In silico analysis of promoter regions to identify regulatory elements in TetR family transcriptional regulatory genes of Mycobacterium colombiense CECT 3035

PM2.5, component cause of severe metabolically abnormal obesity: An in silico, observational and analytical study

Obesity is currently one of the most alarming pathological conditions due to the progressive increase in its prevalence. In the last decade, it has been associated with fine particulate matter suspended in the air (PM2.5). The purpose of this study was to explore the mechanistic interaction of PM2.5 with a high-fat diet (HFD) through the differential regulation of transcriptional signatures, aiming to identify the association of these particles with metabolically abnormal obesity. The research design was observational, using bioinformatic methods and an explanatory approach based on Rothman's causal model. We propose three new transcriptional signatures in murine adipose tissue. The sum of transcriptional differences between the group exposed to an HFD and PM2.5, compared to the control group, were 0.851, 0.265, and -0.047 (p > 0.05). The HFD group increased body mass by 20% with two positive biomarkers of metabolic impact. The group exposed to PM2.5 maintained a similar weight to the control group but exhibited three positive biomarkers. Enriched biological pathways (p < 0.05) included PPAR signaling, small molecule transport, adipogenesis genes, cytokine-cytokine receptor interaction, and HIF-1 signaling. Transcriptional regulation predictions revealed CpG islands and common transcription factors. We propose three new transcriptional signatures: FAT-PM2.5-CEJUS, FAT-PM2.5-UP, and FAT-PM2.5-DN, whose transcriptional regulation profile in adipocytes was statistically similar by dietary intake and HFD and exposure to PM2.5 in mice; suggesting a mechanistic interaction between both factors. However, HFD-exposed murines developed moderate metabolically abnormal obesity, and PM2.5-exposed murines developed severe abnormal metabolism without obesity. Therefore, in Rothman's terms, it is concluded that HFD is a sufficient cause of the development of obesity, and PM2.5 is a component cause of severe abnormal metabolism of obesity. These signatures would be integrated into a systemic biological process that would induce transcriptional regulation in trans, activating obesogenic biological pathways, restricting lipid mobilization pathways, decreasing adaptive thermogenesis and angiogenesis, and altering vascular tone thus inducing a severe metabolically abnormal obesity.

Phytochemical Composition, Antioxidant, Antimicrobial, Antibiofilm, and Antiquorum Sensing Potential of Methanol Extract and Essential Oil from Acanthus polystachyus Delile (Acanthaceae)

The evolution of microbes in response to conventional antimicrobials leads to antimicrobial resistance (AMR) and multidrug resistance (MDR), and it is a global threat to public health. Natural products are possible solutions to this massive challenge. In this study, the potential of Acanthus polystachyus extracts was investigated for phytochemical composition and biological properties as antimicrobials. Gas chromatography-mass spectra (GC-MS) analysis of methanol extract (ME) and essential oil (EO) detected 79 and 20 compounds, respectively. The major compounds identified in ME and their abundance were β-sitosterol acetate (16.06%), cholest-5-en-3-yl (9Z)-9-octadecenoate (9.54%), 1-dodecanol (7.57%), (S)-(E)-(-)-4-acetoxy-1-phenyl-2-dodecen-1-one (6.03%), neophytadiene (5.7%), (E)-2-nonadecene (3.9%), hexanol-4-D2 (2.92%), and decane (2.4%). Most compounds have known bioactive functions. In EO, the major compounds were stearyl alcohol (25.38%); cis-9-tetradecenoic acid, isobutyl ester (22.95%); butyl 9-tetradecenoate (10.62%); 11,13-dimethyl-12-tetradecen-1-ol acetate (10.14%); ginsenol (3.48%); and diisooctyl phthalate (2.54%). All compounds are known to be bioactive. The antioxidant activity of ME and EO ranged from 48.3 to 84.2% radical scavenging activity (RSA) and 45.6 to 82% RSA, respectively, with dose dependency. The disc diffusion assay for the antimicrobial activity of ME revealed high inhibition against Acenetobacter baumannii (130.2%), Pseudomonas aeruginosa (100.3%), and Staphylococcus aureus (87.7%). The MIC, MBC/MFC, and MBIC values for ME were 0.5-1.0, 2-4, and 0.5-1.0 mg/mL and for EO were 0.31-0.62, 1.25-2.5, and 0.31-0.62 μL/mL, respectively, indicating inhibition potential as well as inhibition of biofilm formation. The tolerance test values indicated bactericidal activity against most strains and bacteriostatic/fungistatic activity against A. baumannii, E. faecalis, and C. albicans. The antiquorum sensing activity of ME achieved by pyocyanin inhibition assay on P. aeruginosa showed a 51.6% inhibition at 500 μg/mL. These results suggest that ME and EO derived from A. polystachyus leaves are potent, valuable, cost-effective antioxidants and antimicrobials. Both extracts may effectively combat pathogenic and resistant microbes.

In Silico Study of Mercury Resistance Genes Extracted from Pseudomonas spp. Involved in Bioremediation: Understanding the Promoter Regions and Regulatory Elements

Microbial genes and their product were diverse and beneficial for heavy metal bioremediation from the contaminated sites. Screening of genes and gene products plays a significant role in the detoxification of pollutants. Understanding of the promoter region and its regulatory elements is a vital implication of microbial genes. To the best of our knowledge, there is no in silico study reported so far on mer gene families used for heavy metal bioremediation. The motif distribution was observed densely upstream of the TSSs (transcription start sites) between +1 and -350 bp and sparsely distributed above -350 bp, according to the current study. MEME identified the best common candidate motifs of TFs (transcription factors) binding with the lowest e value (7.2 $e$ -033) and is the most statistically significant candidate motif. The EXPREG output of the 11 TFs with varying degrees of function such as activation, repression, transcription, and dual purposes was thoroughly examined. Data revealed that transcriptional gene regulation in terms of activation and repression was observed at 36.4% and 54.56%, respectively. This shows that most TFs are involved in transcription gene repression rather than activation. Likewise, EXPREG output revealed that transcriptional conformational modes, such as monomers, dimers, tetramers, and other factors, were also analyzed. The data indicated that most of the transcriptional conformation mode was dual, which accounts for 96%. CpG island analysis using online and offline tools revealed that the gene body had fewer CpG islands compared to the promoter regions. Understanding the common candidate motifs, transcriptional factors, and regulatory elements of the mer operon gene cluster using a machine learning approach could help us better understand gene expression patterns in heavy metal bioremediation.