In vivo and in silico determination of essential genes of Campylobacter jejuni

Metabolic model guided CRISPRi identifies a central role for phosphoglycerate mutase in Chlamydia trachomatis persistence

Upon nutrient starvation, Chlamydia trachomatis serovar L2 (CTL) shifts from its normal growth to a non-replicating form, termed persistence. It is unclear if persistence reflects an adaptive response or a lack thereof. To understand this, transcriptomics data were collected for CTL grown under nutrient-replete and nutrient-starved conditions. Applying K-means clustering on transcriptomics data revealed a global transcriptomic rewiring of CTL under stress conditions in the absence of any canonical global stress regulator. This is consistent with previous data that suggested that CTL's stress response is due to a lack of an adaptive response mechanism. To investigate the impact of this on CTL metabolism, we reconstructed a genome-scale metabolic model of CTL (iCTL278) and contextualized it with the collected transcriptomics data. Using the metabolic bottleneck analysis on contextualized iCTL278, we observed that phosphoglycerate mutase (pgm) regulates the entry of CTL to the persistence state. Our data indicate that pgm has the highest thermodynamics driving force and lowest enzymatic cost. Furthermore, CRISPRi-driven knockdown of pgm in the presence or absence of tryptophan revealed the importance of this gene in modulating persistence. Hence, this work, for the first time, introduces thermodynamics and enzyme cost as tools to gain a deeper understanding on CTL persistence.

IMPORTANCE

This study uses a metabolic model to investigate factors that contribute to the persistence of Chlamydia trachomatis serovar L2 (CTL) under tryptophan and iron starvation conditions. As CTL lacks many canonical transcriptional regulators, the model was used to assess two prevailing hypotheses on persistence-that the chlamydial response to nutrient starvation represents a passive response due to the lack of regulators or that it is an active response by the bacterium. K-means clustering of stress-induced transcriptomics data revealed striking evidence in favor of the lack of adaptive (i.e., a passive) response. To find the metabolic signature of this, metabolic modeling pin-pointed pgm as a potential regulator of persistence. Thermodynamic driving force, enzyme cost, and CRISPRi knockdown of pgm supported this finding. Overall, this work introduces thermodynamic driving force and enzyme cost as a tool to understand chlamydial persistence, demonstrating how systems biology-guided CRISPRi can unravel complex bacterial phenomena.

Genome-scale metabolic modeling of the human milk oligosaccharide utilization by Bifidobacterium longum subsp. infantis

Bifidobacterium longum subsp. infantis is a representative and dominant species in the infant gut and is considered a beneficial microbe. This organism displays multiple adaptations to thrive in the infant gut, regarded as a model for human milk oligosaccharides (HMOs) utilization. These carbohydrates are abundant in breast milk and include different molecules based on lactose. They contain fucose, sialic acid, and N-acetylglucosamine. Bifidobacterium metabolism is complex, and a systems view of relevant metabolic pathways and exchange metabolites during HMO consumption is missing. To address this limitation, a refined genome-scale network reconstruction of this bacterium is presented using a previous reconstruction of B. infantis ATCC 15967 as a template. The latter was expanded based on an extensive revision of genome annotations, current literature, and transcriptomic data integration. The metabolic reconstruction (iLR578) accounted for 578 genes, 1,047 reactions, and 924 metabolites. Starting from this reconstruction, we built context-specific genome-scale metabolic models using RNA-seq data from cultures growing in lactose and three HMOs. The models revealed notable differences in HMO metabolism depending on the functional characteristics of the substrates. Particularly, fucosyl-lactose showed a divergent metabolism due to a fucose moiety. High yields of lactate and acetate were predicted under growth rate maximization in all conditions, whereas formate, ethanol, and 1,2-propanediol were substantially lower. Similar results were also obtained under near-optimal growth on each substrate when varying the empirically observed acetate-to-lactate production ratio. Model predictions displayed reasonable agreement between central carbon metabolism fluxes and expression data across all conditions. Flux coupling analysis revealed additional connections between succinate exchange and arginine and sulfate metabolism and a strong coupling between central carbon reactions and adenine metabolism. More importantly, specific networks of coupled reactions under each carbon source were derived and analyzed. Overall, the presented network reconstruction constitutes a valuable platform for probing the metabolism of this prominent infant gut bifidobacteria.IMPORTANCEThis work presents a detailed reconstruction of the metabolism of Bifidobacterium longum subsp. infantis, a prominent member of the infant gut microbiome, providing a systems view of its metabolism of human milk oligosaccharides.

Machine Learning and Metabolic Model Guided CRISPRi Reveals a Central Role for Phosphoglycerate Mutase in Chlamydia trachomatis Persistence

Upon nutrient starvation, Chlamydia trachomatis serovar L2 (CTL) shifts from its normal growth to a non-replicating form, termed persistence. It is unclear if persistence is an adaptive response or lack of it. To understand that transcriptomics data were collected for nutrient-sufficient and nutrient-starved CTL. Applying machine learning approaches on transcriptomics data revealed a global transcriptomic rewiring of CTL under stress conditions without having any global stress regulator. This indicated that CTL's stress response is due to lack of an adaptive response mechanism. To investigate the impact of this on CTL metabolism, we reconstructed a genome-scale metabolic model of CTL (iCTL278) and contextualized it with the collected transcriptomics data. Using the metabolic bottleneck analysis on contextualized iCTL278, we observed phosphoglycerate mutase (pgm) regulates the entry of CTL to the persistence. Later, pgm was found to have the highest thermodynamics driving force and lowest enzymatic cost. Furthermore, CRISPRi-driven knockdown of pgm and tryptophan starvation experiments revealed the importance of this gene in inducing persistence. Hence, this work, for the first time, introduced thermodynamics and enzyme-cost as tools to gain deeper understanding on CTL persistence.

Application of TraDIS to define the core essential genome of Campylobacter jejuni and Campylobacter coli

Campylobacter species are the major cause of bacterial gastroenteritis. As there is no effective vaccine, combined with the rapid increase in antimicrobial resistant strains, there is a need to identify new targets for intervention. Essential genes are those that are necessary for growth and/or survival, making these attractive targets. In this study, comprehensive transposon mutant libraries were created in six C. jejuni strains, four C. coli strains and one C. lari and C. hyointestinalis strain, allowing for those genes that cannot tolerate a transposon insertion being called as essential. Comparison of essential gene lists using core genome analysis can highlight those genes which are common across multiple strains and/or species. Comparison of C. jejuni and C. coli, the two species that cause the most disease, identified 316 essential genes. Genes of interest highlighted members of the purine pathway being essential for C. jejuni whilst also finding that a functional potassium uptake system is essential. Protein-protein interaction networks using these essential gene lists also highlighted proteins in the purine pathway being major 'hub' proteins which have a large number of interactors across the network. When adding in two more species (C. lari and C. hyointestinalis) the essential gene list reduces to 261. Within these 261 essential genes, there are many genes that have been found to be essential in other bacteria. These include htrB and PEB4, which have previously been found as core virulence genes across Campylobacter species in other studies. There were 21 genes which have no known function with eight of these being associated with the membrane. These surface-associated essential genes may provide attractive targets. The essential gene lists presented will help to prioritise targets for the development of novel therapeutic and preventative interventions.

The Use of Interdisciplinary Approaches to Understand the Biology of Campylobacter jejuni

Campylobacter jejuni is a bacterial pathogen recognised as a major cause of foodborne illness worldwide. While Campylobacter jejuni generally does not grow outside its host, it can survive outside of the host long enough to pose a health concern. This review presents an up-to-date description and evaluation of biological, mathematical, and statistical approaches used to understand the behaviour of this foodborne pathogen and suggests future avenues which can be explored. Specifically, the incorporation of mathematical modelling may aid the understanding of C. jejuni biofilm formation both outside and inside the host. Predictive studies may be improved by the introduction of more standardised protocols for assessments of disinfection methods and by assessment of novel physical disinfection strategies as well as assessment of the efficiency of plant extracts on C. jejuni eradication. A full description of the metabolic pathways of C. jejuni, which is needed for the successful application of metabolic models, is yet to be achieved. Finally, a shift from animal models (except for those that are a source of human campylobacteriosis) to human-specific data may be made possible due to recent technological advancements, and this may lead to more accurate predictions of human infections.

Substrate Utilisation and Energy Metabolism in Non-Growing Campylobacter jejuni M1cam

Campylobacter jejuni, the major cause of bacterial foodborne illness, is also a fastidious organism that requires strict growth requirements in the laboratory. Our aim was to study substrate utilisation and energy metabolism in non-growing C. jejuni to investigate the ability of these bacteria to survive so effectively in the food chain. We integrated phenotypic microarrays and genome-scale metabolic modelling (GSM) to investigate the survival of C. jejuni on 95 substrates. We further investigated the underlying metabolic re-adjustment associated with varying energy demands on each substrate. We identified amino acids, organic acids and H2, as single substrates supporting survival without growth. We identified several different mechanisms, which were used alone or in combination, for ATP production: substrate-level phosphorylation via acetate kinase, the TCA cycle, and oxidative phosphorylation via the electron transport chain that utilised alternative electron donors and acceptors. The benefit of ATP production through each of these mechanisms was associated with the cost of enzyme investment, nutrient availability and/or O2 utilisation. C. jejuni can utilise a wide range of substrates as energy sources, including organic acids commonly used for marination or preservation of ingredients, which might contribute to the success of their survival in changing environments.

DEG 15, an update of the Database of Essential Genes that includes built-in analysis tools

Essential genes refer to genes that are required by an organism to survive under specific conditions. Studies of the minimal-gene-set for bacteria have elucidated fundamental cellular processes that sustain life. The past five years have seen a significant progress in identifying human essential genes, primarily due to the successful use of CRISPR/Cas9 in various types of human cells. DEG 15, a new release of the Database of Essential Genes (www.essentialgene.org), has provided major advancements, compared to DEG 10. Specifically, the number of eukaryotic essential genes has increased by more than fourfold, and that of prokaryotic ones has more than doubled. Of note, the human essential-gene number has increased by more than tenfold. Moreover, we have developed built-in analysis modules by which users can perform various analyses, such as essential-gene distributions between bacterial leading and lagging strands, sub-cellular localization distribution, enrichment analysis of gene ontology and KEGG pathways, and generation of Venn diagrams to compare and contrast gene sets between experiments. Additionally, the database offers customizable BLAST tools for performing species- and experiment-specific BLAST searches. Therefore, DEG comprehensively harbors updated human-curated essential-gene records among prokaryotes and eukaryotes with built-in tools to enhance essential-gene analysis.

Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens

Pathogens give rise to a wide range of diseases threatening global health and hence drawing public health agencies' attention to establish preventative and curative solutions. Genome-scale metabolic modeling is ever increasingly used tool for biomedical applications including the elucidation of antibiotic resistance, virulence, single pathogen mechanisms and pathogen-host interaction systems. With this approach, the sophisticated cellular system of metabolic reactions inside the pathogens as well as between pathogen and host cells are represented in conjunction with their corresponding genes and enzymes. Along with essential metabolic reactions, alternate pathways and fluxes are predicted by performing computational flux analyses for the growth of pathogens in a very short time. The genes or enzymes responsible for the essential metabolic reactions in pathogen growth are regarded as potential drug targets, as a priori guide to researchers in the pharmaceutical field. Pathogens alter the key metabolic processes in infected host, ultimately the objective of these integrative constraint-based context-specific metabolic models is to provide novel insights toward understanding the metabolic basis of the acute and chronic processes of infection, revealing cellular mechanisms of pathogenesis, identifying strain-specific biomarkers and developing new therapeutic approaches including the combination drugs. The reaction rates predicted during different time points of pathogen development enable us to predict active pathways and those that only occur during certain stages of infection, and thus point out the putative drug targets. Among others, fatty acid and lipid syntheses reactions are recent targets of new antimicrobial drugs. Genome-scale metabolic models provide an improved understanding of how intracellular pathogens utilize the existing microenvironment of the host. Here, we reviewed the current knowledge of genome-scale metabolic modeling in pathogen cells as well as pathogen host interaction systems and the promising applications in the extension of curative strategies against pathogens for global preventative healthcare.

Elucidating potential molecular signatures through host-microbe interactions for reactive arthritis and inflammatory bowel disease using combinatorial approach

Reactive Arthritis (ReA), a rare seronegative inflammatory arthritis, lacks exquisite classification under rheumatic autoimmunity. ReA is solely established using differential clinical diagnosis of the patient cohorts, where pathogenic triggers linked to enteric and urogenital microorganisms e.g. Salmonella, Shigella, Yersinia, Campylobacter, Chlamydia have been reported. Inflammatory Bowel Disease (IBD), an idiopathic enteric disorder co-evolved and attuned to present gut microbiome dysbiosis, can be correlated to the genesis of enteropathic arthropathies like ReA. Gut microbes symbolically modulate immune system homeostasis and are elementary for varied disease patterns in autoimmune disorders. The gut-microbiota axis structured on the core host-microbe interactions execute an imperative role in discerning the etiopathogenesis of ReA and IBD. This study predicts the molecular signatures for ReA with co-evolved IBD through the enveloped host-microbe interactions and microbe-microbe 'interspecies communication', using synonymous gene expression data for selective microbes. We have utilized a combinatorial approach that have concomitant in-silico work-pipeline and experimental validation to corroborate the findings. In-silico analysis involving text mining, metabolic network reconstruction, simulation, filtering, host-microbe interaction, docking and molecular mimicry studies results in robust drug target/s and biomarker/s for co-evolved IBD and ReA. Cross validation of the target/s or biomarker/s was done by targeted gene expression analysis following a non-probabilistic convenience sampling. Studies were performed to substantiate the host-microbe disease network consisting of protein-marker-symptom/disease-pathway-drug associations resulting in possible identification of vital drug targets, biomarkers, pathways and inhibitors for IBD and ReA.Our study identified Na(+)/H(+) anti-porter (NHAA) and Kynureninase (KYNU) to be robust early and essential host-microbe interacting targets for IBD co-evolved ReA. Other vital host-microbe interacting genes, proteins, pathways and drugs include Adenosine Deaminase (ADA), Superoxide Dismutase 2 (SOD2), Catalase (CAT), Angiotensin I Converting Enzyme (ACE), carbon metabolism (folate biosynthesis) and methotrexate. These can serve as potential prognostic/theranostic biomarkers and signatures that can be extrapolated to stratify ReA and related autoimmunity patient cohorts for further pilot studies.

From bag-of-genes to bag-of-genomes: metabolic modelling of communities in the era of metagenome-assembled genomes

Metagenomic sequencing of complete microbial communities has greatly enhanced our understanding of the taxonomic composition of microbiotas. This has led to breakthrough developments in bioinformatic disciplines such as assembly, gene clustering, metagenomic binning of species genomes and the discovery of an incredible, so far undiscovered, taxonomic diversity. However, functional annotations and estimating metabolic processes from single species - or communities - is still challenging. Earlier approaches relied mostly on inferring the presence of key enzymes for metabolic pathways in the whole metagenome, ignoring the genomic context of such enzymes, resulting in the 'bag-of-genes' approach to estimate functional capacities of microbiotas. Here, we review recent developments in metagenomic bioinformatics, with a special focus on emerging technologies to simulate and estimate metabolic information, that can be derived from metagenomic assembled genomes. Genome-scale metabolic models can be used to model the emergent properties of microbial consortia and whole communities, and the progress in this area is reviewed. While this subfield of metagenomics is still in its infancy, it is becoming evident that there is a dire need for further bioinformatic tools to address the complex combinatorial problems in modelling the metabolism of large communities as a 'bag-of-genomes'.

Genome-Scale Metabolic Model Driven Design of a Defined Medium for Campylobacter jejuni M1cam

Campylobacter jejuni, the most frequent cause of food-borne bacterial gastroenteritis, is a fastidious organism when grown in the laboratory. Oxygen is required for growth, despite the presence of the metabolic mechanism for anaerobic respiration. Amino acid auxotrophies are variably reported and energy metabolism can occur through several electron donor/acceptor combinations. Overall, the picture is one of a flexible, but vulnerable metabolism. To understand Campylobacter metabolism, we have constructed a fully curated, metabolic model for the reference organism M1 (our variant is M1cam) and validated it through laboratory experiments. Our results show that M1cam is auxotrophic for methionine, niacinamide, and pantothenate. There are complete biosynthesis pathways for all amino acids except methionine and it can produce energy, but not biomass, in the absence of oxygen. M1cam will grow in DMEM/F-12 defined media but not in the previously published Campylobacter specific defined media tested. Using the model, we identified potential auxotrophies and substrates that may improve growth. With this information, we designed simple defined media containing inorganic salts, the auxotrophic substrates, L-methionine, niacinamide, and pantothenate, pyruvate and additional amino acids L-cysteine, L-serine, and L-glutamine for growth enhancement. Our defined media supports a 1.75-fold higher growth rate than Brucella broth after 48 h at 37°C and sustains the growth of other Campylobacter jejuni strains. This media can be used to design reproducible assays that can help in better understanding the adaptation, stress resistance, and the virulence mechanisms of this pathogen. We have shown that with a well-curated metabolic model it is possible to design a media to grow this fastidious organism. This has implications for the investigation of new Campylobacter species defined through metagenomics, such as C. infans.

ePath: an online database towards comprehensive essential gene annotation for prokaryotes

Experimental techniques for identification of essential genes (EGs) in prokaryotes are usually expensive, time-consuming and sometimes unrealistic. Emerging in silico methods provide alternative methods for EG prediction, but often possess limitations including heavy computational requirements and lack of biological explanation. Here we propose a new computational algorithm for EG prediction in prokaryotes with an online database (ePath) for quick access to the EG prediction results of over 4,000 prokaryotes ( https://www.pubapps.vcu.edu/epath/ ). In ePath, gene essentiality is linked to biological functions annotated by KEGG Ortholog (KO). Two new scoring systems, namely, E_score and P_score, are proposed for each KO as the EG evaluation criteria. E_score represents appearance and essentiality of a given KO in existing experimental results of gene essentiality, while P_score denotes gene essentiality based on the principle that a gene is essential if it plays a role in genetic information processing, cell envelope maintenance or energy production. The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on validation from five new experimental studies on EG identification. Our overall goal with ePath is to provide a comprehensive and reliable reference for gene essentiality annotation, facilitating the study of those prokaryotes without experimentally derived gene essentiality information.

Metabolic models and gene essentiality data reveal essential and conserved metabolism in prokaryotes

Essential metabolic reactions are shaping constituents of metabolic networks, enabling viable and distinct phenotypes across diverse life forms. Here we analyse and compare modelling predictions of essential metabolic functions with experimental data and thereby identify core metabolic pathways in prokaryotes. Simulations of 15 manually curated genome-scale metabolic models were integrated with 36 large-scale gene essentiality datasets encompassing a wide variety of species of bacteria and archaea. Conservation of metabolic genes was estimated by analysing 79 representative genomes from all the branches of the prokaryotic tree of life. We find that essentiality patterns reflect phylogenetic relations both for modelling and experimental data, which correlate highly at the pathway level. Genes that are essential for several species tend to be highly conserved as opposed to non-essential genes which may be conserved or not. The tRNA-charging module is highlighted as ancestral and with high centrality in the networks, followed closely by cofactor metabolism, pointing to an early information processing system supplied by organic cofactors. The results, which point to model improvements and also indicate faults in the experimental data, should be relevant to the study of centrality in metabolic networks and ancient metabolism but also to metabolic engineering with prokaryotes.

If we tried to list every known chemical reaction within an organism–human, plant or even bacteria–we would get quite a long and confusing read. But when this information is represented in so-called genome-scale metabolic networks, we have the means to access computationally each of those reactions and their interconnections. Some parts of the network have alternatives, while others are unique and therefore can be essential for growth. Here, we simulate growth and compare essential reactions and genes for the simplest type of unicellular species–prokaryotes–to understand which parts of their metabolism are universally essential and potentially ancestral. We show that similar patterns of essential reactions echo phylogenetic relationships (this makes sense, as the genome provides the building plan for the enzymes that perform those reactions). Our computational predictions correlate strongly with experimental essentiality data. Finally, we show that a crucial step of protein synthesis (tRNA charging) and the synthesis and transformation of small molecules that enzymes require (cofactors) are the most essential and conserved parts of metabolism in prokaryotes. Our results are a step further in understanding the biology and evolution of prokaryotes but can also be relevant in applied studies including metabolic engineering and antibiotic design.

Structure and Function of the Campylobacter jejuni Chromosome Replication Origin

Campylobacter jejuni is the leading bacterial cause of foodborne infections worldwide. However, our understanding of its cell cycle is poor. We identified the probable C. jejuni origin of replication (oriC) - a key element for initiation of chromosome replication, which is also important for chromosome structure, maintenance and dynamics. The herein characterized C. jejuni oriC is monopartite and contains (i) the DnaA box cluster, (ii) the DnaA-dependent DNA unwinding element (DUE) and (iii) binding sites for regulatory proteins. The cluster of five DnaA boxes and the DUE were found in the dnaA-dnaN intergenic region. Binding of DnaA to this cluster of DnaA-boxes enabled unwinding of the DUE in vitro. However, it was not sufficient to sustain replication of minichromosomes, unless the cluster was extended by additional DnaA boxes located in the 3' end of dnaA. This suggests, that C. jejuni oriC requires these boxes to initiate or to regulate replication of its chromosome. However, further detailed mutagenesis is required to confirm the role of these two boxes in initiation of C. jejuni chromosome replication and thus to confirm partial localization of C. jejuni oriC within a coding region, which has not been reported thus far for any bacterial oriC. In vitro DUE unwinding by DnaA was inhibited by Cj1509, an orphan response regulator and a homolog of HP1021, that has been previously shown to inhibit replication in Helicobacter pylori. Thus, Cj1509 might play a similar role as a regulator of C. jejuni chromosome replication. This is the first systematic analysis of chromosome replication initiation in C. jejuni, and we expect that these studies will provide a basis for future research examining the structure and dynamics of the C. jejuni chromosome, which will be crucial for understanding the pathogens' life cycle and virulence.

Next generation microbiological risk assessment meta-omics: The next need for integration

The development of a multi-omics approach has provided a new approach to the investigation of microbial communities allowing an integration of data, which can be used to better understand the behaviour of and interactions between community members. Metagenomics, metatranscriptomics, metaproteomics and metabolomics have the potential of producing a large amount of data in a very short time, however an important challenge is how to exploit and interpret these data to assist risk managers in food safety and quality decisions. This can be achieved by integrating multi-omics data in microbiological risk assessment. In this paper we identify limitations and challenges of the multi-omics approach, underlining promising potentials, but also identifying gaps, which should be addressed for its full exploitation. A view on how this new way of investigation will impact the traditional microbiology schemes in the food industry is also presented.

Essential genome of Campylobacter jejuni

BACKGROUND

Campylobacter species are a leading cause of bacterial foodborne illness worldwide. Despite the global efforts to curb them, Campylobacter infections have increased continuously in both developed and developing countries. The development of effective strategies to control the infection by this pathogen is warranted. The essential genes of bacteria are the most prominent targets for this purpose. In this study, we used transposon sequencing (Tn-seq) of a genome-saturating library of Tn5 insertion mutants to define the essential genome of C. jejuni at a high resolution.

RESULT

We constructed a Tn5 mutant library of unprecedented complexity in C. jejuni NCTC 11168 with 95,929 unique insertions throughout the genome and used the genomic DNA of the library for the reconstruction of Tn5 libraries in the same (C. jejuni NCTC 11168) and different strain background (C. jejuni 81-176) through natural transformation. We identified 166 essential protein-coding genes and 20 essential transfer RNAs (tRNA) in C. jejuni NCTC 11168 which were intolerant to Tn5 insertions during in vitro growth. The reconstructed C. jejuni 81-176 library had 384 protein coding genes with no Tn5 insertions. Essential genes in both strain backgrounds were highly enriched in the cluster of orthologous group (COG) categories of 'Translation, ribosomal structure and biogenesis (J)', 'Energy production and conversion (C)', and 'Coenzyme transport and metabolism (H)'.

CONCLUSION

Comparative analysis among this and previous studies identified 50 core essential genes of C. jejuni, which can be further investigated for the development of novel strategies to control the spread of this notorious foodborne bacterial pathogen.

The Suf Iron-Sulfur Cluster Biosynthetic System Is Essential in Staphylococcus aureus, and Decreased Suf Function Results in Global Metabolic Defects and Reduced Survival in Human Neutrophils

Staphylococcus aureus remains a causative agent for morbidity and mortality worldwide. This is in part a result of antimicrobial resistance, highlighting the need to uncover novel antibiotic targets and to discover new therapeutic agents. In the present study, we explored the possibility that iron-sulfur (Fe-S) cluster synthesis is a viable antimicrobial target. RNA interference studies established that Suf (sulfur mobilization)-dependent Fe-S cluster synthesis is essential in S. aureus We found that sufCDSUB were cotranscribed and that suf transcription was positively influenced by sigma factor B. We characterized an S. aureus strain that contained a transposon inserted in the intergenic space between sufC and sufD (sufD*), resulting in decreased transcription of sufSUB Consistent with the transcriptional data, the sufD* strain had multiple phenotypes associated with impaired Fe-S protein maturation. They included decreased activities of Fe-S cluster-dependent enzymes, decreased growth in media lacking metabolites that require Fe-S proteins for synthesis, and decreased flux through the tricarboxylic acid (TCA) cycle. Decreased Fe-S cluster synthesis resulted in sensitivity to reactive oxygen and reactive nitrogen species, as well as increased DNA damage and impaired DNA repair. The sufD* strain also exhibited perturbed intracellular nonchelated Fe pools. Importantly, the sufD* strain did not exhibit altered exoprotein production or altered biofilm formation, but it was attenuated for survival upon challenge by human polymorphonuclear leukocytes. The results presented are consistent with the hypothesis that Fe-S cluster synthesis is a viable target for antimicrobial development.

Genome-wide fitness analyses of the foodborne pathogen Campylobacter jejuni in in vitro and in vivo models

Campylobacter is the most common cause of foodborne bacterial illness worldwide. Faecal contamination of meat, especially chicken, during processing represents a key route of transmission to humans. There is a lack of insight into the mechanisms driving C. jejuni growth and survival within hosts and the environment. Here, we report a detailed analysis of C. jejuni fitness across models reflecting stages in its life cycle. Transposon (Tn) gene-inactivation libraries were generated in three C. jejuni strains and the impact on fitness during chicken colonisation, survival in houseflies and under nutrient-rich and -poor conditions at 4 °C and infection of human gut epithelial cells was assessed by Tn-insertion site sequencing (Tn-seq). A total of 331 homologous gene clusters were essential for fitness during in vitro growth in three C. jejuni strains, revealing that a large part of its genome is dedicated to growth. We report novel C. jejuni factors essential throughout its life cycle. Importantly, we identified genes that fulfil important roles across multiple conditions. Our comprehensive screens showed which flagella elements are essential for growth and which are vital to the interaction with host organisms. Future efforts should focus on how to exploit this knowledge to effectively control infections caused by C. jejuni.

Morphology heterogeneity within a Campylobacter jejuni helical population: the use of calcofluor white to generate rod-shaped C. jejuni 81-176 clones and the genetic determinants responsible for differences in morphology within 11168 strains

Campylobacter jejuni helical shape is important for colonization and host interactions with straight mutants having altered biological properties. Passage on calcofluor white (CFW) resulted in C. jejuni 81‐176 isolates with morphology changes: either a straight morphology from frameshift mutations and single nucleotide polymorphisms in peptidoglycan hydrolase genes pgp1 or pgp2 or a reduction in curvature due a frameshift mutation in cjj81176_1105, a putative peptidoglycan endopeptidase. Shape defects were restored by complementation. Whole genome sequencing of CFW‐passaged strains showed no specific changes correlating to CFW exposure. The cjj81176_1279 (recR; recombinational DNA repair) and cjj81176_1449 (unknown function) genes were highly variable in all 81‐176 strains sequenced. A frameshift mutation in pgp1 of our laboratory isolate of the straight genome sequenced variant of 11168 (11168‐GS) was also identified. The PG muropeptide profile of 11168‐GS was identical to that of Δpgp1 in the original minimally passaged 11168 strain (11168‐O). Introduction of wild type pgp1 into 11168‐GS did not restore helical morphology. The recR gene was also highly variable in 11168 strains. Microbial cell‐to‐cell heterogeneity is proposed as a mechanism of ensuring bacterial survival in sub‐optimal conditions. In certain environments, changes in C. jejuni morphology due to genetic heterogeneity may promote C. jejuni survival.

Ex vivo proteomics of Campylobacter jejuni 81-176 reveal that FabG affects fatty acid composition to alter bacterial growth fitness in the chicken gut

Campylobacter jejuni is one of the leading causes of foodborne gastrointestinal illness worldwide. Here we performed ex vivo proteomic analysis of C. jejuni 81-176 in chicken, a main reservoir for human infection. At 0, 1 and 4 weeks post-infection (p.i.) with the GFP-expressing 81-176 strain, inocula were recovered from chicken ceca by cell sorting using flow cytometry. iTRAQ-coupled 2D-LC-MS/MS analyses that detected 55 C. jejuni proteins, among which either 3 (FabG, HydB, CJJ81176_0876) or 7 (MscS, CetB, FlhF, PurH, PglJ, LpxC, Icd) proteins exhibited >1.4-fold-increased expression at 1 or 4 week(s) p.i. compared with those at 0 weeks p.i., respectively. Deletion of the fabG gene clearly decreased the proportion of bacterial unsaturated fatty acids (UFAs) and chicken colonization. The UFA proportion of the parental strain was not altered when grown at 42 °C. These findings suggest that FabG might play a pivotal role in UFA production, linked to bacterial adaptation in the poultry host. To our knowledge, this is the first example of ex vivo C. jejuni proteomics, in which fatty acid metabolism might affect bacterial adaptation to the chicken host.

High-Frequency Variation of Purine Biosynthesis Genes Is a Mechanism of Success in Campylobacter jejuni

Phenotypic variation is prevalent in the zoonotic pathogen Campylobacter jejuni, the leading agent of enterocolitis in the developed world. Heterogeneity enhances the survival and adaptive malleability of bacterial populations because variable phenotypes may allow some cells to be protected against future stress. Exposure to hyperosmotic stress previously revealed prevalent differences in growth between C. jejuni strain 81-176 colonies due to resistant or sensitive phenotypes, and these isolated colonies continued to produce progeny with differential phenotypes. In this study, whole-genome sequencing of isolated colonies identified allelic variants of two purine biosynthesis genes, purF and apt, encoding phosphoribosyltransferases that utilize a shared substrate. Genetic analyses determined that purF was essential for fitness, while apt was critical. Traditional and high-depth amplicon-sequencing analyses confirmed extensive intrapopulation genetic variation of purF and apt that resulted in viable strains bearing alleles with in-frame insertion duplications, deletions, or missense polymorphisms. Different purF and apt alleles were associated with various stress survival capabilities under several niche-relevant conditions and contributed to differential intracellular survival in an epithelial cell infection model. Amplicon sequencing revealed that intracellular survival selected for stress-fit purF and apt alleles, as did exposure to oxygen and hyperosmotic stress. Putative protein recognition direct repeat sequences were identified in purF and apt, and a DNA-protein affinity screen captured a predicted exonuclease that promoted the global spontaneous mutation rate. This work illustrates the adaptive properties of high-frequency genetic variation in two housekeeping genes, which influences C. jejuni survival under stress and promotes its success as a pathogen.

IMPORTANCE

C. jejuni is an important cause of bacterial diarrheal illness. Bacterial populations have many strategies for stress survival, but phenotypic variation due to genetic diversity has a powerful advantage: no matter how swift the change in environment, a fraction of the population already expresses the survival trait. Nonclonality is thus increasingly viewed as a mechanism of population success. Our previous work identified prominent resistant/sensitive colonial variation in C. jejuni bacteria in response to hyperosmotic stress; in the work presented here, we attribute that to high-frequency genetic variation in two purine biosynthesis genes, purF and apt. We demonstrated selective pressure for nonlethal mutant alleles of both genes, showed that single-cell variants had the capacity to give rise to diverse purF and apt populations, and determined that stress exposure selected for desirable alleles. Thus, a novel C. jejuni adaptive strategy was identified, which was, unusually, reliant on prevalent genetic variation in two housekeeping genes.

A transferable plasticity region in Campylobacter coli allows isolates of an otherwise non-glycolytic food-borne pathogen to catabolize glucose

Thermophilic Campylobacter species colonize the intestine of agricultural and domestic animals commensally but cause severe gastroenteritis in humans. In contrast to other enteropathogenic bacteria, Campylobacter has been considered to be non-glycolytic, a metabolic property originally used for their taxonomic classification. Contrary to this dogma, we demonstrate that several Campylobacter coli strains are able to utilize glucose as a growth substrate. Isotopologue profiling experiments with (13) C-labeled glucose suggested that these strains catabolize glucose via the pentose phosphate and Entner-Doudoroff (ED) pathways and use glucose efficiently for de novo synthesis of amino acids and cell surface carbohydrates. Whole genome sequencing of glycolytic C. coli isolates identified a genomic island located within a ribosomal RNA gene cluster that encodes for all ED pathway enzymes and a glucose permease. We could show in vitro that a non-glycolytic C. coli strain could acquire glycolytic activity through natural transformation with chromosomal DNA of C. coli and C. jejuni subsp. doylei strains possessing the ED pathway encoding plasticity region. These results reveal for the first time the ability of a Campylobacter species to catabolize glucose and provide new insights into how genetic macrodiversity through intra- and interspecies gene transfer expand the metabolic capacity of this food-borne pathogen.

The Campylobacter jejuni CprRS two-component regulatory system regulates aspects of the cell envelope

Campylobacter jejuni is a leading cause of food-borne gastroenteritis in humans. It lives commensally in the gastrointestinal tract of animals, and tolerates variable conditions during transit/colonization of susceptible hosts. The C. jejuni CprRS two-component system contains an essential response regulator (CprR), and deletion of the cprS sensor kinase enhances biofilms. We sought to identify CprRS-regulated genes and better understand how the system affects survival. Expression from the cprR promoter was highest during logarithmic growth and dependent on CprS. CprR(D52A) did not support viability, indicating that CprR phosphorylation is essential despite the dispensability of CprS. We identified a GTAAAC consensus bound by the CprR C-terminus; the Asp52 residue of full-length CprR was required for binding, suggesting phosphorylation is required. Transcripts differing in expression in ΔcprS compared with wildtype (WT) contained a putative CprR binding site upstream of their promoter region and encoded htrA (periplasmic protease upstream of cprRS) and peb4 (SurA-like chaperone). Consistent with direct regulation, the CprR consensus in the htrA promoter was bound by CprR(CTD). Finally, ΔhtrA formed enhanced biofilms, and ΔcprS biofilms were suppressed by Mg(2+). CprRS is the first C. jejuni regulatory system shown to control genes related to the cell envelope, the first line of interaction between pathogen and changing environments.

Overcoming drug resistance through in silico prediction

Prediction tools are commonly used in pre-clinical research to assist target selection, to optimize drug potency or to predict the pharmacological profile of drug candidates. In silico prediction and overcoming drug resistance is a new opportunity that creates a high interest in pharmaceutical research. This review presents two main in silico strategies to meet this challenge: a structure-based approach to study the influence of mutations on the drug-target interaction and a system-biology approach to identify resistance pathways for a given drug. In silico screening of synergies between therapeutic and resistant pathways through biological network analysis is an example of technique to escape drug resistance. Structure-based drug design and in silico system biology are complementary approaches to reach few objectives at once: increase efficiency, reduce toxicity and overcoming drug resistance.

Gene essentiality analysis based on DEG 10, an updated database of essential genes

The database of essential genes (DEG, available at http://www.essentialgene.org), constructed in 2003, has been timely updated to harbor essential-gene records of bacteria, archaea, and eukaryotes. DEG 10, the current release, includes not only essential protein-coding genes determined by genome-wide gene essentiality screens but also essential noncoding RNAs, promoters, regulatory sequences, and replication origins. Therefore, DEG 10 includes essential genomic elements under different conditions in three domains of life, with customizable BLAST tools. Based on the analysis of DEG 10, we show that the percentage of essential genes in bacterial genomes exhibits an exponential decay with increasing genome sizes. The functions, ATP binding (GO:0005524), GTP binding (GO:0005525), and DNA-directed RNA polymerase activity (GO:0003899), are likely required for organisms across life domains.

Microarray transposon tracking for the mapping of conditionally essential genes in Campylobacter jejuni

Although whole genome approaches to the study of bacteria have grown substantially in the past decade, there is still a need for quick and easy methods for the determination of which genes are essential for the growth of these bacteria under specific growth conditions. There are numerous methods to accomplish this depending on the resources and equipment available, each with their own advantages and disadvantages. Here we describe a method we successfully employed to map the essential genes of Campylobacter jejuni using a microarray transposon tracking approach where we constructed a saturated transposon mutant library in the C. jejuni strain NCTC11168 and used a genomic microarray approach to identify genes lacking transposon insertions under standard laboratory growth conditions. With a fully saturated library, the absence of transposon insertions can be used as an indicator of a gene essential for the survival and growth for the conditions used for the mutant library.

Defining the metabolic requirements for the growth and colonization capacity of Campylobacter jejuni

During the last decade Campylobacter jejuni has been recognized as the leading cause of bacterial gastroenteritis worldwide. This facultative intracellular pathogen is a member of the Epsilonproteobacteria and requires microaerobic atmosphere and nutrient rich media for efficient proliferation in vitro. Its catabolic capacity is highly restricted in contrast to Salmonella Typhimurium and other enteropathogenic bacteria because several common pathways for carbohydrate utilization are either missing or incomplete. Despite these metabolic limitations, C. jejuni efficiently colonizes various animal hosts as a commensal intestinal inhabitant. Moreover, C. jejuni is tremendously successful in competing with the human intestinal microbiota; an infectious dose of few hundreds bacteria is sufficient to overcome the colonization resistance of humans and can lead to campylobacteriosis. Besides the importance and clear clinical manifestation of this disease, the pathogenesis mechanisms of C. jejuni infections are still poorly understood. In recent years comparative genome sequence, transcriptome and metabolome analyses as well as mutagenesis studies combined with animal infection models have provided a new understanding of how the specific metabolic capacity of C. jejuni drives its persistence in the intestinal habitat of various hosts. Furthermore, new insights into the metabolic requirements that support the intracellular survival of C. jejuni were obtained. Because C. jejuni harbors distinct properties in establishing an infection in comparison to pathogenic Enterobacteriaceae, it represents an excellent organism for elucidating new aspects of the dynamic interaction and metabolic cross talk between a bacterial pathogen, the microbiota and the host.

Novel components of the flagellar system in epsilonproteobacteria

Motility is essential for the pathogenesis of many bacterial species. Most bacteria move using flagella, which are multiprotein filaments that rotate propelled by a cell wall-anchored motor using chemical energy. Although some components of the flagellar apparatus are common to many bacterial species, recent studies have shown significant differences in the flagellar structures of different bacterial species. The molecular bases for these differences, however, are not understood. The flagella from epsilonproteobacteria, which include the bacterial pathogens Campylobacter jejuni and Helicobacter pylori, are among the most divergent. Using next-generation sequencing combined with transposon mutagenesis, we have conducted a comprehensive high-throughput genetic screen in Campylobacter jejuni, which identified several novel components of its flagellar system. Biochemical analyses detected interactions between the identified proteins and known components of the flagellar machinery, and in vivo imaging located them to the bacterial poles, where flagella assemble. Most of the identified new components are conserved within but restricted to epsilonproteobacteria. These studies provide insight into the divergent flagella of this group of bacteria and highlight the complexity of this remarkable structure, which has adapted to carry out its conserved functions in the context of widely diverse bacterial species.

IMPORTANCE

Motility is essential for the normal physiology and pathogenesis of many bacterial species. Most bacteria move using flagella, which are multiprotein filaments that rotate propelled by a motor that uses chemical energy as fuel. Although some components of the flagellar apparatus are common to many bacterial species, recent studies have shown significant divergence in the flagellar structures across bacterial species. However, the molecular bases for these differences are not understood. The flagella from epsilonproteobacteria, which include the bacterial pathogens Campylobacter jejuni and Helicobacter pylori, are among the most divergent. We conducted a comprehensive genetic screen in Campylobacter jejuni and identified several novel components of the flagellar system. These studies provide important information to understand how flagella have adapted to function in the context of widely diverse sets of bacterial species and bring unique insight into the evolution and function of this remarkable bacterial organelle.

Promise and reality in the expanding field of network interaction analysis: metabolic networks

In the last few decades, metabolic networks revealed their capabilities as powerful tools to analyze the cellular metabolism. Many research fields (eg, metabolic engineering, diagnostic medicine, pharmacology, biochemistry, biology and physiology) improved the understanding of the cell combining experimental assays and metabolic network-based computations. This process led to the rise of the “systems biology” approach, where the theory meets experiments and where two complementary perspectives cooperate in the study of biological phenomena. Here, the reconstruction of metabolic networks is presented, along with established and new algorithms to improve the description of cellular metabolism. Then, advantages and limitations of modeling algorithms and network reconstruction are discussed.

Metabolomic analysis of the food-borne pathogen Campylobacter jejuni: application of direct injection mass spectrometry for mutant characterisation

Campylobacter jejuni is the most frequent cause of human food-borne bacterial gastroenteritis but its physiology and biochemistry are poorly understood. Only a few amino-acids can be catabolised and these are known to be important for host colonization. Here we have established methods for rapid high throughput analyses of global metabolism in C. jejuni using direct injection mass spectrometry (DIMS) to compare metabolite fingerprints of wild-type and mutant strains. Principal component analyses show that the metabolic fingerprint of mutants that have a genomic deletion in genes for key amino-acid catabolic enzymes (either sdaA, serine dehydratase; aspA, aspartase or aspB, aspartate:glutamate transaminase) can easily be distinguished from the isogenic parental strain. Assignment of putative metabolites showed predictable changes directly associated with the particular metabolic lesion in these mutants as well as more extensive changes in the aspA mutant compared to the sdaA or aspB strains. Further analyses of a cj0150c mutant strain, which has no obvious phenotype, suggested a role for Cj0150 in the conversion of cystathionine to homocysteine. Our results show that DIMS is a useful technique for probing the metabolism of this important pathogen and may help in assigning function to genes encoding novel enzymes with currently unknown metabolic roles.

A multi-level multi-scale approach to study essential genes in Mycobacterium tuberculosis

Background

The set of indispensable genes that are required by an organism to grow and sustain life are termed as essential genes. There is a strong interest in identification of the set of essential genes, particularly in pathogens, not only for a better understanding of the pathogen biology, but also for identifying drug targets and the minimal gene set for the organism. Essentiality is inherently a systems property and requires consideration of the system as a whole for their identification. The available experimental approaches capture some aspects but each method comes with its own limitations. Moreover, they do not explain the basis for essentiality in most cases. A powerful prediction method to recognize this gene pool including rationalization of the known essential genes in a given organism would be very useful. Here we describe a multi-level multi-scale approach to identify the essential gene pool in a deadly pathogen, Mycobacterium tuberculosis.

Results

The multi-level workflow analyses the bacterial cell by studying (a) genome-wide gene expression profiles to identify the set of genes which show consistent and significant levels of expression in multiple samples of the same condition, (b) indispensability for growth by using gene expression integrated flux balance analysis of a genome-scale metabolic model, (c) importance for maintaining the integrity and flow in a protein-protein interaction network and (d) evolutionary conservation in a set of genomes of the same ecological niche. In the gene pool identified, the functional basis for essentiality has been addressed by studying residue level conservation and the sub-structure at the ligand binding pockets, from which essential amino acid residues in that pocket have also been identified. 283 genes were identified as essential genes with high-confidence. An agreement of about 73.5% is observed with that obtained from the experimental transposon mutagenesis technique. A large proportion of the identified genes belong to the class of intermediary metabolism and respiration.

Conclusions

The multi-scale, multi-level approach described can be generally applied to other pathogens as well. The essential gene pool identified form a basis for designing experiments to probe their finer functional roles and also serve as a ready shortlist for identifying drug targets.

DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements

The combination of high-density transposon-mediated mutagenesis and high-throughput sequencing has led to significant advancements in research on essential genes, resulting in a dramatic increase in the number of identified prokaryotic essential genes under diverse conditions and a revised essential-gene concept that includes all essential genomic elements, rather than focusing on protein-coding genes only. DEG 10, a new release of the Database of Essential Genes (available at http://www.essentialgene.org), has been developed to accommodate these quantitative and qualitative advancements. In addition to increasing the number of bacterial and archaeal essential genes determined by genome-wide gene essentiality screens, DEG 10 also harbors essential noncoding RNAs, promoters, regulatory sequences and replication origins. These essential genomic elements are determined not only in vitro, but also in vivo, under diverse conditions including those for survival, pathogenesis and antibiotic resistance. We have developed customizable BLAST tools that allow users to perform species- and experiment-specific BLAST searches for a single gene, a list of genes, annotated or unannotated genomes. Therefore, DEG 10 includes essential genomic elements under different conditions in three domains of life, with customizable BLAST tools.

Neisseria meningitidis expresses a single 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase that is inhibited primarily by phenylalanine

Neisseria meningitidis is the causative agent of meningitis and meningococcal septicemia is a major cause of disease worldwide, resulting in brain damage and hearing loss, and can be fatal in a large proportion of cases. The enzyme 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase (DAH7PS) catalyzes the first reaction in the shikimate pathway leading to the biosynthesis of aromatic metabolites including the aromatic acids l-Trp, l-Phe, and l-Tyr. This pathway is absent in humans, meaning that enzymes of the pathway are considered as potential candidates for therapeutic intervention. As the entry point, feedback inhibition of DAH7PS by pathway end products is a key mechanism for the control of pathway flux. The structure of the single DAH7PS expressed by N. meningitidis was determined at 2.0 Å resolution. In contrast to the other DAH7PS enzymes, which are inhibited only by a single aromatic amino acid, the N. meningitidis DAH7PS was inhibited by all three aromatic amino acids, showing greatest sensitivity to l-Phe. An N. meningitidis enzyme variant, in which a single Ser residue at the bottom of the inhibitor-binding cavity was substituted to Gly, altered inhibitor specificity from l-Phe to l-Tyr. Comparison of the crystal structures of both unbound and Tyr-bound forms and the small angle X-ray scattering profiles reveal that N. meningtidis DAH7PS undergoes no significant conformational change on inhibitor binding. These observations are consistent with an allosteric response arising from changes in protein motion rather than conformation, and suggest ligands that modulate protein dynamics may be effective inhibitors of this enzyme.

Distribution of colonization and antimicrobial resistance genes in Campylobacter jejuni isolated from chicken

Campylobacter jejuni is an important worldwide foodborne pathogen commonly found as a commensal organism in poultry that can reach high numbers within the gut after colonization. Although information regarding some genes involved in colonization is available, little is known about their distribution in strains isolated specifically from chickens and whether there is a linkage between antimicrobial resistance (AMR) and colonization genes. To assess the distribution and relevance of genes associated with chicken colonization and AMR, a C. jejuni microarray was created to detect 254 genes of interest in colonization and AMR including variants. DNA derived from chicken-specific Campylobacter isolates collected in 2003 (n=29) and 2008 (n=28) was hybridized to the microarray and compared. Hybridization results showed variable colonization-associated gene presence. Acquired AMR genes were low in prevalence whereas chemotaxis receptors, arsenic resistance genes, as well as genes from the cell envelope and flagella functional groups were highly variable in their presence. Strains clustered into two groups, each linked to different control strains, 81116 and NCTC11168. Clustering was found to be independent of collection time. We also show that AMR weakly associated with the CJ0628 and arsR genes. Although other studies have implicated numerous genes associated with C. jejuni chicken colonization, our data on chicken-specific isolates suggest the opposite. The enormous variability in presumed colonization gene prevalence in our chicken isolates suggests that many are of lesser importance than previously thought. Alternatively, this also suggests that combinations of genes may be required for natural colonization of chicken intestines.

Contribution of amino acid catabolism to the tissue specific persistence of Campylobacter jejuni in a murine colonization model

Campylobacter jejuni is a major cause of food-borne disease in industrialized countries. Carbohydrate utilization by C. jejuni is severely restricted, and knowledge about which substrates fuel C. jejuni infection and growth is limited. Some amino acids have been shown to serve as carbon sources both in vitro and in vivo. In the present study we investigated the contribution of serine and proline catabolism to the invitro and invivo growth of C. jejuni 81-176. We confirmed that the serine transporter SdaC and the serine ammonia-lyase SdaA are required for serine utilization, and demonstrated that a predicted proline permease PutP and a bifunctional proline/delta-1-pyrroline-5-carboxylate dehydrogenase PutA are required for proline utilization by C. jejuni 81-176. C. jejuni 81-176 mutants unable to utilize serine were shown to be severely defective for colonization of the intestine and systemic tissues in a mouse model of infection. In contrast, C. jejuni 81-176 mutants unable to utilize proline were only defective for intestinal colonization. These results further emphasize the importance of amino acid utilization in C. jejuni colonization of various tissues.

Identification of essential genes of the periodontal pathogen Porphyromonas gingivalis

Background

Porphyromonas gingivalis is a Gram-negative anaerobic bacterium associated with periodontal disease onset and progression. Genetic tools for the manipulation of bacterial genomes allow for in-depth mechanistic studies of metabolism, physiology, interspecies and host-pathogen interactions. Analysis of the essential genes, protein-coding sequences necessary for survival of P. gingivalis by transposon mutagenesis has not previously been attempted due to the limitations of available transposon systems for the organism. We adapted a Mariner transposon system for mutagenesis of P. gingivalis and created an insertion mutant library. By analyzing the location of insertions using massively-parallel sequencing technology we used this mutant library to define genes essential for P. gingivalis survival under in vitro conditions.

Results

In mutagenesis experiments we identified 463 genes in P. gingivalis strain ATCC 33277 that are putatively essential for viability in vitro. Comparing the 463 P. gingivalis essential genes with previous essential gene studies, 364 of the 463 are homologues to essential genes in other species; 339 are shared with more than one other species. Twenty-five genes are known to be essential in P. gingivalis and B. thetaiotaomicron only. Significant enrichment of essential genes within Cluster of Orthologous Groups ‘D’ (cell division), ‘I’ (lipid transport and metabolism) and ‘J’ (translation/ribosome) were identified. Previously, the P. gingivalis core genome was shown to encode 1,476 proteins out of a possible 1,909; 434 of 463 essential genes are contained within the core genome. Thus, for the species P. gingivalis twenty-two, seventy-seven and twenty-three percent of the genome respectively are devoted to essential, core and accessory functions.

Conclusions

A Mariner transposon system can be adapted to create mutant libraries in P. gingivalis amenable to analysis by next-generation sequencing technologies. In silico analysis of genes essential for in vitro growth demonstrates that although the majority are homologous across bacterial species as a whole, species and strain-specific subsets are apparent. Understanding the putative essential genes of P. gingivalis will provide insights into metabolic pathways and niche adaptations as well as clinical therapeutic strategies.

Transcriptional regulation of the CmeABC multidrug efflux pump and the KatA catalase by CosR in Campylobacter jejuni

CosR is an essential response regulator in Campylobacter jejuni, a major food-borne pathogen causing enteritis worldwide. A transcriptomic analysis performed in this study discovered 93 genes whose transcriptional levels were changed >2-fold due to the repression of CosR expression by antisense peptide nucleic acid. The identified CosR-regulated genes are involved in various cellular functions, such as energy production, protein synthesis and folding, flagellum biogenesis, and lipid metabolism. Interestingly, 17 of the 93 CosR-regulated genes (18.3%) are predicted essential genes, indicating that CosR may participate in the regulation of vital biological processes in C. jejuni. In particular, CosR knockdown increased the transcriptional levels of cmeA, cmeB, and cmeC genes, whose protein product (CmeABC) is an important determinant conferring multidrug resistance in Campylobacter. Negative regulation of cmeABC by CosR was verified by quantitative real-time PCR (qRT-PCR) and P(cmeABC)::lacZ assay. The results of electrophoretic mobility shift assays (EMSAs) and DNase I footprinting assays demonstrated that CosR directly binds to the cmeABC promoter. Another notable finding is that CosR regulates the transcription of katA, the sole catalase gene in C. jejuni. Further characterization with qRT-PCR, the catalase enzyme assay, EMSA, and DNase I footprinting assays successfully demonstrated that CosR affects the katA transcription and the catalase activity by direct interactions with the katA promoter. The findings in this study clearly demonstrated that CosR regulates resistance mechanisms in C. jejuni by controlling the expression of genes involved in oxidative stress defense and extrusion of toxic compounds out of the cell.

How a sugary bug gets through the day: recent developments in understanding fundamental processes impacting Campylobacter jejuni pathogenesis

Campylobacter jejuni is a highly prevalent yet fastidious bacterial pathogen that poses a significant health burden worldwide. Lacking many hallmark virulence factors, it is becoming increasingly clear that C. jejuni pathogenesis involves different strategies compared with other well-characterized enteric organisms. This includes the involvement of basic biological processes and cell envelope glycans in a number of aspects related to pathogenesis. The past few years have seen significant progress in the understanding of these pathways and how they relate to C. jejuni fundamental biology, stress survival, colonization, and virulence attributes. This review focuses on recent studies in three general areas where "pathogenesis" and "basic biology" overlap: physiology, stress responses and glycobiology.