Berkeley Lab


Biotechnology DevelopmentResearchers in the Biotechnology component of ENIGMA are expanding the scope of capabilities by developing and applying a suite of technological tools for studies of genetics, protein abundance, structure, localization, and metabolism that will provide systems-level insights into microbial activity. Such insights will form the foundation for predictive models of key microorganisms from a single environment that will serve as valuable resources for assessing ecological questions relevant to microbial community structure and function.

To this end, researchers in the ENIGMA biology component have established a flexible experimental pipeline in metal-reducing and sulfate-reducing bacteria. This pipeline will generate new and improved tools for high-throughput strain/construct mutants; evidence-based annotation of gene function using mutagenesis and extensive phenotyping; evidence-based annotation of transcripts using tiling microarrays and RNAseq; protein and protein complex isolation and structural analysis; mass spectrometry-based proteomics and metabolomics analysis; and high resolution imaging.

Further technology development will enable the rapid and cost-effective applications of these tools to environmental isolates. In addition, researchers in the ENIGMA biology component are exploring the integration of diverse data types including metabolomics and high-throughput genetics to elucidate gene functions.

Biotechnology Team

    Deutschbauer, Adam
    Deputy Director, Biotechnology Development (510) 643-5683
  • Trent Northern
    Northen, Trent
    Director, Biotechnology Development (510) 486-5240
  • Siuzdak Gary
    Siuzdak, Gary
    Principal Investigator (858) 784-9415
  • Walian Peter
    Walian, Peter
    Principal Investigator (510) 486-7469
  • Predicting-metabolic-properties-using-dynamic-substrate-preference (1)
    Predicting metabolic properties using dynamic substrate...
    Exometabolomic profiling was used to examine the time-varying substrate depletion from...
  • DigitalDropletDisplacementAmplification_Singh
    Digital Droplet Multiple Displacement Amplification
    Digital Droplet Multiple Displacement Amplification (ddMDA) for whole genome sequencing of...
  • Stable protein interactome of the model sulfate reducing bacterium Desulfovibrio vulgaris Hildenborough
    Stable protein interactome of the model...
    Combined (AP-MS + tagless) interactome for D. vulgaris
  • Benchmark properties for highly accurate bacterial protein interactions
    Benchmark properties for highly accurate bacterial...
    D. vulgaris protein interaction network comprised of 459 high confidence PPIs....