Pick a host, any host – synthetic biology tools for biopharmaceutical manufacturing – David McElroy

  1. 01st May, 2020

Biopharmaceuticals now account for a significant proportion of new drugs being released onto the market, providing alternative treatment strategies for many medical conditions, as well as offering new hope for previously untreatable or orphan diseases. Unlike the manufacture of small molecule drugs, production of these novel biological agents can be highly complex and difficult to scale up, limiting their therapeutic and commercial potential. 

Fortunately, the last decade has seen an explosion in biomanufacturing, driven by advances in synthetic biology (synbio). This has enabled the scale and scope of biologically-derived medicines to be improved to previously unachievable levels, allowing the transition of many novel biotherapies from the lab bench to the clinic. 

Biotherapeutic production generally relies on inserting genetic elements encoding the peptide, protein or antibody of interest into a host organism capable of producing it in large quantities. There are a wide range of potential cellular hosts that can be employed for bioproduction – each with its own unique advantages and limitations. 

At present, E. coli or CHO cells are the ‘go to’ systems for the majority of labs looking to produce biological molecules that are ultimately intended for clinical applications. However, more often than not, this is often because they are the host organisms researchers are most familiar with, rather than the optimal choice of expression system. This is a real stumbling block for many potential biotherapeutics, as the resources required to scale up production in an inefficient or unsuitable host can make it economically unviable.   

Foreseeing and overcoming the various issues that can arise during the biomanufacture of novel drug products requires a broad understanding of the various host organisms available, their strengths and, crucially, their weaknesses. While there are no set rules to determine which host may be the most effective for the production of a given biomolecule, Ingenza’s broad expertise and holistic understanding of each organisms’ metabolism can help to avoid problems downstream in product development. 

The major challenge for drug discovery groups – or even biotech companies – attempting to develop and exploit these technologies in house is that most simply don’t have the breadth of knowledge necessary for success. They are no doubt experts in their specific technology or disease area, but the scale-up production of biotherapeutics requires a very different skill set. Our knowledgeable multidisciplinary team brings together aspects of synbio and molecular biology, fermentation, and chemistry – as well as GMP manufacturing – to help ensure the success of each project. 

This experience, together with our extensive toolbox of synbio and metabolic engineering technologies (Table 1), allow us to optimise gene expression and production of the target molecule in the shortest possible timeframe. The true power of this approach comes from our ability to combine these commercially validated tools with other techniques and technologies to enhance the overall production system. For example, transcriptomics and proteomics – and even more traditional bioengineering techniques, such as UV mutagenesis – can be used to identify further enhancements that improve the hosts’ overall production capabilities. This allows the host organism to produce large quantities of a heterologous product that would normally be outside of its metabolic ‘repertoire’. 

It is only by understanding each of these elements, while still considering the system as a whole, that biomanufacturing can reach its true potential, and working with a knowledgeable and experienced synbio partner is the best way to ensure successful scale up of novel biotherapeutics, on time and on budget.

Table 1: Summary of synthetic biology approaches to enhance biologics production.
Bioprocess steps Current limitations Synthetic biology benefits
Gene design – cloning and construction Restriction enzyme-based DNA cloning/manipulation:
  • Slow and inefficient
  • No rapid iteration
  • Error prone due to PCR-derived DNA mutations
‘One-pot’ combinatorial assembly of DNA:
  • Cheaper optimisation of gene expression designs by re-using all parts
  • Better construct integrity by eliminating PCR errors
Gene design – expression elements Limited range of naturally occurring expression elements:
  • Limits freedom to operate
  • Unstable
  • Negatively impacts host gene expression
Synthetic elements to control target gene expression:
  • Greater diversity of induction protocols available
  • Better stability from non-repeating/orthogonal expression elements
Expression optimisation – protein yield Traditional mutation/screening:
  • Slow and unpredictable
  • Damage to host from mutations
  • Difficult to define and combine beneficial traits

Trial and error testing:
  • Slow, unpredictable
  • Costly rebuilding of systems to be tested
Omics-driven exploitation of host factors impacting target production:
  • Predictable genome editing to optimise gene expression
  • Faster and cheaper host bioengineering precision (e.g. protease KOs)

Direct selection and/or screening of high producing clones:
  • Faster identification of high yielding clones
  • Cheaper process optimisation
  • Adaptable to apply to new targets
Expression optimisation – yield stability Random gene integration into the host genome:
  • Unpredictable outcomes
  • Slow process to identify best expressing strains
Precise gene targeting into the host genome:
  • Predictable integration at most favoured genomic locations
  • Better expression and stability by re-use of optimal locations
Analytical methods – expression optimisation Trial and error testing:
  • Slow and unpredictable process
  • Costly rebuilding of systems to be tested
Gene design ‘rules’ and colorimetric reporters for best expressers:
  • Cheaper production by direct selection of well-expressed soluble product
  • Better definition and translation of performance criteria to new targets
Upstream processing – fermentation Large (>10,000 l) steel fermentation systems:
  • Expensive capital investment
  • Slow turnaround between runs
  • High resource consumption – water, energy, chemicals
Disposable (1-200 l), single use fermenters:
  • Lower capital investment
  • Cheaper manufacturing due to simpler process
  • Reduced environmental impact from less cleaning/validation
Downstream processing – protein purification Large-scale, multi-column chromatography:
  • Time-consuming and costly
  • Multiple cGMP process steps
  • Separate operations for target purification and maturation
Proprietary target protein capture, release/maturation and concentration:
  • Faster and cheaper purification with fewer DSP steps
  • Better purity through unique capture
  • Adaptable to new targets
  • Safer handling of potent targets through simultaneous recovery/maturation

By Dr David McElroy, Chief Business Officer at Ingenza Ltd