Reconstruction and modeling protein translocation and compartmentalization in Escherichia coli at the genome-scale

BackgroundMembranes play a crucial role in cellular functions. Membranes provide a physical barrier, control the trafficking of substances entering and leaving the cell, and are a major determinant of cellular ultra-structure. In addition, components embedded within the membrane participate in cell signaling, energy transduction, and other critical cellular functions. All these processes must share the limited space in the membrane; thus it represents a notable constraint on cellular functions. Membrane- and location-based processes have not yet been reconstructed and explicitly integrated into genome-scale models.ResultsThe recent genome-scale model of metabolism and protein expression in Escherichia coli (called a ME-model) computes the complete composition of the proteome required to perform whole cell functions. Here we expand the ME-model to include (1) a reconstruction of protein translocation pathways, (2) assignment of all cellular proteins to one of four compartments (cytoplasm, inner membrane, periplasm, and outer membrane) and a translocation pathway, (3) experimentally determined translocase catalytic and porin diffusion rates, and (4) a novel membrane constraint that reflects cell morphology. Comparison of computations performed with this expanded ME-model, named iJL1678-ME, against available experimental data reveals that the model accurately describes translocation pathway expression and the functional proteome by compartmentalized mass.ConclusioniJL1678-ME enables the computation of cellular phenotypes through an integrated computation of proteome composition, abundance, and activity in four cellular compartments (cytoplasm, periplasm, inner and outer membrane). Reconstruction and validation of the model has demonstrated that the iJL1678-ME is capable of capturing the functional content of membranes, cellular compartment-specific composition, and that it can be utilized to examine the effect of perturbing an expanded set of network components. iJL1678-ME takes a notable step towards the inclusion of cellular ultra-structure in genome-scale models

GABA-modulating bacteria of the human gut microbiota.

The gut microbiota affects many important host functions, including the immune response and the nervous system1. However, while substantial progress has been made in growing diverse microorganisms of the microbiota2, 23-65% of species residing in the human gut remain uncultured3,4, which is an obstacle for understanding their biological roles. A likely reason for this unculturability is the absence in artificial media of key growth factors that are provided by neighbouring bacteria in situ5,6. In the present study, we used co-culture to isolate KLE1738, which required the presence of Bacteroides fragilis to grow. Bioassay-driven purification of B. fragilis supernatant led to the isolation of the growth factor, which, surprisingly, is the major inhibitory neurotransmitter GABA (γ-aminobutyric acid). GABA was the only tested nutrient that supported the growth of KLE1738, and a genome analysis supported a GABA-dependent metabolism mechanism. Using growth of KLE1738 as an indicator, we isolated a variety of GABA-producing bacteria, and found that Bacteroides ssp. produced large quantities of GABA. Genome-based metabolic modelling of the human gut microbiota revealed multiple genera with the predicted capability to produce or consume GABA. A transcriptome analysis of human stool samples from healthy individuals showed that GABA-producing pathways are actively expressed by Bacteroides, Parabacteroides and Escherichia species. By coupling 16S ribosmal RNA sequencing with functional magentic resonance imaging in patients with major depressive disorder, a disease associated with an altered GABA-mediated response, we found that the relative abundance levels of faecal Bacteroides are negatively correlated with brain signatures associated with depression

Metabolic capability and in situ activity of microorganisms in an oil reservoir

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Comparison of three rapid and easy bacterial DNA extraction methods for use with quantitative real-time PCR

The development of fast and easy on-site molecular detection and quantification methods for hazardous microbes on solid surfaces is desirable for several applications where specialised laboratory facilities are absent. The quantification of bacterial contamination necessitates the assessment of the efficiency of the used methodology as a whole, including the preceding steps of sampling and sample processing. We used quantitative real-time polymerase chain reaction (qrtPCR) for Escherichia coli and Staphylococcus aureus to measure the recovery of DNA from defined numbers of bacterial cells that were subjected to three different DNA extraction methods: the QIAamp® DNA Mini Kit, Reischl et al.’s method and FTA® Elute. FTA® Elute significantly showed the highest median DNA extraction efficiency of 76.9% for E. coli and 108.9% for S. aureus. The Reischl et al. method and QIAamp® DNA Mini Kit inhibited the E. coli qrtPCR assay with a 10-fold decrease of detectable DNA. None of the methods inhibited the S. aureus qrtPCR assay. The FTA® Elute applicability was demonstrated with swab samples taken from the International Space Station (ISS) interior. Overall, the FTA® Elute method was found to be the most suitable to selected criteria in terms of rapidity, easiness of use, DNA extraction efficiency, toxicity, and transport and storage conditions

Rubrivivax benzoatilyticus sp.nov., an aromatic hydrocarbon-degrading purple betaproteobacterium

A brown-coloured bacterium was isolated from photoheterotrophic (benzoate) enrichments of flooded paddy soil from Andhra Pradesh, India. On the basis of 16S rRNA gene sequence analysis, strain JA2(T) was shown to belong to the class Betaproteobacteria, related to Rubrivivax gelatinosus (99 % sequence similarity). Cells of strain JA2(T) are Gram-negative, motile rods with monopolar single flagella. The strain contained bacteriochlorophyll a and most probably the carotenoids spirilloxanthin and sphaeroidene, but did not have internal membrane structures. Intact cells had absorption maxima at 378, 488, 520, 590, 802 and 884 nm. No growth factors were required. Strain JA2(T) grew on benzoate, 2-aminobenzoate (anthranilate), 4-aminobenzoate, 4-hydroxybenzoate, phthalate, phenylalanine, trans-cinnamate, benzamide, salicylate, cyclohexanone, cyclohexanol and cyclohexane-2-carboxylate as carbon sources and/or electron donors. The DNA G+C content was 74.9 mol%. Based on DNA-DNA hybridization studies, 16S rRNA gene sequence analysis and morphological and physiological characteristics, strain JA2(T) is different from representatives of other photosynthetic species of the Betaproteobacteria and was recognised as representing a novel species, for which the name Rubrivivax benzoatilyticus sp. nov. is proposed. The type strain is JA2(T) (=ATCC BAA-35(T)=JCM 13220(T)=MTCC 7087(T))

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

<p>Abstract</p> <p>Background</p> <p>Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. <it>Salmonella enterica </it>subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem.</p> <p>Results</p> <p>Here, we describe a community-driven effort, in which more than 20 experts in <it>S</it>. Typhimurium biology and systems biology collaborated to reconcile and expand the <it>S</it>. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for <it>S</it>. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches.</p> <p>Conclusion</p> <p>Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.</p

Microdroplet-Enabled Highly Parallel Co-Cultivation of Microbial Communities

Microbial interactions in natural microbiota are, in many cases, crucial for the sustenance of the communities, but the precise nature of these interactions remain largely unknown because of the inherent complexity and difficulties in laboratory cultivation. Conventional pure culture-oriented cultivation does not account for these interactions mediated by small molecules, which severely limits its utility in cultivating and studying “unculturable” microorganisms from synergistic communities. In this study, we developed a simple microfluidic device for highly parallel co-cultivation of symbiotic microbial communities and demonstrated its effectiveness in discovering synergistic interactions among microbes. Using aqueous micro-droplets dispersed in a continuous oil phase, the device could readily encapsulate and co-cultivate subsets of a community. A large number of droplets, up to ∼1,400 in a 10 mm×5 mm chamber, were generated with a frequency of 500 droplets/sec. A synthetic model system consisting of cross-feeding E. coli mutants was used to mimic compositions of symbionts and other microbes in natural microbial communities. Our device was able to detect a pair-wise symbiotic relationship when one partner accounted for as low as 1% of the total population or each symbiont was about 3% of the artificial community

Culture Enriched Molecular Profiling of the Cystic Fibrosis Airway Microbiome

The microbiome of the respiratory tract, including the nasopharyngeal and oropharyngeal microbiota, is a dynamic community of microorganisms that is highly diverse. The cystic fibrosis (CF) airway microbiome refers to the polymicrobial communities present in the lower airways of CF patients. It is comprised of chronic opportunistic pathogens (such as Pseudomonas aeruginosa) and a variety of organisms derived mostly from the normal microbiota of the upper respiratory tract. The complexity of these communities has been inferred primarily from culture independent molecular profiling. As with most microbial communities it is generally assumed that most of the organisms present are not readily cultured. Our culture collection generated using more extensive cultivation approaches, reveals a more complex microbial community than that obtained by conventional CF culture methods. To directly evaluate the cultivability of the airway microbiome, we examined six samples in depth using culture-enriched molecular profiling which combines culture-based methods with the molecular profiling methods of terminal restriction fragment length polymorphisms and 16S rRNA gene sequencing. We demonstrate that combining culture-dependent and culture-independent approaches enhances the sensitivity of either approach alone. Our techniques were able to cultivate 43 of the 48 families detected by deep sequencing; the five families recovered solely by culture-independent approaches were all present at very low abundance (<0.002% total reads). 46% of the molecular signatures detected by culture from the six patients were only identified in an anaerobic environment, suggesting that a large proportion of the cultured airway community is composed of obligate anaerobes. Most significantly, using 20 growth conditions per specimen, half of which included anaerobic cultivation and extended incubation times we demonstrate that the majority of bacteria present can be cultured

New Detection Systems of Bacteria Using Highly Selective Media Designed by SMART: Selective Medium-Design Algorithm Restricted by Two Constraints

Culturing is an indispensable technique in microbiological research, and culturing with selective media has played a crucial role in the detection of pathogenic microorganisms and the isolation of commercially useful microorganisms from environmental samples. Although numerous selective media have been developed in empirical studies, unintended microorganisms often grow on such media probably due to the enormous numbers of microorganisms in the environment. Here, we present a novel strategy for designing highly selective media based on two selective agents, a carbon source and antimicrobials. We named our strategy SMART for highly Selective Medium-design Algorithm Restricted by Two constraints. To test whether the SMART method is applicable to a wide range of microorganisms, we developed selective media for Burkholderia glumae, Acidovorax avenae, Pectobacterium carotovorum, Ralstonia solanacearum, and Xanthomonas campestris. The series of media developed by SMART specifically allowed growth of the targeted bacteria. Because these selective media exhibited high specificity for growth of the target bacteria compared to established selective media, we applied three notable detection technologies: paper-based, flow cytometry-based, and color change-based detection systems for target bacteria species. SMART facilitates not only the development of novel techniques for detecting specific bacteria, but also our understanding of the ecology and epidemiology of the targeted bacteria