Short Courses


Short courses listed below are offered at US HUPO 2019 at the Hilton Washington DC/Rockville Executive Conference Center & Hotel. Short Course enrollment is open to all, conference registration is not required. To register, please go to the Registration page.

On this page you will find short course listing and fees, plus a descriptions of each course.

 

Short Course Titles and Tuition Fees

Two-day course (Saturday-Sunday, March 2-3) Tuition: Member $350; Non-member $450; Student or Post-doc Member $250; Student or Post-doc Non-member $350

Half-day courses (Sunday, March 3) Tuition for each half-day course: Member $150; Non-member $200; Student or Post-doc Member $125; Student or Post-doc Non-member $150

 

How to Sign-up for a Short Course

To sign-up for a short course, please use online registration or printable form (posted on the Registration page).

 

Short Course Descriptions

Design and Analysis of Quantitative Proteomic Experiments: Introduction to Statistical Methods and Practical Examples using Skyline, R and MS Stats

Two-day Course, Saturday-Sunday, March 2-3, 9am-4pm each dayInstructors: Meena Choi (Northeastern University), Brendan MacLean (University of Washington), Birgit Schilling (Buck Institute on Aging), and Olga Vitek (Northeastern University)

This 2-day course will discuss details of statistical experimental design of quantitative mass spectrometry-based proteomic experiments, and the analysis of the acquired data with Skyline and MSstats. It is designed for experimentalists looking to enhance their statistical and data analysis skills, and will contain both lectures and practical hands-on exercises.

First, the course will discuss the fundamental concepts of statistical experimental design, that are key for designing reproducible investigations. Second, the course will introduce the open-source software Skyline. In particular, we will demonstrate the use of Skyline for proteome-wide profiling of samples with label-free shotgun data-dependent spectral acquisition (DDA), and the process of building libraries from DDA spectra to analyze profiling experiments with data-independent acquisition (DIA). The participants will practice these analysis steps using example datasets. Finally, we will discuss the principles of statistical inference, including summarization of protein abundances from multiple spectral features, derivation of confidence intervals for fold changes, and testing proteins for differential abundance. The participants will perform hands-on analyses of the example datasets with open-source software R and MSstats.

The participants should bring their own laptop computers. Instructions regarding downloading and installing the software will be provided prior to the course. 


Cross-Linking Mass Spectrometry: Practical Uses in Studying Protein Interactions and Structures

Sunday, March 3, 9:00 am - 12:00 pm

Instructors: Lan Huang (University of California, Irvine) and Robert Chalkley (University of California, San Francisco)

Protein-protein interactions are fundamental to the assembly, structure and function of protein complexes. Aberrant protein interactions can have drastic impacts on cellular functions and thus lead to various human diseases. Mapping protein interactions and their binding interfaces in living cells is critical not only for understanding protein function, but also for therapeutic interventions. Cross-linking mass spectrometry represents a powerful and emergent technology which possesses unparalleled capabilities for studying protein interactions. The identification of cross-linked peptides by mass spectrometry provides direct molecular evidence describing the physical contacts between and within proteins. This information can be used for generating experimentally derived protein interaction network topology maps and for computational modeling to establish architectures of large protein complexes. This course will cover basic principles and practical uses of various cross-linking mass spectrometry approaches for studying protein interactions and structures. Specially, we will discuss about 1) sample preparation; 2) experimental workflows with conventional and MS-cleavable cross-linking reagents; 3) data analysis for identifying cross-linked peptides; 4) result interpretation, validation and usage.


Glycomics and Glycoproteomics: The Basics

Sunday morning, March 3, 9:00 am - 12:00 pm

Instructors: Parastoo Azadi (Complex Carbohydrate Center, University of Georgia) and Joe Zaia (Boston University)

The basics half-day course will cover different forms of glycosylation and diversity of glycoprotein structures and various chemical (hydrazinolysis and β-eliminations) and enzymatic methods available to release N and O-linked glycans. The pros and cons of each release method and their subsequent yields will be discussed. Participants will learn basic techniques for the isolation, purification and characterization of oligosaccharides by mass spectrometry techniques such as ESI-MS, MALDI-MS and GC-MS. Glycomics protocols including derivatization of glycans and glycomics methods starting from cells, tissues or purified glycoproteins will be covered. The optimization methods for analysis of sialic acid containing oligosaccharides by MS techniques discussed. Various monosaccharide procedures including hydrolysis conditions needed for different residues will be reviewed as well as linkage analysis (methylation) of oligosaccharides.

Glycomics and Glycoproteomics: Advanced

Sunday afternoon, March 3, 1:00 - 4:00 pm

Instructors: Parastoo Azadi (Complex Carbohydrate Center, University of Georgia) and Joe Zaia (Boston University)

In the advanced course topics that will be covered include:
-Mapping N and O-linked glycosylation sites (LCMS)
-Glycoproteomics (glycopeptide analysis ETD /HCD fragmentation)
-Glycosylation site occupancy
-Determining the composition of glycans
-Sequencing of oligosaccharides by MS/MS and MSn including branching points and fragmentation pattern
-Glycan quantitation using MS and internal standards
-Optimization methods for analysis of Non-carbohydrate constituents such as sulfates and phosphates on glycans
-Data interpretation and available software and databases
-Glycoprotein biopharmaceuticals and their structural analysis by mass spectrometry



Stable and Transient Protein-Protein Interactions: Discovery, Quantification and Validation

Sunday afternoon, March 3, 1:00 - 4:00 pm

Instructors: Ileana Cristea (Princeton University) and Alexey Nesvizhskii (University of Michigan)

Dynamic protein interactions carry out the majority of the processes within a cell, including cellular responses to environmental stimuli and pathogens. Isolation of protein complexes and characterization of protein-protein interactions provide critical insights into their biological functions. An ideal isolation would maintain the protein-protein interaction or the protein assembly as close as possible to the original state in the cell. Therefore, proteomic-based methodologies that can access stable and transient interactions are invaluable for diverse studies, such as those of cell cycle or pathogen infection that require characterization of temporal and spatial protein interactions. This course will cover fundamental and practical aspects of studying protein interactions. Topics discussed will include:

  • protein function considerations for workflow design,
  • cell lysis methods for efficient protein extraction,
  • critical choices for optimizing an immunoaffinity purification experiment, including resin type and speed of isolation,
  • denaturing and non-denaturing methods of eluting captured protein complexes,
  • assessing the specificity of interactions using bioinformatics approaches, metabolic labeling with stable isotopes, or peptide labeling with isobaric tags,
  • challenges for assessing direct or indirect interactions,
  • aspects of data analysis and generation of interaction networks.

As we will gradually cover fundamental and more advanced topics concerning protein interactions, the course will be appropriate for both beginner- and advanced-level participants. Detailed protocols will be provided, and enough time will be set aside for discussing these topics from either a mass spectrometry or biology perspective.


 

New Course Ideas for 2020?

Do you have a suggestion for a new course or topic that you would like to see at next year's US HUPO meeting? Let us know. Please send ideas to office@ushupo.og. Thank you!

 

May Institute on Computation and Statistics for Mass Spectrometry and Proteomics

Application deadline is January 31.

The May Institute on Computation and Statistics for Mass Spectrometry and Proteomics, taking place on April 29 – May 10, 2019 on campus of Northeastern University in Boston MA, is now accepting applications. The application deadline is January 31, 2019.

Participants can select a subset of the following programs:

- Targeted proteomics with Skyline    
- Proteomics and metabolomics with OpenMS    
- [NEW THIS YEAR!] Imaging mass spectrometry with Cardinal
- Beginner’s statistics in R    
- Advanced R     
- Statistics for quantitative mass spectrometry     
- Visualization of biomolecular data    
- [NEW THIS YEAR!] Scientific writing
- Capstone – case studies in data-independent acquisition (DIA)

Instructors are leading experts, who contributed numerous experimental and computational methods and software. The target audience are both beginners and experienced scientists, with both experimental and computational expertise.

Tuition fee wavers and travel fellowships will be available for students and postdocs affiliated with academic institutions in the US.

More information is at https://computationalproteomics.ccis.northeastern.edu/