Cargando…

Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content

Urine features an ideal source of non-invasive diagnostic markers. Some intrinsic and methodological issues still pose barriers to its full potential as liquid biopsy substrate. Unlike blood, urine concentration varies with nutrition, hydration and environmental factors. Urine is enriched with EVs f...

Descripción completa

Detalles Bibliográficos
Autores principales: Vago, Riccardo, Radano, Giorgia, Zocco, Davide, Zarovni, Natasa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587215/
https://www.ncbi.nlm.nih.gov/pubmed/36271135
http://dx.doi.org/10.1038/s41598-022-22577-3
_version_ 1784813856944553984
author Vago, Riccardo
Radano, Giorgia
Zocco, Davide
Zarovni, Natasa
author_facet Vago, Riccardo
Radano, Giorgia
Zocco, Davide
Zarovni, Natasa
author_sort Vago, Riccardo
collection PubMed
description Urine features an ideal source of non-invasive diagnostic markers. Some intrinsic and methodological issues still pose barriers to its full potential as liquid biopsy substrate. Unlike blood, urine concentration varies with nutrition, hydration and environmental factors. Urine is enriched with EVs from urinary-genital tract, while its conservation, purification and normalization can introduce bias in analysis of EV subsets in inter-and intra-individual comparisons. The present study evaluated the methods that decrease such biases such as appropriate and feasible urine storage, optimal single-step EV purification method for recovery of proteins and RNAs from small urine volumes and a normalization method for quantitative analysis of urine EV RNAs. Ultracentrifugation, chemical precipitation and immuno-affinity were used to isolate EVs from healthy donors’ urine that was stored frozen or at room temperature for up to 6 months. Multiple urine biochemical and EV parameters, including particle count and protein content, were compared across urine samples. To this purpose nanoparticle tracking analysis (NTA) and protein assessment by BCA, ELISA and WB assays were performed. These measurements were correlated with relative abundances of selected EV mRNAs and miRNAs assessed by RT-PCR and ranked for the ability to reflect and correct for EV content variations in longitudinal urine samples. All purification methods enabled recovery and downstream analysis of EVs from as few as 1 ml of urine. Our findings highlight long term stability of EV RNAs upon urine storage at RT as well as excellent correlation of EV content in urine with some routinely measured biochemical features, such as total urine protein and albumin, but not creatinine most conventionally used for urine normalization. Comparative evaluation of mRNA and miRNAs in EV isolates revealed specific RNAs, in particular RNY4 and small miRNA panel, levels of which well reflected the inter-sample EV variation and therefore useful as possible post-analytical normalizers of EV RNA content. We describe some realistic urine processing and normalization solutions for unbiased readout of EV biomarker studies and routine clinical sampling and diagnostics providing the input for design of larger validation studies employing urine EVs as biomarkers for particular conditions and diseases.
format Online
Article
Text
id pubmed-9587215
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-95872152022-10-23 Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content Vago, Riccardo Radano, Giorgia Zocco, Davide Zarovni, Natasa Sci Rep Article Urine features an ideal source of non-invasive diagnostic markers. Some intrinsic and methodological issues still pose barriers to its full potential as liquid biopsy substrate. Unlike blood, urine concentration varies with nutrition, hydration and environmental factors. Urine is enriched with EVs from urinary-genital tract, while its conservation, purification and normalization can introduce bias in analysis of EV subsets in inter-and intra-individual comparisons. The present study evaluated the methods that decrease such biases such as appropriate and feasible urine storage, optimal single-step EV purification method for recovery of proteins and RNAs from small urine volumes and a normalization method for quantitative analysis of urine EV RNAs. Ultracentrifugation, chemical precipitation and immuno-affinity were used to isolate EVs from healthy donors’ urine that was stored frozen or at room temperature for up to 6 months. Multiple urine biochemical and EV parameters, including particle count and protein content, were compared across urine samples. To this purpose nanoparticle tracking analysis (NTA) and protein assessment by BCA, ELISA and WB assays were performed. These measurements were correlated with relative abundances of selected EV mRNAs and miRNAs assessed by RT-PCR and ranked for the ability to reflect and correct for EV content variations in longitudinal urine samples. All purification methods enabled recovery and downstream analysis of EVs from as few as 1 ml of urine. Our findings highlight long term stability of EV RNAs upon urine storage at RT as well as excellent correlation of EV content in urine with some routinely measured biochemical features, such as total urine protein and albumin, but not creatinine most conventionally used for urine normalization. Comparative evaluation of mRNA and miRNAs in EV isolates revealed specific RNAs, in particular RNY4 and small miRNA panel, levels of which well reflected the inter-sample EV variation and therefore useful as possible post-analytical normalizers of EV RNA content. We describe some realistic urine processing and normalization solutions for unbiased readout of EV biomarker studies and routine clinical sampling and diagnostics providing the input for design of larger validation studies employing urine EVs as biomarkers for particular conditions and diseases. Nature Publishing Group UK 2022-10-21 /pmc/articles/PMC9587215/ /pubmed/36271135 http://dx.doi.org/10.1038/s41598-022-22577-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Vago, Riccardo
Radano, Giorgia
Zocco, Davide
Zarovni, Natasa
Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content
title Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content
title_full Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content
title_fullStr Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content
title_full_unstemmed Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content
title_short Urine stabilization and normalization strategies favor unbiased analysis of urinary EV content
title_sort urine stabilization and normalization strategies favor unbiased analysis of urinary ev content
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587215/
https://www.ncbi.nlm.nih.gov/pubmed/36271135
http://dx.doi.org/10.1038/s41598-022-22577-3
work_keys_str_mv AT vagoriccardo urinestabilizationandnormalizationstrategiesfavorunbiasedanalysisofurinaryevcontent
AT radanogiorgia urinestabilizationandnormalizationstrategiesfavorunbiasedanalysisofurinaryevcontent
AT zoccodavide urinestabilizationandnormalizationstrategiesfavorunbiasedanalysisofurinaryevcontent
AT zarovninatasa urinestabilizationandnormalizationstrategiesfavorunbiasedanalysisofurinaryevcontent