Biology subjects

Robinson, A.

Publications and source records attributed to Robinson, A..

3 recordsLinked to original sources

bioRxiv2017

The essential genome of Escherichia coli K-12

Transposon-Directed Insertion-site Sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries and therefore it remains unclear whether the two methodologies are comparable. To address this, a high density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false positive identification of essential gene candidates, statistical data analysis included corrections for both gene length and genome length. Through this analysis new essential genes and genes previously incorrectly designated as essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects and fine resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis datasets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.\n\nIMPORTANCEIncentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in E. coli, we constructed a very high density transposon mutant library. Initial automated analysis of the resulting data revealed many discrepancies when compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high density TraDIS sequencing data for each putative essential gene for the model laboratory organism, Escherichia coli. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone and a provides new standard for the analysis of TraDIS data.

microbiology↗

bioRxiv2017

A genetic screen suggests an alternative mechanism for inhibition of SecA by azide

Sodium azide prevents bacterial growth by inhibiting the activity of SecA, which is required for translocation of proteins across the cytoplasmic membrane. Azide inhibits ATP turnover in vitro, but its mechanism of action in vivo is unclear. To investigate how azide inhibits SecA in cells, we used transposon directed insertion-site sequencing (TraDIS) to screen a library of transposon insertion mutants for mutations that affect the susceptibility of E. coli to azide. Insertions disrupting components of the Sec machinery generally increased susceptibility to azide, but insertions truncating the C-terminal tail (CTT) of SecA decreased susceptibility of E. coli to azide. Treatment of cells with azide caused increased aggregation of the CTT, suggesting that azide disrupts its structure. Analysis of the metal-ion content of the CTT indicated that SecA binds to iron and the azide disrupts the interaction of the CTT with iron. Azide also disrupted binding of SecA to membrane phospholipids, as did alanine substitutions in the metal-coordinating amino acids. Furthermore, treating purified phospholipid-bound SecA with azide in the absence of added nucleotide disrupted binding of SecA to phospholipids. Our results suggest that azide does not inhibit SecA by inhibiting the rate of ATP turnover in vivo. Rather, azide inhibits SecA by causing it to \"backtrack\" from the ADP-bound to the ATP-bound conformation, which disrupts the interaction of SecA with the cytoplasmic membrane.\n\nSignificance statementSecA is a bacterial ATPase that is required for the translocation of a subset of secreted proteins across the cytoplasmic membrane. Sodium azide is a well-known inhibitor of SecA, but its mechanism of action in vivo is poorly understood. To investigate this mechanism, we examined the effect of azide on the growth of a library of [~]1 million transposon insertion mutations. Our results suggest that azide causes SecA to backtrack in its ATPase cycle, which disrupts binding of SecA to the membrane and to its metal cofactor, which is iron. Our results provide insight into the molecular mechanism by which SecA drives protein translocation and how this essential biological process can be disrupted.

microbiology↗

bioRxiv2017

MitoCore: A Curated Constraint-Based Model For Simulating Human Central Metabolism

BackgroundThe complexity of metabolic networks can make the origin and impact of profound changes in central metabolism occurring during disease difficult to understand. Computer simulations can help unravel this complexity, and progress has advanced in genome-scale metabolic models. However, many current models produce unrealistic results when challenged to simulate abnormal metabolism as they include incorrect specification and localization of reactions and transport steps, incorrect reaction parameters, and confounding of prosthetic groups and free metabolites in reactions. Other common drawbacks are due to their scale, such as being difficult to parameterise and simulation results being hard to interpret. Therefore, it remains important to develop smaller, manually curated models to represent central metabolism accurately.\n\nResultsWe present MitoCore, a manually curated constraint-based computer model of human metabolism that incorporates the complexity of central metabolism and simulates this metabolism successfully under normal and abnormal conditions, including hypoxia and mitochondrial diseases. MitoCore describes 324 metabolic reactions, 83 transport steps between mitochondrion and cytosol, and 74 metabolite inputs and outputs through the plasma membrane, to produce a model of manageable scale for easy data interpretation. Its key innovations include accurate partitioning of metabolism between cytosol and mitochondrial matrix; correct modelling of connecting transport steps; proper differentiation of prosthetic groups and free co-factors in reactions; and a new representation of the respiratory chain and the proton motive force. MitoCores default parameters simulate normal cardiomyocyte metabolism, and to improve usability and allow comparison with other models and types of analysis, its reactions and metabolites have extensive annotation, and cross-reference identifiers from Virtual Metabolic Human database and KEGG. These innovations--including over 100 reactions absent or modified from Recon 2--are essential to model central metabolism accurately.\n\nConclusionWe anticipate MitoCore as a research tool for scientists, from experimentalists looking to interpret data and generate further hypotheses, to experienced modellers predicting the consequences of disease or using computationally intensive methods that are infeasible with larger models, as well as a teaching tool for those new to modelling and needing a small manageable model on which to learn and experiment.

systems biology↗