Multi-oligomeric and catalytically compromised serine acetyltransferase and cysteine regulatory complex of Mycobacterium tuberculosis.

l-cysteine, a primary building block of mycothiol, plays an essential role in the defense mechanism of Mycobacterium tuberculosis (Mtb). However, it is unclear how Mtb regulates cysteine biosynthesis as no study has reported the cysteine regulatory complex (CRC) in Mtb. Serine acetyltransferase (SAT) and cysteine synthase (CS) interact to form CRC. Although MtCS has been characterized well, minimal information is available on MtSAT, which synthesizes, O-acetylserine (OAS), the precursor of cysteine. This study fills the gap and provides experimental evidence for the presence of MtCRC and a non-canonical multi-oligomeric MtSAT. We employed multiple analytical methods to characterize the oligomeric and kinetic properties of MtSAT and MtCRC. Results show that MtSAT, lacking >75 N-terminal amino acids exists in three different assembly states; trimer, hexamer, and dodecamer, compared to the single hexameric state of SAT of other bacteria. While hexamers display the highest catalytic turnover, the trimer is the least active. The predominance of trimers at low physiologically relevant concentrations suggests that MtSAT displays the lowest catalytic potential known. Further, the catalytic potential of MtSAT is also significantly reduced in CRC state, in contrast to enhanced activity of SAT in CRC of other organisms. Our study provides insights into multi-oligomeric MtSAT with reduced catalytic potential and demonstrates that both MtSAT and MtCS of Mycobacterium interact to form CRC, although with altered catalytic properties. We discuss our results in light of the altered biochemistry of the last step of canonical sulfate-dependent cysteine biosynthesis of Mycobacterium.

Multifaceted personality and roles of heme enzymes in industrial biotechnology.

Heme enzymes are the most prominent category of iron-containing metalloenzymes with the capability of catalyzing an astonishingly wide range of reactions like epoxidation, hydroxylation, demethylation, desaturation, reduction, sulfoxidation, and decarboxylation. Various enzymes in this category are P450s, heme peroxidases, catalases, myoglobin, cytochrome C, and others. Besides this, the natural promiscuity and amenability of these enzymes to protein engineering and evolution have also added several non-native reactions such as C-H, N-H, S-H insertions, cyclopropanation, and other industrially important reactions to their capabilities. Surprisingly, all of these reactions and their wide substrate scopes are attributed to changes in the active site scaffold of different heme enzymes as the center of all enzymes is constituted by a porphyrin ring containing iron. Multiple prominent research groups across the world, including 2018, Nobel Laureate Frances Arnold's group, have shown keen interest in engineering and evolving these enzymes for utilizing their industrial potential. Besides engineering the active site, researchers have also explored the possibility of these enzymes catalyzing non-native reactions by replacing the center porphyrin ring with other cofactors or by changing the iron in the porphyrin ring with other metal ions along with engineering the active site and thereby creating novel artificial metalloenzymes. Thus, in this mini-review from our group, for the first time, we are trying to catalog various activities catalyzed by heme enzymes and their engineered variants and their active usage in various industries along with shedding light on their potential for use in various applications in the future.

Integration of text mining and biological network analysis: Identification of essential genes in sulfate-reducing bacteria.

The growth and survival of an organism in a particular environment is highly depends on the certain indispensable genes, termed as essential genes. Sulfate-reducing bacteria (SRB) are obligate anaerobes which thrives on sulfate reduction for its energy requirements. The present study used Oleidesulfovibrio alaskensis G20 (OA G20) as a model SRB to categorize the essential genes based on their key metabolic pathways. Herein, we reported a feedback loop framework for gene of interest discovery, from bio-problem to gene set of interest, leveraging expert annotation with computational prediction. Defined bio-problem was applied to retrieve the genes of SRB from literature databases (PubMed, and PubMed Central) and annotated them to the genome of OA G20. Retrieved gene list was further used to enrich protein-protein interaction and was corroborated to the pangenome analysis, to categorize the enriched gene sets and the respective pathways under essential and non-essential. Interestingly, the sat gene (dde_2265) from the sulfur metabolism was the bridging gene between all the enriched pathways. Gene clusters involved in essential pathways were linked with the genes from seleno-compound metabolism, amino acid metabolism, secondary metabolite synthesis, and cofactor biosynthesis. Furthermore, pangenome analysis demonstrated the gene distribution, where 69.83% of the 116 enriched genes were mapped under "persistent," inferring the essentiality of these genes. Likewise, 21.55% of the enriched genes, which involves specially the formate dehydrogenases and metallic hydrogenases, appeared under "shell." Our methodology suggested that semi-automated text mining and network analysis may play a crucial role in deciphering the previously unexplored genes and key mechanisms which can help to generate a baseline prior to perform any experimental studies.

Text-Mining to Identify Gene Sets Involved in Biocorrosion by Sulfate-Reducing Bacteria: A Semi-Automated Workflow.

A significant amount of literature is available on biocorrosion, which makes manual extraction of crucial information such as genes and proteins a laborious task. Despite the fast growth of biology related corrosion studies, there is a limited number of gene collections relating to the corrosion process (biocorrosion). Text mining offers a potential solution by automatically extracting the essential information from unstructured text. We present a text mining workflow that extracts biocorrosion associated genes/proteins in sulfate-reducing bacteria (SRB) from literature databases (e.g., PubMed and PMC). This semi-automatic workflow is built with the Named Entity Recognition (NER) method and Convolutional Neural Network (CNN) model. With PubMed and PMCID as inputs, the workflow identified 227 genes belonging to several Desulfovibrio species. To validate their functions, Gene Ontology (GO) enrichment and biological network analysis was performed using UniprotKB and STRING-DB, respectively. The GO analysis showed that metal ion binding, sulfur binding, and electron transport were among the principal molecular functions. Furthermore, the biological network analysis generated three interlinked clusters containing genes involved in metal ion binding, cellular respiration, and electron transfer, which suggests the involvement of the extracted gene set in biocorrosion. Finally, the dataset was validated through manual curation, yielding a similar set of genes as our workflow; among these, hysB and hydA, and sat and dsrB were identified as the metal ion binding and sulfur metabolism genes, respectively. The identified genes were mapped with the pangenome of 63 SRB genomes that yielded the distribution of these genes across 63 SRB based on the amino acid sequence similarity and were further categorized as core and accessory gene families. SRB's role in biocorrosion involves the transfer of electrons from the metal surface via a hydrogen medium to the sulfate reduction pathway. Therefore, genes encoding hydrogenases and cytochromes might be participating in removing hydrogen from the metals through electron transfer. Moreover, the production of corrosive sulfide from the sulfur metabolism indirectly contributes to the localized pitting of the metals. After the corroboration of text mining results with SRB biocorrosion mechanisms, we suggest that the text mining framework could be utilized for genes/proteins extraction and significantly reduce the manual curation time.

Transcriptomics and Functional Analysis of Copper Stress Response in the Sulfate-Reducing Bacterium Desulfovibrio alaskensis G20.

Copper (Cu) is an essential micronutrient required as a co-factor in the catalytic center of many enzymes. However, excess Cu can generate pleiotropic effects in the microbial cell. In addition, leaching of Cu from pipelines results in elevated Cu concentration in the environment, which is of public health concern. Sulfate-reducing bacteria (SRB) have been demonstrated to grow in toxic levels of Cu. However, reports on Cu toxicity towards SRB have primarily focused on the degree of toxicity and subsequent elimination. Here, Cu(II) stress-related effects on a model SRB, Desulfovibrio alaskensis G20, is reported. Cu(II) stress effects were assessed as alterations in the transcriptome through RNA-Seq at varying Cu(II) concentrations (5 µM and 15 µM). In the pairwise comparison of control vs. 5 µM Cu(II), 61.43% of genes were downregulated, and 38.57% were upregulated. In control vs. 15 µM Cu(II), 49.51% of genes were downregulated, and 50.5% were upregulated. The results indicated that the expression of inorganic ion transporters and translation machinery was massively modulated. Moreover, changes in the expression of critical biological processes such as DNA transcription and signal transduction were observed at high Cu(II) concentrations. These results will help us better understand the Cu(II) stress-response mechanism and provide avenues for future research.

Gene Sets and Mechanisms of Sulfate-Reducing Bacteria Biofilm Formation and Quorum Sensing With Impact on Corrosion.

Sulfate-reducing bacteria (SRB) have a unique ability to respire under anaerobic conditions using sulfate as a terminal electron acceptor, reducing it to hydrogen sulfide. SRB thrives in many natural environments (freshwater sediments and salty marshes), deep subsurface environments (oil wells and hydrothermal vents), and processing facilities in an industrial setting. Owing to their ability to alter the physicochemical properties of underlying metals, SRB can induce fouling, corrosion, and pipeline clogging challenges. Indigenous SRB causes oil souring and associated product loss and, subsequently, the abandonment of impacted oil wells. The sessile cells in biofilms are 1,000 times more resistant to biocides and induce 100-fold greater corrosion than their planktonic counterparts. To effectively combat the challenges posed by SRB, it is essential to understand their molecular mechanisms of biofilm formation and corrosion. Here, we examine the critical genes involved in biofilm formation and microbiologically influenced corrosion and categorize them into various functional categories. The current effort also discusses chemical and biological methods for controlling the SRB biofilms. Finally, we highlight the importance of surface engineering approaches for controlling biofilm formation on underlying metal surfaces.