Dataset Information

The Mycobacterium tuberculosis H37Ra gene MRA_1916 causes growth defects upon down-regulation.

ABSTRACT: D-amino acid oxidases play an important role in converting D-amino acids to their corresponding ?-keto acids. MRA_1916 of Mycobacterium tuberculosis H37Ra (Mtb-Ra) is annotated to be a D-amino acid oxidase (DAO). However, not much information is available about its physiological role during Mtb-Ra growth and survival. The present study was taken-up to understand the role of DAO during different stages of growth and effect of its down-regulation on growth. Recombinant Mtb-Ra strains with DAO and GlcB (malate synthase: MRA_1848) gene knockdown were developed and their growth was studied using Microtiter Alamar Blue Assay (MABA) with glycerol, acetate and glycine as a carbon source. Ethyl bromopyruvate (BrP) was used as an inhibitor of GlcB. MABA study showed inhibition of wild-type (WT) and knockdowns in the presence of BrP (2.5mM). However, growth inhibition of WT was less noticeable at lower concentrations of BrP. Mtb-Ra with DAO knockdown showed poor utilization of glycine in the presence of BrP. The DAO localization study showed its prominent distribution in cytosolic fraction and to some extent in cell wall and membrane fractions. Growth profile of WT under oxygen and nutritional stress showed changes in expression of DAO, GlcB, PckA (phosphoenolpyruvate carboxykinase: MRA_0219) and GlyA1 (serine hydroxymethyltransferase: MRA_1104).

SUBMITTER: Singh KS

PROVIDER: S-EPMC4632087 | biostudies-other | 2015

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

The Mycobacterium tuberculosis H37Ra gene MRA_1916 causes growth defects upon down-regulation.

Singh Kumar Sachin KS Singh Sudheer Kumar SK

Scientific reports 20151104

D-amino acid oxidases play an important role in converting D-amino acids to their corresponding α-keto acids. MRA_1916 of Mycobacterium tuberculosis H37Ra (Mtb-Ra) is annotated to be a D-amino acid oxidase (DAO). However, not much information is available about its physiological role during Mtb-Ra growth and survival. The present study was taken-up to understand the role of DAO during different stages of growth and effect of its down-regulation on growth. Recombinant Mtb-Ra strains with DAO and ...[more]

PMID: 26531045

Similar Datasets

Project description:Genome-scale metabolic models of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, have been envisioned as a platform for drug discovery. By systematically probing the networks that underpin such models, the reactions that are essential for Mtb are identified. A majority of these reactions are catalyzed by enzymes and thus represent candidate drug targets to fight an Mtb infection. Nevertheless, this is complicated by the limited knowledge on the environment that Mtb encounters during infection. Modeling the behavior of the bacteria during infection requires knowledge of the so-called biomass reaction that represents bacterial biomass composition. This composition varies in different environments or bacterial growth phases. Accurate modeling of the metabolic state requires a precise biomass reaction for the described condition. In recent years, additional insights in the in-host environment occupied by Mtb have been gained as transcript abundance data of interacting host and pathogen have become available. Therefore, we used transcript abundance data and developed a straightforward and systematic method to obtain a condition-specific biomass reaction for Mtb during in vitro growth and during infection of its host. The method described herein is virtually free of any pre-set assumptions on uptake rates of nutrients, making it suitable for exploring environments with limited accessibility. The condition-specific biomass reaction represents the "metabolic objective" of Mtb in a given environment (in-host growth and growth on defined medium) at a specific time point, and as such allows modeling the bacterial metabolic state in these environments. Five different biomass reactions were used to predict nutrient uptake rates and gene essentiality. Predictions were subsequently compared to available experimental data. Our results show that nutrient uptake can accurately be predicted. Gene essentiality can also be predicted but accurate predictions remain difficult to obtain. In conclusion, a viable strategy to model Mtb metabolism in hard-to-access environments that is virtually free of pre-set assumptions is provided.

Dataset Information

The Mycobacterium tuberculosis H37Ra gene MRA_1916 causes growth defects upon down-regulation.

Publications

The Mycobacterium tuberculosis H37Ra gene MRA_1916 causes growth defects upon down-regulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets