Mycobacterium tuberculosis gene Rv2136c is dispensable for acid resistance and virulence in mice

Cell wall peptidoglycan in Mycobacterium tuberculosis: An Achilles' heel for the TB-causing pathogen

Tuberculosis (TB), caused by the intracellular pathogen Mycobacterium tuberculosis, remains one of the leading causes of mortality across the world. There is an urgent requirement to build a robust arsenal of effective antimicrobials, targeting novel molecular mechanisms to overcome the challenges posed by the increase of antibiotic resistance in TB. Mycobacterium tuberculosis has a unique cell envelope structure and composition, containing a peptidoglycan layer that is essential for maintaining cellular integrity and for virulence. The enzymes involved in the biosynthesis, degradation, remodelling and recycling of peptidoglycan have resurfaced as attractive targets for anti-infective drug discovery. Here, we review the importance of peptidoglycan, including the structure, function and regulation of key enzymes involved in its metabolism. We also discuss known inhibitors of ATP-dependent Mur ligases, and discuss the potential for the development of pan-enzyme inhibitors targeting multiple Mur ligases.

The structural basis of acid resistance in Mycobacterium tuberculosis: insights from multiple pH regime molecular dynamics simulations

The dormant Mycobacterium tuberculosis is evolved to develop the tolerance against the acidification of phagolysosome by the action of gamma interferon. The molecular mechanism responsible for the development of the resistance towards the acidic conditions in M. tuberculosis is not fully understood. Therefore, the current analysis was performed which studies the mechanism of acid tolerance by correlating the alteration in the protonation state of conserved residues in virulent proteins with changes in their folding states. The pH dependencies of proteins were studied using an efficient computational scheme which enables the understanding of their conformational behavior by molecular dynamics (MD) simulations. The adopted methodology involves cyclically updating of the ionization states of titrable residues in the studied proteins with conventional MD steps, which were applied to the newly generated ionization configuration. Significant pH-dependent protein structural stability parameters consistent with the changes of the protonation states of conserved residues were observed. Among the studied proteins, the peptidoglycan binding protein ompATB, carboxylesterase LipF and two-component systems' transcriptional regulator PhoP showed highest structural conservation in the observed acidic pH range throughout the course of MD simulations. The current study provides a better understanding of acid tolerance mechanisms present in M. tuberculosis and can facilitate the drug development strategies against the dormant protein targets.Communicated by Ramaswamy H. Sarma.

Characterization of blue light irradiation effects on pathogenic and nonpathogenic Escherichia coli

Blue light irradiation (BLI) is an FDA-approved method for treating certain types of infections, like acne, and is becoming increasingly attractive as an antimicrobial strategy as the prevalence of antibiotic-resistant "superbugs" rises. However, no study has delineated the effectiveness of BLI throughout different bacterial growth phases, especially in more BLI-tolerant organisms such as Escherichia coli. While the vast majority of E. coli strains are nonpathogenic, several E. coli pathotypes exist that cause infection within and outside the gastrointestinal tract. Here, we compared the response of E. coli strains from five phylogenetic groups to BLI with a 455 nm wavelength (BLI₄₅₅ ), using colony-forming unit and ATP measurement assays. Our results revealed that BLI₄₅₅ is not bactericidal, but can retard E. coli growth in a manner that is dependent on culture age and strain background. This observation is critical, given that bacteria on and within mammalian hosts are found in different phases of growth.

Functional characterization of two members of histidine phosphatase superfamily in Mycobacterium tuberculosis

Background

Functional characterization of genes in important pathogenic bacteria such as Mycobacterium tuberculosis is imperative. Rv2135c, which was originally annotated as conserved hypothetical, has been found to be associated with membrane protein fractions of H37Rv strain. The gene appears to contain histidine phosphatase motif common to both cofactor-dependent phosphoglycerate mutases and acid phosphatases in the histidine phosphatase superfamily. The functions of many of the members of this superfamily are annotated based only on similarity to known proteins using automatic annotation systems, which can be erroneous. In addition, the motif at the N-terminal of Rv2135c is ‘RHA’ unlike ‘RHG’ found in most members of histidine phosphatase superfamily. These necessitate the need for its experimental characterization. The crystal structure of Rv0489, another member of the histidine phosphatase superfamily in M. tuberculosis, has been previously reported. However, its biochemical characteristics remain unknown. In this study, Rv2135c and Rv0489 from M. tuberculosis were cloned and expressed in Escherichia coli with 6 histidine residues tagged at the C terminal.

Results

Characterization of the purified recombinant proteins revealed that Rv0489 possesses phosphoglycerate mutase activity while Rv2135c does not. However Rv2135c has an acid phosphatase activity with optimal pH of 5.8. Kinetic parameters of Rv2135c and Rv0489 are studied, confirming that Rv0489 is a cofactor dependent phosphoglycerate mutase of M. tuberculosis. Additional characterization showed that Rv2135c exists as a tetramer while Rv0489 as a dimer in solution.

Conclusion

Most of the proteins orthologous to Rv2135c in other bacteria are annotated as phosphoglycerate mutases or hypothetical proteins. It is possible that they are actually phosphatases. Experimental characterization of a sufficiently large number of bacterial histidine phosphatases will increase the accuracy of the automatic annotation systems towards a better understanding of this important group of enzymes.

Whole cell screen for inhibitors of pH homeostasis in Mycobacterium tuberculosis

Bacterial pathogens like Mycobacterium tuberculosis (Mtb) encounter acidic microenvironments in the host and must maintain their acid-base homeostasis to survive. A genetic screen identified two Mtb strains that cannot control intrabacterial pH (pH_IB) in an acidic environment; infection with either strain led to severe attenuation in mice. To search for additional proteins that Mtb requires to survive at low pH, we introduced a whole-cell screen for compounds that disrupt pH_IB, along with counter-screens that identify ionophores and membrane perturbors. Application of these methods to a natural product library identified four compounds of interest, one of which may inhibit novel pathway(s). This approach yields compounds that may lead to the identification of pathways that allow Mtb to survive in acidic environments, a setting in which Mtb is resistant to most of the drugs currently used to treat tuberculosis.

Computational comparative study of tuberculosis proteomes using a model learned from signal peptide structures

Secretome analysis is important in pathogen studies. A fundamental and convenient way to identify secreted proteins is to first predict signal peptides, which are essential for protein secretion. However, signal peptides are highly complex functional sequences that are easily confused with transmembrane domains. Such confusion would obviously affect the discovery of secreted proteins. Transmembrane proteins are important drug targets, but very few transmembrane protein structures have been determined experimentally; hence, prediction of the structures is essential. In the field of structure prediction, researchers do not make assumptions about organisms, so there is a need for a general signal peptide predictor.To improve signal peptide prediction without prior knowledge of the associated organisms, we present a machine-learning method, called SVMSignal, which uses biochemical properties as features, as well as features acquired from a novel encoding, to capture biochemical profile patterns for learning the structures of signal peptides directly.We tested SVMSignal and five popular methods on two benchmark datasets from the SPdb and UniProt/Swiss-Prot databases, respectively. Although SVMSignal was trained on an old dataset, it performed well, and the results demonstrate that learning the structures of signal peptides directly is a promising approach. We also utilized SVMSignal to analyze proteomes in the entire HAMAP microbial database. Finally, we conducted a comparative study of secretome analysis on seven tuberculosis-related strains selected from the HAMAP database. We identified ten potential secreted proteins, two of which are drug resistant and four are potential transmembrane proteins.SVMSignal is publicly available at http://bio-cluster.iis.sinica.edu.tw/SVMSignal. It provides user-friendly interfaces and visualizations, and the prediction results are available for download.