Ecosystems and Networks Integrated with Genes and Molecular Assemblies

Improving microbial isolate and metagenomics workflows in KBase

Microbes are essential in cycling carbon, nitrogen, and phosphorus in subsurface environments. The Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA) Science Focus Area (SFA), managed by Paul D. Adams and Adam P. Arkin (Technical Co-manager) at Lawrence Berkeley National Laboratory (LBNL), aims to advance microbiology across multiple scales from the single molecule to the ecosystem level. The goal is to develop a mechanistic understanding of microbial community formation and activity in complex environments; exploring interactions between microbial communities in ground water and sediment. The Oak Ridge Field Research Site has complex gradients of nutrients, stressors, and contaminants; which provide a robust framework to explore spatial and temporal impacts. The ENIGMA project integrates high-resolution monitoring of subsurface hydrology, chemistry, and biology with advanced microbial isolation and characterization techniques to link microbial genotypes to environmental functions. This approach generates mechanistic models that elucidate microbial influences on field-scale processes like nitrate reduction. By replicating field conditions in the lab and collaborating across sites, ENIGMA aims to extend its findings, offering broader insights into subsurface processes that govern nutrient cycling.

Collaborative Development Projects

Long read assembly of microbial isolates*

Dr. Lauren Lui is lead Co-PI on a project for building pipelines for long read assembly of microbial isolate genomes in KBase, alongside John-Marc Chandonia and Torben Nielsen. Learn more about Dr. Lui’s research in this Berkeley Lab Basics-2-Breakthroughs video, and how she uses KBase in our Community Highlight.

Functionality and Tools:
  • Unicycler: Assembles Illumina-only read sets (SPAdes-optimiser), long-read-only sets (PacBio or Nanopore), but for the best possible assemblies, do a hybrid assembly with both Illumina short-reads and long-reads. (Released)
  • Polypolish: Uses short-read alignments to repair long-read assembly errors, typically repeat sequences. (Beta-only)
  • Filtlong: Filters a long-read set using read length (longer is better) and read identity (higher is better). (Beta-only)
  • Flye: Assembles long-read sequencings using the Flye de novo assembler for single-molecule sequencing reads produced by PacBio and Oxford Nanopore. (Beta-only)

Reference-based metagenome workflow^

Functionality and Tools:

Isolate phenotyping

The ENIGMA and Plant Microbe Interfaces (PMI) SFAs have embarked on a joint effort to characterize microbial isolates of interest across both projects. PMI works in surface soils, especially in and around the roots of high-priority plant stocks such as poplar tree (Populus). ENIGMA works in subsurface environments that share many of the same microbes, at least the genus level, but these microbes likely play very different roles and utilize different functions. By establishing joint protocols for measuring isolate growth across a range of culture environments, ENIGMA and PMI are able to form robust phenotype observations. These observations are used to test and validate KBase’s metabolic models of microbes, enhancing and improving our mechanistic understanding of microbial metabolism across a variety of conditions. Together a more detailed picture of microbial community composition in terrestrial and subsurface environments will be gained.

Additional Information

Meet the Members

SFA Principal Investigator: Paul D. Adams1,2
SFA Technical Co-Manager, Science Lead: Adam P. Arkin1,2,3
SFA Contact: Astrid Terry1
KBase Contact: Elisha Wood-Charlson (elishawc-at-lbl-dot-gov)1,3
Lead Developers: John-Marc Chandonia1,3, Alexey Kazakov1, Lauren Lui1, Torben Nielsen1, Anni Zhang4
Project Team Lead: Eric J. Alm4^, Lauren Lui1*
Affiliations: 1Lawrence Berkeley National Laboratory, 2University of California at Berkeley, 3KBase, 4Massachussetts Institute of Technology