What does it take to understand the complex movement of carbon through the environment and which organisms are involved at each step?
Tools of Science visited the Joint Genome Institute (run by the DOE) in Walnut Creek, California to find out how the study of metagenomics can help create better models for carbon cycling (which affects climate) and discover more efficient processes for turning biomass into sugar and eventually fuels or other useful materials.
In this video Susannah Tringe, Deputy of User Programs at JGI, talks a little bit about her work on the metagenomics of microbes in wetland soils in the Sacramento River delta.
Susannah explains the workflows she employs to understand carbon cycling and improve models that predict the eventual disposition of CO2.
She wants to know what organisms are present and what genes they possess that are involved in moving carbon through the environment. Amazingly (to me) they start by managing to get DNA and even RNA, from thousands of organisms living in mud.
To estimate the number of organisms present they sequence a relatively conserved 16S ribosomal RNA gene. There can be thousands or tens of thousands of organisms in the sample.
For detailed analysis of individual organisms, Susannah and her colleagues use a flow sorter to separate single cells into 384 well plates, lyse them and amplify whole DNA to a single amplified genome (SAG). They then amplify the 16S gene from each to sequence and identify which organisms they want to study further.
Ideally, they’d like get as much sequence as possible to cover as much of the complex community as possible. The Illumina HiSeq is the primary tool for that. Because it’s also helpful to know what a complete gene looks like and what genes are present in a single organism, they also use PacBio RS II and Sequel systems to get longer (multiple KB) reads to help with assembly.
Transcriptomics identifies important players
Just because a gene involved in carbon metabolism is present in the community doesn’t mean it’s active or important in the disposition of CO2. Knowing what genes are transcriptionally active would get us closer to the goal of understanding which organisms are they key players. While it’s possible to see differences in transcriptome data, good reference genomes are needed to help with that analysis.
Find out more at http://jgi.doe.gov
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