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Semiautomated device for batch extraction of metabolites from tissue samples.

ABSTRACT: Metabolomics has become a mainstream analytical strategy for investigating metabolism. The quality of data derived from these studies is proportional to the consistency of the sample preparation. Although considerable research has been devoted to finding optimal extraction protocols, most of the established methods require extensive sample handling. Manual sample preparation can be highly effective in the hands of skilled technicians, but an automated tool for purifying metabolites from complex biological tissues would be of obvious utility to the field. Here, we introduce the semiautomated metabolite batch extraction device (SAMBED), a new tool designed to simplify metabolomics sample preparation. We discuss SAMBED's design and show that SAMBED-based extractions are of comparable quality to extracts produced through traditional methods (13% mean coefficient of variation from SAMBED versus 16% from manual extractions). Moreover, we show that aqueous SAMBED-based methods can be completed in less than a quarter of the time required for manual extractions.

SUBMITTER: Ellinger JJ

PROVIDER: S-EPMC3284190 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Semiautomated device for batch extraction of metabolites from tissue samples.

Ellinger James J JJ Miller Dan C DC Lewis Ian A IA Markley John L JL

Analytical chemistry 20120207 4

Metabolomics has become a mainstream analytical strategy for investigating metabolism. The quality of data derived from these studies is proportional to the consistency of the sample preparation. Although considerable research has been devoted to finding optimal extraction protocols, most of the established methods require extensive sample handling. Manual sample preparation can be highly effective in the hands of skilled technicians, but an automated tool for purifying metabolites from complex ...[more]

PMID: 22292466

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Project description:BackgroundArchived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples.ResultsAs a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range (< 5%), and collectively shared a "C > T|G > A" mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates.ConclusionsThrough this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.

Project description:The detection of single nucleotide polymorphisms (SNPs) is of increasing importance in many areas including clinical diagnostics, patient stratification for pharmacogenomics, and advanced forensic analysis. In the work reported, we apply a semiautomated system for solid-phase electrochemical melting curve analysis (éMCA) for the identification of the allele present at a specific SNP site associated with an increased risk of bone fracture and predisposition to osteoporosis. Asymmetric isothermal recombinase polymerase amplification using ferrocene labeled forward primers was employed to generate single stranded redox labeled amplicons. In a first approach to demonstrate the proof of concept of combining asymmetric RPA with solid-phase éMCA, a simplified system housing a multielectrode array within a polymeric microsystem, sandwiched between two aluminum plates of a heater device, was used. Sample manipulation through the microfluidic channel was controlled by a syringe pump, and an external Ag/AgCl reference electrode was employed. Individual electrodes of the array were functionalized with four different oligonucleotide probes, each probe equivalent in design with the exception of the middle nucleotide. The isothermally generated amplicons were allowed to hybridize to the surface-tethered probes and subsequently subjected to a controlled temperature ramp, and the melting of the duplex was monitored electrochemically. A clear difference between the fully complementary and a single mismatch was observed. Having demonstrated the proof-of-concept, a device for automated éMCA with increased flexibility to house diverse electrode arrays with internal quasi-gold reference electrodes, higher resolution, and broader melting temperature range was developed and exploited for the detection of SNP hetero/homozygosity. Using the optimized conditions, the system was applied to the identification of the allele present at an osteoporosis associated SNP site, rs2741856, in 10 real fingerprick/venous blood samples, with results validated using Sanger sequencing.

Dataset Information

Semiautomated device for batch extraction of metabolites from tissue samples.

Publications

Semiautomated device for batch extraction of metabolites from tissue samples.

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