BSSD 2019 Performance Metric Q4

Abstract

The LANL SFA in Terrestrial Microbial Carbon Cycling aims to inform climate modeling and enable carbon management in terrestrial ecosystems by discovering widespread biological processes that control carbon storage and release in temperate biome soils. To achieve these goals, computational approaches are essential to analyze increasingly complex ‘omics’ data from microbial communities in environmental samples. The SFA continues to leverage advances in ‘omics' measurement technology and computation tools to decipher microbial community function in environmental samples. The computational approach is aligned with the recent shift in the SFA’s research approach. When the SFA began 10 years ago, computational approaches principally addressed “who is there” with extremely limited insight into function. Accessible ‘omics' data for complex soil communities were primarily amplicon DNA sequences of taxonomic or functional marker genes obtained by PCR, cloning, and Sanger sequencing. Computational tools for community analysis were nascent. Over the past decade, genome resources (DOE-Integrated Microbial Genomics database) and data acquisition increased 1000-fold, common computational pipelines for many analysis tasks have arisen, and the variety of ‘omics’ measurements has expanded to routinely include shotgun metagenomics, metatranscriptomics, and versions of metabolomics. The SFA is capitalizing on these advances while also developing new computational techniques to decipher how communities with different patterns of carbon cycling function from the species to ecosystem level.