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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5515_Библиотеки_им_академика_М_И_Перельмана.pdf
endocannabinoid system. As we explore the effects of AEA on our nervous system, we
need to keep in mind that it is very fragile compared with THC and CBD. It breaks
down easily into arachidonic acid and other components, which is the job of the fatty
acid amide hydrolase enzyme shown in figure 11.4. THC and CBD are tougher
molecules and like to linger for longer periods, especially in fatty tissues.
The synthesized AEA waits in the cells for some physical or physiological stimulus
to go to work. As with the endocannabinoid system, AEA also has many
neurotransmitter functions, including regulation of sleep, memory, appetite, pain
regulation, and hormonal regulation of ovulation in females. The other major
endocannabinoid, 2-AG, is also synthesized from arachidonic acid using different
enzymes than does AEA. It is more abundant in our cells than AEA and is the major
neurotransmitter that interacts with CB-2. Both AEA and 2-AG will interact with CB-1.
Most transmission of information via our synapses is routed from the presynaptic
cells to the postsynaptic cells. But not AEA and 2-AG in the endocannabinoid system:
their movement is reversed. AEA and 2-AG are synthesized primarily in the
postsynaptic cell, and when induced these neurotransmitters will travel backward
across the synaptic cleft and bind to CB-1 and CB-2 receptor proteins in the membrane
of the presynaptic cell. By doing this they can regulate the strength of the synaptic
connection (i.e., how efficiently it transmits information) and hence the long-term utility
and function of the synapse. This process, called retrograde signaling, affords an
impacted synapse a lot of versatility and enables the AEA and 2-AG neurotransmitters
to be both excitatory and inhibitory. Since the AEA impacting part of the
endocannabinoid system is distributed in different regions of the brain, AEA will have
effects on the many different kinds of neural regulation systems such as the dopamine
system or the serotonin system. In other words, it will regulate other neurotransmitters
and either tone down or ramp up their activity.
Let’s return to our AEA molecule, which has been synthesized in the postsynaptic
cell and is ready to be released into the cleft of the synapse. When you are hungry, many
different neurotransmitters are synthesized as a result. But let’s also posit that as a result
of smelling something really tasty, a signal from your olfactory system triggers the
release of the newly synthesized AEA into the synaptic cleft in a region of your brain
where there are dopamine-regulated synapses. Actually, this will be happening in many
other brain cells as a result of the olfactory stimulus. The AEA travels backward across
the synapse and finds a CB-1 or CB-2 receptor on the presynaptic cell which it binds to.
Such binding triggers a regulatory response in the presynaptic cell that regulates GABA,
which is the regulatory neurotransmitter that stimulates the release of dopamine.
Dopamine is the pleasure molecule that drives many behaviors. When you are full, the
synthesis of AEA in this part of the brain slows down, as does your appetite, because
the CB-1 and CB-2 receptors are not triggered and the response is to stop
downregulating GABA, which in turn downregulates dopamine. The rest of stopping
eating is a balance between the reward system and other brain functions. The reward
system is an important element in understanding THC use and abuse.
I have oversimplified a lot here. But the primary messages are that the
endocannabinoid system evolved to regulate some of our behaviors, and that a lynchpin
of this regulatory system is the synthesis and binding of our internal endocannabinoids
(such as AEA and 2-AG) to cannabinoid receptors on many of our neurons (primarily
CB-1 and CB-2). The simple ingestion of THC or CBD (or other natural and synthetic
cannabinoids) can throw this regulatory system off in many ways, which is the reason
why cannabis consumption can influence a variety of behaviors and physiological
factors. This brings us back to following our THC molecule through the
endocannabinoid system.
Figure 11.5. Space-filling diagrams depicting the similarity of the shape and size of the endocannabinoids
and THC. The diagrams show carbons, hydrogens, and oxygens. Note that THC has a shape quite similar
to anandamide.
As explained in chapter 8, when you take a toke on a marijuana cigarette, much of
the THCA in the cannabis is decarboxylated and rendered active by the heat of the
burning cigarette. In the inhalant are billions of molecules of THC that enter your lungs.
The majority of these molecules enter your bloodstream. Our THC molecule is one of
these. It moves through the bloodstream to the brain, where it passes into the brain’s
neural tissue. The THC molecule makes it to a cluster of neural cell synapses that are
part of the dopamine system. Due to the similarity of the endocannabinoids to THC (fig.
11.5), competition occurs for binding to the CB-1 and CB-2 receptors. Because there is
so much THC that has been transferred to the brain via the toke, THC binds to many of
the CB-1 receptors, clogging them up and stopping them from regulating GABA. This
dysregulation enables a lot of GABA to be delivered to the synapse, and unusual loads
of dopamine are pumped into the synapse. Hence the euphoric, pleasurable feeling one
gets from smoking marijuana. The increased amount of dopamine also produces the
effect of “wanting more” in your brain.
Elsewhere in your body after the toke, your bloodstream moves THC and CBD to
all points in the endocannabinoid system, where CB-1 and CB-2 receptors reside. Both
THC and CBD disrupt the proper functioning of the endocannabinoid system by binding
to and clogging up the CB-1 and CB-2 receptors that are dispersed throughout your
body. If some of the CBD molecules get into a tissue with cells that regulate pain, the
many cells with receptors in this tissue can also respond to mechanical, thermal,
chemical, or a combination of the three kinds of insult to the tissue. When a pain
receptor cell is stimulated or irritated, it will communicate with nerve cells, which then
send a message to the brain that some insult has occurred. Different pain receptors will
elicit different responses that the brain interprets as heat, cold, or pressure. The
alleviation of pain that THC and especially CBD deliver works in several ways
regarding pain. One way is to simply block the nerve cells that transmit the insult from
the pain receptor cell to the brain. A second way is to target receptors in the immune
response and in turn reduce inflammation. Yet another way is to stimulate the production
of adenosine in the brain, which has been shown to be an analgesic. Chapter 14 will
delve into the many ways that CBD and other cannabinoid derivatives and synthetics
can impact pain treatment.
The extent of the effects of THC and CBD relative to one another relies on the
concentrations of both exogenous cannabinoids in the original intake toke. Consequently,
adjusting the ratio of CBD to THC in many marijuana products has been an important
but sometimes bewildering task. With the superhigh THC concentrated strains now
available, the effects are much more powerful because they deliver more of the
“clogging” agent to your neurons, and more of the neural effects that clogging produces.
Like anything with cannabis, balance of effect is of the utmost importance.
12
Genes, Genomes, and Cannabis
Until about ten years ago, it was taboo to work with cannabis in the United States, even
if you were an academic researcher you needed some kind of dispensation. And some
major restrictions on the movement or transport of the plant hindered much of the
research that could be done. If you were a researcher working on cannabis, you ran the
risk that a representative of a legal or regulatory agency who had read your papers
would come knocking on your door. That would put a damper on doing research on
banned plants, much in the same way that Michael Pollan, author of This Is Your Mind
on Plants, avoided being too specific about his experiences with the opium plants he
grew in his backyard. But as research biologists Conor Jenkins and Ben Orsburn point
out in their paper on generating the first cannabis genome, “The passage of the Farm Act
of 2019 in the United States has allowed nation-wide access to Cannabis plants that
possess a total concentration of THC of less than 0.3 percent weight. Coupled with
decriminalization and legalization of all Cannabis plants in Canada and an increasing
number of states, the interest in Cannabis spans multiple areas of medical and industrial
science.”
In some ways it might have been for the best, although that research was held back
at least for genomics, as it was only about ten years ago that DNA sequencing
techniques moved into what was called the “next generation.” The human genome and
several other model system genomes were sequenced in the early 2000s. At that time,
sequencing a genome the size of the human genome or the cannabis genome was a
herculean task involving an estimated $3 billion and employing armies of technicians.
The shift to next generation sequencing (NGS) accelerated the sequencing process by
several orders of magnitude, and it also became several orders of magnitude cheaper to
do.
Sequencing of the cannabis genome has resulted in unprecedented progress in the
understanding of the plant’s biology. Nearly all the genes involved in THCA and CBDA
synthesis have been identified at the DNA sequence level, and the primary information
in the genes in these pathways has been deduced. Other aspects of cannabis not related
to THCA and CBDA such as growth time, flowering time, height, flower weight per
total, and other phenotypes are also being studied using genome wide association
studies (GWAS). The overall potential for understanding cannabis at the genetic and
genomic level is poised to revolutionize cannabis cultivation, so it is important to
understand the shift in resolution that we now have as a result of the next generation
sequencing approaches. After pondering the impact of genomics on cannabis cultivation,
Jeremy Plumb, who works at a commercial cannabis operation, recently predicted that
“within three years none of the plants that we are growing currently will continue to be
produced.”
Some Genomics Fundamentals
The first thing to realize about cannabis genomics is that it is focused on the DNA
sequence of the plant. At its most simple, the cannabis genome (like every genome of
every organism on this planet) is a string of microscopic building blocks called
nucleotides. These nucleotides come in four varieties in the genome of most organisms:
guanine (G), adenine (A), cytosine (C), and thymine (T). That’s all there is at the most
basic level in the cells of living things (including viruses, if you count them as living).
But there are millions of these nucleotides in linear arrangements, and it is the order of
these nucleotides that imparts information to the cannabis cell.
How is the DNA packaged in the cells of the cannabis plant, and what does the
packaging mean for its life cycle? There are two major ways cells are organized in
organisms. The first way is simple: the DNA lives inside the cell membranes. The
second involves packaging the DNA away in another membrane-bound structure called
the nucleus. Microbes such as bacteria are examples of the former, and humans and
cannabis are examples of the latter. The organisms with a nucleus surrounding their
DNA are known as eukaryotes.
A sexually reproducing eukaryotic organism (like us and cannabis) has millions of
cells that are basically of two types. The cells that make up most of a cannabis plant are
diploid, meaning they have two copies of each gene in the genome. (These diploid cells
are also known as somatic cells.) The other kinds of cells in a diploid organism are the
gametes, which are haploid, with a single copy of the genome tucked away inside the
cell’s nucleus. When a pollen cell fertilizes an ovum, the amount of DNA returns to the
diploid state and the nascent plant can start to develop. Diploid genomes such as that of
cannabis hold tons of information in the guise of these Gs, As, Ts, and Cs, and a
remarkably efficient mechanism has evolved to ensure that both parents contribute to the
next generation.
The size of any genome gives us an upper limit of the potential amount of
information contained in an organism’s genetic makeup. The genome size can be
determined using cytometric techniques (techniques that measure the components of
cells), and it is fairly clear that diploid and haploid male cannabis cells have more
DNA in them than in the corresponding cell types in females. It is a slight disparity, but
nonetheless enough to recognize with available techniques. The difference arises from
the way sex is determined in cannabis, which involves about 47 million nucleotides in
number. This may sound like a lot, but it is only a 2 percent difference, as the male
genome is 1 billion, 683 million nucleotides long, and the female genome is 1 billion,
636 million nucleotides long. The overall amount of nucleotides in the cannabis genome
is average for a plant (fig. 12.1).
The DNA in the nuclei of eukaryotes is packaged further into smaller discrete
bundles called chromosomes. Cannabis has ten of these bundles in each haploid cell,
and ten pairs to make twenty total in each somatic cell. The cannabis genome is really a
collection of linear stretches of nucleotides, as chromosomes are also linear strings of
nucleotides. Chromosomes vary in size from organism to organism. For humans the
twenty-three chromosomes of our haploid genome range in size from about 50 million
nucleotides to 250 million nucleotides. The autosomal chromosomes in the human
genome were named based on their size, as judged from microscope pictures (called
karyotypes) of the genome showing the actual chromosomes in the cell. Chromosome 1
was judged to be the largest, and chromosome 21 the smallest. Sometimes a
chromosome got its name based on this size criterion but later, when its size was
determined more precisely with DNA sequencing, the convention was violated. This
means that some human chromosomes do not fall in line with the largest-to-smallest
naming convention. The same naming convention is conceptually true for cannabis (the
largest chromosome is named chromosome 1 and so on to chromosome 10). As with
human chromosomes, the size naming convention has been violated in some instances.
Figure 12.1. Distribution of the sizes of different plant genomes. Plant genomes range in size from about 63
million bases for Genlisea margaretae, a eudicot in the higher category of what are called asterids, or plants
such as common daisies, to about 26 billion bases for Sequoia sempervirens, the sequoia tree. The arrow
points to where the Cannabis genome lies in this distribution; it is neither very lean nor very obese with
respect to genome size.
In humans, female cells have more DNA because of the sex chromosomes: namely,
the X and Y chromosomes. Human sex is determined through an X–Y system, which is a
parsimonious system that many organisms have adopted to ensure that both males and
females are produced in each generation of the life cycle. Females end up with two X’s
(they are XX), and males are XY. The human X chromosomes carry over five times the
number of nucleotides as the Y chromosome. Cannabis has a similar sex determination
system called an X-to-autosome balance system, where sex chromosome makeup is XY
for males and XX for females. Unlike humans, where the X chromosome is larger than
the Y, the cannabis Y chromosome is bigger than the X, and thus XY individuals
(cannabis males) have more DNA than XX individuals (cannabis females).
Whereas all the other chromosomes in the genomes of most eukaryotes come into
contact with each other and exchange parts of their chromosomes with each other (a
process called recombination), the Y chromosome and the X chromosome in an XY
system recombine rarely. In humans, the Y chromosome is physically quite different
from the X; it is smaller and more condensed. In cannabis, parts of the two sex
chromosomes do recombine, but there is a long block on each of the two chromosomes
that does not, and this is where the sex determining factors for cannabis lie. The rest of
the chromosome is called “X-specific.” This is a strange arrangement, and one that is
very old in evolutionary terms.
It is strange because most plants are dioecious (hermaphroditic), with no need to
have sex chromosomes. They only need the genetic instructions to make male and
female genitalia. It appears that the XY sex determining system has arisen several times
in the evolution of plants, and we can compare the sex determining systems of other
plants to that in cannabis. When the XY system of cannabis and its relatives arose can
then be estimated. It appears that the cannabis sex determination system arose at the
very latest in the common ancestor of hops and marijuana over 20 million years ago,
making it perhaps one of the oldest in plants.
If other members of the Cannabaceae (such as Trema and Celtis) have XY systems,
then this would make the origin of the XY system in cannabis even older. Evolutionary
biologist Djivan Prentout and colleagues found large amounts of divergence between
the genes that are on both the cannabis X and Y chromosomes. This told them that the
sequences of these genes are degenerating and will perhaps eventually be shed by the
cannabis genome. This is a situation that is similar to many mammalian sex
chromosomes, where it has been observed that the Y chromosome is degenerating and
may someday be lost by mammalian genomes like ours. Apparently, cannabis is going
through similar genomic growing pains as some animal systems.
Chromosomes are further subdivided into regions that code for gene products
(usually proteins) and regions that do not (called intervening sequences). While these
intervening sequences were at first thought to be extraneous and called “junk DNA,”
researchers are discovering more functional aspects of these regions that lie between
the coding regions. There are two kinds of noncoding regions that come into contact
with coding regions. The first type are the intervening regions between the coding
region units. The second kind of noncoding regions are embedded within the coding
regions, and these are called introns. The coding regions in these genes that are
interrupted by introns are called exons. We humans have a little over 30,000 discrete
genes in our genome, and cannabis has a little over 25,000 genes that code for gene
products. These estimates are much lower than previously thought, as the human genome
was initially thought to code for over 100,000 genes before the entire genome was
sequenced. The reason for the discrepancy is that before the genome was sequenced,
researchers were trying to estimate the number of different functions of genes that they
thought would line up well with the overall number of genes. But it turned out that many
genes can code for different functions, and the number of functions had been
overestimated by about a factor of three to five.
Other information that a genome sequence can tell us includes how close in the
genome certain genes are to each other (linkage); whether a gene has many copies of
itself scattered throughout the genome (copy number); whether a gene has mutations
relative to a reference genome; whether genomes have certain kinds of genes (like
resistance genes or sex determining genes); and how variable a gene might be in a
natural or agricultural population. All these factors are significant for the breeding and
health of cannabis.
The way genomes are now sequenced relies on brute strength. That is, much more
sequence is generated than what is contained in a typical genome. Let’s posit that a
genome has 1 billion nucleotides in it. One might need to obtain 100 times that amount
to reach a full understanding of this genome. This amount of information would be
called 100x coverage of the genome.
Sequences are obtained by fracturing the long genome strands into small fragments
(usually a tiny fraction of the overall genome), and then these fragments are treated with
biochemicals to produce the string of nucleotides on the fragments. When a genome is
sequenced, it resembles a bunch of small pieces of DNA with strings of Gs, As, Ts, and
Cs. To obtain the full genome from these short sequences, two processes need to be
accomplished: assembly and annotation. Assembly involves taking the millions or
billions of pieces of the initially fragmented genome of sequenced DNA and putting
them back together. This is possible thanks to brute computational force. If the genome
was initially fragmented using a random process, then every fragment will have some
overlap with some other fragments. These overlaps can be used to lace the millions of
small fragments together into what are called contigs (contiguous sequence fragments).
It’s like putting a linear puzzle together, and when you can’t add any more to one
contiguous reconstructed section, you start on a new one. Most of the time the breaks in
contiguous reconstructions mean that the sequences come from different chromosomes
(which is how the chromosomal structure of genomes can be inferred).
After assembly what you have are large strings of Gs, As, Ts, and Cs, which don’t
tell you much except maybe the number of nucleotides in the genome. This is where the
second approach—annotation—comes in. Annotation involves the systematic
translation of the DNA-based Gs, As, Ts, and Cs into the amino acid strings of proteins
the DNA codes for. This is achieved by using a set of rules (the genetic code) for
predicting what amino acid sequence a given DNA might produce. This is another
computationally intense step, as every possible way of decoding the DNA sequence is
accomplished and placed in a database. Then this temporary data base is searched using
algorithms that determine whether the predicted amino acid sequences of the newly
sequenced genome match with proteins known to exist in other organisms.
Amino acid sequences can fold into three-dimensional structures, which will
render the protein some of its function. Thus another approach is to determine whether
the predicted amino acid sequence makes a protein that folds into a shape that has a
function. Both these approaches are used to annotate the DNA sequences so that we can
ascertain which DNA stretches are potential genes and what the function of those genes
might be.
Ten Chromosomes, 25,000 (or So) Genes, and 1,001 (or More)
Secondary Compounds
Most of the genes in an organism’s genome contain the basic instructions for building
and maintaining the organism, and in this sense are not terribly exciting aspects of
cannabis. These genes are shared across related organisms and are responsible for what
make a eukaryote a eukaryote or a plant a plant, but they have little to do with what
makes one organism different from another. These “boring” genes are part of the core
genome of an organism; they might not be boring to a botanist who wants to know what
makes a plant a plant, but they have little importance to what makes a cannabis plant at
the genomic level. The core genome of plants in general can be estimated by comparing
the genomes of a range of different plants and determining which genes occur in all of
the genomes studied. Another thing that can be done when comparing genomes within a
species is to sum all the different genes in the various individuals to describe the
genomic distribution of the species. This result yields what is called the pangenome of a
species (fig. 12.2). Pangenomics has become an important part of studying cultivated
organisms, because the pangenome will indicate the full extent of genomic potential a
species might have.
Figure 12.2. Venn diagram representation of the pangenome, core genome, shell genome, and cloud
genome of a group of related organisms. The diagram shows the core genome in the middle of the
diagram, which is simply the overlap of all the genomes in the comparison. The shell genome consists of
any genes that are in two or more of the individuals in the study. The cloud genome is the collection of those
genes that are present in only a single individual species. Here there are four cloud genomes, one for each
of the individuals included in the comparison. The pangenome is the sum of all the genes in the diagram.