Building standards in biology (2 of 2)

So now the question is: how are the engineering concepts of building standards applicable to biology? Are biological standards transferrable among organisms? What are the best case scenarios and boundary conditions?

To answer these questions and many more that emerge when you walk the space of unknown, one needs to find develop an inventory of ‘fixed quantities’ in biology. Quantities that are fixed by nature are our ‘natural standards’ and quantities that can be artificially fixed may be considered ‘designer’s standards’. Both natural standards and designer’s standards together help in rational design and controlled construction in biology.

So what are the examples of natural standards ? At the very fundamental level (this goes back to Mendel’s experiments), the consistent correlation between genotype and phenotype (seven pairs of contrasting characters) was the first evidence in support of constants designed by nature. It is interesting that the adjective ‘constant’ appeared 69 times in his paper on plant hybridisation e.g., constant characters, constant offspring, constant combinations, constant forms and so on…

Moving away from phenotypic to the cellular and molecular level, one discovers new ‘natural constants’. For example the length and weight of DNA per cell, the dry weight of the cell, cytosolic volume, diffusion coefficient, transcription factors, promoters, ORFs, rate of transciption and translation, construction material used in building organelles and so on. These quantities are fixed, or ‘relatively fixed’ (by nature) and qualify to be considered natural biological standards.

Developing new biological standards comes with two basic requirements/ challenges i.e., developing (a) process standards and (b) component standards.

Given that the process itself impacts the behavior of components, developing process standards is the precursor to building component standards that come in the form of parts, modules, pathways and cells). For example, the method used to purify enzymes itself impacts their turnover rates calculated in-vitro. Furthermore, given that there are so many ways to extract and purify DNA and RNA, which method should one fix and call it a ‘process standard’? Quite frankly, people don’t want to give up ‘what works’ in their lab. For them that IS the standard process.

Thus, in view of the lab-to-lab variations in procuring reagents, culturing cells, extracting molecules, assaying RNA expression, measuring biomolecular properties, there is a need to ‘find a common ground’ and build a “standard registry of biomethods”.

The next unmet need is building an inventory of standard biological components that comprises of parts, modules, pathways and cells. A standard biological component may be considered a genetically encoded entity that meets performance requirements. The BioBricks project is a right step in the direction. However, there are several limitations : frequently parts don’t work as specified in the data sheet. The biobrick data may be considered more as a guideline than quantities cast-in-stone. Also, the BioBrick project focuses only on the parts.

It’s time to move to the next level i.e., Registry of Standard Biological Pathways. What would such a registry look like ? This registry would be comprised on an inventory of vector constructs that plug-in a metabolic pathway or a signaling circuit. A mega cloning vector may be used that contains all the elements necessary to trigger glycolysis, lipid synthesis pathway and so on in a non native or cell free setting. The advantage of building such an inventory would be that the errors / failures observed at the level of engineering component expression, could be minimized, as the i/o measurements of the entire pathway would be available for customisation, as against individual parts datasheet.

Irrespective of the need for standard parts / pathways registry, performance reliability of the design over a large number cell divisions (robustness) is the core requirement of any biological engineering effort. However, given that biological systems are analog, non linear and run on probabilties - establishing ‘engineering level of standards’ is a grand challenge that deserves a closer attention and consistent contribution.

Photo by National Cancer Institute on Unsplash