Conserved Aspartate Residues and Phosphorylation in Signal Transduction by the Chemotaxis Protein CheY

The CheY protein is phosphorylated by CheA and dephosphorylated by CheZ as part of the chemotactic signal transduction pathway in Escherichia coli. Phosphorylation of CheY has been proposed to occur on an aspartate residue. Each of the eight aspartate residues of CheY was replaced by using site-directed mutagenesis. Substitutions at Asp-12, Asp-13, or Asp-57 resulted in loss of chemotaxis. Most of the mutant CheY proteins were still phosphorylated by CheA but exhibited modified biochemical properties, including reduced ability to accept phosphate from CheA, altered phosphate group stability, and/or resistance to CheZ-mediated dephosphorylation. The properties of CheY proteins bearing a substitution at position 57 were most aberrant, consistent with the hypothesis that Asp-57 is the normal site of acyl phosphate formation. Evidence for an alternate site of phosphorylation in the Asp-57 mutants is presented. Phosphorylated CheY is believed to cause tumbling behavior. However, a dominant mutant CheY protein that was not phosphorylated in vitro caused tumbling in vivo in the absence of CheA. This phenotype suggests that the role of phosphorylation in the wild-type CheY protein is to stabilize a transient conformational change that can generate tumbling behavior

Science To Support DOE Site Cleanup: The Pacific Northwest National Laboratory Environmental Management Science Program Awards

Pacific Northwest National Laboratory (PNNL) was awarded ten Environmental Management Science Program (EMSP) research grants in fiscal year 1996, six in fiscal year 1997, nine in fiscal year 1998, seven in fiscal year 1999, and five in fiscal year 2000. All of the fiscal year 1996 award projects have published final reports. The 1997 and 1998 award projects have been completed or are nearing completion. Final reports for these awards will be published, so their annual updates will not be included in this document. This section summarizes how each of the 1999 and 2000 grants address significant U.S. Department of Energy (DOE) cleanup issues, including those at the Hanford Site. The technical progress made to date in each of these research projects is addressed in more detail in the individual progress reports contained in this document. The 1999 and 2000 EMSP awards at PNNL are focused primarily in two areas: Tank Waste Remediation, and Soil and Groundwater Cleanup

Insights into the Physiology and Ecology of the Brackish-Water-Adapted Cyanobacterium Nodularia spumigena CCY9414 Based on a Genome-Transcriptome Analysis

Peer reviewe

Strain field analysis on Montserrat (W.I.) as tool for assessing permeable flow paths in the magmatic system of Soufrière Hills Volcano

Strain dilatometers have been operated on the volcanic island of Montserrat (West Indies) for more than a decade and have proven to be a powerful technique to approach short-term dynamics in the deformational field in response to pressure changes in the magmatic system of the andesitic dome-building Soufrière Hills Volcano (SHV). We here demonstrate that magmatic activity in each of the different segments of the SHV magmatic system (shallow dyke-conduit, upper and lower magma chambers) generates a characteristic strain pattern that allows the identification of operating sources in the plumbing system based on a simple scheme of amplitude ratios. We use this method to evaluate strain data from selected Vulcanian explosions and gas emission events that occurred at SHV between 2003 and 2012. Our results show that the events were initiated by a short phase of contraction of either one or both magma chambers and a simultaneous inflation of the shallow feeder system. The initial phase of the events usually lasted only tens to hundreds of seconds before the explosion/gas emission started and the system recovered. The short duration of this process points at rapid transport of fluids rather than magma ascent to generate the pressure changes. We suggest the propagation of tensile hydraulic fractures as viable mechanism to provide a pathway for fluid migration in the magmatic system at the observed time scale. Fluid mobilization was initiated by a sudden destabilization of large pockets of already segregated fluid in the magma chambers. Our study demonstrates that geodetic observables can provide unprecedented insights into complex dynamic processes within a magmatic system commonly assessed by theoretical modeling and petrologic observations. Key Points Strain data analysis from explosions/degassing events at Soufriere Hills Volcano Pressure release deep within the magmatic system sec-min prior to events Rapid gas rise from magma reservoir to surface via tensile hydraulic fractures © 2014. American Geophysical Union. All Rights Reserved

Discovering collectively informative descriptors from high-throughput experiments

<p>Abstract</p> <p>Background</p> <p>Improvements in high-throughput technology and its increasing use have led to the generation of many highly complex datasets that often address similar biological questions. Combining information from these studies can increase the reliability and generalizability of results and also yield new insights that guide future research.</p> <p>Results</p> <p>This paper describes a novel algorithm called BLANKET for symmetric analysis of two experiments that assess informativeness of descriptors. The experiments are required to be related only in that their descriptor sets intersect substantially and their definitions of case and control are consistent. From resulting lists of n descriptors ranked by informativeness, BLANKET determines <b>shortlists </b>of descriptors from each experiment, generally of different lengths p and q. For any pair of shortlists, four numbers are evident: the number of descriptors appearing in both shortlists, in exactly one shortlist, or in neither shortlist. From the associated contingency table, BLANKET computes Right Fisher Exact Test (RFET) values used as scores over a plane of possible pairs of shortlist lengths <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr></abbrgrp>. BLANKET then chooses a pair or pairs with RFET score less than a threshold; the threshold depends upon n and shortlist length limits and represents a quality of intersection achieved by less than 5% of random lists.</p> <p>Conclusions</p> <p>Researchers seek within a universe of descriptors some minimal subset that collectively and efficiently predicts experimental outcomes. Ideally, any smaller subset should be insufficient for reliable prediction and any larger subset should have little additional accuracy. As a method, BLANKET is easy to conceptualize and presents only moderate computational complexity. Many existing databases could be mined using BLANKET to suggest optimal sets of predictive descriptors.</p

Predicting Bison Migration out of Yellowstone National Park Using Bayesian Models

Long distance migrations by ungulate species often surpass the boundaries of preservation areas where conflicts with various publics lead to management actions that can threaten populations. We chose the partially migratory bison (Bison bison) population in Yellowstone National Park as an example of integrating science into management policies to better conserve migratory ungulates. Approximately 60% of these bison have been exposed to bovine brucellosis and thousands of migrants exiting the park boundary have been culled during the past two decades to reduce the risk of disease transmission to cattle. Data were assimilated using models representing competing hypotheses of bison migration during 1990–2009 in a hierarchal Bayesian framework. Migration differed at the scale of herds, but a single unifying logistic model was useful for predicting migrations by both herds. Migration beyond the northern park boundary was affected by herd size, accumulated snow water equivalent, and aboveground dried biomass. Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded. Simulations of migrations over the next decade suggest that allowing increased numbers of bison beyond park boundaries during severe climate conditions may be the only means of avoiding episodic, large-scale reductions to the Yellowstone bison population in the foreseeable future. This research is an example of how long distance migration dynamics can be incorporated into improved management policies

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment