Modeling association in microbial communities with clique loglinear models

There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequencing of metagenomic samples to determine community composition. We propose a statistical technique based on clique loglinear models and Bayes model averaging to identify microbial components in a metagenomic sample at various taxonomic levels that have significant associations. We describe the model class, a stochastic search technique for model selection, and the calculation of estimates of posterior probabilities of interest. We demonstrate our approach using data from the Human Microbiome Project and from a study of the skin microbiome in chronic wound healing. Our technique also identifies significant dependencies among microbial components as evidence of possible microbial syntrophy. KEYWORDS: contingency tables, graphical models, model selection, microbiome, next generation sequencingComment: 30 pages, 17 figur

Modeling Association in Microbial Communities with Clique Loginear Models

There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequencing of metagenomic samples to determine community composition. We propose a statistical technique based on clique loglinear models and Bayes model averaging to identify microbial components in a metagenomic sample at various taxonomic levels that have significant associations. We describe the model class, a stochastic search technique for model selection, and the calculation of estimates of posterior probabilities of interest. We demonstrate our approach using data from the Human Microbiome Project and from a study of the skin microbiome in chronic wound healing. Our technique also identifies significant dependencies among microbial components as evidence of possible microbial syntrophy

Modeling Association in Microbial Communities with Clique Loginear Models

There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequencing of metagenomic samples to determine community composition. We propose a statistical technique based on clique loglinear models and Bayes model averaging to identify microbial components in a metagenomic sample at various taxonomic levels that have significant associations. We describe the model class, a stochastic search technique for model selection, and the calculation of estimates of posterior probabilities of interest. We demonstrate our approach using data from the Human Microbiome Project and from a study of the skin microbiome in chronic wound healing. Our technique also identifies significant dependencies among microbial components as evidence of possible microbial syntrophy

Association between baseline abundance of Peptoniphilus, a Gram-positive anaerobic coccus, and wound healing outcomes of DFUs

Diabetic foot ulcers (DFUs) lead to nearly 100,000 lower limb amputations annually in the United States. DFUs are colonized by complex microbial communities, and infection is one of the most common reasons for diabetes-related hospitalizations and amputations. In this study, we examined how DFU microbiomes respond to initial sharp debridement and off- loading and how the initial composition associates with 4 week healing outcomes. We employed 16S rRNA next generation sequencing to perform microbial profiling on 50 sam- ples collected from 10 patients with vascularized neuropathic DFUs. Debrided wound sam- ples were obtained at initial visit and after one week from two DFU locations, wound bed and wound edge. Samples of the foot skin outside of the wounds were also collected for compar- ison. We showed that DFU wound beds are colonized by a greater number of distinct bacte- rial phylotypes compared to the wound edge or skin outside the wound. However, no significant microbiome diversity changes occurred at the wound sites after one week of stan- dard care. Finally, increased initial abundance of Gram-positive anaerobic cocci (GPAC), especially Peptoniphilus (p \u3c 0.05; n = 5 subjects), was associated with impaired healing; thus, GPAC’s abundance could be a predictor of the wound-healing outcome

Comparative whole-genome analysis of Streptococcus mutans isolates within and among individuals of different caries status

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74592/1/j.1399-302X.2008.00495.x.pd

Lack of the Delta Subunit of RNA Polymerase Increases Virulence Related Traits of Streptococcus mutans

The delta subunit of the RNA polymerase, RpoE, maintains the transcriptional specificity in Gram-positive bacteria. Lack of RpoE results in massive changes in the transcriptome of the human dental caries pathogen Streptococcus mutans. In this study, we analyzed traits of the ΔrpoE mutant which are important for biofilm formation and interaction with oral microorganisms and human cells and performed a global phenotypic analysis of its physiological functions. The ΔrpoE mutant showed higher self-aggregation compared to the wild type and coaggregated with other oral bacteria and Candida albicans. It formed a biofilm with a different matrix structure and an altered surface attachment. The amount of the cell surface antigens I/II SpaP and the glucosyltransferase GtfB was reduced. The ΔrpoE mutant displayed significantly stronger adhesion to human extracellular matrix components, especially to fibronectin, than the wild type. Its adhesion to human epithelial cells HEp-2 was reduced, probably due to the highly aggregated cell mass. The analysis of 1248 physiological traits using phenotype microarrays showed that the ΔrpoE mutant metabolized a wider spectrum of carbon sources than the wild type and had acquired resistance to antibiotics and inhibitory compounds with various modes of action. The reduced antigenicity, increased aggregation, adherence to fibronection, broader substrate spectrum and increased resistance to antibiotics of the ΔrpoE mutant reveal the physiological potential of S. mutans and show that some of its virulence related traits are increased

Remodeling of the Streptococcus agalactiae Transcriptome in Response to Growth Temperature

BACKGROUND: To act as a commensal bacterium and a pathogen in humans and animals, Streptococcus agalactiae (group B streptococcus, GBS) must be able to monitor and adapt to different environmental conditions. Temperature variation is a one of the most commonly encountered variables. METHODOLOGY/PRINCIPAL FINDINGS: To understand the extent to which GBS modify gene expression in response to temperatures encountered in the various hosts, we conducted a whole genome transcriptome analysis of organisms grown at 30 degrees C and 40 degrees C. We identified extensive transcriptome remodeling at various stages of growth, especially in the stationary phase (significant transcript changes occurred for 25% of the genes). A large proportion of genes involved in metabolism was up-regulated at 30 degrees C in stationary phase. Conversely, genes up-regulated at 40 degrees C relative to 30 degrees C include those encoding virulence factors such as hemolysins and extracellular secreted proteins with LPXTG motifs. Over-expression of hemolysins was linked to larger zones of hemolysis and enhanced hemolytic activity at 40 degrees C. A key theme identified by our study was that genes involved in purine metabolism and iron acquisition were significantly up-regulated at 40 degrees C. CONCLUSION/SIGNIFICANCE: Growth of GBS in vitro at different temperatures resulted in extensive remodeling of the transcriptome, including genes encoding proven and putative virulence genes. The data provide extensive new leads for molecular pathogenesis research

Bioinformatics and Structural Characterization of a Hypothetical Protein from Streptococcus mutans: Implication of Antibiotic Resistance

As an oral bacterial pathogen, Streptococcus mutans has been known as the aetiologic agent of human dental caries. Among a total of 1960 identified proteins within the genome of this organism, there are about 500 without any known functions. One of these proteins, SMU.440, has very few homologs in the current protein databases and it does not fall into any protein functional families. Phylogenetic studies showed that SMU.440 is related to a particular ecological niche and conserved specifically in some oral pathogens, due to lateral gene transfer. The co-occurrence of a MarR protein within the same operon among these oral pathogens suggests that SMU.440 may be associated with antibiotic resistance. The structure determination of SMU.440 revealed that it shares the same fold and a similar pocket as polyketide cyclases, which indicated that it is very likely to bind some polyketide-like molecules. From the interlinking structural and bioinformatics studies, we have concluded that SMU.440 could be involved in polyketide-like antibiotic resistance, providing a better understanding of this hypothetical protein. Besides, the combination of multiple methods in this study can be used as a general approach for functional studies of a protein with unknown function

Activation of the SMU.1882 Transcription by CovR in Streptococcus mutans

In Streptococcus mutans, the global response regulator CovR plays an important role in biofilm formation, stress-tolerance response, and caries production. We have previously shown that CovR acts as a transcriptional repressor by binding to the upstream promoter regions of its target genes. Here, we report that in vivo, CovR activates the transcription of SMU.1882, which encodes a small peptide containing a double-glycine motif. We also show that SMU.1882 is transcriptionally linked to comA that encodes a putative ABC transporter protein. Several genes from man gene clusters that encode mannose phosphotranferase system flank SMU.1882 -comA genes. Genomic comparison with other streptococci indicates that SMU.1882 is uniquely present in S. mutans, while the man operon is conserved among all streptococci, suggesting that a genetic rearrangement might have taken place at this locus. With the use of a transcriptional reporter system and semi-quantitative RT-PCR, we demonstrated the transcriptional regulation of SMU.1882 by CovR. In vitro gel shift and DNase I foot-printing analyses with purified CovR suggest that CovR binds to a large region surrounding the -10 region of the P1882. Using this information and comparing with other CovR regulated promoters, we have developed a putative consensus binding sequence for CovR. Although CovR binds to P1882, in vitro experiments using purified S. mutans RpoD, E. coli RNA polymerase, and CovR did not activate transcription from this promoter. Thus, we speculate that in vivo, CovR may interfere with the binding of a repressor or requires a cofactor

The tuberculosis necrotizing toxin kills macrophages by hydrolyzing NAD.

Mycobacterium tuberculosis (Mtb) induces necrosis of infected cells to evade immune responses. Recently, we found that Mtb uses the protein CpnT to kill human macrophages by secreting its C-terminal domain, named tuberculosis necrotizing toxin (TNT), which induces necrosis by an unknown mechanism. Here we show that TNT gains access to the cytosol of Mtb-infected macrophages, where it hydrolyzes the essential coenzyme NAD(+). Expression or injection of a noncatalytic TNT mutant showed no cytotoxicity in macrophages or in zebrafish zygotes, respectively, thus demonstrating that the NAD(+) glycohydrolase activity is required for TNT-induced cell death. To prevent self-poisoning, Mtb produces an immunity factor for TNT (IFT) that binds TNT and inhibits its activity. The crystal structure of the TNT-IFT complex revealed a new NAD(+) glycohydrolase fold of TNT, the founding member of a toxin family widespread in pathogenic microorganisms