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Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory...

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Autores principales: Emetu, Sophia, Troiano, Morgan, Goldmintz, Jacob, Tomberlin, Jensen, Grelet, Simon, Howe, Philip H., Korey, Christopher, Geslain, Renaud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MyJove Corporation 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908660/
https://www.ncbi.nlm.nih.gov/pubmed/29364226
http://dx.doi.org/10.3791/56898
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author Emetu, Sophia
Troiano, Morgan
Goldmintz, Jacob
Tomberlin, Jensen
Grelet, Simon
Howe, Philip H.
Korey, Christopher
Geslain, Renaud
author_facet Emetu, Sophia
Troiano, Morgan
Goldmintz, Jacob
Tomberlin, Jensen
Grelet, Simon
Howe, Philip H.
Korey, Christopher
Geslain, Renaud
author_sort Emetu, Sophia
collection PubMed
description Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory functions. However, a growing body of evidence indicates that cellular tRNA levels fluctuate in correspondence to varying conditions such as cell type, environment, and stress. The fluctuation of tRNA expression directly influences gene translation, favoring or repressing the expression of particular proteins. Ultimately comprehending the dynamic of protein synthesis requires the development of methods able to deliver high-quality tRNA profiles. The method that we present here is named SPOt, which stands for Streamlined Platform for Observing tRNA. SPOt consists of three steps starting with metabolic labeling of cell cultures with radioactive orthophosphate, followed by guanidinium thiocyanate-phenol-chloroform extraction of radioactive total RNAs and finally hybridization on in-house printed macroarrays. tRNA levels are estimated by quantifying the radioactivity intensities at each probe spot. In the protocol presented here we profile tRNAs in Mycobacterium smegmatis mc(2)155, a nonpathogenic bacterium often used as a model organism to study tuberculosis.
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spelling pubmed-59086602018-05-09 Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays Emetu, Sophia Troiano, Morgan Goldmintz, Jacob Tomberlin, Jensen Grelet, Simon Howe, Philip H. Korey, Christopher Geslain, Renaud J Vis Exp Genetics Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory functions. However, a growing body of evidence indicates that cellular tRNA levels fluctuate in correspondence to varying conditions such as cell type, environment, and stress. The fluctuation of tRNA expression directly influences gene translation, favoring or repressing the expression of particular proteins. Ultimately comprehending the dynamic of protein synthesis requires the development of methods able to deliver high-quality tRNA profiles. The method that we present here is named SPOt, which stands for Streamlined Platform for Observing tRNA. SPOt consists of three steps starting with metabolic labeling of cell cultures with radioactive orthophosphate, followed by guanidinium thiocyanate-phenol-chloroform extraction of radioactive total RNAs and finally hybridization on in-house printed macroarrays. tRNA levels are estimated by quantifying the radioactivity intensities at each probe spot. In the protocol presented here we profile tRNAs in Mycobacterium smegmatis mc(2)155, a nonpathogenic bacterium often used as a model organism to study tuberculosis. MyJove Corporation 2018-01-16 /pmc/articles/PMC5908660/ /pubmed/29364226 http://dx.doi.org/10.3791/56898 Text en Copyright © 2018, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Genetics
Emetu, Sophia
Troiano, Morgan
Goldmintz, Jacob
Tomberlin, Jensen
Grelet, Simon
Howe, Philip H.
Korey, Christopher
Geslain, Renaud
Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
title Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
title_full Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
title_fullStr Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
title_full_unstemmed Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
title_short Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
title_sort metabolic labeling and profiling of transfer rnas using macroarrays
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908660/
https://www.ncbi.nlm.nih.gov/pubmed/29364226
http://dx.doi.org/10.3791/56898
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