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Registration for the Annual Mass Spectrometry Summer School Opens Jan 8

Registration for the 3rd annual North American Mass Spectrometry Summer School is now open.

This free event, which will take place June 15-18, 2020 in Madison, Wisconsin will feature world-leading experts in Mass Spectrometry, who will deliver lectures and tutorials on both plant (NSF) and animal (NIH) mass spec applications. 

Program details and registration can be found on the NCQBCS website, located here:

Please help us spread the word about Mass Spec Summer School by telling your colleagues and friends who might benefit from attending. 

Registration for this opportunity closes on March 1.

Metandem, a free and online software for MS-based isobaric labeling metabolomics

Hao et al. (2019) recently published a paper in Analytica Chimica Acta detailing the utility of Metandem, a data analysis software which is aids in isobaric labeling-based metabolomics.

While mass spectrometry-based stable isotope labeling is advantageous compared to other methods of isotope labeling due to its multiplexing and accurate quantification capabilities, its data analysis requires specifically customized bioinformatic tools. However, Metandem, a free, unique and online software, can aid in the analysis of stable isotope labeling-based metabolomics data.

Metandem has a number of different features that assist in MS-based isobaric labeling, such as integrating feature extraction, metabolite quantification and identification, batch processing of multiple data files, online parameter optimization for custom datasets, data normalization and statistical analysis.

Metatandem is available free and online at http://metandem.com/web/

Software Highlight: Compass

The Coon OMSSA Proteomic Analysis Software Suite, or COMPASS, is one of many custom software and web-based data tools that NCQBCS offers in an effort to extend its expertise to the broader scientific community.

Compass is a free and open-source software pipeline designed around the Open Mass Spectrometry Search Algorithm. Compass aids in high-throughput analysis of proteomics data such as FASTA database creation, peptide-spectral matching, calculation of false discovery rates, and protein grouping, as well as spectral reduction, peptide quantitation via isobaric labeling (or without), and protein parsimony.

Furthermore Compass utilizes graphical user interfaces which work well with data files in original instrument vendor format, making it easy to use.

The manuscript for Compass is available here, and the software can be downloaded here. Additionally, information on other software that the National Center for Quantitative Biology of Complex Systems offers can be found here.

Selecting a Labeling Strategy for Quantitative Proteomics of Multiple Samples

Buchberger AR et al (2019) recently published a chapter reviewing various labelling strategies for quantitative proteomic analysis in Mass Spectrometry-Based Chemical Proteomics.

Specifically, the chapter reviews strategies such as label-free quantitation, metabolic labeling, and chemical stable isotope labeling, and also discusses which labeling approach is best for various types of proteomic analyses. The chapter also provides an explanation on how to use N,N‐dimethyl alanine (DiAla) and N,N‐ dimethyl valine (DiVal) isobaric labeling strategies for quantitative analyses in ways which are economic and effective.

The chapter states that quantitative proteomics is crucial for biomarker discovery in studying and understanding various diseases and biological research, as proteins are crucial in all biological processes. Because biomarker studies can be time-consuming, heavily reliant on instruments and vary depending on the strategy used, selecting the appropriate labeling strategy is important in quantitative analysis.

NCQBCS Offers Broad Range of Training Programs for all Levels of Learners

A key goal of the National Center for Quantitative Biology of Complex Systems is to extend its expertise to the broader scientific community. Therefore, NCQBCS offers hands-on-training programs ranging from basic basic proteomic methodology to advanced technological techniques.

NCQBCS, which works to develop next-generation protein measurement technologies for biomedical application, has programs available for a wide range of students. This means that there are introductory training programs available for those interested in learning the basics of mass spectrometry, as well as programs geared for experts on specific technologies.

NCQBCS divides its training topics into four broad categories: Sample Preparation, Instrumentation, Data Analysis, and Protein Quantification. Trainees can build their own syllabus of workshops from a variety of categories and experience levels.

Comprehensively, we offer programs in:
Sample Preparation: Peptide Fractionation, Protein Digestion, Protein extraction.
Mass Spectrometry: MS Methods, Instrument Troubleshooting, Nano-chromatography.
Data Analysis: Data Visualization, Data Interpretation, Data Searching.
Protein Quantification: Label-free, Metabolic labeling, Isobaric chemical labeling.

More information on our training programs are located here, and one can sign up for training here.

Additionally, one can also receive coaching at the 3rd Annual North American Mass Spectrometry Summer School, which will take place June 15-18, 2020. This event, which will be hosted by international experts on Mass Spectrometry, will feature workshops, lectures and networking, among other activities.

One may find more information, as well as sign up for summer school, here.

Increasing MS lipidomics power through parameter optimization and In Silico Simulation

Huchins et al (2019) recently published a paper in Analytical Chemistry presenting an algorithm which identifies parameter sets in a way that is quicker and more accurate than typical methods.

The issue of effectively profiling the diversity and range of biomolecules is an important one to consider in Mass Spectrometry, and relies on well-sought out selection of acquisition parameters. However, acquisition parameters are generally selected in a way that is time-consuming and tends to produce lacking results.

By creating an algorithm which simulates LC-MS/MS lipidomic data acquisition performance in a benchtop quadrupole-Orbitrap Mass Spectrometer system and pairing it with an algorithm that defines constrained parameter optimization, researchers were able to efficiently identify LC-MS/MS method parameter sets for specific sample matrices. Additionally, researchers used a simulation called in silico to demonstrate how developments in mass spectrometer speed and sensitivity will result in even more effective biomolecule identification.