Biology subjects

Azra Yasmin

Publications and source records attributed to Azra Yasmin.

4 recordsLinked to original sources

bioRxiv2016

Structure, interaction and post-translational modification study of arsenic reduction system in Bifidobacterium longum

Microbial metabolism contributes to degradation of organoarsenicals, where arsenic reductases (glutaredoxins) play pivotal role in bacterial resistance to arsenic. Ars operon studies have revealed reduction of arsenate As(V) to arsenite As(III) by respiratory-chain-linked reductase enzyme complexes. Although structure of some bacterial arsenate reductases has been solved but not attempted for Bifidobacterium longum DJO10A colonizing the human gastrointestinal tract. Here it has been endeavoured to analyze and understand the structure, properties, interaction, evolution and action mechanism of this enzyme (arsC1) and its accessory interactors (arsB1, arsB2 and arsR). A systematic bioinformatic based analysis was carried out using a battery of tools and web servers for this purpose. Arsenic resistance gene cluster of gram-positive Bifidobacterium obtained from STRING database illustrated contiguous arsC and arsB genes and absence of arsA gene. ArsC1 was determined to be a cytoplasmic small-molecular-mass protein (~15 kDa) related to a class of tyrosine phosphatases mediating the reduction of As(V) to As(III). ArsC1 was found to be involved in dephosphorylation of arsR, arsB1 and arsB2, indicating its role in post translational modification (PTM) of interacting proteins. 3D structure analysis revealed that it was composed of 1 sheet,1 beta alpha beta unit, 4 strands, 5 helices, 3 helix-helix interacs, 13 beta turns and 1 gamma turn. All proteins in the cluster exhibited hydrophobic interactions. Explicit protein-protein hydrogen, ionic, aromatic and cation-pi interactions in arsenate reducing operon of Bifidobacterium longum DJO10A further aided structural understanding of arsenate reduction process.\n\nNoteThis research was carried out in 2015. Availability of new information or changes in the algorithm behind software/database used for text mining interaction analysis in the meantime might impact some of the analyzed values. The preprint version may contain grammatical and proofreading mistakes. Errors and omissions excepted.

Bioinformatics↗

bioRxiv2016

Sequence based prediction of novel domains in the cellulosome of Ruminiclostridium thermocellum

Ruminiclostridium thermocellum strain ATCC 27405 is valuable with reference to the next generation biofuel production being a degrader of crystalline cellulose. The completion of its genome sequence has revealed that this organism carries 3,376 genes with more than hundred genes encoding for enzymes involved in cellulysis. Novel protein domain discovery in the cellulose degrading enzyme complex of this strain has been attempted to understand this organism at molecular level. Streamlined automated methods were employed to generate possibly unreported or new domains. A set of 12 novel Pfam-B domains was developed after detailed analysis. This finding will enhance our understanding of this bacterium and its molecular processes involved in the degradation of cellulose. This approach of in silico analysis prior to experimentation facilitates in lab study. Previously uncorrelated data has been utilized for rapid generation of new biological information in this study.\n\nNoteThis research was conducted in 2014 for Clostridium thermocellum ATCC 27405. The bacterium was later reannotated as Ruminiclostridium thermocellum. See NCBI nonredundant RefSeq protein annotation details at http://www.ncbi.nlm.nih.gov/refseq/about/prokaryotes/reannotation/. The study utilizes Pfam-B database, which was discontinued with effect from release 28.0 (5/2015). Availability of new information, reannotation/modification in accession numbers might impact some of the analyzed values although effort has been made to provide latest accession numbers and reference strain parameters. The preprint version may contain grammatical and proofreading mistakes. Errors and omissions excepted.

Microbiology↗

bioRxiv2016

Digital dissection of arsenate reductase enzyme from an arsenic hyperccumulating fern Pteris vittata

Action of arsenate reductase is crucial for the survival of an organism in arsenic polluted area. Pteris vittata, also known as Chinese ladder brake, was the first identified arsenic hyperaccumulating fern with the capability to convert [As(V)] to arsenite [As(III)]. This study aims at sequence analysis of the most important protein of the arsenic reduction mechanism in this specie. Phosphorylation potential of the protein along with possible interplay of phosphorylation with O-{beta}-GlcNAcylation was predicted using neural network based webservers. Secondary and tertiary structure of arsenate reductase was then analysed. Active site region of the protein comprised a rhodanese-like domain. Cursory dynamics simulation revealed that folds remained conserved in the rhodanese main but variations were observed in the structure in other regions. This information sheds light on the various characteristics of the protein and may be useful to enzymologists working on the improvement of its traits for arsenic reduction.

Bioinformatics↗

bioRxiv2016

Understanding properties of the master effector of phage shock operon in Mycobacterium tuberculosis via bioinformatics approach

The phage shock protein (Psp) is a part of the Psp operon, which assists in safeguarding the survival of bacterium in stress and shields the cell against proton motif force challenge. It is strongly induced by bacterium allied phages, improperly localized mutant porins and various other stresses. Master effector of the operon, PspA has been modeled and simulated, illustrating how it undergoes significant conformational transition at the far end in Mycobacterium tuberculosis. Association of this key protein of the operon influences action of Psp system on the whole. We are further working on the impact of phosphorylation perturbation and changes in the structure of PspA during complex formation with other moieties of interest.

Bioinformatics↗