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The Heartbreak of Wheat-Related Disorders
Published in Stephen T. Sinatra, Mark C. Houston, Nutritional and Integrative Strategies in Cardiovascular Medicine, 2022
Such a differentiated approach identifying sources of inflammation is in line with the growing appreciation and ongoing introduction of precision medicine in cardiology.26 Precision medicine incorporates standard clinical and health record data with advanced panomics (i.e., genomics, transcriptomics, epigenomics, proteomics, metabolomics, microbiomics) for deep phenotyping.27 These phenotypic data can then be analyzed within the framework of molecular interaction (interactome) networks to uncover previously unrecognized disease phenotypes, relationships between comorbidities, and unique inflammatory triggers to the individual.28 Functional medicine addresses chronic disease by delivering precision medicine with an emphasis on reducing the triggers of inflammation. The ability to deliver precision medicine relies on one’s capability to not only collect data, but also organize it in a way that extracts an understanding of a patient’s biological processes and then maps these processes to human disease.29,30
Computational Biology and Bioinformatics in Anti-SARS-CoV-2 Drug Development
Published in Debmalya Barh, Kenneth Lundstrom, COVID-19, 2022
Selection of host proteins as drug targets and/or the discovery of drug candidates depends on the knowledge of the SARS-CoV-2/human interactome [101–103]. MS-assisted proteomics represents an important means for a better understanding of the roles of viral and host proteins during SARS-CoV-2 infection, their protein–protein interactions, and post-translational modifications. Bittremieux et al. describe freely available data and computational resources that can be used to facilitate mass spectrometry-based analysis of SARS-CoV-2 [104]. Important information on the potentially druggable host proteins and the molecular mechanisms at play during infection can also be retrieved from the comparisons of SARS-CoV-2 with other viruses [105].
“Omics” Technologies in Vaccine Research
Published in Mesut Karahan, Synthetic Peptide Vaccine Models, 2021
A detailed picture of the protein-to-protein interactions related to the immune responses against infections, virulence of the pathogen, or host-pathogen interactions can be obtained via proteomics, and “interactome” of the cell is revealed. Proteins undergo modifications to gain their function or they are found in different locations of the cell. These certain groups of proteins can be isolated and identified using proteomics techniques. For instance, phosphorylated proteins playing roles in the signal transduction are identified via the phosphoproteomics technique, and the “kinome” of the cell is identified (Buonaguro and Pulendran 2011) or secreted proteins can be identified via “secretome” analysis (Bidmos et al. 2018).
Gene expression profiles and cytokine environments determine the in vitro proliferation and expansion capacities of human hematopoietic stem and progenitor cells
Published in Hematology, 2022
Roberto Dircio-Maldonado, Rosario Castro-Oropeza, Patricia Flores-Guzman, Alberto Cedro-Tanda, Fredy Omar Beltran-Anaya, Alfredo Hidalgo-Miranda, Hector Mayani
In order to visualize significant gene expression changes, we constructed volcano plots. Each plot showed the distributions of fold changes and FDRs of 67,528 probes for each comparison. The transcriptome analysis of MPCs and HSCs showed that only 54 protein-coding transcripts (12 upregulated and 42 downregulated) and 12 non-coding transcripts (5 upregulated and 7 downregulated) were differentially expressed (Figure 2A). Among the most significant transcripts upregulated in MPCs we found CD48, TRAT1, JCHAIN, CD38, MPO, and GPR183; whereas among the most downregulated genes we found LXN, GBP5, FOXO1, IL1RL1, LRIG1, TNFSF10, MEIS1, and PI3K (Table 1). To gain deeper insight into the behavior of MPCs and HSCs, we performed pathway enrichment analysis using Key Pathway Advisor (KPA). Network processes and pathways were predicted using causal reasoning interactome analysis. The predicted pathways in the MPC vs HSC samples indicated that only the B cell antigen receptor pathway (BCR) was positively regulated (Figure 2B). The low number of differentially expressed genes between MPCs and HSCs prevented the identification of molecular processes enriched in the MPCs. GSEA analysis showed that, as compared with MPCs, myeloid differentiation was negatively enriched in HSCs (Figure 2C, D). Gene expression levels were corroborated in selected genes by real time qRT-PCR (Supplemental Figure 2).
Endothelial cell-derived extracellular vesicles alter vascular smooth muscle cell phenotype through high-mobility group box proteins
Published in Journal of Extracellular Vesicles, 2020
Michael J. Boyer, Yayoi Kimura, Tomoko Akiyama, Ariele Y. Baggett, Kyle J. Preston, Rosario Scalia, Satoru Eguchi, Victor Rizzo
To further assess cell-type enriched EV proteins, proteins expressed greater than twofold in abundance (p < 0.05) were characterized with DAVID analysis [37]. VSMC enriched EVs possessed proteins which are implicated in complex biological processes, molecular functions, and cellular components that include cytoskeleton organization, cell adhesion, molecule binding and external side of the plasma membrane, respectively, whereas EC enriched EVs showed much simpler characteristics in Gene Ontology terms (Online Figure IV and Online Table IV). Among the identified peptide populations, interactome analysis was further performed on the cell-type specific populations with p values less than 0.01. EC EVs contained 12 associating proteins while VSMC expressed 30 proteins within their EVs. There were five common proteins identified with distinct peptide fragments (Online Table V). STRING gene interaction analysis illustrates a complex web of interactions between the proteins enriched in VSMC EVs, while EC analysis produced a smaller interactome even with the inclusion of the five common proteins (Online Figure V). Western blot analysis was performed to verify protein expression of the peptide fragments which were significantly enriched in the proteome analyses. The analysis confirmed that Clathrin heavy chain (Cltc) and Hsc70 (Hspa8) were indeed present in EC EVs and Enolase 1 (Eno1) and Calmodulin (Calm1) were present in VSMC EVs, respectively (Online Figure VI).
In vitro and in vivo efficacy of Caenorhabditis elegans recombinant antimicrobial protein against Gram-negative bacteria
Published in Biofouling, 2019
Dilawar Ahmad Mir, Krishnaswamy Balamurugan
High throughput protein profile and expression data were further subjected to bioinformatic analysis. The gene ontology (GO) classification of regulated proteins was performed using the UniProt KB tool, and interaction among the differentially regulated proteins in this study was assessed using the STRING10.5 tool with a medium confidence score 0.400 (Schmidt et al. 2014) The interactome network was built separately for both downregulated and upregulated proteins to predict functional association and interactions maps. STRING also compriseD direct (physical) and indirect (functional) associations. The STRING network allows the entire dynamic prediction methods of regulated proteins and helped to categorize the function of the interacting partners (Schmutz et al. 2013) and provide both well-known and predicted protein interactions. The functional annotation and gene enrichment scores of differentially regulated proteins were performed using the DAVID tool (Szklarczyk et al. 2015).