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Modular automated bottom-up proteomic sample preparation for high-throughput applications
Manual proteomic sample preparation methods limit sample throughput and often lead to poor data quality when thousands of samples must be analyzed. Automated liquid handler systems are increasingly used to overcome these issues for many of the sample preparation steps. Here, we detail a step-by-step...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880914/ https://www.ncbi.nlm.nih.gov/pubmed/35213656 http://dx.doi.org/10.1371/journal.pone.0264467 |
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author | Chen, Yan Kaplan Lease, Nurgul Gin, Jennifer W. Ogorzalek, Tadeusz L. Adams, Paul D. Hillson, Nathan J. Petzold, Christopher J. |
author_facet | Chen, Yan Kaplan Lease, Nurgul Gin, Jennifer W. Ogorzalek, Tadeusz L. Adams, Paul D. Hillson, Nathan J. Petzold, Christopher J. |
author_sort | Chen, Yan |
collection | PubMed |
description | Manual proteomic sample preparation methods limit sample throughput and often lead to poor data quality when thousands of samples must be analyzed. Automated liquid handler systems are increasingly used to overcome these issues for many of the sample preparation steps. Here, we detail a step-by-step protocol to prepare samples for bottom-up proteomic analysis for Gram-negative bacterial and fungal cells. The full modular protocol consists of three optimized protocols to: (A) lyse Gram-negative bacteria and fungal cells; (B) quantify the amount of protein extracted; and (C) normalize the amount of protein and set up tryptic digestion. These protocols have been developed to facilitate rapid, low variance sample preparation of hundreds of samples, be easily implemented on widely-available Beckman-Coulter Biomek automated liquid handlers, and allow flexibility for future protocol development. By using this workflow 50 micrograms of protein from 96 samples can be prepared for tryptic digestion in under an hour. We validate these protocols by analyzing 47 Pseudomonas putida and Rhodosporidium toruloides samples and show that this modular workflow provides robust, reproducible proteomic samples for high-throughput applications. The expected results from these protocols are 94 peptide samples from Gram-negative bacterial and fungal cells prepared for bottom-up quantitative proteomic analysis without the need for desalting column cleanup and with protein relative quantity variance (CV%) below 15%. |
format | Online Article Text |
id | pubmed-8880914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-88809142022-02-26 Modular automated bottom-up proteomic sample preparation for high-throughput applications Chen, Yan Kaplan Lease, Nurgul Gin, Jennifer W. Ogorzalek, Tadeusz L. Adams, Paul D. Hillson, Nathan J. Petzold, Christopher J. PLoS One Lab Protocol Manual proteomic sample preparation methods limit sample throughput and often lead to poor data quality when thousands of samples must be analyzed. Automated liquid handler systems are increasingly used to overcome these issues for many of the sample preparation steps. Here, we detail a step-by-step protocol to prepare samples for bottom-up proteomic analysis for Gram-negative bacterial and fungal cells. The full modular protocol consists of three optimized protocols to: (A) lyse Gram-negative bacteria and fungal cells; (B) quantify the amount of protein extracted; and (C) normalize the amount of protein and set up tryptic digestion. These protocols have been developed to facilitate rapid, low variance sample preparation of hundreds of samples, be easily implemented on widely-available Beckman-Coulter Biomek automated liquid handlers, and allow flexibility for future protocol development. By using this workflow 50 micrograms of protein from 96 samples can be prepared for tryptic digestion in under an hour. We validate these protocols by analyzing 47 Pseudomonas putida and Rhodosporidium toruloides samples and show that this modular workflow provides robust, reproducible proteomic samples for high-throughput applications. The expected results from these protocols are 94 peptide samples from Gram-negative bacterial and fungal cells prepared for bottom-up quantitative proteomic analysis without the need for desalting column cleanup and with protein relative quantity variance (CV%) below 15%. Public Library of Science 2022-02-25 /pmc/articles/PMC8880914/ /pubmed/35213656 http://dx.doi.org/10.1371/journal.pone.0264467 Text en © 2022 Chen et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Lab Protocol Chen, Yan Kaplan Lease, Nurgul Gin, Jennifer W. Ogorzalek, Tadeusz L. Adams, Paul D. Hillson, Nathan J. Petzold, Christopher J. Modular automated bottom-up proteomic sample preparation for high-throughput applications |
title | Modular automated bottom-up proteomic sample preparation for high-throughput applications |
title_full | Modular automated bottom-up proteomic sample preparation for high-throughput applications |
title_fullStr | Modular automated bottom-up proteomic sample preparation for high-throughput applications |
title_full_unstemmed | Modular automated bottom-up proteomic sample preparation for high-throughput applications |
title_short | Modular automated bottom-up proteomic sample preparation for high-throughput applications |
title_sort | modular automated bottom-up proteomic sample preparation for high-throughput applications |
topic | Lab Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880914/ https://www.ncbi.nlm.nih.gov/pubmed/35213656 http://dx.doi.org/10.1371/journal.pone.0264467 |
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