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Short Courses Description
SHORT-COURSE OUTLINE & TOPICS
Target Audience: It will it be mainly for beginners and also for advanced students.
Description
A one-day course on fundamentals of mass spectrometry aimed to give principles and applications of MS of organic and bioorganic molecules.
The course starts with an overview of modern mass spectrometry and a description of the main ionization techniques, for volatile and polar molecules, and ambient MS techniques, followed by an overview on in-space and in- time analyzers.
The course develops presenting isotopic patterns, ion formation and ion internal energy, together with some criteria for interpretation of mass spectra.
High-resolution MS and accurate mass measurements for molecular formula determination and different techniques of tandem mass spectrometry complete the course.
For each topic, exercises involving active participation by students and applications in different fields will be presented.
Summary
· Mass spectrometry: an overview
· Ionization techniques: volatile molecules: EI, CI
· Ionization techniques: polar molecules : ESI, APCI, APPI, MALDI
· Ambient MS
· Analyzers: BE, Q, Tof, Ion trap, Orbitrap, FTICR
· High resolution mass spectrometry and accurate mass measurements
· Molecular formula determination
· Tandem mass spectrometry
· Principles of interpretation of MS and MS/MS spectra
· Exercises and applications
Methodology
Lectures
Language
English
Course Coordinator
Dr. Gianluca Giorgi
1990: Ph.D. in Chemistry.
1997-2003: Director of "Interdepartmental Center of Analysis and Structural Determinations" of the University of Siena.
2000-2008: Researcher of organic chemistry at the Faculty of Mathematics, Physics and Natural Sciences of the University of Siena.
2008-: Associate Professor of Organic Chemistry at the Department of Biotechnology, Chemistry and Pharmacy of the University of Siena.
2017: National Academic Qualification as Full Professor in Organic Chemistry.
2008-2010, 2014-2016: President of the Division of Mass Spectrometry of the Italian Chemical Society.
2014-2018: Representative of Area A (Europe and Africa) in the International Mass Spectrometry Foundation.
2018: Chair of the 22nd International Mass Spectrometry Conference held in Florence (Italy) on August 26-31, 2018.
His scientific research concerns the study of gas phase ion chemistry of organic and bioorganic compounds using different approaches of mass spectrometry and computational methods, with special regards to structural, regio- and stereochemical features and aggregation properties.
He is author and co-author of 190 publications in international journals, monographs, editorials and more than 250 communications at national and international conferences.
Hirsh h-index: 27 Total number of citations: 2564, Total number of citations without self-citation: 2361.
He is member of the Editorial Board of the Journal of Mass Spectrometry and member of the Society Advisory Board of the Portal "Chemistry", both published by Wiley.
He is member of the American Society of Mass Spectrometry and of the Italian Chemical Society.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
C02 - Introduction to High Resolution Mass Spectrometry for Qualitative and Quantitative Bioanalysis
SHORT-COURSE OUTLINE & TOPICS
Target Audience: Beginners on high resolution mass spectrometry
Fundamental Concepts for HRMS
• Mass Terminology: nominal, average, accurate, exact, monoisotopic
• Mass Separation : resolution, resolving power
• Mass Measurement: centroid, profile, peak top, millimass units vs. parts per million
• Mass Defect: the story in the decimal places
• Isotopes
Instrument Types and Concepts
• Major operating principles and challenges in
• Time of Flight MS: delayed extraction, reflectron, orthogonal acceleration
• Fourier Transform Ion Cyclotron Resonance (FTICR) MS: Magnet, cell types, ressure/vacuum requirements, ultrahigh resolution
• Orbitrap MS: ion storage and injection techniques, MS/MS options, scan speed vs.resolution
• Quadrupole and Quadrupole--based ion traps: resolution capability, impact on hybrid S/MS systems
MS/MS
• Major options
– Resolution in each mass analyzer
– Scan speed compatibility ( full scan and MS/MS switching, parallel processing options)
• Fragmentation Options: CAD, ETD, etc.
Qualitative Analysis
• HRMS based options for metabolite/ degradant/ unknown structural elucidation
• Interpretation of elemental composition
• Mass Defect Filter
• Nitrogen Rule
• Ring Double Bond
• Interpretation of MS/MS data-Narrowing the site of Metabolic modification
• Utility of Hydrogen--Deuterium Exchange for structural Elucidation
• HRMS options for Drug-to-Antibody (DAR) ratio determination
• HRMS for biomarker discovery
Quantitative Analysis
• Key variables in HRMS quantitation:
– Operating resolution during acquisition
– Selection of m/z for quantitation: peak summing; multiply charged analytes; resolved isotopic envelopes
– Data processing peak widths
– Processing of centroid vs. profile data
• Data mining for metabolites, biomarkers and other non targeted and non-anticipated components
• ADC Payload Quantitation
Course Coordinator
Dr. Ragu Ramanathan
Bioanalytical Group Pfizer, Inc. Groton, CT, USA
Dr. Ragu Ramanathan is a Director of Global Small Molecule Bioanalysis in the Global Bioanalytical Laboratories at Pfizer Inc. (CT, USA). Ragu earned his BS degree in Chemistry from the University of Southern Mississippi (MS, USA) (1988) and a PhD degree in Analytical/Physical Chemistry from the University of Florida (FL, USA) (1994). Ragu’s postdoctoral research was performed at Washington University (MO, USA) (1995-1997). Through a research grant from the NIH, at Washington University Mass Spectrometry resources, Ragu expanded his training in mass spectrometry through application to breast cancer research and protein characterization. From this training, Ragu’s interest ventured into application of mass spectrometry at several pharmaceutical research and contract research organizations, including Analytical Bio-Chemistry Laboratories (MO, USA), Schering-Plough Research Institute (now Merck; NJ, USA), Warner-Lambert (now Pfizer; MI, USA), Bristol-Myers Squibb (NJ, USA), QPS (DE, USA), and Pfizer, Inc. (CT, USA). Through collaborations and direct contributions, Ragu was fortunate to have published over 65 peer-reviewed research papers and over 12 book chapters in pharmaceutical bioanalysis, drug metabolism, metabolite identification, ion-molecule reactions, high resolution mass spectrometry and clinical biomarkers.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
SHORT-COURSE OUTLINE & TOPICS
Target Audience: Beginners on high resolution mass spectrometry
Course Coordinators: Carla Porto da Silva (SUM - BRA), Pieter Dorrestein (UCSD), Ricardo R. da Silva (UCSD - USA)
Summary
In this short-course, the participants will learn how to analyze mass-spectrometry-based metabolomics data using the Global Natural Products Social Molecular Networking (GNPS) analysis infrastructure.
(https://gnps.ucsd.edu).
Schedule
9:00-9:30 Introduction to the workshop (Pieter) (welcome, goals and brief overview)
9:30-11:30 Dataset submission and running a molecular network
1. Public dataset submission - Convert, submit, and make public the dataset to GNPS along with aReDU and MASST (Single Spectrum) compatible metadata file.
2. Running a molecular network - Present the principles of molecular networking, perform a classical molecular networking job, and interpret the results.
3. Interpreting molecular networks - Interpretation, annotation and propagations of a molecular family. Add annotations to GNPS.
13:30-16:30 Data Analysis tools session
4. Introduction to Feature-based molecular networking with MZmine and GNPS - submit a FBMN job in GNPS, present FBMN and compare it to classic MN, present MZmine and processing steps, guide the participants into processing and launching data for FBMN analysis on GNPS, and go into íon identity networking (IIN).
5. Analyzing feature-based molecular networking with Cytoscape - explore data with Cytoscape.
6. Repository scale re and co-analysis and finding datasets with data. Contextualizing mass spectra - use MASST to search the occurrence of mass spectra in public datasets, and compare a study to other studies with ReDu.
7. DEREPLICATOR, and Network Annotation Propagation - brief introduction about how these tools can help in annotation and how to use them in GNPS.
8. Substructure annotation with MS2LDA . Search your data for fragmentation patterns of often co-occurring mass fragment peaks and/or neutral losses (called Mass2Motifs) that often represent molecular substructures.
9. MolNetEnhancer: MolNetEnhancer is a workflow that combines the outputs from molecular networking, MS2LDA, in silico annotation tools, and the automated chemical classification through ClassyFire to provide a more comprehensive chemical overview of metabolomics.
Course attendees must have a laptop to complete exercises.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
SHORT-COURSE OUTLINE & TOPICS
Target Audience: Beginners on high resolution mass spectrometry
Description:
One-day course with the fundamentals, principles, and applications of Top-Down Proteomics. The course will start with an overview of proteomics techniques and a description of proteforms and their biological importance. Further, it will explore the state-of-art of protein fractionation, mass spectrometry, and data analysis techniques/methodologies used on Top-down Proteomics. Finally, some of the most important applications of Top-down Proteomics will be in depth presented in a friendly and openly environment.
Summary:
- Proteomics: Bottom-up vs Top-down
- What are Proteoforms?
- Protein separation
- Mass spectrometry
- Data analysis
- Applications and examples
Course Coordinator: Dr. Rafael D. Melani (NU - USA)
Dr. Rafael Melani is a Senior Research Associate in the Kelleher Research Group at Northwestern University (Evanston, IL - USA) since 2017. He earned his BS degree in Biology (2010) and a master degree in Animal Biology (2012) from the University of Brasilia (Brasilia, DF - Brazil), and a PhD degree in Biochemistry (2016) from the Federal University of Rio de Janeiro (Rio de Janeiro, Rj – Brazil). During his PhD he spent 18 months at the Kelleher Research Group as a visiting scholar learning Top-down proteomics and expanding his expertise in mass spectrometry under the mentoring of Dr. Neil Kelleher. His thesis was awarded with the CAPES Thesis Award as one of the three best Biochemistry theses from Brazil in 2016. Rafael's postdoctoral research (2016-2017) was performed in the Proteomics Unit at Federal University of Rio de Janeiro (Rio de Janeiro, Rj – Brazil) under supervision of Dr. Gilberto Domont. Dr. Melani has large experience and extensive training on proteomics (especially Top-down proteomics), venomics, protein fractionation, mass spectrometry, and native mass spectrometry. Through direct work and fruitful collaborations, Rafael was privileged to have published over 15 peer-reviewed research papers and book chapters in topics related to proteomics, venomics, native mass spectrometry, charge detection mass spectrometry, and mass spectrometry.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
SHORT-COURSE OUTLINE & TOPICS
Target Audience: Beginners on high resolution mass spectrometry
Course Coordinator: Jürgen Cox (MPIB)
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
SHORT-COURSE OUTLINE & TOPICS
Target Audience: Beginners on high resolution mass spectrometry
Course Coordinators:
Dr. Patrick Mathias: School of Medicine – UW, USA
Dr. Aline M A Martins: The Scripps Research Institute - CA, USA
Getting the Basics of Reproducible Data Analysis: developing skills on R Programming and application of Machine Learning and Artificial Intelligence in Health Science
Course date: 10-11th December
Course Information:
Do you have little to no experience in programming but a desire to learn this valuable skill? Or do you rely on scripts in R or another programming language for your data analysis needs but feel you don’t have the basics down? In this course, we will focus on foundational workflows for completing data analyses in R, an open source statistical programming language. By walking through the core steps of an analysis with representative data sets, this highly interactive course will take learners from data import through transformation, summarization, and visualization. Coding and workflow exercises will be frequent to reinforce concepts shortly after discussion. Best practices for completing data analyses reproducibly will be built into the content, exposing learners to concepts such as literate programming (using R Markdown), optimal project organization, and version control. By the last part of the course, you will be introduce to successful examples on how you can use Machine Learning and Artificial Intelligence to integrate data in Health Science. These skills are increasingly important for fully utilizing and extracting value from the data we collect every day so this course will emphasize tips and practices to make your work efficient and reproducible.
Topics:
- Introduction to RStudio
- Reproducibility through R Markdown
- Importing data from files
- Transforming and summarizing data using Tidyverse tools
- Visualizing data with ggplot
- Joining multiple data sets
- Structuring projects to optimize your efficiency
- Version control using Git
- Modeling data
- Application of successful examples of Machine Learning and Artificial Intelligence in Health Science
Participant Requirements:
Course attendees must have a laptop to complete exercises. Course material will be available in RStudio Cloud, which requires access to the Internet. Alternately learners can download RStudio and required packages to their computer prior to the course.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
SHORT-COURSE OUTLINE & TOPICS
Target Audience: For beginners and also for advanced students.
Description:
This course shows how to analyze shotgun proteomic data using PatternLab for proteomics. We will review peptide spectrum matching concepts and concepts converging into reliable results. We will use modules for the application of differential proteomics for label-free and chemically labeled data. The course will be taught by the authors of the computational tool.
Course date: December 10th, 9:00 am - 5:00pm
Course Coordinators:
Researchers Paulo Carvalho, Marlon Santos, Milan Clasen and Louise Kurt
Paulo Costa Carvalho
Paulo obtained his undergraduate degree in Engineering by PUC-Rio; Master degree in Cellular and Molecular Biology (2006) by Instituto Oswaldo Cruz (CAPES 7), Fiocruz; PhD by the Program of Computer Systems Engineering (2010) COPPE/UFRJ (CAPES 7) with a period of sandwich fellowship at the Scripps Research Institute, California, under the supervision of Dr. John R Yates, III (index H: 168). Paulo is a level two CNPq productivity researcher (Computer Science Committee), member of the permanent board of graduate professors in Biosciences and Biotecnology at ICC-Fiocruz, permanent professor of the graduate program in Biochemostry at the Institute of Chemistry- UFRJ. He is an adviser by the Program of Computer Systems Engineering (2010) COPPE/UFRJ. Paulo has two patent files, more than 100 published articles, highlighting: first and last authorship in Nature Methods, Nature Protocols, and Bioinformatics. His awards deserving attention: Google Award for Academic Excellence, honorable mention in CAPES PhD thesis award, another honorable mention in CAPES PhD thesis (2016) jointly with his student Diogo Borges Lima, Innovation by Fleury Laboratory and recently he has been granted with the Talent Award of the Institute Pasteur network. He was a member of the features panel of the journal Analytical Chemistry and is the executive editor of the Journal of Proteomics – Elsevier. Paulo coordinates events and courses at international level, delivers lectures in international meetings, and is part of a lot of committees. From August 2018, Paulo created and started to lead the Structural and Computational Proteomics Laboratory at Fiocruz Paraná.
Marlon Dias Mariano dos Santos
He obtained his undergraduate degree in Engineering of Bioprocesses and Biotechnology by Universidade Positivo (2017) and Master degree in Biosciences and Biotechnology by Instituto Carlos Chagas, Fiocruz (2019). He is currently a PhD fellow at the Structural and Computational Proteomics Laboratory at Instituto Carlos Chagas, Fiocruz, Paraná. He works in the field of development of experimental and computational methods applied to mass spectrometry and proteomic data analysis.
Milan Avila Clasen
PhD fellow in Biosciences and Biotechnology at the Structural and Computational Proteomics Laboratory of Instituto Carlos Chagas - Fiocruz. He has experience in the development of tools and methodologies for mass spectrometry data analysis.
Louise Kurt
PhD fellow in Biosciences and Biotechnology at the Structural and Computational Proteomics Laboratory of Instituto Carlos Chagas - Fiocruz. She has experience in the development of tools and methodologies for mass spectrometry data analysis.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
SHORT-COURSE OUTLINE & TOPICS
Course Coordinator:
Dr. Marina Tavares
Co-Coordinator:
Daniel Rossado Oliveira
Duration: 4h teoretical class and 4h (Hands-on/Laptop required)
Objective:
To introduce fundamental and practical aspects of metabolomics, in both targeted and untargeted formats, describing in detail the metabolomics workflow, from the design of experiments to the biological interpretation of the problem under examination, with emphasis on modern analytical techniques commonly used for data acquisition, the statistical concepts involved in the processing of omics data, as well as on a general revision of human metabolism and major metabolic routes.
Justification:
Among the omics sciences and in the context of systems biology, metabolomics has occupied an important niche, because it offers the revolutionary possibility of characterizing the phenotype of an individual to the molecular level, so necessary to aid the understanding of cellular biology towards personalized medicine. Interests in metabolomics have grown considerably in many areas, not only the discovery of biomarkers for early diagnosis of diseases, but include applications in biotechnology and agriculture, development of new pharmaceuticals, nutrition, food quality and safety, environmental chemistry, toxicology, among others.
Syllabus:
This course intends to review the terminology and to discuss the denominations in use in the field of metabolomics, as well to describe systematically its workflow for both untargeted and targeted metabolomics, from the metabolite selection (targeted metabolomics), biological sample collection and preparation, introducing general principles of multiplatform instrumental analysis in current use for data acquisition, the statistical concepts involved in data processing (using R platform), and finally, to provide an overview of human metabolism and principal biological routes to support biological interpretation of results. Among the analytical instrumentation, GC-MS, LC-MS in both reversed-phase and hydrophilic interaction modes, and CE-MS will be reviewed. The processing of omics data, the methods used for group discrimination, discriminant metabolite selection and structural identification of putative metabolites by assessing metabolomics databases (FiehnLib, KEGG, Metlin, HMDB, MassBank, etc.) as well as MS/MS fragmentation strategies will all be addressed by theoretical and practical lectures using the institution multimedia facility, where the students will have access to real metabolomics datasets and pertinent softwares (XCMS and SIMCA-P). Finally, examples of representative applications of metabolomics will be presented in supervised group discussions.
Note: The mini-course will happen only upon the minimal amount of 10 registrations/mini-course. In case of cancelation, the attendee should choose other mini-course (the registration fee will not be reimbursed).
Bibliography:
- G.A.B. Canuto, J.L. da Costa, P.L.R. da Cruz, A.R.L. de Souza, A.T. Faccio, A. Klassen, K.T. Rodrigues, M.F.M. Tavares, Metabolômica: definições, estado-da-arte e aplicações representativas, Quimica Nova 2018, http://dx.doi.org/10.21577/0100-4042.20170134.
- A. Klassen, A.T. Faccio, G.A.B. Canuto, P.L.R. da Cruz, H.C. Ribeiro, M.F.M. Tavares, A. Sussulini, Metabolomics: definitions and significance in systems biology, In Metabolomics: from fundamentals to clinical applications, (Ed. A. Sussulini), Series "Proteomics, Metabolomics, Interactomics and Systems Biology" (Ed. Daniel Martins-de-Souza), Springer, 2017, p3-17.
- J.M. Berg, J.L. Tymoczko, G.J. Gatoo Jr, L. Stryer, Biochemistry, W.H. Freeman, 2015, 8th edition.
- L. Eriksson, T. Byrne, E. Johansson, J. Trygg and C. Vikström, Multi- and Megavariate Data Analysis - Basic Principles and Applications, Umetrics Academy, 2013, 3rd edition.
- https://masspec.scripps.edu/landing_page.php?pgcontent=whatIsMassSpec