Inferring Carbon Sources from Gene Expression Profiles Using Metabolic Flux Models

Background: Bacteria have evolved the ability to efficiently and resourcefully adapt to changing environments. A key means by which they optimize their use of available nutrients is through adjustments in gene expression with consequent changes in enzyme activity. We report a new method for drawing environmental inferences from gene expression data. Our method prioritizes a list of candidate carbon sources for their compatibility with a gene expression profile using the framework of flux balance analysis to model the organism’s metabolic network. Principal Findings: For each of six gene expression profiles for Escherichia coli grown under differing nutrient conditions, we applied our method to prioritize a set of eighteen different candidate carbon sources. Our method ranked the correct carbon source as one of the top three candidates for five of the six expression sets when used with a genome-scale model. The correct candidate ranked fifth in the remaining case. Additional analyses show that these rankings are robust with respect to biological and measurement variation, and depend on specific gene expression, rather than general expression level. The gene expression profiles are highly adaptive: simulated production of biomass averaged 94.84% of maximum when the in silico carbon source matched the in vitro source of the expression profile, and 65.97% when it did not. Conclusions: Inferences about a microorganism’s nutrient environment can be made by integrating gene expression data into a metabolic framework. This work demonstrates that reaction flux limits for a model can be computed which are realistic in the sense that they affect in silico growth in a manner analogous to that in which a microorganism’s alteration of gene expression is adaptive to its nutrient environment.National Institute of Allergy and Infectious Diseases (U.S.) (grant HHSN 2722008000059C)National Institute of Allergy and Infectious Diseases (U.S.) (grant HHSN 26620040000IC)Bill & Melinda Gates Foundation (grant 18651010-37352-A

Probabilistic Inference for Nucleosome Positioning with MNase-Based or Sonicated Short-Read Data

We describe a model-based method, PING, for predicting nucleosome positions in MNase-Seq and MNase- or sonicated-ChIP-Seq data. PING compares favorably to NPS and TemplateFilter in scalability, accuracy and robustness to low read density. To demonstrate that PING predictions from widely available sonicated data can have sufficient spatial resolution to be to be useful for biological inference, we use Illumina H3K4me1 ChIP-seq data to detect changes in nucleosome positioning around transcription factor binding sites due to tamoxifen stimulation, to discriminate functional and non-functional transcription factor binding sites more effectively than with enrichment profiles, and to confirm that the pioneer transcription factor Foxa2 associates with the accessible major groove of nucleosomal DNA

Organizational readiness to change assessment (ORCA): Development of an instrument based on the Promoting Action on Research in Health Services (PARIHS) framework

<p>Abstract</p> <p>Background</p> <p>The Promoting Action on Research Implementation in Health Services, or PARIHS, framework is a theoretical framework widely promoted as a guide to implement evidence-based clinical practices. However, it has as yet no pool of validated measurement instruments that operationalize the constructs defined in the framework. The present article introduces an Organizational Readiness to Change Assessment instrument (ORCA), organized according to the core elements and sub-elements of the PARIHS framework, and reports on initial validation.</p> <p>Methods</p> <p>We conducted scale reliability and factor analyses on cross-sectional, secondary data from three quality improvement projects (n = 80) conducted in the Veterans Health Administration. In each project, identical 77-item ORCA instruments were administered to one or more staff from each facility involved in quality improvement projects. Items were organized into 19 subscales and three primary scales corresponding to the core elements of the PARIHS framework: (1) Strength and extent of evidence for the clinical practice changes represented by the QI program, assessed with four subscales, (2) Quality of the organizational context for the QI program, assessed with six subscales, and (3) Capacity for internal facilitation of the QI program, assessed with nine subscales.</p> <p>Results</p> <p>Cronbach's alpha for scale reliability were 0.74, 0.85 and 0.95 for the evidence, context and facilitation scales, respectively. The evidence scale and its three constituent subscales failed to meet the conventional threshold of 0.80 for reliability, and three individual items were eliminated from evidence subscales following reliability testing. In exploratory factor analysis, three factors were retained. Seven of the nine facilitation subscales loaded onto the first factor; five of the six context subscales loaded onto the second factor; and the three evidence subscales loaded on the third factor. Two subscales failed to load significantly on any factor. One measured resources in general (from the context scale), and one clinical champion role (from the facilitation scale).</p> <p>Conclusion</p> <p>We find general support for the reliability and factor structure of the ORCA. However, there was poor reliability among measures of evidence, and factor analysis results for measures of general resources and clinical champion role did not conform to the PARIHS framework. Additional validation is needed, including criterion validation.</p

Early Stage Biomineralization in the Periostracum of the ‘Living Fossil’ Bivalve Neotrigonia

A detailed investigation of the shell formation of the palaeoheterodont ‘living fossil’ Neotrigonia concentrated on the timing and manufacture of the calcified ‘bosses’ which stud the outside of all trigonioid bivalves (extant and fossil) has been conducted. Electron microscopy and optical microscopy revealed that Neotrigonia spp. have a spiral-shaped periostracal groove. The periostracum itself is secreted by the basal cell, as a thin dark pellicle, becoming progressively transformed into a thin dark layer by additions of secretions from the internal outer mantle fold. Later, intense secretion of the internal surface of the outer mantle fold forms a translucent layer, which becomes transformed by tanning into a dark layer. The initiation of calcified bosses occurred at a very early stage of periostracum formation, deep within the periostracal groove immediately below the initialmost dark layer. At this stage, they consist of a series of polycyclically twinned crystals. The bosses grow as the periostracum traverse through the periostracal groove, in coordination with the thickening of the dark periostracal layer and until, upon reaching the mantle edge, they impinge upon each other and become transformed into large prisms separated by dark periostracal walls. In conclusion, the initial bosses and the external part of the prismatic layer are fully intraperiostracal. With later growth, the prisms transform into fibrous aggregates, although the details of the process are unknown. This reinforces the relationships with other groups that have the ability to form intraperiostracal calcifications, for example the unionoids with which the trigonioids form the clade Paleoheterodonta. The presence of similar structures in anomalodesmatans and other euheterodonts raises the question of whether this indicates a relationship or represents a convergence. The identification of very early calcification within an organic sheet has interesting implications for our understanding of how shells may have evolved.Coordinated Research Projects CGL2010-20748-C02-01 (AGC, EMH) and 02 (CS) (DGI, Spanish MICINN); the Research Group RNM363 (Consejería de Economía, Investigación, Ciencia y Empleo, Junta de Andalucía); and the FP7 COST Action TD0903 of the European Community

Capturing Single Cell Genomes of Active Polysaccharide Degraders: An Unexpected Contribution of Verrucomicrobia

Microbial hydrolysis of polysaccharides is critical to ecosystem functioning and is of great interest in diverse biotechnological applications, such as biofuel production and bioremediation. Here we demonstrate the use of a new, efficient approach to recover genomes of active polysaccharide degraders from natural, complex microbial assemblages, using a combination of fluorescently labeled substrates, fluorescence-activated cell sorting, and single cell genomics. We employed this approach to analyze freshwater and coastal bacterioplankton for degraders of laminarin and xylan, two of the most abundant storage and structural polysaccharides in nature. Our results suggest that a few phylotypes of Verrucomicrobia make a considerable contribution to polysaccharide degradation, although they constituted only a minor fraction of the total microbial community. Genomic sequencing of five cells, representing the most predominant, polysaccharide-active Verrucomicrobia phylotype, revealed significant enrichment in genes encoding a wide spectrum of glycoside hydrolases, sulfatases, peptidases, carbohydrate lyases and esterases, confirming that these organisms were well equipped for the hydrolysis of diverse polysaccharides. Remarkably, this enrichment was on average higher than in the sequenced representatives of Bacteroidetes, which are frequently regarded as highly efficient biopolymer degraders. These findings shed light on the ecological roles of uncultured Verrucomicrobia and suggest specific taxa as promising bioprospecting targets. The employed method offers a powerful tool to rapidly identify and recover discrete genomes of active players in polysaccharide degradation, without the need for cultivation

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

Clinical correlates of grey matter pathology in multiple sclerosis

Traditionally, multiple sclerosis has been viewed as a disease predominantly affecting white matter. However, this view has lately been subject to numerous changes, as new evidence of anatomical and histological changes as well as of molecular targets within the grey matter has arisen. This advance was driven mainly by novel imaging techniques, however, these have not yet been implemented in routine clinical practice. The changes in the grey matter are related to physical and cognitive disability seen in individuals with multiple sclerosis. Furthermore, damage to several grey matter structures can be associated with impairment of specific functions. Therefore, we conclude that grey matter damage - global and regional - has the potential to become a marker of disease activity, complementary to the currently used magnetic resonance markers (global brain atrophy and T2 hyperintense lesions). Furthermore, it may improve the prediction of the future disease course and response to therapy in individual patients and may also become a reliable additional surrogate marker of treatment effect