We are excited to announce today that we have appointed Dan Knights, PhD – an expert in machine learning and microbiome analysis – as a scientific advisor to DNA Genotek.Read More
DNA Genotek's Sample Collection Blog
So, you’ve just completed your latest human genomics research study and you’re waiting to hear if it has been accepted for publication. In the meantime, you’ve been exploring other hypotheses for health conditions and are interested in the growing field of microbiome and metagenomics research. According to a recent review, genetics explains ~20-50% of observed ‘heritability’ of medically important traits[i] but you’re interested in learning more about what makes up ‘the other 50%’. The dynamic microbiome is impacted by our daily activities and our environment (diet, exercise, sleep etc.) plays an important role in the etiology of chronic diseases not accounted for in GWAS. But there are a few items of interest that have delayed your decision to initiate a microbiome study. At the top of the list is how easy is it to integrate a microbiome study into your workflow? Is your lab set up to take on such a project? And what about the downstream applications and analysis. How different is it from SNP genotyping or whole genome sequencing? You also have to consider that you are used to working with saliva or blood and now you have to get familiar with a new sample type (and possibly an unpleasant one) – like feces. All these questions are getting into the ‘meat’ of things you consider when taking on your first microbiome project. But let’s back up a little and look at the big picture and find out why the microbiome is an interesting study area to pursue in the first place. Why all this fuss over some microbes?Read More
One of the most critical components of studying the microbiome is ensuring you have a profile that is representative of the microbial community present in the donor. The reality of microbiome research, and any research for that matter, is that a variety of factors can impact the quality of your sample and its microbial community and thus, the quality of your data. Assume for example, that the microbial profile resembles Diagram “A” when in the in vivo state. The goal is to minimize any potential source of variability so that your sample accurately reflects that of the in vivo state (Diagram B) rather than an “ex vivo” artefact (Diagram C). Think of it like this: you could take a “snapshot” of the microbial community at the time of collection, preserve it through the analysis and generate an accurate microbiome profile.
DNA Genotek has been a leader in the biostabilization technology field for many years and throughout that time, many customers, like you, have used our Oragene product line. The expertise we have garnered in this field allowed us to transfer our knowledge of saliva collection and stabilization to address a new challenge: the ambient temperature stabilization of blood and blood components.