High-throughput tissue extraction protocol for NMR- and MS-based metabolomics

In metabolomics, tissues typically are extracted by grinding in liquid nitrogen followed by the stepwise addition of solvents. This is time-consuming and difficult to automate, and the multiple steps can introduce variability. Here we optimize tissue extraction methods compatible with high-throughput, reproducible nuclear magnetic resonance (NMR) spectroscopy- and mass spectrometry (MS)-based metabolomics. Previously, we concluded that methanol/chloroform/water extraction is preferable for metabolomics, and we further optimized this here using fish liver and an automated Precellys 24 bead-based homogenizer, allowing rapid extraction of multiple samples without carryover. We compared three solvent addition strategies: stepwise, two-step, and all solvents simultaneously. Then we evaluated strategies for improved partitioning of metabolites between solvent phases, including the addition of extra water and different partition times. Polar extracts were analyzed by NMR and principal components analysis, and the two-step approach was preferable based on lipid partitioning, reproducibility, yield, and throughput. Longer partitioning or extra water increased yield and decreased lipids in the polar phase but caused metabolic decay in these extracts. Overall, we conclude that the two-step method with extra water provides good quality data but that the two-step method with 10 min partitioning provides a more accurate snapshot of the metabolome. Finally, when validating the two-step strategy using NMR and MS metabolomics, we showed that technical variability was considerably smaller than biological variability.     

Procedure for tissue sample preparation and metabolite extraction for high-throughput targeted metabolomics

Reproducible quantification of metabolites in tissue samples is of high importance for characterization of animal models and identification of metabolic changes that occur in different tissue types in specific diseases. However, the extraction of metabolites from tissue is often the most labor-intensive and error-prone step in metabolomics studies. Here, we report the development of a standardized high-throughput method for rapid and reproducible extraction of metabolites from multiple tissue samples from different organs of several species. The method involves a bead-based homogenizer in combination with a simple extraction protocol and is compatible with state-of-the-art metabolomics kit technology for quantitative and targeted flow injection tandem mass spectrometry. We analyzed different extraction solvents for both reproducibility as well as suppression effects for a range of different animal tissue types including liver, kidney, muscle, brain, and fat tissue from mouse and bovine. In this study, we show that for most metabolites a simple methanolic extraction is best suited for reliable results. An additional extraction step with phosphate buffer can be used to improve the extraction yields for a few more polar metabolites. We provide a verified tissue extraction setup to be used with different indications. Our results demonstrate that this high-throughput procedure provides a basis for metabolomic assays with a wide spectrum of metabolites. The developed method can be used for tissue extraction setup for different indications like studies of metabolic syndrome, obesity, diabetes or cardiovascular disorders and nutrient transformation in livestock.     

High-throughput DNA extraction method suitable for PCR

PCR has become one of the most popular techniques in functional genomics. Projects in both forward and reverse genetics routinely require PCR amplification of thousands of samples. Processing samples to extract DNA of sufficient purity for PCR is often a limiting step. We have developed a simple 96-well plate-based high-throughput DNA extraction method that is applicable to many plant species. The method involves a simple incubation of plant tissue samples in a DNA extraction buffer followed by a neutralization step. With the addition of a modified PCR buffer, the extracted DNA enabled the robust amplification of genomic fragments from samples of Arabidopsis, tobacco, sorghum, cotton, moss, and even pine needles. Several thousand DNA samples can be economically processed in a single day by one person without the use of robotics. This procedure will facilitate many technologies including high-throughput genotyping, map-based cloning, and identification of T-DNA or transposon-tagged mutants for known gene sequences.     

A robust,single-injection method for targeted,broad-spectrum plasma metabolomics

Background

Metabolomics is a powerful emerging technology for studying the systems biology and chemistry of health and disease. Current targeted methods are often limited by the number of analytes that can be measured, and/or require multiple injections.

Methods

We developed a single-injection, targeted broad-spectrum plasma metabolomic method on a SCIEX Qtrap 5500 LC-ESI-MS/MS platform. Analytical validation was conducted for the reproducibility, linearity, carryover and blood collection tube effects. The method was also clinically validated for its potential utility in the diagnosis of chronic fatigue syndrome (CFS) using a cohort of 22 males CFS and 18 age- and sex-matched controls.

Results

Optimization of LC conditions and MS/MS parameters enabled the measurement of 610 key metabolites from 63 biochemical pathways and 95 stable isotope standards in a 45-minute HILIC method using a single injection without sacrificing sensitivity. The total imprecision (CV_total) of peak area was 12% for both the control and CFS pools. The 8 metabolites selected in our previous study (PMID: 27573827) performed well in a clinical validation analysis even when the case and control samples were analyzed 1.5 years later on a different instrument by a different investigator, yielding a diagnostic accuracy of 95% (95% CI 85–100%) measured by the area under the ROC curve.

Conclusions

A reliable and reproducible, broad-spectrum, targeted metabolomic method was developed, capable of measuring over 600 metabolites in plasma in a single injection. The method might be a useful tool in helping the diagnosis of CFS or other complex diseases.

     

A large-scale assay library for targeted protein quantification in renal cell carcinoma tissues

Renal cell carcinoma (RCC) represents 2.2% of all cancer incidences; however, prognostic or predictive RCC biomarkers at protein level are largely missing. To support proteomics research of localized and metastatic RCC, we introduce a new library of targeted mass spectrometry assays for accurate protein quantification in malignant and normal kidney tissue. Aliquots of 86 initially localized RCC, 75 metastatic RCC and 17 adjacent non-cancerous fresh frozen tissue lysates were trypsin digested, pooled, and fractionated using hydrophilic chromatography. The fractions were analyzed using LC-MS/MS on QExactive HF-X mass spectrometer in data-dependent acquisition (DDA) mode. A resulting spectral library contains 77,817 peptides representing 7960 protein groups (FDR = 1%). Further, we confirm applicability of this library on four RCC datasets measured in data-independent acquisition (DIA) mode, demonstrating a specific quantification of a substantially increased part of RCC proteome, depending on LC-MS/MS instrumentation. Impact of sample specificity of the library on the results of targeted DIA data extraction was demonstrated by parallel analyses of two datasets by two pan human libraries. The new RCC specific library has potential to contribute to better understanding the RCC development at molecular level, leading to new diagnostic and therapeutic targets.     

Analytical strategies for LC-MS-based targeted metabolomics

Recent advances in mass spectrometry are enabling improved analysis of endogenous metabolites. Here we discuss several issues relevant to developing liquid chromatography-electrospray ionization-mass spectrometry methods for targeted metabolomics (i.e., quantitative analysis of dozens to hundreds of specific metabolites). Sample preparation and liquid chromatography approaches are discussed, with an eye towards the challenge of dealing with a diversity of metabolite classes in parallel. Evidence is presented that heated electrospray ionization (ESI) generally gives improved signal compared to the more traditional unheated ESI. Applicability to targeted metabolomics of triple quadrupole mass spectrometry operating in multiple reaction monitoring (MRM) mode and high mass resolution full scan mass spectrometry (e.g., time-of-flight, Orbitrap) are described. We suggest that both are viable solutions, with MRM preferred when targeting a more limited number of analytes, and full scan preferred for its potential ability to bridge targeted and untargeted metabolomics.     

High-throughput quantification of hydroxyproline for determination of collagen

An accurate and high-throughput assay for collagen is essential for collagen research and development of collagen products. Hydroxyproline is routinely assayed to provide a measurement for collagen quantification. The time required for sample preparation using acid hydrolysis and neutralization prior to assay is what limits the current method for determining hydroxyproline. This work describes the conditions of alkali hydrolysis that, when combined with the colorimetric assay defined by Woessner, provide a high-throughput, accurate method for the measurement of hydroxyproline.     

High-throughput non-heme iron assay for animal tissues

Iron has been widely studied in nearly every realm of biology. However, current methodologies, such as genetic mapping or mutation screening, have been difficult to apply due to the lack of robust high-throughput methods for quantifying iron levels from cells or tissues. The measurement of total iron levels in tissues, usually done with atomic absorption spectroscopy, is impractical for large numbers of samples and includes the contribution of heme iron from hemoglobin contained in red blood cells. The measurement of non-heme iron by reaction with a bathophenanthroline reagent, a commonly used assay reported more than 30 years ago, is also not feasible for large-scale analyses because it is cuvette-based. We therefore have modified this method to a microplate format that will facilitate large-scale analysis. The microplate assay is highly sensitive and specific, and is a simple and effective method for the measurement of non-heme iron for animal tissues that will enable the application of high-throughput of genetic methodologies.     

An efficient and scalable extraction and quantification method for algal derived biofuel

Microalgae are capable of synthesizing a multitude of compounds including biofuel precursors and other high value products such as omega-3-fatty acids. However, accurate analysis of the specific compounds produced by microalgae is important since slight variations in saturation and carbon chain length can affect the quality, and thus the value, of the end product. We present a method that allows for fast and reliable extraction of lipids and similar compounds from a range of algae, followed by their characterization using gas chromatographic analysis with a focus on biodiesel-relevant compounds. This method determines which range of biologically synthesized compounds is likely responsible for each fatty acid methyl ester (FAME) produced; information that is fundamental for identifying preferred microalgae candidates as a biodiesel source. Traditional methods of analyzing these precursor molecules are time intensive and prone to high degrees of variation between species and experimental conditions. Here we detail a new method which uses microwave energy as a reliable, single-step cell disruption technique to extract lipids from live cultures of microalgae. After extractable lipid characterization (including lipid type (free fatty acids, mono-, di- or tri-acylglycerides) and carbon chain length determination) by GC–FID, the same lipid extracts are transesterified into FAMEs and directly compared to total biodiesel potential by GC–MS. This approach provides insight into the fraction of total FAMEs derived from extractable lipids compared to FAMEs derived from the residual fraction (i.e. membrane bound phospholipids, sterols, etc.). This approach can also indicate which extractable lipid compound, based on chain length and relative abundance, is responsible for each FAME. This method was tested on three species of microalgae; the marine diatom Phaeodactylum tricornutum, the model Chlorophyte Chlamydomonas reinhardtii, and the freshwater green alga Chlorella vulgaris. The method is shown to be robust, highly reproducible, and fast, allowing for multiple samples to be analyzed throughout the time course of culturing, thus providing time-resolved information regarding lipid quantity and quality. Total time from harvesting to obtaining analytical results is less than 2 h.     

16S rRNA targeted sandwich hybridization method for direct quantification of mycobacteria in soils

Boreal soils have been suspected reservoirs of infectious environmental mycobacteria. Detection of these bacteria in the environment is hampered by their slow growth. We applied a quantitative sandwich hybridization approach for direct detection of mycobacterial 16S rRNA in soil without a nucleic acid amplification step. The numbers of mycobacterial 16S rRNA molecules found in the soil indicated the presence of up to 10(7) to 10(8) mycobacterial cells per gram of soil. These numbers exceed by factor of 10 to 100 x the previous estimates of mycobacteria in soil based on culture methods. When real-time PCR with mycobacteria targeting primers was used to estimate the number of 16S rDNA copies in soil, one copy of 16S rDNA was detected per 10(4) copies of 16S rRNA. This is close to the number of 16S rRNA molecules detected per cell by the same method in laboratory pure cultures of M. chlorophenolicum. Therefore a major part of the mycobacterial DNA in the studied soils may thus have represented metabolically active cells. The 16S rRNA sandwich hybridization method described in this paper offers a culture independent solution for tracking environmental reservoirs of viable and potentially infectious mycobacteria.     

Large-scale phosphosite quantification in tissues by a spike-in SILAC method

Despite progress in mass spectrometry (MS)-based phosphoproteomics, large-scale in vivo analyses remain challenging. Here we report a 'spike-in' stable-isotope labeling with amino acids in cell culture (SILAC) methodology using standards derived from labeled mouse liver cell lines, using which we analyzed insulin signaling. With this approach we identified 15,000 phosphosites and quantitatively compared 10,000 sites in response to insulin treatment, creating a very large, accurately quantified in vivo phosphoproteome dataset.     

High-throughput determination of malondialdehyde in plant tissues

Malondialdehyde (MDA) is a widely used marker of oxidative lipid injury whose concentration varies in response to biotic and abiotic stress. Commonly, MDA is quantified as a strong light-absorbing and fluorescing adduct following reaction with thiobarbituric acid (TBA). However, plant tissues in particular contain many compounds that potentially interfere with this reaction and whose concentrations also vary according to the tissue type and stress conditions. As part of our studies into the stress responses of plant tissues, we were interested in developing a rapid, accurate, and robust protocol for MDA analysis using reverse-phased HPLC to avoid these problems with reaction specificity. We demonstrate that a partitioning step into n-butanol during sample preparation is essential and that gradient HPLC analysis is necessary to prevent sample carryover between injections. Furthermore, the starting composition of the mobile phase must be sufficiently hydrophobic to allow direct injection of the n-butanol extracts without peak splitting, tailing, and other artifacts. To minimize analysis times, we used a short, so-called "Rocket" HPLC column and high flow rates. The optimized HPLC separation has a turnaround time of 2.5 min per sample. Butanolic extracts of MDA(TBA)(2) were stable for at least 48 h, and recoveries were linear between 0.38 and 7.5 pmol MDA added. Importantly, this procedure proved to be compatible with existing extraction procedures for l-ascorbate and glutathione analysis in different plant species, allowing multiple "stress metabolite" analyses to be carried out on a single tissue extract.     

Histidine-rich peptide selection and quantification in targeted proteomics

Agarose based immobilized copper (II) affinity chromatography (Cu(II)-IMAC) in tandem with reversed-phase chromatography was applied to a yeast protein extract. Histidine-rich peptides were selected and, in the process, samples were substantially simplified prior to mass spectral analysis. Samples of proteins from the yeast extract at fermentation time periods of 2.5 and 10 h were compared quantitatively used the GIST protocol. Acylation of the N-terminus of tryptic peptides with N-acetoxysuccinamide was used to globally label and quantify relative protein concentration changes. Together with N-terminal acylation, an imidazole elution procedure allowed histidine-rich peptides to be preferentially selected by Cu(II)-IMAC. An inverse labeling strategy was applied to increase reliability in determinations of up- and down-regulation. It was found that the concentration of some histidine-rich proteins changed in excess of 4-fold during fermentation. These proteins covered a wide range of molecular weight and pI values.     

A fully automatable enzymatic method for DNA extraction from plant tissues

Background  

DNA extraction from plant tissues, unlike DNA isolation from mammalian tissues, remains difficult due to the presence of a rigid cell wall around the plant cells. Currently used methods inevitably require a laborious mechanical grinding step, necessary to disrupt the cell wall for the release of DNA.     

A reliable method for extraction of RNA from various conifer tissues

Summary A simple and efficient procedure suitable for extraction of high-quality RNA from cultured conifer tissues, somatic embryos, zygotic embryos, needles, stem and root tissues was developed. It produced from 100 g up to 700 g total RNA per gram tissue dependent on the types of tissues used. RNA quality was estimated by spectrophotometry, agarose gel electrophoresis, in vitro translation of mRNA, cDNA synthesis and Northern blot analysis. The method also worked well with Arabidopsis thaliana and tobacco tissues.Abbreviations CTAB cetyltrimethylammonium bromide - DEPC diethylpyrocarbonate - PVP polyvinylpyrrolidone - SDS-PAGE sodium dodecyl sulphate-polyacrylamide gel electrophoresis     

High-throughput method for detecting DNA methylation

Aberrant DNA methylation of CpG site is among the earliest and most frequent alterations in cancer. Detection of promoter hypermethylation of cancer-related gene may be useful for cancer diagnosis or the detection of recurrence. However, most of the studies have focused on a single gene only and gave little information about the concurrent methylation status of multiple genes. In this study, we attempted to develop a microarray method coupled with linker-PCR for detecting methylation status of multiple genes in the tumor tissue. A series of synthesized oligonucleotides were synthesised and purified to completely match with 16 investigated targets. Then they were immobilized on the aldehyde-coated glass slide to fabricate a DNA microarray for detecting methylation status of these genes. The results indicated that these genes were all methylated in the positive control. However, no methylated was found in these genes for the negative control. Only p16 and p15 genes were methylated in investigated genes for the gastric tumor tissue, whereas others were not methylated. The above results were validated by bisulfite DNA sequencing. Our experiments successfully demonstrated that the DNA microarray could be applied as a high-throughput tool to determine methylation status of the investigated genes.     

Complexity and pitfalls of mass spectrometry-based targeted metabolomics in brain research

Current quantitative metabolomic research in brain tissue is challenged by several analytical issues. To compare data of metabolite pattern, ratios of individual metabolite concentrations and composed classifiers characterizing a distinct state, standardized workup conditions, and extraction medium are crucial. Differences in physicochemical properties of individual compounds and compound classes such as polarity determine extraction yields and, thus, ratios of compounds with varying properties. Also, variations in suppressive effects related to coextracted matrix components affect standards or references and their concentration-dependent responses.The selection of a common tissue extraction protocol is an ill-posed problem because it can be regarded as a multiple objective decision depending on factors such as sample handling practicability, measurement precision, control of matrix effects, and relevance of the chemical assay. This study systematically evaluates the impact of extraction solvents and the impact of the complex brain tissue on measured metabolite levels, taking into account ionization efficiency as well as challenges encountered in the trace-level quantification of the analytes in brain matrices. In comparison with previous studies that relied on nontargeted platforms, consequently emphasizing the global behavior of the metabolomic fingerprint, here we focus on several series of metabolites spanning over extensive polarity, concentration, and molecular mass ranges.     

High-throughput magnetic resonance imaging in murine colonic inflammation

The aim of this study was to investigate if a rapid magnetic resonance imaging (MRI) screening protocol (<5min/mouse) could characterize colonic inflammation in a chronic experimental colitis model. No respiratory triggering or spasmolytic agent was used during MRI-acquisition. Biomarkers assessed in vivo were colon wall thickness and T2w signal intensity (reflecting oedema) and ex vivo inflammatory score, colon weight, and plasma haptoglobin. The inflammation was characterised by significantly higher local and systemic inflammatory markers in the colitic mice compared to healthy mice. MRI-colon wall thickness and T2w signal intensity correlated well with inflammatory score (r=0.95 and 0.94), colon weight (r=0.92 and 0.93) and plasma haptoglobin (r=0.89 and 0.95). Thus, the data showed that in vivo MRI screening could be used to assess colon wall inflammation, suggesting that high-throughput MRI can be used to follow the potential efficacy of new IBD therapies in individual animal in longitudinal studies.     

An optimized method for extraction and quantification of nucleotides and nucleotide sugars from mammalian cells

Glycosylation is a critical attribute of therapeutic proteins given its impact on the clinical safety and efficacy of these molecules. The biochemical process of glycosylation is inextricably dependent on metabolism and ensuing availability of nucleotides and nucleotide sugars (NSs) during cell culture. Herein, we present a comprehensive methodology to extract and quantify these metabolites from cultured cells. To establish the full protocol, two methods for the extraction of these compounds were evaluated for efficiency, and the requirement for quenching and washing the sample was assessed. A chromatographic method based on anion exchange has been optimized to separate and quantify eight nucleotides and nine NSs in less than 30 min. Degradation of nucleotides and NSs under extraction conditions was evaluated to aid in selection of the most efficient extraction protocol. We conclude that the optimized chromatographic method is quick, robust, and sensitive for quantifying nucleotides and NSs. Furthermore, our results show that samples taken from cell culture should be treated with 50% v/v acetonitrile and do not require quenching or washing for reliable extraction of nucleotides and NSs. This comprehensive protocol should prove useful in determining the impact of nucleotide and NS metabolism on protein glycosylation.