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Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties

Peptidomics allows the identification of peptides that are derived from proteins. Urinary peptidomics has revolutionized the field of diagnostics as the samples represent complete systemic changes happening in the body. Moreover, it can be collected in a non-invasive manner. We profiled the peptides...

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Autores principales: Kumar, Rohit, Ali, Syed Azmal, Singh, Sumit Kumar, Bhushan, Vanya, Kaushik, Jai Kumar, Mohanty, Ashok Kumar, Kumar, Sudarshan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8203733/
https://www.ncbi.nlm.nih.gov/pubmed/34127704
http://dx.doi.org/10.1038/s41598-021-91684-4
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author Kumar, Rohit
Ali, Syed Azmal
Singh, Sumit Kumar
Bhushan, Vanya
Kaushik, Jai Kumar
Mohanty, Ashok Kumar
Kumar, Sudarshan
author_facet Kumar, Rohit
Ali, Syed Azmal
Singh, Sumit Kumar
Bhushan, Vanya
Kaushik, Jai Kumar
Mohanty, Ashok Kumar
Kumar, Sudarshan
author_sort Kumar, Rohit
collection PubMed
description Peptidomics allows the identification of peptides that are derived from proteins. Urinary peptidomics has revolutionized the field of diagnostics as the samples represent complete systemic changes happening in the body. Moreover, it can be collected in a non-invasive manner. We profiled the peptides in urine collected from different physiological states (heifer, pregnancy, and lactation) of Sahiwal cows. Endogenous peptides were extracted from 30 individual cows belonging to three groups, each group comprising of ten animals (biological replicates n = 10). Nano Liquid chromatography Mass spectrometry (nLC-MS/MS) experiments revealed 5239, 4774, and 5466 peptides in the heifer, pregnant and lactating animals respectively. Urinary peptides of <10 kDa size were considered for the study. Peptides were extracted by 10 kDa MWCO filter. Sequences were identified by scanning the MS spectra ranging from 200 to 2200 m/z. The peptides exhibited diversity in sequences across different physiological states and in-silico experiments were conducted to classify the bioactive peptides into anti-microbial, anti-inflammatory, anti-hypertensive, and anti-cancerous groups. We have validated the antimicrobial effect of urinary peptides on Staphylococcus aureus and Escherichia coli under an in-vitro experimental set up. The origin of these peptides was traced back to certain proteases viz. MMPs, KLKs, CASPs, ADAMs etc. which were found responsible for the physiology-specific peptide signature of urine. Proteins involved in extracellular matrix structural constituent (GO:0005201) were found significant during pregnancy and lactation in which tissue remodeling is extensive. Collagen trimers were prominent molecules under cellular component category during lactation. Homophilic cell adhesion was found to be an important biological process involved in embryo attachment during pregnancy. The in-silico study also highlighted the enrichment of progenitor proteins on specific chromosomes and their relative expression in context to specific physiology. The urinary peptides, precursor proteins, and proteases identified in the study offers a base line information in healthy cows which can be utilized in biomarker discovery research for several pathophysiological studies.
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spelling pubmed-82037332021-06-16 Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties Kumar, Rohit Ali, Syed Azmal Singh, Sumit Kumar Bhushan, Vanya Kaushik, Jai Kumar Mohanty, Ashok Kumar Kumar, Sudarshan Sci Rep Article Peptidomics allows the identification of peptides that are derived from proteins. Urinary peptidomics has revolutionized the field of diagnostics as the samples represent complete systemic changes happening in the body. Moreover, it can be collected in a non-invasive manner. We profiled the peptides in urine collected from different physiological states (heifer, pregnancy, and lactation) of Sahiwal cows. Endogenous peptides were extracted from 30 individual cows belonging to three groups, each group comprising of ten animals (biological replicates n = 10). Nano Liquid chromatography Mass spectrometry (nLC-MS/MS) experiments revealed 5239, 4774, and 5466 peptides in the heifer, pregnant and lactating animals respectively. Urinary peptides of <10 kDa size were considered for the study. Peptides were extracted by 10 kDa MWCO filter. Sequences were identified by scanning the MS spectra ranging from 200 to 2200 m/z. The peptides exhibited diversity in sequences across different physiological states and in-silico experiments were conducted to classify the bioactive peptides into anti-microbial, anti-inflammatory, anti-hypertensive, and anti-cancerous groups. We have validated the antimicrobial effect of urinary peptides on Staphylococcus aureus and Escherichia coli under an in-vitro experimental set up. The origin of these peptides was traced back to certain proteases viz. MMPs, KLKs, CASPs, ADAMs etc. which were found responsible for the physiology-specific peptide signature of urine. Proteins involved in extracellular matrix structural constituent (GO:0005201) were found significant during pregnancy and lactation in which tissue remodeling is extensive. Collagen trimers were prominent molecules under cellular component category during lactation. Homophilic cell adhesion was found to be an important biological process involved in embryo attachment during pregnancy. The in-silico study also highlighted the enrichment of progenitor proteins on specific chromosomes and their relative expression in context to specific physiology. The urinary peptides, precursor proteins, and proteases identified in the study offers a base line information in healthy cows which can be utilized in biomarker discovery research for several pathophysiological studies. Nature Publishing Group UK 2021-06-14 /pmc/articles/PMC8203733/ /pubmed/34127704 http://dx.doi.org/10.1038/s41598-021-91684-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kumar, Rohit
Ali, Syed Azmal
Singh, Sumit Kumar
Bhushan, Vanya
Kaushik, Jai Kumar
Mohanty, Ashok Kumar
Kumar, Sudarshan
Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
title Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
title_full Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
title_fullStr Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
title_full_unstemmed Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
title_short Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
title_sort peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8203733/
https://www.ncbi.nlm.nih.gov/pubmed/34127704
http://dx.doi.org/10.1038/s41598-021-91684-4
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