The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Interaction-Dependent PCR: Identification of Ligand−Target Pairs from Libraries of Ligands and Libraries of Targets in a Single Solution-Phase Experiment

Interaction-dependent PCR (IDPCR) is a solution-phase method to identify binding partners from combined libraries of small-molecule ligands and targets in a single experiment. Binding between DNA-linked targets and DNA-linked ligands induces formation of an extendable duplex. Extension links codes that identify the ligand and target into one selectively amplifiable DNA molecule. In a model selection, IDPCR resulted in the enrichment of DNA encoding all five known protein−ligand pairs out of 67 599 possible sequences.Chemistry and Chemical Biolog

Towards a consistent mechanism of emulsion polymerization—new experimental details

The application of atypical experimental methods such as conductivity measurements, optical microscopy, and nonstirred polymerizations to investigations of the ‘classical’ batch ab initio emulsion polymerization of styrene revealed astonishing facts. The most important result is the discovery of spontaneous emulsification leading to monomer droplets even in the quiescent styrene in water system. These monomer droplets with a size between a few and some hundreds of nanometers, which are formed by spontaneous emulsification as soon as styrene and water are brought into contact, have a strong influence on the particle nucleation, the particle morphology, and the swelling of the particles. Experimental results confirm that micelles of low-molecular-weight surfactants are not a major locus of particle nucleation. Brownian dynamics simulations show that the capture of matter by the particles strongly depends on the polymer volume fraction and the size of the captured species (primary free radicals, oligomers, single monomer molecules, or clusters)

Metabolomic and transcriptomic analysis of the rice response to the bacterial blight pathogen Xanthomonas oryzae pv. oryzae

Bacterial leaf blight (BLB), caused by Xanthomonas oryzae pv. oryzae (Xoo), gives rise to devastating crop losses in rice. Disease resistant rice cultivars are the most economical way to combat the disease. The TP309 cultivar is susceptible to infection by Xoo strain PXO99. A transgenic variety, TP309_Xa21, expresses the pattern recognition receptor Xa21, and is resistant. PXO99△raxST, a strain lacking the raxST gene, is able to overcome Xa21-mediated immunity. We used a single extraction solvent to demonstrate comprehensive metabolomics and transcriptomics profiling under sample limited conditions, and analyze the molecular responses of two rice lines challenged with either PXO99 or PXO99△raxST. LC–TOF raw data file filtering resulted in better within group reproducibility of replicate samples for statistical analyses. Accurate mass match compound identification with molecular formula generation (MFG) ranking of 355 masses was achieved with the METLIN database. GC–TOF analysis yielded an additional 441 compounds after BinBase database processing, of which 154 were structurally identified by retention index/MS library matching. Multivariate statistics revealed that the susceptible and resistant genotypes possess distinct profiles. Although few mRNA and metabolite differences were detected in PXO99 challenged TP309 compared to mock, many differential changes occurred in the Xa21-mediated response to PXO99 and PXO99△raxST. Acetophenone, xanthophylls, fatty acids, alkaloids, glutathione, carbohydrate and lipid biosynthetic pathways were affected. Significant transcriptional induction of several pathogenesis related genes in Xa21 challenged strains, as well as differential changes to GAD, PAL, ICL1 and Glutathione-S-transferase transcripts indicated limited correlation with metabolite changes under single time point global profiling conditions

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods

The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

Anaerobiosis revisited: growth of Saccharomyces cerevisiae under extremely low oxygen availability

The budding yeast Saccharomyces cerevisiae plays an important role in biotechnological applications, ranging from fuel ethanol to recombinant protein production. It is also a model organism for studies on cell physiology and genetic regulation. Its ability to grow under anaerobic conditions is of interest in many industrial applications. Unlike industrial bioreactors with their low surface area relative to volume, ensuring a complete anaerobic atmosphere during microbial cultivations in the laboratory is rather difficult. Tiny amounts of O2 that enter the system can vastly influence product yields and microbial physiology. A common procedure in the laboratory is to sparge the culture vessel with ultrapure N2 gas; together with the use of butyl rubber stoppers and norprene tubing, O2 diffusion into the system can be strongly minimized. With insights from some studies conducted in our laboratory, we explore the question ‘how anaerobic is anaerobiosis?’. We briefly discuss the role of O2 in non-respiratory pathways in S. cerevisiae and provide a systematic survey of the attempts made thus far to cultivate yeast under anaerobic conditions. We conclude that very few data exist on the physiology of S. cerevisiae under anaerobiosis in the absence of the anaerobic growth factors ergosterol and unsaturated fatty acids. Anaerobicity should be treated as a relative condition since complete anaerobiosis is hardly achievable in the laboratory. Ideally, researchers should provide all the details of their anaerobic set-up, to ensure reproducibility of results among different laboratories. A correction to this article is available online at http://eprints.whiterose.ac.uk/131930/ https://doi.org/10.1007/s00253-018-9036-

Oxygen therapy attenuates neuroinflammation after spinal cord injury

Abstract Acute hyperbaric O2 (HBO) therapy after spinal cord injury (SCI) can reduce inflammation and increase neuronal survival. To our knowledge, it is unknown if these benefits of HBO require hyperbaric vs. normobaric hyperoxia. We used a C4 lateralized contusion SCI in adult male and female rats to test the hypothesis that the combination of hyperbaria and 100% O2 (i.e. HBO) more effectively mitigates spinal inflammation and neuronal loss, and enhances respiratory recovery, as compared to normobaric 100% O2. Experimental groups included spinal intact, SCI no O2 therapy, and SCI + 100% O2 delivered at normobaric pressure (1 atmosphere, ATA), or at 2- or 3 ATA. O2 treatments lasted 1-h, commenced within 2-h of SCI, and were repeated for 10 days. The spinal inflammatory response was assessed with transcriptomics (RNAseq) and immunohistochemistry. Gene co-expression network analysis showed that the strong inflammatory response to SCI was dramatically diminished by both hyper- and normobaric O2 therapy. Similarly, both HBO and normobaric O2 treatments reduced the prevalence of immunohistological markers for astrocytes (glial fibrillary acidic protein) and microglia (ionized calcium binding adaptor molecule) in the injured spinal cord. However, HBO treatment also had unique impacts not detected in the normobaric group including upregulation of an anti-inflammatory cytokine (interleukin-4) in the plasma, and larger inspiratory tidal volumes at 10-days (whole body-plethysmography measurements). We conclude that normobaric O2 treatment can reduce the spinal inflammatory response after SCI, but pressured O2 (i.e., HBO) provides further benefit