Simply Complex – The parallels between biology and Cannabis production

The licensed cannabis space is expanding at a steady rate, and as such, there is a combination of new players to the game as well as older heads which have seen the industry move forward in the recent past. One thing that becomes apparent to new entrants as they progress along the journey is the seemingly never-ending variables which influence a Licensed Producers (LPs) level of success. On paper, it can look like all you need is a good facility set-up, the right genetics and a successful cultivation – 3 separate elements which are very co-dependant.

However, as LPs start to peel back the layers of these 3 basic inputs, it can become overwhelmingly complex very quickly. Although the license itself acts as the gateway to production and is therefore more of a binary component, the level of input required to attain a license is extremely detailed, time-consuming, and very costly. This is especially true in stricter regions – the UK, for example – and is further compounded by the infrastructure of the facility, which must be appropriate for all elements downstream, such as cultivation methods, as well satisfying the license requirements and any further regulatory accreditation such as GMP.

This has a likeness to one of the major biological principles which state that biological information flows from DNA to RNA to protein. This central dogma governs biological systems where the relationship between DNA and the functional molecules they give rise to – proteins – have a logical and comprehensible flow. This is so fundamental that any first-year biology undergraduate will be able to recite the order in which this information flows – DNA to RNA to Protein (Figure1). But much like the description above of licensed cannabis production, the level of complexity deepens very quickly when the layers are peeled back and expose the underlying mechanisms of action.

Biology.. easy as pi…squared

What this central biological dogma really means is that the genes in the DNA are transcribed (or converted) to a special type of RNA molecule known as mRNA (messenger RNA), and this mRNA is then translated (or converted) into a protein, A.K.A. an amino acid sequence with a complex 3D structure. The language used in biology to describe each of these suites of molecules is Genome (All DNA including genes), Transcriptome (all the DNA that is converted to RNA), and the Proteome (all products resulting from translation otherwise put, conversion from RNA to amino acid), including the subsequent modifications (Figure1).





Figure 1. The central biological dogma. This diagram shows the way information flows from DNA to protein through the mRNA intermediate. Listed in text boxes coloured blue, gold, and red are examples of modification (DNA, RNA and protein respectively) which can occur at each step and can affect the end product.

The 3 elements described also represent important regulation/control or check points. A simplified example of the variables for each of these can be described by:

1) how much is the gene expressed (i.e. how much is turned into RNA)

2) how much of the RNA gets degraded vs that which gets translated, and

3) of the translated protein, what amount is present at any given time

Relating back to the licensed cannabis industry and sticking with the 3 elements aforementioned (bearing in mind there are many ways to divide the requirements of a successful LP), facility set-up, the right genetics and a successful cultivation, an example of variables for each could be:

1) When does the license begin and end

2) What is the output of the chosen genetics

3) Does the finished product meet the standards of the offtake agreement

Complexity – the fractals of reality

Of course, in reality, there are numerous other considerations for each step in both scenarios, with both quantitative and qualitative elements to each, but more so, there is a plethora of other important steps which must be included to ensure success at each of the ‘big three’ stages. For example, DNA contains genes, and genes can be active or inactive (on or off), and genes can be highly expressed or lowly expressed.

One gene can give rise to more than one version of its protein product through, for example, modification to the mRNA via a process called ‘alternative splicing’. Gene expression can be temporally regulated and/or can be controlled by master regulatory elements which orchestrate entire suites of genes – such as flowering initiation. There are several ways the mRNA can be modified, and a whole host of modifications which can be made to the protein itself (Figure 2).


Figure 2. Examples of modification which can occur to proteins. Some modifications will change protein function depending on where they sit on the protein, and how many times the modification occurs throughout the protein.

What this means is that there is significantly more than one variation downstream of the DNA than there is number of genes in the DNA. For example, an organism with 20-25,000 genes is capable of producing over 1 million proteins/protein variants (Figure 3). This perfectly captures how variable the outcome of a biological system can be, and even though not every variable is considered here, it helps conceptualise the unpredictable nature of biology through modifications, variations and combinations that influence the output.*


Figure 3. Genes to Proteins. Infographic showing the increase of complexity as information flows from DNA to protein. At each step there are numerous modifications that amplify the number of products from the previous step, resulting in a highly variable end product

In the comparison, the license can therefore be likened to whether any one cultivar has a particular trait or not, and the infrastructure itself could represent how genes are expressed. As this analogy continues, and when considering the choice of genetics and the success of the cultivation, obviously the level of complexity jumps exponentially as cultivators consider cultivation techniques, feed delivery systems & media, genetics & germplasm, personnel, and so on – all of which can also be further subcategorised.

Having the correct set up is crucial to productivity and therefore when a license holder is seeking their genetic starting material it must be in line with the setup and the desired output. And even after a successful grow, there are considerations regarding product readiness such as harvest method and trimming, drying and curing, packaging, storage and so on – comparisons with the modification that can be added to proteins (figure 2)

These steps are in every way as essential as any prior step, as the condition of the final product can still be vetoed by the buyer if it does not meet their required standard.

Conclusions

The reason these two seemingly unrelated topics have parallels stems from the numerous variables involved in each scenario. With the biology, quantifying is made easier as there are decades of research to prop up the numbers, as well as the ever-growing layers of regulation and control which are frequently being discovered and written about. This, along with subjects being divided into new disciplines, creates a constant stream of new information which is being built upon from the preceding data and published work.

However, in the licensed cannabis space, the variables are much harder to quantify and there is not the same level of consistent data to fall back on – in fact, on many occasions, licensed producers are so busy dealing with one set of variables that they often overlook another set of variables. This, like the science counterpart, is better remedied by compartmentalisation of each discipline. Supply of genetics, for example, is best served with a professional growing plan and cultivation instructions to optimise the genetic potential. This will only work in facilities where the set up is suitable for the recommended genetics, hence the need to have specialist suppliers.

By having these specialists focused on their area of expertise, i.e. matching genetics to the environment they are intended to be grown in, and by having the entire system orchestrated from build of site to offtake, there is then a much greater likelihood that everything functions as it should. If a gene should pick up a mutation which affects the protein product of that gene, then there is a good chance the function of the protein (and therefore function of the gene) could be altered, resulting in disease.

This is similar to a part of a growing facility’s infrastructure failing and causing unfavourable conditions which result in a drop of yield or quality in the plant. Much like in biological systems, small changes at the input stage (genes) can cause devastating changes to the ability of that biological system to function properly. This is also true in modern cannabis cultivation where the lack of real-time monitoring, coupled with the lack of good contingencies can further escalate those which would otherwise be small problems when they arise. As with human health, where early detection of disease often stands the patient in better stead for treatment and recovery, so does early identification of problems in a grow chamber. If an issue can be known to the grower before it has a chance to affect the plants then there is obviously less chance of it manifesting into a real problem, especially if good contingencies are in place. Selection of the correct infrastructure, genetics, growing system and personnel can all help reduce the risk to crops.

When the genetic information flow was first published and biologists started to understand DNA, RNA and protein function, no one could have predicted the numerous levels of regulation and other influential factors involved in controlling these biological systems. This is echoed in the license cannabis industry where the further into the process anyone goes, the more learning must be done. Much like in biology there is too much information throughout all the disciplines for one person to truly master it all, so as with any industry, dedicated personnel controlling finance, sales, cultivation and so on are needed in order to maximise the return on investment and fulfil the industry’s potential.  

*During my undergraduate studies, the human genetics lecturer described the maths involved in multifactorial inheritance (many genes involved in determining the phenotype, for example predisposition to a disease state such as heart disease) as surpassing the complexity of maths use in rocket science calculations – an interesting and surprising little fact! 

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