Biochemical EngineeringCEN 551 Instructor: Dr. Christine Kelly Utilizing Genetically Engineering Organisms (Chapter 14)
Schedule • Posters due on Tuesday, April 13, 3 weeks from today. Format for editing (black and white, not on poster board). • Poster Presentations: Saturday afternoon, April 17, 3 weeks from this Saturday. • Oral presentations: April 15, 20, 22, 27.
April 15: Mittal, Sameer, Xu, Anitescu April 20: Meka, Chapeaux, Chang, Price April 22: Pasenello, Prantil, Lu, Menon April 27 Sayut, Reis If your project is similar to your presentation during the semester – do not repeat your presentation. Presentations should be about 20 minutes long.
Outline • Host-Vector Systems • Genetic Instability • Plasmid Design • Predicting Host-Vector Interactions • Regulatory Constraints • Metabolic Engineering • Protein engineering
Products from Genetically Engineering Organisms • Proteins • Most current industrial efforts. • Human therapeutics - over 200 in clinical trials. • Food processing. • Industrial catalysts. • $32 billion by 2006. • Nonproteins • Metabolic engineering, altering existing pathways with an enhanced capacity to produce a metabolite.
Constraints based on product type • Pharmaceutical • Objective is safety and efficacy. • Purity, authenticity, posttranslational possessing. • Cost result of research and clinical trials – not manufacturing. Cost of manufacturing not as an important issue. • Animal feed supplements or pharmaceuticals • Purity is requirement. • Cost important also.
Industrial • Low manufacturing cost critical. • Can tolerate lower levels of purity. • Food Processing • Safety important. • Purity requirements less stringent than pharmaceuticals. • Volume is large. • Cost important for penetrating the market.
Host Organisms • E. coli • Gram positive bacteria • Lower eukaryotic cells • Mammalian cells • Insect-baculovirus system • Transgenic animals • Plants and plant cell culture
E. coli • If no post translational modifications necessary, E. coli selected. • Physiology and genetics well understood. • Wide range of vectors, hosts, promoters available. • High growth rates, high cell density achievable. • Will grow on simple and inexpensive media.
Glucose feeding regime important to regulate the production of inhibitory by-products like acetate. • Does not secrete proteins. • Inclusion bodies: misfolded recombinant protein, must be lysed and resolubilized. • Disulfide bridges. • Methionine first amino acid, in mammals methionine removed in post translational processing.
Gram-positive Bacteria • Bacillus subtilis most studied gram positive organisms. • Contains no outer membrane. • Very effective excreter of proteins. • Produces many proteases. • Limited range of vectors and promoters. • Plasmids less stable.
Lower Eukaryotic Cells (Yeast and Fungi) Saccharomyces cerevisiae • extensively used in food and industrial fermentations. • High cell densities, high growth rate (25% of E. coli). • Simple glycosylation, but hyperglycosylates. • GRAS (generally accepted as safe) list. • Secretion bottlenecks can occur.
Pichia pastoris and Hansenula polymorpha • Methanol as sole carbon and energy source. • Very strong promoter. • Simple glycosylation, less likely to hyperglycosylate. • Very high cell density. Aspergillus • Good protein secretion. • Filamentous growth – bioreactor production more problematic.
Mammalian Cells • Authenticity – posttranslational processing. • Readily excreted. • Slow growing. • Expensive media. • CHO most common. • Must have transformed cell line. • Vectors derived from primate viruses – concern about reversion. • Quality changes upon scale-up.
Insect Cell – Baculovirus System • Small scales. • Good for characterization studies. • Very strong promoter. • Secreted and glycosylated proteins produced at lower levels than intracellular proteins. • Naturally continuous – not transformed. • Not pathogenic.
Transgenic Animals • Animals engineering to express the protien in specific fluids (milk or urine). • High concentrations of complex proteins. • Sheep, goats, pigs most common. • Costly.
Plants • Inexpensive. • Fewer safety concerns. • Scale up simple – more acres. • Edible delivery. • Low expression levels. • Glycosylation incomplete. • Long lead times. • Corn common. • Also plant cell cultures – Taxol.
Genetic Instability • Maximum target-protein production vs. well growing culture. • Production of lots of recombinant protein is always detrimental to the cell.
Cells lose the capacity to make the target protein – they often grow more quickly that the original strain. • Segregational loss. • Structural instability. • Host cell regulatory mutations. • Growth rate ratio.
Segregational loss • Cells divide – daughter cell receives no plasmids. • Plasmids can be “low copy number” or “high copy number”. • High copy number randomly distributed between daughter cells. • Low probability of daughter receiving no plasmids. • Affected by many process variables.
Structural Instability • Retain the plasmid, but alter to reduce the harmful effects of the plasmid. • Mutations may arise that result in the inability to produce the recombinant protein but retain beneficial plasmid encoded functions like antibiotic resistance. • These plasmids are able to grow faster therefore they take over the culture.
Host Cell Mutations • Alter cellular regulation to reduce recombinant protein synthesis. • The mutation confers a growth advantage to the mutant so that the mutant will eventually dominate the culture.
Growth Rate Dominated Instability • All of the three previous instability mechanisms become a problem because of the difference in growth rate between the altered strain and the original strain. • Growth rate ratio is a function of medium (antibiotics, inducer).
Plasmid Design • Origin of replication. Regulates reproduction of plasmid and copy number of plasmid. Different origins for different host types. • Number of gene copies. Higher levels of production with more copies of the gene. Multiple plasmids or multiple copies on the same plasmid. E. coli typically has 25-250 plasmids per cell.
Promoter/Inducer. Strong promoter means higher rate of transcription faster production. Promoter should be tightly regulated – off = very little transcription, on = lots of transcription. Inducer should not be toxic or expensive, easy to manipulate. • Terminator. Strong promoters need strong terminator to prevent read through (transcription) of the DNA after the gene. • Fusion proteins. Can fuse small part of host’s native protein to prevent destruction. Can fuse handle or tail for affinity chromatography. Can fuse host’s secretion signal to direct out of the cell.
Selective pressure. Antibiotic resistance or necessary metabolite gene on plasmid to ensure only the plasmid containing cells will grow in the bioreactor environment. Can leak complimenting factor to medium and cells that lose the plasmid will still have some complementing factor for several generations. • Par and cer loci. Sections of DNA on the plasmid that promote even distribution of plasmids to daughter cells.
Predicting Host-Vector Interactions and Genetic Instability • n+ = cells with plasmid. • n- = cells without plasmid. • P = probability of forming a plasmid free cell. • + = growth rate of plasmid containing cells. • R = P+
Performing a balance around a CSTR on n+ and n-. • Assuming no selective agents present, total number of cells is approximately constant, metabolic burden of plasmid is not too great, and D< 80% of maximum growth rate, constant delta growth rate and R. • Simplifying for three cases, we can get an analytical solution for fraction of cells that do not contain the plasmid.
= - - + >> R growth-rate instability dominant (eqn. 14.23) 2. = R segragational instability dominant (eqn. 14.24) • < 0 and abs val()>>R effect selective pressure (eqn. 14.25)
Linearize the equations to obtain parameter R from experimental data, then use equations to predict plasmid loss different reactor. • Note. Lots of assumptions! • Can also perform balance on batch reactor to get an idea of how many cells will have lost the plasmid by the end of the batch.
Regulatory Constraints Regulatory constraints on genetically engineering organisms are in place to reduce the chance of release of DNA that encodes for dangerous substances or antibiotics into the environment. This DNA can be taken up by environmental organisms, and possible these organisms could then produce the recombinant compounds.
Containment required depends on • The ability of the host to survive in the environment • The ability of the vector to cross species lines or the DNA to be transformed into another species. • Nature of the recombinant genes.
Metabolic Engineering Using genetic engineering to… • Make a totally new pathway. • Amplify an existing pathway. • Disable an undesired pathway. • Alter the regulation of a pathway.
Products from metabolic engineering • Specialty chemicals (indigo, biotin, amino acids) • Utilization of alternative substrates (pentose sugars from hemicellulose) • Degradation of hazardous wastes.
Why not just use the natural strain? Put a pathway under the control of a regulated promoter – turn on the pathway when it wouldn’t normally be turned on. Example: to degrade hazardous waste to lower concentrations than would normally induce the pathway.
Increase the concentration of enzymes with a strong promoter. • Produce the product in an easier to grow host. • Combining several pathways. • Patent the organism – cannot patent ‘unengineered’ organisms.
For protein products (not metabolites), the protein can be made at the end of batch culture, not exerting a burden on the cell during growth. • Metabolites are produced at lower rates, but produce a high burden. • Nature of the reactor system difficult: waste degradation not sterile. • Good numerical understanding of pathways is required. Need to express genes the ‘right’ amount – not just overexpress.
DuPont has commercialized a process to produce a polymer from corn with a metabolically engineered organisms. • Other products include precurser for vitamin C and xylitol – both processes that I have worked on.
Protein Engineering • New proteins or altering the amino acid sequence of existing proteins. • Can require crystal structure of the protein to examine modifications that may have benefit. • Driving force for computer modeling of protein structure from amino acid sequence.
Site-Directed Mutagenesis • Method used to change an amino acid in a protein sequence. • Rational design of proteins as opposed to random mutagenesis.