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ABSTRACT A comprehensive pangenomic approach was employed to analyze the genomes of 75 type II methylotrophs spanning various genera. Our investigation revealed 256 exact core gene families shared by all 75 organisms, emphasizing their crucial role in the survival and adaptability of these organisms. Additionally, we predicted the functionality of 12 hypothetical proteins. The analysis unveiled a diverse array of genes associated with key metabolic pathways, including methane, serine, glyoxylate, and ethylmalonyl-CoA (EMC) metabolic pathways. While all selected organisms possessed essential genes for the serine pathway,Methylooceanibacter marginalislacked serine hydroxymethyltransferase (SHMT), andMethylobacterium variabileexhibited both isozymes of SHMT, suggesting its potential to utilize a broader range of carbon sources. Notably,Methylobrevissp. displayed a unique serine-glyoxylate transaminase isozyme not found in other organisms. Only nine organisms featured anaplerotic enzymes (isocitrate lyase and malate synthase) for the glyoxylate pathway, with the rest following the EMC pathway.Methylovirgulasp. 4MZ18 stood out by acquiring genes from both glyoxylate and EMC pathways, andMethylocapsasp. S129 featured an A-form malate synthase, unlike the G-form found in the remaining organisms. Our findings also revealed distinct phylogenetic relationships and clustering patterns among type II methylotrophs, leading to the proposal of a separate genus forMethylovirgulasp. 4M-Z18 andMethylocapsasp. S129. This pangenomic study unveils remarkable metabolic diversity, unique gene characteristics, and distinct clustering patterns of type II methylotrophs, providing valuable insights for future carbon sequestration and biotechnological applications. IMPORTANCEMethylotrophs have played a significant role in methane-based product production for many years. However, a comprehensive investigation into the diverse genetic architectures across different genera of methylotrophs has been lacking. This study fills this knowledge gap by enhancing our understanding of core hypothetical proteins and unique enzymes involved in methane oxidation, serine, glyoxylate, and ethylmalonyl-CoA pathways. These findings provide a valuable reference for researchers working with other methylotrophic species. Furthermore, this study not only unveils distinctive gene characteristics and phylogenetic relationships but also suggests a reclassification forMethylovirgulasp. 4M-Z18 andMethylocapsasp. S129 into separate genera due to their unique attributes within their respective genus. Leveraging the synergies among various methylotrophic organisms, the scientific community can potentially optimize metabolite production, increasing the yield of desired end products and overall productivity. 

Over the past decade, copper (Cu) has been recognized as a crucial metal in the differential expression of soluble (sMMO) and particulate (pMMO) forms of methane monooxygenase (MMO) through a mechanism referred to as the “Cu switch”. In this study, we used Methylosinus trichosporium OB3b as a model bacterium to investigate the range of Cu concentrations that trigger the expression of sMMO to pMMO and its effect on growth and methane oxidation. The Cu switch was found to be regulated within Cu concentrations from 3 to 5 µM, with a strict increase in the methane consumption rates from 3.09 to 3.85 µM occurring on the 6th day. Our findings indicate that there was a decrease in the fold changes in the expression of methanobactin (Mbn) synthesis gene (mbnA) with a higher Cu concentration, whereas the Ton-B siderophore receptor gene (mbnT) showed upregulation at all Cu concentrations. Furthermore, the upregulation of the di-heme enzyme at concentrations above 5 µM Cu may play a crucial role in the copper switch by increasing oxygen consumption; however, the role has yet not been elucidated. We developed a quantitative assay based on the naphthalene–Molisch principle to distinguish between the sMMO- and pMMO-expressing cells, which coincided with the regulation profile of the sMMO and pMMO genes. At 0 and 3 µM Cu, the naphthol concentration was higher (8.1 and 4.2 µM, respectively) and gradually decreased to 0 µM naphthol when pMMO was expressed and acted as the sole methane oxidizer at concentrations above 5 µM Cu. Using physical protein–protein interaction, we identified seven transporters, three cell wall biosynthesis or degradation proteins, Cu resistance operon proteins, and 18 hypothetical proteins that may be involved in Cu toxicity and homeostasis. These findings shed light on the key regulatory genes of the Cu switch that will have potential implications for bioremediation and biotechnology applications. 

Sulfate-reducing bacteria (SRB) are anaerobic bacteria that form biofilm and induce corrosion on various material surfaces. The quorum sensing (QS) system that employs acyl homoserine lactone (AHL)-type QS molecules primarily govern biofilm formation. Studies on SRB have reported the presence of AHL, but no AHL synthase have been annotated in SRB so far. In this computational study, we used a combination of data mining, multiple sequence alignment (MSA), homology modeling and docking to decode a putative AHL synthase in the model SRB, Desulfovibrio vulgaris Hildenborough (DvH). Through data mining, we shortlisted 111 AHL synthase genes. Conserved domain analysis of 111 AHL synthase genes generated a consensus sequence. Subsequent MSA of the consensus sequence with DvH genome indicated that DVU_2486 (previously uncharacterized protein from acetyltransferase family) is the gene encoding for AHL synthase. Homology modeling revealed the existence of seven α-helices and six β sheets in the DvH AHL synthase. The amalgamated study of hydrophobicity, binding energy, and tunnels and cavities revealed that Leu99, Trp104, Arg139, Trp97, and Tyr36 are the crucial amino acids that govern the catalytic center of this putative synthase. Identifying AHL synthase in DvH would provide more comprehensive knowledge on QS mechanism and help design strategies to control biofilm formation. 

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 usedOleidesulfovibrio alaskensisG20 (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, thesatgene (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. 

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. 

Particulate methane monooxygenase (pMMO), a membrane-bound enzyme having three subunits (α, β, and γ) and copper-containing centers, is found in most of the methanotrophs that selectively catalyze the oxidation of methane into methanol. Active sites in the pMMO of Methylosinus trichosporium OB3b were determined by docking the modeled structure with ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene. The docking energy between the modeled pMMO structure and ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene was −5.2, −5.7, −4.2, and −3.8 kcal/mol, respectively, suggesting the existence of more than one active site within the monomeric subunits due to the presence of multiple binding sites within the pMMO monomer. The evaluation of tunnels and cavities of the active sites and the docking results showed that each active site is specific to the radius of the substrate. To increase the catalysis rates of methane in the pMMO of M. trichosporium OB3b, selected amino acid residues interacting at the binding site of ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene were mutated. Based on screening the strain energy, docking energy, and physiochemical properties, five mutants were downselected, B:Leu31Ser, B:Phe96Gly, B:Phe92Thr, B:Trp106Ala, and B:Tyr110Phe, which showed the docking energy of −6.3, −6.7, −6.3, −6.5, and −6.5 kcal/mol, respectively, as compared to the wild type (−5.2 kcal/mol) with ethylbenzene. These results suggest that these five mutants would likely increase methane oxidation rates compared to wild-type pMMO. 

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. 

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. 

The mimicking of evolution on a laboratory timescale to enhance biocatalyst specificity, substrate utilization activity, and/or product formation, is an effective and well-established approach that does not involve genetic engineering or regulatory details of the microorganism. The present work employed an evolutionary adaptive approach to improve the lignocellulose deconstruction capabilities of the strain by inducing the expression of laccase, a multicopper oxidase, in Geobacillus sp. strain WSUCF1. This bacterium is highly efficient in depolymerizing unprocessed lignocellulose, needing no preprocessing/pretreatment of the biomasses. However, it natively produces low levels of laccase. After 15 rounds of serially adapting this thermophilic strain in the presence of unprocessed corn stover as the selective pressure, we recorded a 20-fold increase in catalytic laccase activity, at 9.23 ± 0.6 U/mL, in an adapted yet stable strain of Geobacillus sp. WSUCF1, compared with the initial laccase production (0.46 ± 0.04 U/mL) obtained with the unadapted strain grown on unprocessed corn stover before optimization. Chemical composition analysis demonstrated that lignin removal by the adapted strain was 22 wt.% compared with 6 wt.% removal by the unadapted strain. These results signify a favorable prospect for fast, cost competitive bulk production of this thermostable enzyme. Also, this work has practical importance, as this fast adaptation of the Geobacillus sp. strain WSUCF1 suggests the possibility of growing industrial quantities of Geobacillus sp. strain WSUCF1 cells as biocatalysts on reasonably inexpensive carbon sources for commercial use. This work is the first application of the adaptive laboratory evolution approach for developing the desired phenotype of enhanced ligninolytic capability in any microbial strain.