Regulation of homocysteine metabolism by Mycobacterium tuberculosis S-adenosylhomocysteine hydrolase

Mycobacterium tuberculosis modulates expression of various metabolism-related genes to adapt in the adverse host environment. The gene coding for M. tuberculosis S-adenosylhomocysteine hydrolase (Mtb-SahH) is essential for optimal growth and the protein product is involved in intermediary metabolism. However, the relevance of SahH in mycobacterial physiology is unknown. In this study, we analyze the role of Mtb-SahH in regulating homocysteine concentration in surrogate host Mycobacterium smegmatis. Mtb-SahH catalyzes reversible hydrolysis of S-adenosylhomocysteine to homocysteine and adenosine and we demonstrate that the conserved His363 residue is critical for bi-directional catalysis. Mtb-SahH is regulated by serine/threonine phosphorylation of multiple residues by M. tuberculosis PknB. Major phosphorylation events occur at contiguous residues Thr219, Thr220 and Thr221, which make pivotal contacts with cofactor NAD+. Consequently, phosphorylation negatively modulates affinity of enzyme towards NAD+ as well as SAH-synthesis. Thr219, Thr220 and Thr221 are essential for enzyme activity, and therefore, responsible for SahH-mediated regulation of homocysteine

retroTECH Online Project Summary, 2018-2020

From 2018-2020, the Georgia Tech Library was part of an Institute of Museum and Library Services-funded cohort of six organizations--the Guggenheim Museum, Living Computers: Museum + Labs, the University of Arizona, the University of Illinois, and the University of Virginia--exploring the key challenges to providing long-term access to software-dependent cultural heritage. The grant project, Fostering a Community of Practice (FCoP): Software Preservation and Emulation Experts in Libraries, Archives, and Museums (IMLS grant RE-95-17-0058-17), aimed to broaden participation in software preservation, advance digital preservation practice, and inform field-wide understanding. Under the umbrella of its retroTECH initiative, which provides access to vintage technologies and seeks to inspire a culture of long-term thinking, the Georgia Tech Library’s project has been to create a proof-of-concept for retroTECH Online, a web presence through which patrons can utilize software from retroTECH’s collections for teaching and learning, explore the stories surrounding that software, and foster a virtual retroTECH community. The project team used oral history and emulation to tell the stories of several software innovations created by Georgia Tech community members--from the graphical simulation that helped win Atlanta's 1996 Olympics bid to Game Boy Advance games coded by current students mastering computer science.Institute of Museum and Library Service

Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19

As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning (ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare

The Ser/Thr protein kinase PrkC imprints phenotypic memory in Bacillus anthracis spores by phosphorylating the glycolytic enzyme enolase

International audienc

Ser/Thr protein kinase PrkC-mediated regulation of GroEL is critical for biofilm formation in Bacillus anthracis

International audienc

Not Available

Not AvailableEquine influenza viruses (EIVs) of H3N8 subtype are culprits of severe acute respiratory infections in horses, and are still responsible for significant outbreaks worldwide. Adaptability of influenza viruses to a particular host is significantly influenced by their codon usage preference, due to an absolute dependence on the host cellular machinery for their replication. In the present study, we analyzed genome-wide codon usage patterns in 92 EIV strains, including both H3N8 and H7N7 subtypes by computing several codon usage indices and applying multivariate statistical methods. Relative synonymous codon usage (RSCU) analysis disclosed bias of preferred synonymous codons towards A/U-ended codons. The overall codon usage bias in EIVs was slightly lower, and mainly affected by the nucleotide compositional constraints as inferred from the RSCU and effective number of codon (ENc) analysis. Our data suggested that codon usage pattern in EIVs is governed by the interplay of mutation pressure, natural selection from its hosts and undefined factors. The H7N7 subtype was found less fit to its host (horse) in comparison to H3N8, by possessing higher codon bias, lower mutation pressure and much less adaptation to tRNA pool of equine cells. To the best of our knowledge, this is the first report describing the codon usage analysis of the complete genomes of EIVs. The outcome of our study is likely to enhance our understanding of factors involved in viral adaptation, evolution, and fitness towards their hosts.Not Availabl

Methylation of two-component response regulator MtrA in mycobacteria negatively modulates 1 its DNA binding and transcriptional activation. 2

International audienc

Identification of Ser/Thr kinase and Forkhead Associated Domains in <i>Mycobacterium ulcerans:</i> Characterization of Novel Association between Protein Kinase Q and MupFHA

<div><p>Background</p><p><i>Mycobacterium ulcerans</i>, the causative agent of Buruli ulcer in humans, is unique among the members of <i>Mycobacterium</i> genus due to the presence of the virulence determinant megaplasmid pMUM001. This plasmid encodes multiple virulence-associated genes, including <i>mup011</i>, which is an uncharacterized Ser/Thr protein kinase (STPK) PknQ.</p><p>Methodology/Principal Findings</p><p>In this study, we have characterized PknQ and explored its interaction with MupFHA (Mup018c), a FHA domain containing protein also encoded by pMUM001. MupFHA was found to interact with PknQ and suppress its autophosphorylation. Subsequent protein-protein docking and molecular dynamic simulation analyses showed that this interaction involves the FHA domain of MupFHA and PknQ activation loop residues Ser¹⁷⁰ and Thr¹⁷⁴. FHA domains are known to recognize phosphothreonine residues, and therefore, MupFHA may be acting as one of the few unusual FHA-domain having overlapping specificity. Additionally, we elucidated the PknQ-dependent regulation of MupDivIVA (Mup012c), which is a DivIVA domain containing protein encoded by pMUM001. MupDivIVA interacts with MupFHA and this interaction may also involve phospho-threonine/serine residues of MupDivIVA.</p><p>Conclusions/Significance</p><p>Together, these results describe novel signaling mechanisms in <i>M. ulcerans</i> and show a three-way regulation of PknQ, MupFHA, and MupDivIVA. FHA domains have been considered to be only pThr specific and our results indicate a novel mechanism of pSer as well as pThr interaction exhibited by MupFHA. These results signify the need of further re-evaluating the FHA domain –pThr/pSer interaction model. MupFHA may serve as the ideal candidate for structural studies on this unique class of modular enzymes.</p></div