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Shatsky, M.

Publications and source records attributed to Shatsky, M..

2 recordsLinked to original sources

Large-scale Genetic Characterization of a Model Sulfate Reducing Bacterium

Sulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources, and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

microbiology↗

A general method to predict the effect of single amino acid substitutions on enzyme catalytic activity

Over the past thirty years, site-directed mutagenesis has become established as one of the most powerful techniques to probe enzyme reaction mechanisms1-3. Substitutions of active site residues are most likely to yield significant perturbations in kinetic parameters, but there are many examples of profound changes in these values elicited by remote mutations4-6. Ortholog comparisons of extant sequences show that many mutations do not have profound influence on enzyme function. As the number of potential single natural amino acid substitutions that can be introduced in a protein of N amino acids in length by directed mutation is very large (19 * N), it would be useful to have a method to predict which amino acid substitutions are more likely to introduce significant changes in kinetic parameters in order to design meaningful probes into enzyme function. What is especially desirable is the identification of critical residues that do not contact the substrate directly, and may be remote from the active site.\n\nWe collected literature data reflecting the effects of 2,804 mutations on kinetic properties for 12 enzymes. These data along with characteristic predictors were used in a machine-learning scheme to train a classifier to predict the effect of mutation. Use of this algorithm allows one to predict with a 2.5-fold increase in precision, if a given mutation, made anywhere in the enzyme, will cause a decrease in kcat/Km value of [≥] 95%. The improved precision allows the experimentalist to reduce the number of mutations necessary to probe the enzyme reaction mechanism.

bioinformatics↗