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Optimization of small-scale sample preparation for high-throughput OpenArray analysis.

ABSTRACT: OpenArray is one of the most high-throughput qPCR platforms available but its efficiency can be limited by sample preparation methods that are slow and costly. To optimize the sample workflow for high-throughput qPCR processing by OpenArray, small-scale sample preparation methods were compared for compatibility with this system to build confidence in a method that maintains quality and accuracy while using less starting material and saving time and money. This study is the first to show that the Cells-to-CT kit can be used to prepare samples within the dynamic range of OpenArray directly from cultured cells in a single well of a 96-well plate when used together with a cDNA preamplification PCR step. Use of Cells-to-CT produced results of similar quality and accuracy to that of a preparation method using purified RNA in less than half the sample preparation time. While Cells-to-CT samples also exhibited slightly increased variance, which affects the ability of OpenArray to distinguish small differences in gene expression, overall gene expression mean results correlated well between small-scale methods. This work demonstrates that Cells-to-CT with preamplification can be used to reliably prepare samples for OpenArray analysis while saving time, money, and starting material.

SUBMITTER: Abraham NA

PROVIDER: S-EPMC7884849 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Optimization of small-scale sample preparation for high-throughput OpenArray analysis.

Abraham Neeta A NA Campbell Anne C AC Hirst Warren D WD Nezich Catherine L CL

Journal of biological methods 20210201 1

OpenArray is one of the most high-throughput qPCR platforms available but its efficiency can be limited by sample preparation methods that are slow and costly. To optimize the sample workflow for high-throughput qPCR processing by OpenArray, small-scale sample preparation methods were compared for compatibility with this system to build confidence in a method that maintains quality and accuracy while using less starting material and saving time and money. This study is the first to show that the ...[more]

PMID: 33604395

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Project description:Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput 'peptidomics' methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.

Dataset Information

Optimization of small-scale sample preparation for high-throughput OpenArray analysis.

Publications

Optimization of small-scale sample preparation for high-throughput OpenArray analysis.

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