Free Tutorials (Open to all who are registered as bundled, industry, academic, government, or student conferees, first-come seating)
The tutorial track is part of the educational mission of HPLC 2022. Experts are asked to give presentations on a topic with more background than might be found in a typical 20-minute talk. The goal is to make the topic more accessible to those less expert in the area. In some cases, discussion and other interactive activities may be used. (Open to all who are registered as bundled, industry, academic, government, or student conferees, first-come seating.)
DR. BLAIR K. BERGER, Post-doctoral fellow, The University of Texas at Arlington
Tutorial on “Introduction to Supercritical Fluid Chromatography”
A general introduction for modern packed-column supercritical fluid chromatography (pcSFC). Beginning with an overview of the fundamental aspects of SFC; topics will include carbon dioxide (CO₂)-based mobile phases (MP), SFC-specific instrument hardware, and common co-solvents, stationary phases and detectors employed by SFC. The inherent benefits of using CO₂-based MP’s will be discussed with emphasis on retention controls and highlighting the techniques orthogonality to HPLC. Analyte classes traditionally separated by SFC will be illustrated in context of the fields where SFC currently plays a significant role and exemplified thru applications where SFC could provide critical solutions for difficult separations.
Blair Berger, is a postdoctoral researcher at the University of Texas at Arlington (UTA). She has a bachelor’s degree in marine-biology/chemistry, a master’s degree in natural products LCMS-based metabolomics and her doctorate in analytical chemistry. She has worked with SFC intermittently since 1998, in industry for companies such as Berger Instruments, Mettler-Toledo AutoChem, and later for Aurora SFC Systems during the commercial development phase of their SFC conversion module. Working as an analytical chemist and customer support technician, she has co-published a number of peer-reviewed papers, technical notes, and user manuals. While briefly working in academia (2017-2019), she also managed the Natural Products Laboratory liquid chromatography facility for the Institute of Biology at Leiden University in the Netherlands. Recently receiving her PhD at UTA, her doctoral and postdoctoral research focuses on providing solutions for unique challenges associated with method development using hyphenated instrumentation (via SFE-SFC-MS) for online extraction/analysis of complex biological and environmental matrices.
ELI LARSON, University of Wisconsin-Madison
Tutorial on “LC/MS Strategies for Top-down Proteomics"
CHRISTIAN G. HUBER, Professor, University of Salzburg, Salzburg, Austria
Tutorial on "Making Sense of Proteomics Data in Biological Context: Data Analysis for Proteomics"
During the past two to three decades, wholistic omics technologies have emerged as very powerful techniques for the generation of unbiased hypotheses in biological and biomedical research with the goal of a molecular understanding of biological processes in health and disease. One important branch of omics analysis, proteomics, is based on high-throughput identification and (relative) quantification of proteins in samples of biological relevance. The most successful analytical method for high-throughput protein identification and quantification so far is high-performance-liquid chromatography hyphenated to electrospray-ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Given the fact that modern mass spectrometers are able to generate mass spectra at a rate of 40 spectra per second and more, a typical proteomic workflow generates several ten thousands of mass spectra that require detailed evaluation and interpretation based on sound statistics and bioinformatics. Due to the availability of DNA- and protein sequence databases in combination with computer-based database searching algorithms, fully automated annotation of such a vast number of primary data became feasible in the late 1990ies. We will discuss and compare the most widely used commercial and open access protein annotation tools and introduce statistical parameters to score the statistical relevance of spectrum annotations. Furthermore, experimental designs as well as software tools for isotope-labeled and label-free relative and absolute quantifications will be discussed. Following protein identification and quantification, the biological role of the proteins, especially of those differentially expressed in test versus control state has to be elucidated. Comprehensive public or commercial databases and database searching routines, collecting and archiving knowledge regarding the biological function of genes and proteins such as Gene Ontology or Ingenuity Pathway Analysis provide powerful resources for the interpretation of regulations at the protein level. Finally, we will present approaches to mechanistic interpretation of the annotated and (differentially) quantified proteins in the context of biological and biomedical research on the basis of a few examples in cancer-, allergology-, and toxicology studies.
CHRISTIAN HUBER trained as an analytical chemist at the University of Innsbruck focusing on chromatographic separation methods for biopolymers. After a postdoc in Csaba Horváth’s group at Yale University in 1996 focusing on building an instrument for capillary electrochromatography, he obtained lecturing qualification in analytical chemistry at the University of Innsbruck in 1997. As an associated professor of analytical chemistry at the University of Innsbruck from 1997 to 2002, he developed monolithic stationary phases for hyphenating high efficiency nucleic acid-, peptide-, and protein separations to mass spectrometry. From 2002-2008 he held a position as professor for analytical chemistry at Saarland University, where he started working in the field of proteome analysis and data mining of mass spectrometry data. Since 2008, he is a professor of chemistry for biosciences at the University of Salzburg. From 2013 to 2021 he led the Christian Doppler Laboratory for Biosimilar Characterization, which cooperated with Novartis and Thermo Fisher Scientific. His current research interests include proteome and metabolome analysis of biological models for disease as well as in-depth (therapeutic) protein characterization by means of HPLC and MS.
DR. TIFFANY LIDEN, Research Scientist and Adjunct Professor, The University of Texas at Arlington; Consultant, Medusa Analytical, LLC
Tutorial on "Introduction to Untargeted LC-MS Analysis"
This course is designed for LC users that are looking to expand their ability to discover new molecules in their samples, especially those that can discriminate between sample types. By the end of this course, attends will understand the difference between targeted and untargeted LC-MS analysis. They will learn the steps to design data acquisition parameters, and the tools to help facilitate data processing. Finally, attendees will learn to interpret the results.
Tiffany Liden studied biochemistry at Texas Woman’s University then completed her master’s degree in Chemistry Education from the University of North Texas, and her Ph.D. in Analytical Chemistry from UTA. When she is not facilitating the success of students in the lab, she spends her time using separation science and mass spectrometry to solve a variety of analytical problems. Her research has centered around untargeted metabolomics using GC-MS and LC-MS/MS where she applies mass spectrometry to differentiate between samples. Moreover, she has experience in the evaluation of the efficacy of wastewater treatment technologies with Collaborative Laboratories for Environmental Analysis and Remediation (CLEAR). Tiffany has had the honor of participating in a variety of presentations and invited talks as well as being an instructor for several short courses such as Science for Serious Lawyers and Axion Lab’s LC/GC Bootcamp. Tiffany is also a consultant with Medusa Analytical which is a company that strives to help attorneys interpret scientific findings and improve industrial operations.
JIRI URBAN, Associate Professor, Department of Chemistry, Masaryk University, Brno, Czech Republic
Tutorial on "Isocratic and Gradient HPLC Method Development"
In this tutorial, step-by-step protocol using a standard spreadsheet software is presented to optimize both isocratic and gradient separation of dopamine precursors and metabolites in reversed-phase liquid chromatography. Both an optimal composition of the isocratic mobile phase and a gradient profile are optimized using a resolution as the main optimization criterion. Although shown for a concentration of organic modifier in the mobile phase, presented approach might be successfully used in an optimization of analysis temperature, pH, ionic strength, and other experimental properties.
Jiří Urban received a Ph.D. degree in 2007 at the University of Pardubice, the Czech Republic, where he worked until 2016. During 2009-2011 he followed post-doctoral research at the University of California, Berkeley, USA, in the group of Frantisek Svec and Jean M. J. Fréchet. In 2017 he moved to the Department of Chemistry, Masaryk University, Brno, Czech Republic, where he became an Associate Professor in 2018. He utilizes polymer monoliths to develop multifunctional miniaturized analytical systems in his research. He also focuses on describing the retention behavior of both small molecules and peptides in reversed-phase and hydrophilic interaction liquid chromatography.
FAROOQ WAHAB, Research Engineering Scientist, Department of Chemistry and Biochemistry, The University of Texas at Arlington
Tutorial on "Advanced Signal Processing Toolbox for Separation Scientists"
This presentation is designed to discuss a combination of advanced but easily implemented mathematical methods for practicing separation scientists. Chromatography and capillary electrophoresis frequently encounter signal-related problems such as a small peak riding on the tail of a large peak, tailing or fronting peak shapes, partial or complete overlap, and poor signal-to-noise ratio. Various digital signal processing topics will be covered to address these issues, such as enhancing the resolution of critical peak pairs, correcting tailing or fronting peak shapes while maintaining peak areas, and enhancing signal-to-noise in different scenarios. The advantages of chromatographic data processing in frequency and time domains will be discussed. Using discrete Fourier transform’s windowing operations, one can reduce noise from detectors, pumps, or other electronic sources, resulting in a higher signal-to-noise ratio and lower detection limits. Similarly, time domain techniques such as wavelets can be helpful in specific noise reduction. Furthermore, iterative time-domain deconvolution methods will be shown for enhancing chromatographic resolution.
M. Farooq Wahab is a Research Engineering Scientist at the University of Texas at Arlington. He did his Ph.D. from the University of Alberta, Canada, and a postdoctoral fellowship with Daniel W. Armstrong at the University of Texas at Arlington. Currently, he is working on hyphenating microwave rotational spectroscopy with gas chromatography, focusing on signal enhancement approaches to provide a sensitive detection technology for volatile isobaric, isotopic, and isomeric compounds. He also works on time and frequency domain signal processing techniques for noise suppression and resolution enhancement algorithms. Wahab was listed among “Top 40 Under 40 Analytical Chemists” by the Analytical Scientist Magazine (UK). He received the “Young Investigator Award” from the Chinese American Chromatography Association in Pittcon in 2019. The Journal of Separation Science included him among “Emerging Thought Leaders in Separation Science” in 2020. He is a reviewer for several leading analytical chemistry publications and volunteers for the ACS Division of Analytical Chemistry Education Committee.