asRNAs annotated in H. salinarum belong to genes with an ortholog in Haloferax volcanii, in which an aTSS could be identified with positional equivalence. This shows that most asRNAs are not conserved between these halophilic archaea.

Aerobic prokaryotes do not have higher GC contents than anaerobic prokaryotes, but obligate aerobic prokaryotes have

Background

Among the four bases, guanine is the most susceptible to damage from oxidative stress. Replication of DNA containing damaged guanines results in G to T mutations. Therefore, the mutations resulting from oxidative DNA damage are generally expected to predominantly consist of G to T (and C to A when the damaged guanine is not in the reference strand) and result in decreased GC content. However, the opposite pattern was reported 16 years ago in a study of prokaryotic genomes. Although that result has been widely cited and confirmed by nine later studies with similar methods, the omission of the effect of shared ancestry requires a re-examination of the reliability of the results.

Results

When aerobic and obligate aerobic prokaryotes were mixed together and anaerobic and obligate anaerobic prokaryotes were mixed together, phylogenetic controlled analyses did not detect significant difference in GC content between aerobic and anaerobic prokaryotes. This result is consistent with two generally neglected studied that had accounted for the phylogenetic relationship. However, when obligate aerobic prokaryotes were compared with aerobic prokaryotes, anaerobic prokaryotes, and obligate anaerobic prokaryotes separately using phylogenetic regression analysis, a significant positive association was observed between aerobiosis and GC content, no matter it was calculated from whole genome sequences or the 4-fold degenerate sites of protein-coding genes. Obligate aerobes have significantly higher GC content than aerobes, anaerobes, and obligate anaerobes.

Conclusions

The positive association between aerobiosis and GC content could be attributed to a mutational force resulting from incorporation of damaged deoxyguanosine during DNA replication rather than oxidation of the guanine nucleotides within DNA sequences. Our results indicate a grade in the aerobiosis-associated mutational force, strong in obligate aerobes, moderate in aerobes, weak in anaerobes and obligate anaerobes.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1365-8) contains supplementary material, which is available to authorized users.

Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment

Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination efficacy is unknown. To exhaustively explore the impact of diverse microenvironments on drug-combinations, here we develop a computational framework—Metabolism And GENomics-based Tailoring of Antibiotic regimens (MAGENTA). MAGENTA uses chemogenomic profiles of individual drugs and metabolic perturbations to predict synergistic or antagonistic drug-interactions in different microenvironments. We uncovered antibiotic combinations with robust synergy across nine distinct environments against both E. coli and A. baumannii by searching through 2556 drug-combinations of 72 drugs. MAGENTA also accurately predicted the change in efficacy of bacteriostatic and bactericidal drug-combinations during growth in glycerol media, which we confirmed experimentally in both microbes. Our approach identified genes in glycolysis and glyoxylate pathway as top predictors of synergy and antagonism respectively. Our systems approach enables tailoring of antibiotic therapies based on the pathogen microenvironment.

The antibiotic resistance epidemic has created a pressing need to understand factors that influence antibiotic efficacy. An often-overlooked factor in the search for new treatments is the pathogen environment. Understanding the differences in pathogen sensitivity to antibiotics in lab conditions versus inside the host is necessary for translating new discoveries into the clinic. Hence, we experimentally measured the sensitivity of E. coli to drugs and drug combinations in different metabolic conditions. Our data revealed that the environment dramatically changes treatment potency. Each antibiotic class was affected uniquely by each metabolic condition. The large number of metabolic conditions inside the host greatly complicates the identification of effective therapies. To address this challenge, we present a computational approach called MAGENTA that accurately predicted efficacy of antibiotic regimens in different conditions, which we confirmed experimentally. Furthermore, we show that MAGENTA can be applied to other bacterial pathogens such as A. baumannii and M. tuberculosis without the need for generating expensive data in each organism. MAGENTA accurately predicted efficacy in the pathogen A. baumannii using data from E. coli by identifying genes that are common between the two bacteria. Our study revealed the significant yet predictable impact of environment on drug combination potency.

Predicting Drug Interactions From Chemogenomics Using INDIGO

Designing effective antibiotic combination regimens is critical for countering drug resistance in pathogens. Yet the large combinatorial search-space makes the identification of effective combinations a significant challenge. There is a great need for computational approaches that can rapidly prioritize potential combination regimens based on the antagonistic and synergistic interactions among the constituent antibiotics. This protocol outlines the steps to predict antibiotic interactions from chemogenomics data using the INDIGO algorithm. INDIGO predicted novel drug-drug interaction outcomes quantitatively with high accuracy based on experimental evaluation of predictions in E. coli and S. aureus, and it overcomes several limitations of existing drug-interaction prediction algorithms. The INDIGO approach also expands the applicability of chemogenomic data from model organisms to a broader set of less-studied pathogens. INDIGO can predict drug-interaction outcomes in the bacterial pathogens S. aureus and M. tuberculosis, using chemogenomics data from E. coli by quantifying the degree of conservation of the drug-gene interaction network between different species. The INDIGO approach, which is demonstrated for E. coli and S. aureus in this protocol, can be applied easily to other organisms including pathogens.

The absence of SigX results in impaired carbon metabolism and membrane fluidity in Pseudomonas aeruginosa

In Pseudomonas aeruginosa, SigX is an extra-cytoplasmic function σ factor that belongs to the cell wall stress response network. In previous studies, we made the puzzling observation that sigX mutant growth was severely affected in rich lysogeny broth (LB) but not in minimal medium. Here, through comparative transcriptomic and proteomic analysis, we show that the absence of SigX results in dysregulation of genes, whose products are mainly involved in transport, carbon and energy metabolisms. Production of most of these genes is controlled by carbon catabolite repression (CCR), a key regulatory system than ensures preferential carbon source uptake and utilization, substrate prioritization and metabolism. The strong CCR response elicited in LB was lowered in a sigX mutant, suggesting altered nutrient uptake. Since the absence of SigX affects membrane composition and fluidity, we suspected membrane changes to cause such phenotype. The detergent polysorbate 80 (PS80) can moderately destabilize the envelope resulting in non-specific increased nutrient intake. Remarkably, growth, membrane fluidity and expression of dysregulated genes in the sigX mutant strain were restored in LB supplemented with PS80. Altogether, these data suggest that SigX is indirectly involved in CCR regulation, possibly via its effects on membrane integrity and fluidity.

Mycobacterial Mutagenesis and Drug Resistance Are Controlled by Phosphorylation- and Cardiolipin-Mediated Inhibition of the RecA Coprotease

Infection with Mycobacterium tuberculosis continues to cause substantial human mortality, in part because of the emergence of antimicrobial resistance. Antimicrobial resistance in tuberculosis is solely the result of chromosomal mutations that modify drug activators or targets, yet the mechanisms controlling the mycobacterial DNA-damage response (DDR) remain incompletely defined. Here, we identify RecA serine 207 as a multifunctional signaling hub that controls the DDR in mycobacteria. RecA S207 is phosphorylated after DNA damage, which suppresses the emergence of antibiotic resistance by selectively inhibiting the LexA coprotease function of RecA without affecting its ATPase or strand exchange functions. Additionally, RecA associates with the cytoplasmic membrane during the mycobacterial DDR, where cardiolipin can specifically inhibit the LexA coprotease function of unmodified, but not S207 phosphorylated, RecA. These findings reveal that RecA S207 controls mutagenesis and antibiotic resistance in mycobacteria through phosphorylation and cardiolipin-mediated inhibition of RecA coprotease function.

High-throughput detection of RNA processing in bacteria

Background

Understanding the RNA processing of an organism’s transcriptome is an essential but challenging step in understanding its biology. Here we investigate with unprecedented detail the transcriptome of Pseudomonas aeruginosa PAO1, a medically important and innately multi-drug resistant bacterium. We systematically mapped RNA cleavage and dephosphorylation sites that result in 5′-monophosphate terminated RNA (pRNA) using monophosphate RNA-Seq (pRNA-Seq). Transcriptional start sites (TSS) were also mapped using differential RNA-Seq (dRNA-Seq) and both datasets were compared to conventional RNA-Seq performed in a variety of growth conditions.

Results

The pRNA-Seq library revealed known tRNA, rRNA and transfer-messenger RNA (tmRNA) processing sites, together with previously uncharacterized RNA cleavage events that were found disproportionately near the 5′ ends of transcripts associated with basic bacterial functions such as oxidative phosphorylation and purine metabolism. The majority (97%) of the processed mRNAs were cleaved at precise codon positions within defined sequence motifs indicative of distinct endonucleolytic activities. The most abundant of these motifs corresponded closely to an E. coli RNase E site previously established in vitro. Using the dRNA-Seq library, we performed an operon analysis and predicted 3159 potential TSS. A correlation analysis uncovered 105 antiparallel pairs of TSS that were separated by 18 bp from each other and were centered on single palindromic TAT(A/T)ATA motifs (likely − 10 promoter elements), suggesting that, consistent with previous in vitro experimentation, these sites can initiate transcription bi-directionally and may thus provide a novel form of transcriptional regulation. TSS and RNA-Seq analysis allowed us to confirm expression of small non-coding RNAs (ncRNAs), many of which are differentially expressed in swarming and biofilm formation conditions.

Conclusions

This study uses pRNA-Seq, a method that provides a genome-wide survey of RNA processing, to study the bacterium Pseudomonas aeruginosa and discover extensive transcript processing not previously appreciated. We have also gained novel insight into RNA maturation and turnover as well as a potential novel form of transcription regulation.

NOTE: All sequence data has been submitted to the NCBI sequence read archive. Accession numbers are as follows: [NCBI sequence read archive: SRX156386, SRX157659, SRX157660, SRX157661, SRX157683 and SRX158075]. The sequence data is viewable using Jbrowse on www.pseudomonas.com.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4538-8) contains supplementary material, which is available to authorized users.

A Novel Calcium Uptake Transporter of Uncharacterized P-Type ATPase Family Supplies Calcium for Cell Surface Integrity in Mycobacterium smegmatis

Ca²⁺ plays an important role in the physiology of bacteria. Intracellular Ca²⁺ concentrations are tightly maintained in the nanomolar range. Molecular mechanisms of Ca²⁺ uptake in bacteria remain elusive. Here we show that CtpE is responsible for Ca²⁺ uptake in Mycobacterium smegmatis. It represents a previously uncharacterized P-type ATPase family in bacteria. Disruption of ctpE in M. smegmatis resulted in a mutant with impaired growth under Ca²⁺-deficient conditions. The growth defect of the mutant could be rescued by Ca²⁺ or by ectopic expression of ctpE from M. smegmatis or the orthologous gene (Rv0908) from Mycobacterium tuberculosis H37Rv. Radioactive transport assays revealed that CtpE is a Ca²⁺-specific transporter. Ca²⁺ deficiency increased expression of ctpE, resulting in increased ⁴⁵Ca²⁺ accumulation in cells. ctpE is a gene that is part of an operon, which is negatively regulated by Ca²⁺. The ctpE mutant also showed hypersensitivity to polymyxin B, increased biofilm formation, and higher cell aggregation, indicating cell envelope defects. Our work establishes, for the first time, the presence of Ca²⁺ uptake pumps of the energy-dependent P-type ATPase superfamily in bacteria and also implicates that intracellular Ca²⁺ is essential for growth and cell envelope integrity in M. smegmatis.

Ca²⁺ is essential for gene regulation, enzymatic activity, and maintenance of structural integrity of cell walls in bacteria. Bacteria maintain intracellular calcium concentrations in a narrow range, creating a gradient with low cytoplasmic calcium concentration and high extracellular calcium concentration. Due to this steep gradient, active pumps belonging to family 2 of P-type ATPases and antiporters are used for Ca²⁺ efflux, whereas Ca²⁺ uptake is usually carried out by channels. Molecular mechanisms of Ca²⁺ uptake in bacteria are still elusive and are mainly limited to a nonproteinaceous channel in Escherichia coli and a pH-dependent channel protein from Bacillus subtilis. Energy-dependent active transporters are not reported for Ca²⁺ uptake from any organism. Here we show that CtpE belonging to a family of previously uncharacterized bacterial P-type ATPases is involved in specific uptake of Ca²⁺ into Mycobacterium smegmatis. We also demonstrate that intracellular Ca²⁺ obtained through CtpE is essential for growth and maintenance of cell surface properties under Ca²⁺-deficient conditions.

A review of bioinformatics platforms for comparative genomics. Recent developments of the EDGAR 2.0 platform and its utility for taxonomic and phylogenetic studies

The rapid development of next generation sequencing technology has greatly increased the amount of available microbial genomes. As a result of this development, there is a rising demand for fast and automated approaches in analyzing these genomes in a comparative way. Whole genome sequencing also bears a huge potential for obtaining a higher resolution in phylogenetic and taxonomic classification. During the last decade, several software tools and platforms have been developed in the field of comparative genomics. In this manuscript, we review the most commonly used platforms and approaches for ortholog group analyses with a focus on their potential for phylogenetic and taxonomic research. Furthermore, we describe the latest improvements of the EDGAR platform for comparative genome analyses and present recent examples of its application for the phylogenomic analysis of different taxa. Finally, we illustrate the role of the EDGAR platform as part of the BiGi Center for Microbial Bioinformatics within the German network on Bioinformatics Infrastructure (de.NBI).

Defining the ABC of gene essentiality in streptococci

BACKGROUND

Utilising next generation sequencing to interrogate saturated bacterial mutant libraries provides unprecedented information for the assignment of genome-wide gene essentiality. Exposure of saturated mutant libraries to specific conditions and subsequent sequencing can be exploited to uncover gene essentiality relevant to the condition. Here we present a barcoded transposon directed insertion-site sequencing (TraDIS) system to define an essential gene list for Streptococcus equi subsp. equi, the causative agent of strangles in horses, for the first time. The gene essentiality data for this group C Streptococcus was compared to that of group A and B streptococci.

RESULTS

Six barcoded variants of pGh9:ISS1 were designed and used to generate mutant libraries containing between 33,000-66,000 unique mutants. TraDIS was performed on DNA extracted from each library and data were analysed separately and as a combined master pool. Gene essentiality determined that 19.5% of the S. equi genome was essential. Gene essentialities were compared to those of group A and group B streptococci, identifying concordances of 90.2% and 89.4%, respectively and an overall concordance of 83.7% between the three species.

CONCLUSIONS

The use of barcoded pGh9:ISS1 to generate mutant libraries provides a highly useful tool for the assignment of gene function in S. equi and other streptococci. The shared essential gene set of group A, B and C streptococci provides further evidence of the close genetic relationships between these important pathogenic bacteria. Therefore, the ABC of gene essentiality reported here provides a solid foundation towards reporting the functional genome of streptococci.

Comparative Genomics and Transcriptional Analysis of Flavobacterium columnare Strain ATCC 49512

Flavobacterium columnare is a Gram-negative fish pathogen causing columnaris disease in wild and cultured fish species. Although the pathogen is widespread in aquatic environments and fish worldwide, little is known about biology of F. columnare and mechanisms of columnaris disease pathogenesis. Previously we presented the complete genome sequence of F. columnare strain ATCC 49512. Here we present a comparison of the strain ATCC 49512 genome to four other Flavobacterium genomes. In this analysis, we identified predicted proteins whose functions indicate F. columnare is capable of denitrification, which would enable anaerobic growth in aquatic pond sediments. Anaerobic growth of F. columnare ATCC 49512 with nitrate supplementation was detected experimentally. F. columnare ATCC 49512 had a relatively high number of insertion sequences and genomic islands compared to the other Flavobacterium species, suggesting a larger degree of horizontal gene exchange and genome plasticity. A type VI subtype III secretion system was encoded in F. columnare along with F. johnsoniae and F. branchiophilum. RNA sequencing proved to be a valuable technique to improve annotation quality; 41 novel protein coding regions were identified, 16 of which had a non-traditional start site (TTG, GTG, and CTT). Candidate small noncoding RNAs were also identified. Our results improve our understanding of F. columnare ATCC 49512 biology, and our results support the use of RNA sequencing to improve annotation of bacterial genomes, particularly for type strains.

Hydrocarbonoclastic Alcanivorax Isolates Exhibit Different Physiological and Expression Responses to n-dodecane

Autochthonous microorganisms inhabiting hydrocarbon polluted marine environments play a fundamental role in natural attenuation and constitute promising resources for bioremediation approaches. Alcanivorax spp. members are ubiquitous in contaminated surface waters and are the first to flourish on a wide range of alkanes after an oil-spill. Following oil contamination, a transient community of different Alcanivorax spp. develop, but whether they use a similar physiological, cellular and transcriptomic response to hydrocarbon substrates is unknown. In order to identify which cellular mechanisms are implicated in alkane degradation, we investigated the response of two isolates belonging to different Alcanivorax species, A. dieselolei KS 293 and A. borkumensis SK2 growing on n-dodecane (C12) or on pyruvate. Both strains were equally able to grow on C12 but they activated different strategies to exploit it as carbon and energy source. The membrane morphology and hydrophobicity of SK2 changed remarkably, from neat and hydrophilic on pyruvate to indented and hydrophobic on C12, while no changes were observed in KS 293. In addition, SK2 accumulated a massive amount of intracellular grains when growing on pyruvate, which might constitute a carbon reservoir. Furthermore, SK2 significantly decreased medium surface tension with respect to KS 293 when growing on C12, as a putative result of higher production of biosurfactants. The transcriptomic responses of the two isolates were also highly different. KS 293 changes were relatively balanced when growing on C12 with respect to pyruvate, giving almost the same amount of upregulated (28%), downregulated (37%) and equally regulated (36%) genes, while SK2 transcription was upregulated for most of the genes (81%) when growing on pyruvate when compared to C12. While both strains, having similar genomic background in genes related to hydrocarbon metabolism, retained the same capability to grow on C12, they nevertheless presented very different physiological, cellular and transcriptomic landscapes.

Evolutionary convergence in experimental Pseudomonas populations

Model microbial systems provide opportunity to understand the genetic bases of ecological traits, their evolution, regulation and fitness contributions. Experimental populations of Pseudomonas fluorescens rapidly diverge in spatially structured microcosms producing a range of surface-colonising forms. Despite divergent molecular routes, wrinkly spreader (WS) niche specialist types overproduce a cellulosic polymer allowing mat formation at the air-liquid interface and access to oxygen. Given the range of ways by which cells can form mats, such phenotypic parallelism is unexpected. We deleted the cellulose-encoding genes from the ancestral genotype and asked whether this mutant could converge on an alternate phenotypic solution. Two new traits were discovered. The first involved an exopolysaccharide encoded by pgaABCD that functions as cell-cell glue similar to cellulose. The second involved an activator of an amidase (nlpD) that when defective causes cell chaining. Both types form mats, but were less fit in competition with cellulose-based WS types. Surprisingly, diguanylate cyclases linked to cellulose overexpression underpinned evolution of poly-beta-1,6-N-acetyl-d-glucosamine (PGA)-based mats. This prompted genetic analyses of the relationships between the diguanylate cyclases WspR, AwsR and MwsR, and both cellulose and PGA. Our results suggest that c-di-GMP regulatory networks may have been shaped by evolution to accommodate loss and gain of exopolysaccharide modules facilitating adaptation to new environments.

Novel heterologous bacterial system reveals enhanced susceptibility to DNA damage mediated by yqgF, a nearly ubiquitous and often essential gene

Despite its presence in most bacteria, yqgF remains one of only 13 essential genes of unknown function in Escherichia coli. Predictions of YqgF function often derive from sequence similarity to RuvC, the canonical Holliday junction resolvase. To clarify its role, we deleted yqgF from a bacterium where it is not essential, Acinetobacter baylyi ADP1. Loss of yqgF impaired growth and increased the frequency of transformation and allelic replacement (TAR). When E. coli yqgF was inserted in place of its A. baylyi chromosomal orthologue, wild-type growth and TAR were restored. Functional similarities of yqgF in both gamma-proteobacteria were further supported by defective 16S rRNA processing by the A. baylyi mutant, an effect previously shown in E. coli for a temperature-sensitive yqgF allele. However, our data question the validity of deducing YqgF function strictly by comparison to RuvC. A. baylyi studies indicated that YqgF and RuvC can function in opposition to one another. Relative to the wild type, the ΔyqgF mutant had increased TAR frequency and increased resistance to nalidixic acid, a DNA-damaging agent. In contrast, deletion of ruvC decreased TAR frequency and lowered resistance to nalidixic acid. YqgF, but not RuvC, appears to increase bacterial susceptibility to DNA damage, including UV radiation. Nevertheless, the effects of yqgF on growth and TAR frequency were found to depend on amino acids analogous to catalytically required residues of RuvC. This new heterologous system should facilitate future yqgF investigation by exploiting the viability of A. baylyi yqgF mutants. In addition, bioinformatic analysis showed that a non-essential gene immediately upstream of yqgF in A. baylyi and E. coli (yqgE) is similarly positioned in most gamma- and beta-proteobacteria. A small overlap in the coding sequences of these adjacent genes is typical. This conserved genetic arrangement raises the possibility of a functional partnership between yqgE and yqgF.

An impaired metabolic response to hydrostatic pressure explains Alcanivorax borkumensis recorded distribution in the deep marine water column

Alcanivorax borkumensis is an ubiquitous model organism for hydrocarbonoclastic bacteria, which dominates polluted surface waters. Its negligible presence in oil-contaminated deep waters (as observed during the Deepwater Horizon accident) raises the hypothesis that it may lack adaptive mechanisms to hydrostatic pressure (HP). The type strain SK2 was tested under 0.1, 5 and 10 MPa (corresponding to surface water, 500 and 1000 m depth, respectively). While 5 MPa essentially inactivated SK2, further increase to 10 MPa triggered some resistance mechanism, as indicated by higher total and intact cell numbers. Under 10 MPa, SK2 upregulated the synthetic pathway of the osmolyte ectoine, whose concentration increased from 0.45 to 4.71 fmoles cell⁻¹. Central biosynthetic pathways such as cell replication, glyoxylate and Krebs cycles, amino acids metabolism and fatty acids biosynthesis, but not β-oxidation, were upregulated or unaffected at 10 MPa, although total cell number was remarkably lower with respect to 0.1 MPa. Concomitantly, expression of more than 50% of SK2 genes was downregulated, including genes related to ATP generation, respiration and protein translation. Thus, A. borkumensis lacks proper adaptation to HP but activates resistance mechanisms. These consist in poorly efficient biosynthetic rather than energy-yielding degradation-related pathways, and suggest that HP does represent a major driver for its distribution at deep-sea.

AlgU Controls Expression of Virulence Genes in Pseudomonas syringae pv. tomato DC3000

Plant-pathogenic bacteria are able to integrate information about their environment and adjust gene expression to provide adaptive functions. AlgU, an extracytoplasmic function (ECF) sigma factor encoded by Pseudomonas syringae, controls expression of genes for alginate biosynthesis and genes involved with resisting osmotic and oxidative stress. AlgU is active while these bacteria are associated with plants, where its presence supports bacterial growth and disease symptoms. We found that AlgU is an important virulence factor for P. syringae pv. tomato DC3000 but that alginate production is dispensable for disease in host plants. This implies that AlgU regulates additional genes that facilitate bacterial pathogenesis. We used transcriptome sequencing (RNA-seq) to characterize the AlgU regulon and chromatin immunoprecipitation sequencing (ChIP-seq) to identify AlgU-regulated promoters associated with genes directly controlled by this sigma factor. We found that in addition to genes involved with alginate and osmotic and oxidative stress responses, AlgU regulates genes with known virulence functions, including components of the Hrp type III secretion system, virulence effectors, and the hrpL and hrpRS transcription regulators. These data suggest that P. syringae pv. tomato DC3000 has adapted to use signals that activate AlgU to induce expression of important virulence functions that facilitate survival and disease in plants.

IMPORTANCE

Plant immune systems produce antimicrobial and bacteriostatic conditions in response to bacterial infection. Plant-pathogenic bacteria are adapted to suppress and/or tolerate these conditions; however, the mechanisms controlling these bacterial systems are largely uncharacterized. The work presented here provides a mechanistic explanation for how P. syringae pv. tomato DC3000 coordinates expression of multiple genetic systems, including those dedicated to pathogenicity, in response to environmental conditions. This work demonstrates the scope of AlgU regulation in P. syringae pv. tomato DC3000 and characterizes the promoter sequence regulated by AlgU in these bacteria.

The CsrA-FliW network controls polar localization of the dual-function flagellin mRNA in Campylobacter jejuni

The widespread CsrA/RsmA protein regulators repress translation by binding GGA motifs in bacterial mRNAs. CsrA activity is primarily controlled through sequestration by multiple small regulatory RNAs. Here we investigate CsrA activity control in the absence of antagonizing small RNAs by examining the CsrA regulon in the human pathogen Campylobacter jejuni. We use genome-wide co-immunoprecipitation combined with RNA sequencing to show that CsrA primarily binds flagellar mRNAs and identify the major flagellin mRNA (flaA) as the main CsrA target. The flaA mRNA is translationally repressed by CsrA, but it can also titrate CsrA activity. Together with the main C. jejuni CsrA antagonist, the FliW protein, flaA mRNA controls CsrA-mediated post-transcriptional regulation of other flagellar genes. RNA-FISH reveals that flaA mRNA is expressed and localized at the poles of elongating cells. Polar flaA mRNA localization is translation dependent and is post-transcriptionally regulated by the CsrA-FliW network. Overall, our results suggest a role for CsrA-FliW in spatiotemporal control of flagella assembly and localization of a dual-function mRNA.

Chemogenomics and orthology-based design of antibiotic combination therapies

Combination antibiotic therapies are being increasingly used in the clinic to enhance potency and counter drug resistance. However, the large search space of candidate drugs and dosage regimes makes the identification of effective combinations highly challenging. Here, we present a computational approach called INDIGO, which uses chemogenomics data to predict antibiotic combinations that interact synergistically or antagonistically in inhibiting bacterial growth. INDIGO quantifies the influence of individual chemical–genetic interactions on synergy and antagonism and significantly outperforms existing approaches based on experimental evaluation of novel predictions in Escherichia coli. Our analysis revealed a core set of genes and pathways (e.g. central metabolism) that are predictive of antibiotic interactions. By identifying the interactions that are associated with orthologous genes, we successfully estimated drug‐interaction outcomes in the bacterial pathogens Mycobacterium tuberculosis and Staphylococcus aureus, using the E. coli INDIGO model. INDIGO thus enables the discovery of effective combination therapies in less‐studied pathogens by leveraging chemogenomics data in model organisms.

Cell-Size Homeostasis and the Incremental Rule in a Bacterial Pathogen

How populations of growing cells achieve cell-size homeostasis remains a major question in cell biology. Recent studies in rod-shaped bacteria support the "incremental rule" where each cell adds a constant length before dividing. Although this rule explains narrow cell-size distributions, its mechanism is still unknown. We show that the opportunistic pathogen Pseudomonas aeruginosa obeys the incremental rule to achieve cell-length homeostasis during exponential growth but shortens its cells when entering the stationary phase. We identify a mutant, called frik, which has increased antibiotic sensitivity, cells that are on average longer, and a fraction of filamentous cells longer than 10 μm. When growth slows due to entry in stationary phase, the distribution of frik cell sizes decreases and approaches wild-type length distribution. The rare filamentous cells have abnormally large nucleoids, suggesting that a deficiency in DNA segregation prevents cell division without slowing the exponential elongation rate.

EDGAR 2.0: an enhanced software platform for comparative gene content analyses

The rapidly increasing availability of microbial genome sequences has led to a growing demand for bioinformatics software tools that support the functional analysis based on the comparison of closely related genomes. By utilizing comparative approaches on gene level it is possible to gain insights into the core genes which represent the set of shared features for a set of organisms under study. Vice versa singleton genes can be identified to elucidate the specific properties of an individual genome. Since initial publication, the EDGAR platform has become one of the most established software tools in the field of comparative genomics. Over the last years, the software has been continuously improved and a large number of new analysis features have been added. For the new version, EDGAR 2.0, the gene orthology estimation approach was newly designed and completely re-implemented. Among other new features, EDGAR 2.0 provides extended phylogenetic analysis features like AAI (Average Amino Acid Identity) and ANI (Average Nucleotide Identity) matrices, genome set size statistics and modernized visualizations like interactive synteny plots or Venn diagrams. Thereby, the software supports a quick and user-friendly survey of evolutionary relationships between microbial genomes and simplifies the process of obtaining new biological insights into their differential gene content. All features are offered to the scientific community via a web-based and therefore platform-independent user interface, which allows easy browsing of precomputed datasets. The web server is accessible at http://edgar.computational.bio.

Microbial oil-degradation under mild hydrostatic pressure (10 MPa): which pathways are impacted in piezosensitive hydrocarbonoclastic bacteria?

Oil spills represent an overwhelming carbon input to the marine environment that immediately impacts the sea surface ecosystem. Microbial communities degrading the oil fraction that eventually sinks to the seafloor must also deal with hydrostatic pressure, which linearly increases with depth. Piezosensitive hydrocarbonoclastic bacteria are ideal candidates to elucidate impaired pathways following oil spills at low depth. In the present paper, we tested two strains of the ubiquitous Alcanivorax genus, namely A. jadensis KS_339 and A. dieselolei KS_293, which is known to rapidly grow after oil spills. Strains were subjected to atmospheric and mild pressure (0.1, 5 and 10 MPa, corresponding to a depth of 0, 500 and 1000 m, respectively) providing n-dodecane as sole carbon source. Pressures equal to 5 and 10 MPa significantly lowered growth yields of both strains. However, in strain KS_293 grown at 10 MPa CO2 production per cell was not affected, cell integrity was preserved and PO4(3-) uptake increased. Analysis of its transcriptome revealed that 95% of its genes were downregulated. Increased transcription involved protein synthesis, energy generation and respiration pathways. Interplay between these factors may play a key role in shaping the structure of microbial communities developed after oil spills at low depth and limit their bioremediation potential.

Survival proteomes: the emerging proteotype of antimicrobial resistance

Antimicrobial resistance is one of the greatest challenges in modern medicine. Infectious diseases that have historically been eliminated with routine antibiotic therapy are now re-emerging as life threatening illnesses. A better understanding of the specific mechanisms that contribute to resistance are required to optimize the treatment of infectious microorganisms and limit the survival of recalcitrant populations. This challenging area of research is made more problematic by the observation that multiple, overlapping, and/or compensatory resistance mechanism are often present within a single bacterial species. High-resolution proteomics has emerged as an effective tool to study antimicrobial resistance as it allows for the quantitative investigation of multiple systems concurrently. Furthermore, the ability to examine extracellular mechanisms of resistance and important post-translational modifications make this research tool well suited for the challenge. This review discusses how proteomics has contributed to the understanding of antimicrobial resistance and focuses on advances afforded by the more recent development of technologies that produce quantitative high-resolution proteomic information. We discuss current strategies for studying resistance, including comparative analysis of resistant and susceptible strains and protein-based responses to antimicrobial challenge. Lastly, we suggest specific experimental approaches aimed at advancing our understanding of protein-based resistance mechanisms and maximizing therapeutic outcomes in the future.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.

Databases for Microbiologists

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

General and condition-specific essential functions of Pseudomonas aeruginosa

The essential functions of a bacterial pathogen reflect the most basic processes required for its viability and growth, and represent potential therapeutic targets. Most screens for essential genes have assayed a single condition--growth in a rich undefined medium--and thus have not distinguished genes that are generally essential from those that are specific to this particular condition. To help define these classes for Pseudomonas aeruginosa, we identified genes required for growth on six different media, including a medium made from cystic fibrosis patient sputum. The analysis used the Tn-seq circle method to achieve high genome coverage and analyzed more than 1,000,000 unique insertion positions (an average of one insertion every 6.0 bp). We identified 352 general and 199 condition-specific essential genes. A subset of assignments was verified in individual strains with regulated expression alleles. The profile of essential genes revealed that, compared with Escherichia coli, P. aeruginosa is highly vulnerable to mutations disrupting central carbon-energy metabolism and reactive oxygen defenses. These vulnerabilities may arise from the stripped-down architecture of the organism's carbohydrate utilization pathways and its reliance on respiration for energy generation. The essential function profile thus provides fundamental insights into P. aeruginosa physiology as well as identifying candidate targets for new antibacterial agents.