Stephen A. Martin

Bio: Stephen A. Martin is an academic researcher from Applied Biosystems. The author has contributed to research in topics: Matrix (chemical analysis) & Blood proteins. The author has an hindex of 6, co-authored 7 publications receiving 4560 citations.

Suppression of alpha-cyano-4-hydroxycinnamic acid matrix clusters and reduction of chemical noise in MALDI-TOF mass spectrometry

Abstract: Progress in high-throughput MALDI-TOFMS analysis, especially in proteome applications, requires development of practical and efficient procedures for the preparation of proteins and peptides in a form suitable for high acquisition rates. These methods should improve successful identification of peptides, which depends on the signal intensity and the absence of interfering signals. Contamination of MALDI samples with alkali salts results in reduced MALDI peptide sensitivity and causes matrix cluster formation (widely reported for CHCA matrix) observed as signals dominating in the range below m/z 1200 in MALDI spectra. One way to remove these background signals, especially for concentrations of peptides lower than 10 fmol/microL, is to wash matrix/sample spots after peptide cocrystallization on the MALDI plate with deionized water prior to analysis. This method takes advantage of the low water solubility of the CHCA compared to its alkali salts. We report here that the application of some ammonium salt solutions, such as citrates and phosphates, instead of deionized water greatly improves the efficiency of this washing approach. Another way to reduce matrix cluster formation is to add ammonium salts as a part of the MALDI matrix. The best results were obtained with monoammonium phosphate, which successfully suppressed matrix clusters and improved sensitivity. Combining both of these approaches-the addition of ammonium salts in the CHCA matrix followed by one postcrystallization washing step with ammonium buffer-provided a substantial ( approximately 3-5-fold) improvement in the sensitivity of MALDI-MS detection compared to unwashed sample spots. This sample preparation method resulted in improved spectral quality and was essential for successful database searching for subnanomolar concentrations of protein digests.

Method for characterizing biomolecules utilizing a result driven strategy

Abstract: In various embodiments, the methods for analyzing a sample are provided utilizing a result dependent acquisition strategy. In various embodiments, methods for analyzing a sample are provided wherein the sample is first analyzed by MALDI and MS to produce a first result that is then used to determine a second analysis that is used to analyze the sample again by MALDI and MS/MS or MSn to produce a second result.

Identification of Amadori-Modified Plasma Proteins in Type 2 Diabetes and the Effect of Short-Term Intensive Insulin Treatment

Abstract: OBJECTIVE —Growing evidence supports that nonenzymatic glycation products may cause hyperglycemia-induced diabetes complications. Amadori-modified proteins are the intermediate products of nonenzymatic glycation and constitute the forms of glycated proteins in diabetes. The objective of the current study was to utilize two-dimensional gel electrophoresis, Western blot, and mass spectrometry to identify Amadori-modified plasma proteins in type 2 diabetic patients with poor glycemic control and assess the impact of short-term insulin treatment on the glycation of these proteins. RESEARCH DESIGN AND METHODS —We compared eight type 2 diabetic subjects (aged 56 ± 3 years and BMI 29.7 ± 0.9 kg/m 2 ) with an average diabetes duration of 8.5 years (range 3–19) with equal numbers of weight-matched (aged 56 ± 2 years and BMI 30.1 ± 10.0 kg/m 2 ) and lean (aged 58 ± 2 years and BMI 25 ± 00.5 kg/m 2 ) nondiabetic subjects who have no first-degree relatives with diabetes. Two separate blood samples were collected from the type 2 diabetic subjects, one following 2 weeks of withdrawal of all antidiabetic medications (T 2 D−; plasma glucose 12.6 ± 1.0 mmol/l) and another following 10 days of intensive insulin treatment (T 2 D+; plasma glucose 5.5 ± 0.2 mmol/l). Plasma proteins were separated using single and two-dimensional gel electrophoresis. Western blot analysis was performed, and several proteins, which reacted with the Amadori-antibody (1-deoxyfructosyl lysine), were identified by tandem mass spectrometry. RESULTS —No significant differences in the glycation of proteins between the obese and lean groups were noted, but type 2 diabetic patients had several proteins with higher glycation than the control groups. We identified 12 plasma proteins with reduced reaction to the anti-Amadori antibody upon intensive insulin treatment. A significant ( P 2 D− and control subjects for all these proteins except the Ig light chain. Insulin treatment reduced Amadori modification of albumin (23.2%, P P P P P CONCLUSIONS —The current approach offers the opportunity to identify Amadori modification of many proteins that may cause functional alterations and offers the potential for monitoring short-term glycemic control in diabetic patients.

Result‐driven strategies for protein identification and quantitation – a way to optimize experimental design and derive reliable results

Abstract: Uni- or multidimensional microcapillary liquid chromatography (microLC) matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry (MS/MS) approaches have gained significant attention for quantifying and identifying proteins in complex biological samples. The off-line coupling of microLC with MS quantitation and MS/MS identification methods makes new result-dependent workflows possible. A relational database is used to store the results from multiple high performance liquid chromatography runs, including information about MALDI plate positions, and both peptide and protein quantitations, and identifications. Unlike electrospray methodology, where all the decisions about which peptide to fragment, must be made during peptide fractionations, in the MALDI experiments the samples are effectively "frozen in time". Therefore, additional MS and MS/MS spectra can be acquired, to promote more accurate quantitation or additional identifications until reliable results are derived that meet experimental design criteria. In the case of what can be designated the expression-dependent workflow, quantitation can be detached from identification and only peak pairs with biological relevant expression changes can be selected for further MS/MS analyses. Alternatively, additional MS/MS data can be acquired to confirm tentative peptide mass fingerprint hits in what is designated a search result-dependent workflow. In the MS data-dependent workflow, the goal is to collect as many meaningful spectra as possible by judiciously adjusting the acquisition parameters based on characteristics of the parent masses. This level of sophistication requires the development of innovative algorithms for these three result-dependent workflows that make MS and MS/MS analysis more efficient and also add confidence to experimental results.

Insights into the regulation of protein abundance from proteomic and transcriptomic analyses

Abstract: Recent advances in next-generation DNA sequencing and proteomics provide an unprecedented ability to survey mRNA and protein abundances. Such proteome-wide surveys are illuminating the extent to which different aspects of gene expression help to regulate cellular protein abundances. Current data demonstrate a substantial role for regulatory processes occurring after mRNA is made - that is, post-transcriptional, translational and protein degradation regulation - in controlling steady-state protein abundances. Intriguing observations are also emerging in relation to cells following perturbation, single-cell studies and the apparent evolutionary conservation of protein and mRNA abundances. Here, we summarize current understanding of the major factors regulating protein expression.

The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.

Abstract: MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda This protocol update describes an adaptation of an existing protocol that substantially modifies the technique Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs) The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores The software is written in C# and is freely available at http://wwwmaxquantorg

Mass spectrometry and protein analysis.

Abstract: Mass spectrometry is a central analytical technique for protein research and for the study of biomolecules in general. Driven by the need to identify, characterize, and quantify proteins at ever increasing sensitivity and in ever more complex samples, a wide range of new mass spectrometry-based analytical platforms and experimental strategies have emerged. Here we review recent advances in mass spectrometry instrumentation in the context of current and emerging research strategies in protein science.