Once our lab at UC San Diego receives your sample, it goes through a multi-step process to extract and analyze its information.
Using the barcode on your specimen collection tube, we scan the sample and verify it’s all set for processing. Most importantly, we must ensure that you have completed the consent process online. If we are missing something, you will receive an email on how to correct the issue. In these cases, we store samples in our -20°C freezers to maintain sample quality until you have completed the necessary steps.
Finally, if a sample meets the requirements for processing, we prepare it for molecular work.
First, we use robots to extract genomic DNA from your sample. Using that, we either use a process called shotgun metagenomic sequencing to grab random snippets from all of the DNA found in a sample, or we create many copies of a gene that is present in all bacteria, called the 16S rRNA gene, through a process called Polymerase Chain Reaction (PCR). This helps us identify which bacteria are in your sample by boosting the amount of gene information that can be measured. If you are interested in learning more about the molecular process, our full protocol is available here.
Then, those DNA snippets or 16S copies are sequenced on an Illumina DNA sequencing instrument at the Institute for Genomic Medicine at UC San Diego. This process reads the DNA through chemical processes that result in flashes of light which are interpreted by the sequencing instrument as nucleotides (e.g., As, Ts, Gs, and Cs). Once we receive the sequencing data back, we can dive into the analysis phase.
We use a data analysis software tool called QIIME (“chime”) to analyze Microsetta data. This tool helps us analyze the millions (sometimes billions) of DNA sequences from all the samples we receive and ultimately generate your results. Because the amount of sequence data we analyze is so large, we use supercomputers in what are called high-performance computing systems.
Collecting as many samples as possible to assemble a database will help advance scientific studies, as researchers can look at the data across samples and discover connections. For example, if a researcher wants to ask if a particular microbe is associated with individuals who eat a plant-based diet, they can do so using the Microsetta Initiative data (caution: an association does not mean causation). Adding your sample contributes to research that seeks to make connections between various lifestyle factors and the gut microbiome; large sample sizes are valuable for detecting subtle (but important) effects!