The remarkable idea here is that the DNA is not a real blueprint but a supply system of proteins to a self organizing biology. This has been emerging and this comes closer to an understanding.
How
about another astounding idea. Our biology is guided to conform to
the perfect pattern provided by the 'soul' and is mediated by the
spirit or consciousness in an ongoing manner. This applies for all
biology. This is a natural operator within the biological logic of
all life.
The
internal logic of life continuously manages the pattern that
describes the output range while dealing with the limitations imposed
by the available domain. Suddenly this is not necessaroly embedded
in the DNA or anywhere else physical except consciousness which is
phtysical in the strictest sense only.
A closed loop
.
The DNA helix gave 20th-century biology its symbol. But the more we learn, the more life circles back to an older image
There
is a remarkable fact about identical twins: they have the same DNA,
and therefore the same ‘genetic fingerprint’, yet their actual
fingerprints (such as they might leave behind on a murder weapon) are
different, and can be told apart in standard police observations.
Fingerprints
are, of course, produced by the pattern of tiny ridges in skin. So,
it would appear that certain fine-scale details of our anatomy cannot
be determined by a precise ‘genetic blueprint’.
It
isn’t only fine details that seem open to negotiation in this way:
anyone who has seen Bonsai cultivation knows how the very genes that
would normally build a large tree can instead build a miniature-scale
model, given a suitable environment. Bonsai trees aren’t completely
scaled down, of course: their cells are normal-sized – it’s just
that each component is made with fewer of them.
In
the 1950 and ’60s, many children were affected by their mothers
taking the drug thalidomide while pregnant, when the drug blocked
growth of the internal parts of their limbs. Even though growth of
the skin is not directly affected by thalidomide, the very short
limbs of affected children were covered by an appropriate amount of
skin, not the much larger amount that would be needed to cover a
normal limb. The growth of the skin cannot, therefore, just be in
response to the command of a hard-wired internal blueprint: something
much more adaptive must be going on.
Such
observations are not troubling for biological science as such.
But they are troubling for a certain picture of how biology
works. The symbol for this worldview might be the DNA double helix,
its complementary twisting strands evoking other interdependent pairs
in life: male and female, form and function, living and non-living.
DNA on its own is just a chemical polymer, after all, essential for
life but not itself alive. Yet it holds out the promise that we can
explain living processes purely in terms of the interactions between
simple molecules.
Twentieth-century
biology was dominated by a strongly reductionist agenda even
before James Watson, Francis Crick, Rosalind Franklin and Maurice
Wilkins revealed the structure of DNA in 1953. Early geneticists knew
perfectly well that they were studying statistical correlations (if
one makes such-and-such a change in gene x, then allows the organism
to develop in a fixed environment e, one will observe alteration f,
etc). In later generations, however, the language of causation
started to creep in, and with it the idea of a fixed relationship
between genes and body features. Every reader of this essay will have
read or heard phrases such as ‘the gene for breast cancer’, ‘the
gene for autism’ or even ‘the gene for intelligence’ (try
typing any of those phrases into a search engine).
The cultural idea that went with this slip of meaning – that bodies
are made according to a genetic blueprint
– placed genes at the centre of mainstream biological thought. The
discovery and progressive unravelling of the double helix seemed only
to confirm their place there.
The
union of genetics with molecular biology has undoubtedly created a
powerful new science. By unpicking the molecular interactions inside
cells, we’ve been able to develop drugs to mimic or interfere with
specific processes. The discovery of enzymes that synthesise and edit
DNA laid the foundations for genetic engineering, which is usually
discussed in terms of its commercial applications, but whose most
common use has always been in pure research. In this way, advances in
knowledge create the tools to advance knowledge, in a virtuous
circle. Nevertheless, we appear to have come to a threshold. The more
we know about the molecular processes, the less sense the
gene-centric perspective makes.
In
the early days of genetics, scientists studying different animals
would identify genes and correlate them with body-scale features.
However, they had no way of knowing whether the genes they had
identified in one species were the same ones that were known in
another. Once technologies for reading DNA sequences were invented,
it became possible for researchers to ‘read’ their genes and to
notice when genes in two different species were so related they were
effectively the same thing.
This
often produced surprises. The gene ‘Wingless’, for example, was
identified by fruitfly geneticists as a blueprint for making wings
(fly biologists name their genes after what happens if the gene is
damaged). Cancer specialists working with mice had identified what
they called Int-1 as a gene for mouse breast cancer. But these genes
turned out to be effectively the same: they code for a protein now
given the hybrid name Wnt. Properly analysed, Wnt is neither for
making wings nor for breast cancer. It is for carrying signals
between cells: the meaning of the signal depends on what cell, in
what organism, is receiving it.
This
is just one of very many examples. The
concept of ‘the gene for feature x’ is
giving way to a much more complicated story. Think something like:
‘the
gene for protein a, that interacts with proteins b, c and d to allow
a cell to undertake process p, that allows that cell to co ordinate
with other cells to make body feature x’. The
very length of the above phrase, and the
weakness of the blueprint metaphor,
emphasises a conceptual distance that is opening up between the
molecular-scale, mechanical function of genes and the interesting
large-scale features of bodies. The genes matter – of course they
do, because something has to build all these proteins. But the helix
seems less and less appropriate as an icon for the all-important
control systems that run life, especially at larger scales (cells,
tissues, organisms, populations, ecosystems and so on).
There
is, however, an alternative.
It can be represented by an even simpler icon than the double helix.
It really does seem to pervade life at all scales. This alternative
is a concept, rather than a physical thing. And it can it be glimpsed
most clearly if
we ask how things structure themselves when they must adapt to an
environment that cannot be known in advance.
he
most local environment for many cells consists simply of their
similar neighbours. This is especially so in a very common sort of
structure that we find in all sorts of living things – the sheet.
(Think of the surface of the skin, the lining of the gut, the inside
layer of your blood vessels.) These sheets are collections of cells
stuck together, edge to edge. The cells adhere to one another via a
number of very small, specialised junction complexes. The outside
part of a junction complex on one cell binds to the outside part of a
similar complex on the neighbouring cell, while the inside part binds
to long, strong filaments of protein that form a network inside the
cell: the ‘cytoskeleton’, as it is known. It is the mechanical
connection of each cell’s cytoskeleton to those of its neighbours,
via the junctions, that helps to give the sheet its strength.
When
cells first meet, in normal development or in a culture dish, neither
can ‘know’ in advance precisely where contact will first be made.
The internal cytoskeletons of the cells cannot, therefore, be built
to an advanced plan; they must develop adaptively to suit the precise
conditions at the time. The way they achieve this is both fascinating
in detail and, in its general outline, thoroughly typical of life.
The
cells that are forming the sheet continuously make new branches of
their cytoskeleton network. These branches head towards random points
on the cell periphery. Those that do not happen to land on a junction
will never experience mechanical force, whereas those filaments that
do find and link to a junction will be placed under tension by the
neighbouring cell. Now, it happens that cells are full of enzyme
complexes that rapidly destroy cytoskeleton filaments. This
destruction is, however, strongly inhibited if a filament is under
mechanical load. The many filaments that end up in the wrong place
are therefore quickly destroyed, while those that happen to be
arranged appropriately to carry forces survive. Thus the
cytoskeleton’s anatomy organises itself according to its
environment and adapts continuously to changing mechanical loads.
This
is just a very small-scale example of adaptive self-organisation. But
the same principles work at larger scales, too. Organs consist of
vast numbers of cells of different types, intricately assembled to
perform whatever the organ’s function might be. Some cells have a
very direct connection with that function: the milk-secreting cells
of the breast, for example, or the food-absorbing cells of the
intestines. Others serve a support role, bringing food and oxygen,
removing toxins, carrying the products of the organ wherever they
need to go and so on. For the organ to work, each type of cell needs
to be present in the right numbers at the right places, yet we know
that organs cannot be assembled according to a precise,
blueprint-like spatial plan. We know this because it is possible to
remove organs from animal embryos and culture them in the presence of
artificial spatial restraints, so that the overall anatomy follows
the artificial constraints but the detailed internal anatomy looks
normal, showing that its construction must have adapted to the new
circumstances.
In
some cases, we are starting to understand how this self-organisation
happens, and how it relies on cell-to-cell communication. The growth
of blood capillaries provides a good illustration. Tissues need blood
capillaries to bring them oxygen and nutrients and to take away waste
products, but a cell that is too far from the nearest blood capillary
will find itself short of oxygen. At this point, a protein called
HIF1A, which is normally destroyed by an oxygen-dependent process
almost as soon as it is made, starts to accumulate. HIF1A puts a
temporary brake on further cell proliferation and also causes the
cell to secrete a protein called VEGF, which spreads out through the
surrounding tissue. The cells that make blood capillary walls are
sensitive to VEGF: if they detect it, they begin to proliferate and
extend new capillary branches towards its source, and so the tissue
cells that were short of oxygen will receive a supply from the new
blood vessels. When capillary growth is adequate, there will be
enough oxygen to make HIF1A unstable again, so the brake on tissue
proliferation is released, VEGF production will cease and so will
capillary growth. In a growing organ, this sort of thing happens
again and again to make sure that growth doesn’t outstrip blood
supply.
As bodies grow, they stretch the skin, which expands until the tension has been reduced: the growth of the skin keeps up with that of the body
We
can tell a similar story about the fluid drainage ducts of the
kidney. These ducts consist of a treelike arrangement of tubes,
spread out in space to serve the organ. Even when confronted
experimentally with very peculiar constraints, they will grow into a
well-spaced (if strangely-shaped) tree. My laboratory has recently
discovered that this spacing is achieved by, in effect,
self-loathing: the growing tips of the tree’s branches secrete a
molecule that they themselves find repulsive, so they grow in the
direction that minimises their exposure to it and therefore maximises
their mutual separation. This simple mechanism adapts naturally to
‘unexpected’ anatomical situations, whether due to experimental
interventions or earlier errors in embryonic development.
Or
take the skin, the largest organ of the body. It has to be exactly
the right size to cover all that lies underneath, and yet the
dimensions of the body cannot be predicted from the genes: variations
in diet and exercise have a huge effect on body size, as does
pregnancy (temporarily). Clearly, the growth of the skin has to be
adaptive. A series of experiments on skin cells in culture, performed
mainly by Celeste Nelson’s tissue morphodynamics group in
Princeton, suggests a very elegant mechanism: skin cells respond to
tension by proliferating, the daughter cells of each cell division
being aligned with the tension so that the tissue grows in that
direction. As bodies grow, they stretch the overlying skin, which
proliferates and expands until the tension has been reduced. The
growth of the skin therefore keeps up with that of the body.
If
skin is damaged, it has to repair itself, adapting its activity to
whatever unpredictable location and shape the hole happens to have.
Adult skin heals by scarring – an ‘emergency’ response that
seals the body off from a hostile world. Foetal skin, however, heals
without scars. If it is cut, cells that used to have neighbours
suddenly encounter free space. They respond to it by organising a
contractile band along their exposed edge. This band links the
cytoskeletal fibres of neighbouring cells so that the whole edge of
the wound starts to contract, closing it up. As closure proceeds,
cells that meet make junctions with one another and, as they no
longer feel a free edge, they lose their contractile band and become
normal members of a sheet again. This proceeds until the hole has
disappeared completely.
Self-organising
processes seem to operate at much larger scales, too –
beyond the level of single organisms. Schools of fish, for example,
consist of individuals that align themselves with one another so that
the school moves and changes direction as a cohesive entity. This can
turn a predator species into a highly efficient hunting collective –
when, for example, tuna schools form outstretched arms to engulf
their prey. Similar behaviour can also protect prey species: if a
predator charges a school of pollock, the school will split up and
reunite behind the intruder, always presenting it with a confusing
swirl of hard-to-track, churning fish.
We
still have much to learn about how schooling works, but it seems
obvious that each fish can’t have a detailed choreography stored in
its head, nor a detailed map of the location of every other fish in
the school. Instead, each individual seems to base its behaviour on
purely local influences: most importantly, the distances and speeds
of its immediate neighbours. Computer models produce quite convincing
schooling behaviour when their constituent fish – all the same,
with no special leader in charge – have four basic behaviours:
attraction (closing up to another fish), repulsion (increasing the
distance from another fish), alignment (altering direction to swim
parallel to a neighbour) and searching (looking for a school of
fish). Searching happens only if a fish finds itself isolated.
Repulsion is strong at short distances and attraction kicks in at
larger ones, which tends to keep fish an optimal distance apart, and
they reorientate to swim in the average direction of their various
neighbours.
Large-scale ecosystems of co operating organisms such as trees and fungi show self organising behaviour
These
simple rules are not enough to mimic the particulars of hunting or
predator-evading behaviour, but they are enough to keep a school
organised for its routine swimming. The flocking of birds appears to
work in a similar way: almost 30 years ago, the programmer Craig
Reynolds made a computer model of very simple entities – ‘boids’
– that also showed attraction, repulsion, and alignment. Again, the
behaviour of the model is so good it implies that real birds might
well organise their flocks by each obeying simple, local rules.
Schooling
and flocking behaviours are, of course, restricted to large groups of
individuals from a single species. Might self-organising properties
operate even at the level of multi-species ecosystems? There’s
reason to think that they do. Vegetation on arid soils will, for
example, arrange itself into groups with plain soil between them: the
plants in the groups all benefit from their mutual ability to help
rare rainfall penetrate the ground. And in simple experimental
microbial communities (not, in fact, different species, but yeasts
genetically engineered to have different metabolisms that can
co-operate to use environmental nutrients), the different types of
individual self-organise into mixed clusters that bring co operators
together. Many ecologists believe that large-scale ecosystems of
co operating organisms, for example trees and fungi, show
similar self organising behaviour.
All
of these examples, and many more like them, turn out to have
something in common when analysed at the mechanistic level: in each
case, what has been achieved so far by the system is used to control
its current behaviour. This type of control is called feedback, and
is represented by a loop feeding information from the output of a
process back to its input.
In
the case of the cytoskeleton, the stability of a filament depended on
whether it was carrying a mechanical force, which in turn depended on
whether it was in the right place to connect to cell junctions. The
achievement of a filament (to be in a useful place or not) is
therefore fed back to decide what it will do next (survive, or be
disassembled). In the case of the blood capillaries, the extent to
which present growth has been adequate to bring enough oxygen into
the tissues is fed back, via VEGF, to control whether the capillaries
continue to grow or remain as they are. And the same principle seemed
to explain the schooling of fish: any error in an individual fish’s
relative positions and direction compared to its neighbours is used
to modify its swimming, to make the error smaller. Seen from the
abstract perspective of feedback loops, adaptive self-organisation
looks more or less the same across all scales of life, from the
architecture of subcellular assemblies to the arrangements of
co-operating species in ecosystems.
In
this sense, the loop is a near-universal symbol of living processes.
We
have, then, two very different models for understanding life. In the
gene-centred model, a ‘gene for this’ and a ‘gene for that’
act deterministically to construct a cell, or a body, or an aspect of
behaviour. In the loop-centred model, feedback-rich processes allow
cells, bodies and ecosystems to construct themselves adaptively in
response to the prevailing conditions. Can these models, which seem
on the face of it very different, ever be reconciled? Yes, very
easily. The feedback loops that guide self-organisation, at any
scale, rely ultimately on the action of protein-based mechanisms, and
proteins are encoded by genes.
Genes do not make body features, they make the machines that organise body features adaptively
The
role of proteins in subcellular self-organising systems such as the
cytoskeleton is obvious: the cytoskeleton is made of proteins. In my
account of capillary development, the proteins HIF1A and VEGF
highlighted the importance of specific molecules to organisation at a
larger scale. Even events at much larger scales, such as the
schooling of fish, ultimately rely on protein machines. Genes are
therefore essential to self-organisation at all the scales of life –
just not in a deterministic way. Rather, the genes are needed to make
the machines that mediate feedback-driven self-organisation: the
self-organisation is a high-level property that emerges from the
underlying network, not a feature of any of the individual
components.
This
has interesting consequences. Where any part of the
mechanism is sensitive to the environment, the whole self-organising
loop can be too. The number of red cells in blood, for example, is
set by a feedback loop sensitive to measurements of oxygen deep in
the kidneys. When someone goes to live in the thin air of a high
mountain, they tend to have more blood cells. Why? Because the
‘normal’ complement of cells is not sufficient in that
environment, so the kidneys sense abnormally low oxygen and signal
for more blood cells to be made. The effects of environmental
sensitivity at a single point percolate throughout the entire
organism. If we recognise that genes do not make body features, they
make the machines that organise body features adaptively, that shift
in perspective does much to lay to rest the long debates about nature
versus nurture.
The
DNA helix is important, of course. But the most important thing it
does is make proteins that can operate in regulatory loops. These
loops can also operate at the molecular level: genes make proteins,
but these proteins determine which genes are ‘off’ and which are
‘on’ (as HIF1A does), making a control loop at even the molecular
level. Unlike the helix, loops also operate at scales far above the
molecular, covering a range of sizes from bacterial colonies to the
vast ecosystems of the rainforest – perhaps to the ecosystem of the
entire Earth. Beyond Earth, life without DNA is just about thinkable
(one can imagine alternative strategies for storing information).
Life without feedback loops, though? I have never met any biologist
who can imagine that.
The
helix is too well-established an icon to be deposed any time soon.
And yet, a simple loop would be a much more universal symbol of how
life works at all of its scales and levels. Perhaps the Ouroboros,
beloved of gnostics and alchemists, has been an ideal symbol waiting
in the wings for centuries: there can surely be no more evocative
symbol of feedback than a snake growing by devouring its own tail.
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