Production of recombinant proteins in E. coli by the heat inducible by pptfiles


									 What actually happens inside the cell in
  response to genetic engineering, not just
  how we manipulate and alter cell
 Can use to predict responses of the cell
 Preemptive preparation against
  negative response
 Different induction system
Chemical inducers (eg.                           Heat- inducible expression
IPTG):                                               system pros:
-expensive                                       - λ pL/pR system relies on a
-toxic                                               strong and finely
-Possible additional                                 regulated promoter
controls to remove Systems based on              - No special media or toxic
chemicals (esp . for nutrient exhaustion: (eg.       chem. Inducers
human use!)          Depletion of an a.a.)       - Culture handling and
                     - starvation affects cell       contaminations risks low
                     metabolism, synthesis of    - Easily scalable (culture
                     the recombinant protein         volume)
                     - Precise control of        - Yield up to 30%
                     induction timing is             recombinant protein
                                                     (RP)/ total cell protein
                                                 •   Perfection?
   Heat shock response (HSR)
   Overproduction of RP (often in T7 too) -> heat
    shock like response, stringent response and a
    metabolic burden to the cells
   Both HSR and RP overproduction-> converge
    on activation of genes coding for chaperones
    and proteases (sigma32 regulon)
   Specific growth rates decrease, ribosomes
    degrade, central carbon metabolism altered
     -> affects RP production
   How to avoid growth cessation, increase
    productivity, improve purification of RP
cI857 mutant (1966): retains wild-type properties at low temperature,
but unstable when temperature raised
- Interactions of cI857 with operators released up to 37 C, > 37 C
mutant repressor inactivated
 1979:1st expression vectors using the pL
  promoter (production: 6.6% -> now 30%)
 1983: increased productivity through
  temperature-regulated runaway replication,
  plasmid with cI857 high compatibility
 Other improvements: synthetic RBS, suitable
  poly-linkers, mutation to operator oR -> tight
  repression up to 39 C (Helicobacter) (2005)
 Similar system in l. lactis using comparative
  molecular modeling of the known 3D
  structure of cI857
 Sigma32 regulon includes almost all genes for
  proteins involved in folding and degradation
  (chaperones, proteases)
 Temperature increase -> nucleotide
  misincorporation and chromosome damage;
  sigma32 activation -> DNA and RNA
  protected by members of the regulon; other
  regulon members transfer delta-3-isopentyl-
  PP to tRNA to stabilize codon-anticodon
  pairing to improve tRNA thermal resistance
 overexpression and accumulation of
  unfolded recombinant proteins -> genes
  involved in protein folding and degradation
  respond; most of these controlled by sigma32
-Initial rapid upregulation of genes for chaperons
and proteases (some in minutes) -> unstable
environment -> metabolic burden -> slow growth
rate and quantity protein produced
-High protein production -> a.a. depleted (min.
media) -> deactylated tRNAs bind to ribosome ->
RelA recognizes and makes alarmones (p)ppGpp
-> stringent response -> higher transcription of
stress-related genes and translation process
interrupted-> as above
-Both limit RP production
 Harcum and Haddadin: dual stress of
  heating above 37 C and accumulation
  of unfolded RP (heated 50oC and IPTG-
 Found: 163/1881 genes responded in
  dual stress vs. either heated or induced
 Genes coding for RNA polymerase (eg.
  rpoA/S) and ribosome coding genes
 Decrease in specific growth rate
 Increase in respiration (RP production
  and hsp increase ATP requirements 6x)
 Alteration of central carbon metabolism,
  glucose consumption
 Plasmid segregation
 Host strain
 Recombinant protein and localization
 Culture strategies
 Induction strategy – Heating duration
  and intensity
 Plasmid maintenance and replication ->
  metabolic load and consumption of
  resources (further drained upon induction of
  RP production) = plasmid-load
 Plasmid-free cells favored at higher
  temperatures (derepressed).
 In RP production: avoid plasmid
  segregation and extend the production
  phase after induction: maintain plasmid
  copy number with culture strategies
   Culture modes: batch, fed-batch and continuous
   For plasmid copy# maintenance:
   fed-batch (temporal): restrict specific growth rate to
    low values increasing rates of substrate addition before
    induction -> high cell concentrations
   Continuous (spatial): higher plasmid stability and high
    cell density cultures in 1st , high RP productivity in 2nd
   Lim and Jung: 23x final contration in fed-batch vs.
    batch culture (controlled substrate feed rate during
    growth phase and specific growth rate in production
   Curless et al.: 4-fold production under higher dilution
    rates tested – pre-induction specific growth rate affect
 Different e coli strains have different
  heterologous gene expression capacities
 Protease-deficient: eg. BL21 most
  productive in a study
 We use BL21s for expression
 Thermoinduced system’s response can
  lead to recombinant proteins being
 Comparison study suggests factors: RP’s
  proteolytic sensitivity and thermal lability
Depending on localization signals:
 Aggregates in the cytoplasm –IB easily
  isolated but have to refold after
 Soluble form in cytoplsam
 Soluble form in periplsamic – less proteolytic
  activity, simpler purification, fewer isoforms
  and post-trans. modifications, in vivo
  cleavage of signal peptide, formation of
  disulfide bonds
 secreted to supernatant
 Heat inducible system has many
  advantages but stresses cell out
 Dual stress triggering of chaperone and
  protease production leads to comprised
  RP production
 How to optimize productivity of RP
 How different do you think internal cell
  responses are in other expression systems
 How many of these possible stresses do
  we have to consider in our projects?

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