Bacteria

1
Bacteria

• Single cells
• Small size (1-5 mm)
• Rapid reproduction
• Genomic and genetic capabilities

2
Bacterial Diversity

• 4 billion years of evolution
• Ability to thrive in extreme environments
• Use nutrients unavailable to other organisms
• Tremendous catalytic potential

3
Problem to be Solved Waste Minimization in the
Chemical Industry

• Most of our manufactured goods involve chemicals
• Chemical industry currently based on chemicals
  derived from petroleum
• Not renewable resource
• Many produce hazardous wastes

Use bacteria as the factories of the future
4
Bacteria as Factories
5
Harnessing Catalytic Potential of Bacteria

• Use bacteria as self-replicating multistage
  catalysts for chemical production
• Environmentally benign
• Renewable starting materials (feedstocks)

6
Potential Feedstocks

• Characteristics Inexpensive
• Abundant
• Renewable

• Candidates Source
• Glucose C6H12O6 agricultural wastes
• Methane CH4 natural gas, sewage
• Methanol CH3OH methane
• Carbon dioxide/water CO2/H2O atmosphere/photosy
  nthesis

7
Potential Products

• Fuels
• H2 hydrogen
• CH4 methane
• CH3CH2OH ethanol

8
Potential Products

• Natural products (complex synthesis)
• Vitamins
• Therapeutic agents
• Pigments
• Amino acids
• Viscosifiers
• Industrial enzymes
• PHAs (biodegradable plastics)

9
Potential Products

• Engineered products
• Starting materials for polymers (such as rubber,
  plastics, fabrics)
• Specialty chemicals (chiral)
• Bulk chemicals (C4 acids)

10
Problem to Solve

• If bacteria are such wonderful alternatives, why
  are our chemicals still made from environmentally
  hazardous feedstocks?

Bacterial processes are too expensive
11
Natures Design Solutions

• Competitive advantage in natural niches
• Optimized parameters
• Low nutrients
• Defense systems

12
Opportunity

• Redesign bacteria with industrially-valuable
  parameters optimized
• Redirect metabolism to
• specific products
• Increase metabolic efficiency
• Increase process efficiency

This idea has been around for 30 years, why has
the problem not been solved?
13
Metabolism as a Network

• Metabolism the complex network of chemical
  reactions in the cell
• Must redesign the network
• Understand the connections to achieve end result

14
Whats New?

• Genomics
• Bacterial genomes small (1000 human)
• Hundreds of bacterial genome sequences available
• Provides the blueprint for the organism (the
  parts list)

New platform for redesign
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Whats New?

• Increased understanding of how new kinds of
  metabolism arose

16
How Build Novel Metabolic Pathways?

• Whole metabolic pathways no single gene or
  small number of genes confer selective advantage
• Cannot build a step at a time
• Dilemma how were entire pathways constructed
  during evolution?

17
Modular Aspect of Metabolism

• Metabolic capabilities were built in blocks, like
  puzzle pieces

Strategy Understand the modules and their
connections Redesign in blocks
18
Methanol as an Alternative Biofeedstock

• Soluble in water
• Inexpensive CH3OH
• Pure substrate
• Bacteria that use it chemicals
• well-studied

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Methylotrophic Bacteria
CH3OH (methanol)
O2
CO2, H2O, cells
Specified product
20
Approach
methanol

• Define functional modules by experimental and
  evolutionary analysis

• Optimize process parameters

21
Methylobacterium extorquens AM1

• Grows on one-carbon compounds (reducing power
  limited)
• Also grows on multi-carbon compounds
  (ATP-limited)
• Natural habitat leaf surfaces
• Substantial toolkit for genetic analyses
• Genome sequence available
• Whole genome microarrays available

Clover leaf print showing pink Methylobacterium
strains
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Target Product Biodegradable Plastics
CH3OH
Energy metabolism (dissimilation)
Biosynthesis (assimilation)
C3
CO2
Biomass
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Methylotrophic Metabolic Modules
Methanol
PHA
Formaldehyde
Methylene H4F
Formate
CO2
24
Constraints

• Understanding how the system is integrated in
  time and space
• Changing how it works

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Work in Progress

• Use genome-wide techniques to assess expression
  of genes within each module
• Use metabolic modeling to make predictions about
  flow through each module
• Use labeling techniques to measure flow through
  each module

Results redesign the metabolic network to
overproduce a biodegradable plastic
26
Multi-tiered datasets
27
Global Analysis

• Global analysis provides indepth information
• Transcription of all detectable genes
• Production of all detectable proteins
• Measurement of all major fluxes
• Measurement of 100s of metabolites
• Involves a basic assumption, that all cells are
  roughly in the same physiological state

Growing body of literature shows this is not
correct
28
Final Phase Study Metabolism in Single Cells

• Metabolic studies in averaged populations do not
  capture the range of metabolic events or
  heterogeneity in subpopulations
• Difficult to study multiple metabolic parameters
  in single cells

Need new technologies to study living
individual cells in real time
29
Single Cell Challenges

• Volume of a bacterial cell fl (10-15)
• Number of DNA molecules 2-3
• Number of mRNA molecules for a specific gene
  10-10,000
• Total protein amount amoles (10-18)
• Total moles of specific metabolites amoles
  (10-18)
• Respiration rates fmol/min/cell (10-15 )

30
New Interdisciplinary Approaches

• Combine
• Genomics
• Computational biology
• MEMS (microelectromechanical systems)
• Systems integration
• Nanotechnology

31
Microscale Life Sciences CenterUniversity of
Washington

• Center of Excellence of Genomic Sciences funded
  by NIH NHGRI
• Co-directed by Mary Lidstrom and Deirdre Meldrum
  (EE)

• Started August 2001
• Goal
• Study complex processes in individual living
  cells
• Chemists, biologists, engineers working together

32
Microsystem-Based Devices for Studying Single
Cells

• Move, trap, image single cells (9 cell sets x 11)
• Control environment, make additions
• Measure 4 fluorescent protein fusions
• Single-cell proteomics
• Measure substrate-dependent O2 uptake
  (phosphorescence sensor)

Multi-parameter high throughput analysis at the
single-cell level, leading to understanding of
metabolic networks
N. Dovichi group (Chemistry) L. Burgess group
(Chemistry) D. Meldrum group (Elec Engr) A. Jen
group (Mat Sci Engr)
33
Evidence for Heterogeneity

• Single-cell cell cycle analysis growth

Tim Strovas, Linda Sauter
34
Summary

• Breadth of bacterial diversity provides
  opportunity
• Environmentally benign aspects provide impetus
• New approaches provide strategies
• Result increasing number of microbially-based
  products over the next several years