Animal Physiology & Immunology, TUM School of Life Science, Technische Universität München, Freising-Weihenstephan, Germany
Michael.Pfaffl@wzw.tum.de

​Michael W. Pfaffl started 1986 to study ‘Agriculture - Animal Science’ and ‘Biotechnology’ at the Technical University of Munich (TUM). In 1997 he obtained his PhD in ‘Molecular Physiology’ in the field of molecular muscle and growth physiology at the Chair of Physiology. In June 2003 he completed his Venia Legendi (Dr. habil.) at the Center of Life and Food Sciences Weihenstephan with the title ‘Livestock transcriptomics -- Quantitative mRNA analytics in molecular endocrinology and mammary gland physiology’.

​Early 2010 he became Professor of ‘Molecular Physiology’ at the TUM School of Life Sciences. Today he has reached the ‘Principal Investigator’ status at the Institute of Animal Physiology & Immunology and is one of the leading scientists in the field of Gene Quantification, RT-qPCR technology, RNA sequencing, and complex data analysis in mRNA & small-RNA expression profiling.
He is author of around 180 peer reviewed publications, 45 book chapters, and held more than 230 lectures worldwide. In March 2012 the Elsevier SciVerse Scopus Award 2012 was granted to Prof. Michael W. Pfaffl, whose top cited Scopus article entitled "A new mathematical model for relative quantification in real-time RT-PCR" published 2001 in Nucleic Acids Research 29(9) has been cited today more than 21,800 times.   He is coauthor of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines (2009) and coauthor of the dMIQE guidelines for digital PCR (2013).

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​Professor Michael W. Pfaffl has editorial involvements as Founding- & Section-Editor in ‘Biomolecular Detection and Quantification’, Editor in ‘Methods’ and ‘International Journal of Oncology’, and Editor-in-Chief of the ‘Gene Quantification’ webportal, the world biggest webpage around qPCR, dPCR and Gene Expression profiling techniques and applications. He is initiator and lead organizer of the qPCR, dPCR & NGS Gene Quantification Event series in Freising Weihenstephan in Germany since 2004 (www.eConferences.de).

Prof Michael Pfaffl will be presenting on:

1) MIQE challenges and solutions - The use of efficiency corrected relative quantification models (REST) for transcriptional biomarker discovery.
 
Quantitative real-time RT-PCR (RT-qPCR) is the ‘gold standard’ in molecular diagnostics. Hence it is widely used because of its high sensitivity, good reproducibility, and wide dynamic quantification range. RT-qPCR is the most sensitive method for the detection and quantification of mRNA and microRNA expression levels, in particular for low abundant transcripts in tissues with low RNA concentrations, e.g. in single-cells isolated from the circulation. While RT-qPCR has a tremendous potential for analytical and quantitative applications, a comprehensive understanding of its underlying quantification strategy is important, and how to optimize and validate the quantification workflow to reduce noise.
The first part of the talk will cover practical considerations with focus on RT-qPCR optimization and standardization according to the MIQE guidelines; in particular RNA integrity, PCR efficiency correction, and proper normalization using multiple reference genes.
The second part focuses on the development of an optimal relative quantification model (REST), including qPCR efficiency correction, multiple housekeeping genes, and the statistical analysis.
Final goal is the valid quantification in expression profiling experiments, and the development of ‘transcribed biomarker signatures’ on the mRNA and miRNA level, using MIQE compliant RT-qPCR.
 

2) Exosomal biomarkers in clinical diagnostics – How to optimize micro-vesicle purification and microRNA sequencing in sepsis patients.
 
Extracellular vesicles (EVs) are circulating in body liquids and are involve in the intercellular communication with key functions in physiological or pathological processes. In recent time especially the exosomes have gained huge interest because of their molecular diagnostic potential based on the containing microRNAs. The past decade has brought about the development and commercialization of a multitude of extraction methods to isolate EVs and exosomes, primarily from blood compartments. The exosome purity and which subpopulations of EVs are captured strongly depend on the applied isolation method, which in turn determines how suitable resulting samples are for potential downstream applications and biomarker discovery. Herein we compared the performance of various optimized isolation principles for serum EVs/exosomes in healthy individuals and critically ill patients. The isolation methods were benchmarked regarding their suitability for biomarker discovery as well as biological characteristics of captured vesicles. Isolated vesicles were deeply characterized by NTA (amount, size, distribution), TEM (size, appearance), surface marker proteins (Western Blot, total protein), and containing small-RNA families (small-RNA NGS). To analyze the high complex small-RNA sequencing results, a self-established bioinformatics pipeline for microRNA (based on R) and a deeper analysis of their isoforms (isomiRs) was applied. Goal was the development of microRNA/isomiR biomarker signature for the early diagnosis and for a valid classification of critical ill patients, with focus on sepsis. The results provides guidance for navigating the multitude of EV/exosome isolation methods available, and helps researchers and clinicians in the field of molecular diagnostics to make the right choice about the EV/exosome isolation strategy.