Microbiome research presents us with an opportunity to study all microorganisms on Earth. Nonetheless, many are difficult to isolate in the lab and remain uncultured using traditional microbiology methods, despite more than 100 years of research into developing new cultivation methods. Unraveling the currently undiscovered biodiversity of microbiomes remains a major challenge in microbiology, and it is estimated that more that 99% of all microbes remains uncharacterized by traditional culture methods (1). Just 20 years ago, in 1998, Handelsman first proposed to analyze a soil microbial community without prior cultivation (2). The use of culture-independent metagenomics approaches grew rapidly once the advantages became clear, with just one publication listed in PubMed in 1998 to now more than 11,000 publications.
Metagenomic sequencing is a powerful approach to investigate the microbial diversity of complex samples, with taxonomic classification of organisms sometime reaching strain level precision. Shotgun metagenomics can not only reveal specific organisms in a sample, but is also a powerful approach to characterize the functional genomic profile encoded within microbiomes, and potentially to discover genes with new functions. Although the specific sample preparation, library preparation, and sequencing platform used are all important factors that influence the quality of your results, ultimately the downstream bioinformatics pipelines and reference databases used become the analysis bottleneck. With this last point in mind, we have released a new white paper describing how to carry out functional genomics characterization of unbiased shotgun metagenomics data using CLC Genomics Workbench and the add-on CLC Microbial Genomics Module.
To demonstrate the broad capabilities of our software, we re-analyzed previously published data from Mukan Ji and co-workers (3). Ji et al investigated the surprisingly diverse microbial soil community of a polar desert in Antarctica and sought to understand how these microbes survive in such a harsh and nutrient deficient habitat.
For an in-depth discussion of the study and their exciting findings, we recommend listening to the podcast with microbiology experts Vincent Racaniello, Michael Schmidt, Elio Schaechter, and Michelle Swanson on This Week in Microbiology, TWiM. The paper was discussed in Episode 169 – Breatharian Bacteria.
Read our white paper on functional metagenomics with CLC Genomics Workbench and the Microbial Genomics Module and learn how to reveal the functional potential of microbiomes sequenced using shotgun metagenomics methods.
Variant analysis is becoming more important than ever in clinical settings — which means every interpretation has to be based on the strongest evidence possible. Our new white paper, “HGMD and ClinVar: Avoiding the Knowledge Blind Spot,” is based on the premise that a shortcoming of genetic testing occurs when “valuable information that goes undetected due to inadequate mining and interpretation mechanisms.” It’s getting harder and harder for variant analysts to keep up: the number of published hereditary, disease-associated germline mutations has doubled in the last 10 years.
Two of the most common repositories used to look up variants are the Human Gene Mutation Database (HGMD®) and ClinVar. The white paper compares these databases on several fronts:
An independent review in 2013 found that just 20 percent of variants listed in ClinVar had clinical significance. HGMD included nearly 10 times as many clinically significant variants at the same time, and has continued to grow rapidly.
HGMD and HGMD Professional are frequently updated with expert-curated information, while ClinVar relies on volunteer submitters whose information may or may not be supported by peer-reviewed literature.
HGMD is very simple to navigate, making it easier for users to mine and interpret its breadth of content. A search for information about cystic fibrosis and then quickly scanning each result for relevant mutations, for instance, would take nearly 300 hours on PubMed, but in HGMD the same result could be achieved in just five minutes.
HGMD Professional is licensed exclusively through QIAGEN. To learn more, check out the full white paper.
Clinical lab managers are constantly under pressure to do more with less. Launch more tests, review more information – in less time and for less money. We believe clinical lab members are heroes for their ability to rapidly generate accurate, actionable information that significantly improves patient care. We also believe that better informatics tools could go a long way to easing the pressure these people face every day.
In a new white paper, we review some of the major challenges associated with clinical genomics testing, along with details about how automated interpretation solutions and high-powered, curated databases can address some of these problems. Here are the four key challenges we tackle:
We discuss how each challenge contributes to the ongoing risks of managing a clinical laboratory – in terms of financial operation, technology selection, and analytical support.
Review the full white paper to learn more.
