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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 [email protected] (510) 643-5683
  • Trent Northern
    Northen, Trent
    Director, Biotechnology Development [email protected] (510) 486-5240
  • Walian Peter
    Walian, Peter
    Principal Investigator [email protected] (510) 486-7469
  • Predicting-metabolic-properties-using-dynamic-substrate-preference (1)
    Predicting metabolic properties using dynamic substrate...
    January 23, 2017–Exometabolomic profiling was used to examine the time-varying substrate...
  • DigitalDropletDisplacementAmplification_Singh
    Digital Droplet Multiple Displacement Amplification
    May 31, 2016–Fig. 1. The working principles of ddMDA. The ddMDA...
  • Stable protein interactome of the model sulfate reducing bacterium Desulfovibrio vulgaris Hildenborough
    Stable protein interactome of the model...
    April 20, 2016–The first demonstration of a highly accurate, genome-wide method...
  • Benchmark properties for highly accurate bacterial protein interactions
    Benchmark properties for highly accurate bacterial...
    February 20, 2016–SUMMARY Numerous affinity purification – mass spectrometry (AP-MS) and...
  • Siuzdak-Gary_thumbnail
    Siuzdak, Gary
    Scripps Research Institute Principal Investigator [email protected] (858) 784-9415