Cargando…

Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables

BACKGROUND: A large number of studies have suggested a correlation between the status of telomeres and disease risk. High-throughput quantitative fluorescence in situ hybridization (HT Q-FISH) is a highly accurate telomere measurement technique that can be applied to the study of large cell populati...

Descripción completa

Detalles Bibliográficos
Autores principales: de Pedro, Nuria, Díez, María, García, Irene, García, Jorge, Otero, Lissette, Fernández, Luis, García, Beatriz, González, Rut, Rincón, Sara, Pérez, Diego, Rodríguez, Estefanía, Segovia, Enrique, Najarro, Pilar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6961256/
https://www.ncbi.nlm.nih.gov/pubmed/31956299
http://dx.doi.org/10.1186/s12575-019-0115-z
_version_ 1783487952281665536
author de Pedro, Nuria
Díez, María
García, Irene
García, Jorge
Otero, Lissette
Fernández, Luis
García, Beatriz
González, Rut
Rincón, Sara
Pérez, Diego
Rodríguez, Estefanía
Segovia, Enrique
Najarro, Pilar
author_facet de Pedro, Nuria
Díez, María
García, Irene
García, Jorge
Otero, Lissette
Fernández, Luis
García, Beatriz
González, Rut
Rincón, Sara
Pérez, Diego
Rodríguez, Estefanía
Segovia, Enrique
Najarro, Pilar
author_sort de Pedro, Nuria
collection PubMed
description BACKGROUND: A large number of studies have suggested a correlation between the status of telomeres and disease risk. High-throughput quantitative fluorescence in situ hybridization (HT Q-FISH) is a highly accurate telomere measurement technique that can be applied to the study of large cell populations. Here we describe the analytical performance testing and validation of Telomere Analysis Technology (TAT®), a laboratory-developed HT Q-FISH-based methodology that includes HT imaging and software workflows that provide a highly detailed view of telomere populations. METHODS: TAT was developed for the analysis of telomeres in peripheral blood mononuclear cells (PBMCs). TAT was compared with Terminal Restriction Fragment (TRF) length analysis, and tested for accuracy, precision, limits of detection (LOD) and specificity, reportable range and reference range. RESULTS: Using 6 different lymphocyte cell lines, we found a high correlation between TAT and TRF for telomere length (R(2) ≥ 0.99). The standard variation (assay error) of TAT was 454 base pairs, and the limit of detection of 800 base pairs. A standard curve was constructed to cover human median reportable range values and defined its lower limit at 4700 bp and upper limits at 14,400 bp. Using TAT, up to 223 telomere associated variables (TAVs) can be obtained from a single sample. A pilot, population study, of telomere analysis using TAT revealed high accuracy and reliability of the methodology. CONCLUSIONS: Analytical validation of TAT shows that is a robust and reliable technique for the characterization of a detailed telomere profile in large cell populations. The combination of high-throughput imaging and software workflows allows for the collection of a large number of telomere-associated variables from each sample, which can then be used in epidemiological and clinical studies.
format Online
Article
Text
id pubmed-6961256
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-69612562020-01-17 Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables de Pedro, Nuria Díez, María García, Irene García, Jorge Otero, Lissette Fernández, Luis García, Beatriz González, Rut Rincón, Sara Pérez, Diego Rodríguez, Estefanía Segovia, Enrique Najarro, Pilar Biol Proced Online Methodology BACKGROUND: A large number of studies have suggested a correlation between the status of telomeres and disease risk. High-throughput quantitative fluorescence in situ hybridization (HT Q-FISH) is a highly accurate telomere measurement technique that can be applied to the study of large cell populations. Here we describe the analytical performance testing and validation of Telomere Analysis Technology (TAT®), a laboratory-developed HT Q-FISH-based methodology that includes HT imaging and software workflows that provide a highly detailed view of telomere populations. METHODS: TAT was developed for the analysis of telomeres in peripheral blood mononuclear cells (PBMCs). TAT was compared with Terminal Restriction Fragment (TRF) length analysis, and tested for accuracy, precision, limits of detection (LOD) and specificity, reportable range and reference range. RESULTS: Using 6 different lymphocyte cell lines, we found a high correlation between TAT and TRF for telomere length (R(2) ≥ 0.99). The standard variation (assay error) of TAT was 454 base pairs, and the limit of detection of 800 base pairs. A standard curve was constructed to cover human median reportable range values and defined its lower limit at 4700 bp and upper limits at 14,400 bp. Using TAT, up to 223 telomere associated variables (TAVs) can be obtained from a single sample. A pilot, population study, of telomere analysis using TAT revealed high accuracy and reliability of the methodology. CONCLUSIONS: Analytical validation of TAT shows that is a robust and reliable technique for the characterization of a detailed telomere profile in large cell populations. The combination of high-throughput imaging and software workflows allows for the collection of a large number of telomere-associated variables from each sample, which can then be used in epidemiological and clinical studies. BioMed Central 2020-01-15 /pmc/articles/PMC6961256/ /pubmed/31956299 http://dx.doi.org/10.1186/s12575-019-0115-z Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
de Pedro, Nuria
Díez, María
García, Irene
García, Jorge
Otero, Lissette
Fernández, Luis
García, Beatriz
González, Rut
Rincón, Sara
Pérez, Diego
Rodríguez, Estefanía
Segovia, Enrique
Najarro, Pilar
Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables
title Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables
title_full Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables
title_fullStr Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables
title_full_unstemmed Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables
title_short Analytical Validation of Telomere Analysis Technology® for the High-Throughput Analysis of Multiple Telomere-Associated Variables
title_sort analytical validation of telomere analysis technology® for the high-throughput analysis of multiple telomere-associated variables
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6961256/
https://www.ncbi.nlm.nih.gov/pubmed/31956299
http://dx.doi.org/10.1186/s12575-019-0115-z
work_keys_str_mv AT depedronuria analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT diezmaria analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT garciairene analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT garciajorge analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT oterolissette analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT fernandezluis analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT garciabeatriz analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT gonzalezrut analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT rinconsara analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT perezdiego analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT rodriguezestefania analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT segoviaenrique analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables
AT najarropilar analyticalvalidationoftelomereanalysistechnologyforthehighthroughputanalysisofmultipletelomereassociatedvariables