Mass Spectrometry Applications to Study Human Microbiome.

Microbiotas are an adaptable component of ecosystems, including human ecology. Microorganisms influence the chemistry of their specialized niche, such as the human gut, as well as the chemistry of distant surroundings, such as other areas of the body. Metabolomics based on mass spectrometry (MS) is one of the primary methods for detecting and identifying small compounds generated by the human microbiota, as well as understanding the functional significance of these microbial metabolites. This book chapter gives basic knowledge on the kinds of untargeted mass spectrometry as well as the data types that may be generated in the context of microbiome study. While data analysis remains a barrier, the emphasis is on data analysis methodologies and integrative analysis, particularly the integration of microbiome sequencing data. Mass spectrometry (MS)-based techniques have resurrected culture methods for studying the human gut microbiota, filling in the gaps left by high-throughput sequencing methods in terms of culturing minor populations.

Applications of Proteomics in Probiotics Having Anticancer and Chemopreventive Properties.

Proteomics has grown in importance in molecular sciences because it gives vital information on protein identification, expression levels, and alteration. Cancer is one of the world's major causes of death and is the major focus of much research. Cancer risk is determined by hereditary variables as well as the body's immunological condition. Probiotics have increasing medical importance due to their therapeutic influence on the human body in the prevention and treatment of numerous chronic illnesses, including cancer, with no adverse effects. Several anticancer, anti-inflammatory, and chemopreventive probiotics are studied using different proteomic approaches like two-dimensional gel electrophoresis, liquid chromatography-mass spectrometry, and matrix-assisted laser desorption/ionization mass spectrometry. To gain relevant information about probiotic characteristics, data from the proteomic analysis are evaluated and processed using bioinformatics pipelines. Proteomic studies showed the significance of different proteomic approaches in characterization, comparing strains, and determination of oxidative stress of different probiotics. Moreover, proteomic approaches identified different proteins that are involved in glucose metabolism and the formation of cell walls or cell membranes, and the differences in the expression of critical enzymes in the HIF-1 signaling pathway, starch, and sucrose metabolism, and other critical metabolic pathways.

Associations between Nutrigenomic Effects and Incidences of Microbial Resistance against Novel Antibiotics.

Nutrigenomics is the study of the impact of diets or nutrients on gene expression and phenotypes using high-throughput technologies such as transcriptomics, proteomics, metabolomics, etc. The bioactive components of diets and nutrients, as an environmental factor, transmit information through altered gene expression and hence the overall function and traits of the organism. Dietary components and nutrients not only serve as a source of energy but also, through their interactions with genes, regulate gut microbiome composition, the production of metabolites, various biological processes, and finally, health and disease. Antimicrobial resistance in pathogenic and probiotic microorganisms has emerged as a major public health concern due to the presence of antimicrobial resistance genes in various food products. Recent evidence suggests a correlation between the regulation of genes and two-component and other signaling systems that drive antibiotic resistance in response to diets and nutrients. Therefore, diets and nutrients may be alternatively used to overcome antibiotic resistance against novel antibiotics. However, little progress has been made in this direction. In this review, we discuss the possible implementations of nutrigenomics in antibiotic resistance against novel antibiotics.

Advances in the Applications of Bioinformatics and Chemoinformatics.

Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as "in silico techniques", in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, the incorporation of machine learning has been considered of high importance in the field of drug design, enabling the extraction of chemical data from enormous compound databases to develop drugs endowed with significant biological features. The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals. The virtual libraries address the need to increase the quality of the compounds as well as discover promising ones. On the other hand, various applications of bioinformatics in disease classification, diagnosis, and identification of multidrug-resistant organisms were discussed. The use of ensemble models and brute-force feature selection methodology has resulted in high accuracy rates for heart disease and COVID-19 diagnosis, along with the role of special formulations for targeting meningitis and Alzheimer's disease. Additionally, the correlation between genomic variations and disease states such as obesity and chronic progressive external ophthalmoplegia, the investigation of the antibacterial activity of pyrazole and benzimidazole-based compounds against resistant microorganisms, and its applications in chemoinformatics for the prediction of drug properties and toxicity-all the previously mentioned-were presented in the current review.