An Online Biosensor for the Protection of Water Supplies

Abstract

There are two major aspects to the development of our biosensor: the application of synthetic biology to develop novel microbial sensor strains that will have sensitive and specific responses to critical water toxins, and the use of state-of-the-art microfluidic techniques and optical technology along with computational biology to detect and interpret the signals from these toxin-sensing organisms. Task A focuses mainly on the biological aspect of this project, with the goal of identifying combinations of cellular signals that can be harnessed to provide specific responses to the presence of a range of potential water toxins. In Q1, we searched the literature to identify known cellular signaling pathways responsive to our toxins of interest and selected several candidate promoters from a variety of microbial organisms. We designed plasmids with each of these promoters driving GFP and contracted these sequences to be constructed. As proof of principle, we used microfluidics to test two such plasmids that we built in-house. We subjected these preliminary sensor strains to various toxin levels within a novel microfluidic chip, and we observed bright response signals. In addition to taking advantage of known toxin-sensitive pathways, we conducted a program of Next Generation Sequencing to greatly expand the number of known response promoters for each toxin. In Q2, we developed novel RNA-Seq analysis algorithms to identify specific differentially expressed genes in our large data set. We located the promoter regions of the most promising differentially expressed genes and designed sensor circuits based on them. In Q3, we completed the construction of plasmid-based microbial sensor strains for all toxins, based on promoters identified via literature searches and RNA-Seq. We used microfluidics to demonstrate the proper induction of each strain by various levels of the relevant toxin.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2015
Accession Number
AD1001325

Entities

People

  • Garrett Graham
  • Jeff Hasty
  • Leo Baumgart
  • Michael Ferry
  • Ramon Huerta
  • Ryan C Johnson
  • Scott Cookson

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Biosensors
  • Cells
  • Chemistry
  • Construction
  • Data Transmission
  • Detection
  • Detectors
  • Freeze Drying
  • Image Processing
  • Machine Learning
  • Operating Systems
  • Pattern Recognition
  • Power Distribution
  • Solar Energy
  • Supervised Machine Learning
  • Synthetic Biology

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Systems Analysis and Design

Technology Areas

  • Biotechnology