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Impact of Endosymbionts on Antimicrobial Properties of Medicinal Plants
Published in Mahendra Rai, Chistiane M. Feitosa, Eco-Friendly Biobased Products Used in Microbial Diseases, 2022
Flávia Figueira Aburjaile, José Ribamar Costa Ferreira-Neto, Thamara de Medeiros Azevedo, Juan Carlos Ariute, Jéssica Barboza da Silva, Roberta Lane de Oliveira Silva, Valesca Pandolfi, Ana Maria Benko-Iseppon
Due to methodological advances, ‘Metagenomic’ studies are actually the best choice. This approach involves DNA extraction of whole environmental samples (e.g., from the soil, from the roots of a plant individual or the gut of an animal). In the case of plant endophytes, it can involve any of the niches illustrated in Fig. 14.1. After extraction, purification and quantification the whole sample is submitted to High-Throughput Sequencing (HTS, also called Next-Generation Sequencing, NGS). Such an inference can provide the sequencing depth necessary to cover complex microbial communities (Shendure and Ji 2008).
Gut Microbiota—Specific Food Design
Published in Megh R. Goyal, Preeti Birwal, Santosh K. Mishra, Phytochemicals and Medicinal Plants in Food Design, 2022
Aparna V. Sudhakaran, Himanshi Solanki
The distribution profile of microbes and exact composition in the gut is still unexplored. Developments in metagenomic technology have initiated to discover our microbial partners. Chemical, metabolic, and immunologic gradients of the intestine affect the density and composition of the microbiota. The factors influencing gut microbiome include the diet, age, medication, sleep, stress, environmental factors, etc.
Biochemical Markers in Ophthalmology
Published in Ching-Yu Cheng, Tien Yin Wong, Ophthalmic Epidemiology, 2022
Abdus Samad Ansari, Pirro G. Hysi
Recent advances in genome-sequencing technologies and metagenomic analysis have created a new platform to further understand the link between microbiomes and disease [170]. Large-scale metagenomic projects such as the Human Genome Project and the European Metagenomics Programme have reported a huge diversity in microbial presence in humans, with more than 3 million unique protein-encoding genes, providing information on reference genomes and descriptive data on the microbiota of healthy humans. Such studies have been able to highlight the function of the normal gut flora and underline the vital homeostatic mechanisms behind its influence, including enhanced metabolism [171], resistance to infection and inflammation [172], prevention of autoimmunity [173], and even the synthesis of vitamins [174].
An overview of technologies for MS-based proteomics-centric multi-omics
Published in Expert Review of Proteomics, 2022
Andrew T. Rajczewski, Pratik D. Jagtap, Timothy J. Griffin
Another emerging area that fits in the scope of MS-based proteomic-centered multi-omics is the field of metaproteomics [152]. Metaproteomics incorporates metagenome information on microbial communities from a wide-variety of settings – from human host samples to complex samples (e.g. wastewater, soil) relevant to environmental studies. These multi-omic data can be used to create large protein sequence databases of potential microbe-derived proteins within these samples, which are then used to search for MS/MS data generated from these samples. When analyzed with specialized multi-omic tools [153], the results provide a unique snapshot of the functional proteins expressed by microbial communities, which may drive host biology or regulate characteristics of complex ecological systems. These results can also help identify potential metabolic pathways and small molecules generated by the microbiota that play a role in interactions and regulatory mechanisms. Metaproteomics also expands the reach of proteomic-centered multi-omics to studying flora, fauna, and microbial communities responding to environmental factors (e.g. climate change, pollution [154], bioremediation [155]) in addition to biomedical applications [156].
An ethical investigation into the microbiome: the intersection of agriculture, genetics, and the obesity epidemic
Published in Gut Microbes, 2020
Therefore, there may be hidden harms when a commercially favorable trait such as metabolic efficiency is selected for in livestock. An individual’s genome resides within a hologenome, which in turn resides within the environmental metagenome.42 Even without selecting for an individual’s genome, the genetic milieu a person lives within (i.e. genetic and epigenetic effects) could be augmented by a selection of the microbiome or environmental metagenome, and this selection could impact the individual’s phenotype via transferable mechanisms. If a microbial extended phenotype (e.g. obesity) was selected for artificially in an agricultural species, and that phenotype was then transferred to humans, then the extended phenotype in the human could be obscured partially by epistasis and pleiotropy.43 A conceptual diagram representing the hypothesis of obesogenic gut microbiome transfer between livestock and humans is represented in Figure 3.
Skin exposure to sunlight: a factor modulating the human gut microbiome composition
Published in Gut Microbes, 2020
Liliane Costa Conteville, Ana Carolina P Vicente
The influence of microbes on their hosts, and particularly the contribution of gut microbes for human health and physiology have been deeply explored with the advance of sequencing technologies and metagenomic analysis. In order to gain insights into the gut microbiome evolution and composition, intrinsic and extrinsic factors from the host should be considered, allowing the unraveling of differences among healthy and disease gut bacterial profiles. In the past decade, numerous studies on the gut microbiome of different populations have taken into account a wide range of factors, such as human diet, age, sex, life stage (pregnancy, lactating, menopausal stage), social behavior (use of alcohol, antibiotics, tobacco), geography, environment, ethnicity, and diseases.1–14 Most of these studies established a link of one or more of those factors and the gut microbiome composition. Therefore, the gut microbiome modulation is driven by a complex and dynamic network presenting a wide range of variables. However, some variables are still under-explored, but their careful appraisal may bring insights into the understanding of this complex interaction scenario.