The human microbiome comprises many different varieties of bacteria, viruses, archaea and fungi. These microbes are associated with several different body sites including oral, skin, vaginal, nasal and gut; the gut microbiome is the most studied. It was once widely claimed that the human body contains 10 times more microbial cells than human cells. However, a recent study now estimates that the number of bacteria associated with the human body and the number of human cells in the body are about the same (1). In addition to the microbes living within us, there are also complex microbial communities in other animals, plants, soil and water.
Microbiome research has expanded significantly since the first article detailing the immense diversity of human microflora was published in 1999 (2). To illustrate the massive growth in microbial studies: a PubMed search for “microbiome” in 2005 retrieves 3 publications while the same search in 2015 produces over 3000.
What has contributed to this expansion in microbiome research? One possible reason is that researchers are no longer viewing microbes as simply pathogens that we need to combat. Instead, they are trying to understand how microbiomes interact with each other and how they evolve over time. Another reason is likely the advances in technologies such as next-generation sequencing and bioinformatics tools as these have enabled a deeper characterization of microbial populations than in the past.
Whether you’re knee deep in microbial research or wondering how to design your first study, the best chance of achieving reliable results and advancing your microbiome research is choosing the right tools for your workflow. Now that MO BIO is part of QIAGEN, we can provide everything you need for your microbiome studies beginning with DNA/RNA isolation, continuing with NGS and ending with data analysis. MO BIO’s optimized bead beating technology and patented inhibitor removal technology ensure high quality, inhibitor-free DNA that is ready to use in downstream amplification or NGS library preparation.
To kick off 2017, we offered a 3-part webinar series to help you with your microbiome research workflow – from sample isolation to NGS library prep to data analysis. Catch up on what you missed by downloading the recording and perusing the slide decks below.
Part 1: Nucleic acid isolation from PCR inhibitor-rich sample types
Presenter: Eddie Adams, PhD – Director of R&D, MO BIO Laboratories
In this webinar, we focus on nucleic acid extraction tools developed by MO BIO Laboratories that facilitate accurate non-biased community analysis and eliminate common amplification problems via the depletion of endogenous polymerase inhibitors using our patented Inhibitor Removal Technology.
Part 2: QIAseq technologies for metagenomics and microbiome NGS library prep
Presenter: Jennifer Fostel, PhD – Senior Global Product Manager, QIAGEN
In this webinar, learn about the innovative technologies that form the basis of QIAGEN’s portfolio of QIAseq library prep solutions for metagenomics and microbiome sequencing. Whether your research starts from single microbial cells, 16s rRNA PCR amplicons, or gDNA for whole genome analysis, QIAseq technologies offer tips and tricks for capturing the genomic diversity of your samples in the most unbiased, streamlined way possible.
Part 3: Microbiome profiling with the Microbial Genomics Pro Suite
Presenters: Arne Materna, PhD – Director of Microbial Genomics, QIAGEN and Andreas Sand Pedersen, PhD – Senior Research Bioinformatician, QIAGEN
In this webinar, we introduce the scientist-friendly Microbial Genomics Pro Suite offering workflows optimized for microbiome profiling, microbial typing and outbreak analysis. The workflows and tools for microbial genomics introduced with this software package further extend the comprehensive set of genomics, transcriptomics and epigenomics analysis solutions that researchers know from CLC Genomics Workbench.
The webinar focuses on how users can, with a few simple steps, analyze 16S rRNA data to obtain and compare taxonomic profiles of microbial communities. You will also learn how to assemble and annotate metagenomes to generate functional profiles, and how to carry out statistical comparisons of relative abundance between sample groups in the context of experiment-relevant metadata.