SEP 13, 2018 9:00 AM PDT

Novel Solutions for Unbiased Results in Metagenomic Analysis of Human Microbiome Samples

Sponsored by: QIAGEN
C.E. Credits: P.A.C.E. CE Florida CE
Speakers
  • Scientist BRC Product Development, QIAGEN
    Biography
      Matthew Fosbrink joined QIAGEN in 2009 and is currently a scientist within BRC product development. Matthew received his Ph.D. in Toxicology from University of Maryland, Baltimore where he studied cell signaling and cell cycle activation induced by complement C5b-9. After graduation, he went onto postdoctoral studies at Johns Hopkins School of Medicine where he engineered FRET-based kinase biosensors. At QIAGEN, he is the lead scientist for Targeted Microbial NGS products and Microbial DNA PCR products.
    • Director Microbiome Product Development, QIAGEN
      Biography
        Dominic O'Neil has more than 20 years of experience in the biotechnology industry. Dominic joined Digene in Gaithersburg, MD (now QIAGEN) in 2004 to work on new technology research and development, focusing in particular on sample preparation in diagnostic applications. In 2011, he joined the QIAGEN R&D group in Germany. In 2014 he assumed responsibility for new DNA extraction technologies, where he led a team to launch multiple new products for extraction of DNA from FFPE, stool, tissue, and plasma/serum, as well as managing the R&D integration of MO BIO technologies into the QIAGEN portfolio. Currently, he leads the Microbiome Product Development group as the Director of the team overseeing new product development for the microbiome field.

      Abstract

      This two-part webinar will focus on novel techniques for obtaining unbiased results in 16S rRNA gene sequencing of challenging microbiome samples. Part 1 will feature QIAGEN’s solutions for lysis of tough bacteria and fungi and removal of challenging enzymatic inhibitors in order to obtain sequencing-quality DNA from human stool samples. In Part 2, we will focus on QIAGEN’s novel technology for 16S and ITS sequencing. We will present data from a study showcasing the link between Body Mass Index (BMI) and the salivary.

      Learning Objectives: 

      1. Learn some common workflows for generating microbiome data
      2. Understand the importance of removing inhibitors from difficult samples to ensure best possible NGS results 
      3. Introduction to 16S sequencing and some novel techniques to improve data quality 


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