Biologists Rethink the Logic Behind Cells’ Molecular Signals
quantamagazine.org
quantamagazine.org
A cell has no evolutionary reason to transmit signals. It will however eat molecules it can use, and excrete molecules that are no longer needed, because this allows the cell to survive and reproduce. A white blood cell eating a bacteria doesn't do so with an intention to protect some organ somewhere in the body, it does so like predator eats prey. Leukocytes who eat well, ie face a bacteria they can eat, then multiply, and end up eating all the bacteria, before dying off when there's nothing more to eat. So they protect the body and then remove themselves, not because they have the intention to do it for the greater good, or because they received a signal, but because they have evolved to prey on bacteria within the ecosystem of the body.
Thinking of the body as a well ordered mechanism is a flawed view, there are no locks and keys, and most likely very few signals if any. Thinking of the body as a dynamically balanced ecosystem seems much closer to how cells behave and to the fantastically complex feedback systems that have evolved over eons and are now balancing the populations of cells in our bodies.
We may be ecosystems of individually oblivious and dumb little cells, but isn't it wondrous that from this emerges a complexity that can say "I" and has consciousness of self?
In other words the T cell doesn't get feedback on its own fitness. The fitness feedback is at the level of the reproductive success of a human being (healthy humans can have more kids than sick ones), not the reproductive success of a T cell (because it has no reproductive capabilities and therefore cannot be subject to selection pressures). Correct me if I'm wrong.
From https://www.nature.com/articles/nature.2016.19136 :
> A 'reference man' (one who is 70 kilograms, 20–30 years old and 1.7 metres tall) contains on average about 30 trillion human cells and 39 trillion bacteria, […] Those numbers are approximate — another person might have half as many or twice as many bacteria, for example — but far from the 10:1 ratio commonly assumed.
Symbiosis https://en.wikipedia.org/wiki/Symbiosis :
> Symbiosis […] is any type of a close and long-term biological interaction between two different biological organisms, be it mutualistic, commensalistic, or parasitic. […]
> Symbiosis can be obligatory, which means that one or more of the symbionts depend on each other for survival, or facultative (optional), when they can generally live independently. […]
> Symbiosis is also classified by physical attachment. When symbionts form a single body it is called conjunctive symbiosis, while all other arrangements are called disjunctive symbiosis.[3] When one organism lives on the surface of another, such as head lice on humans, it is called ectosymbiosis; when one partner lives inside the tissues of another, such as Symbiodinium within coral, it is termed endosymbiosis.
Endosymbiont: https://en.wikipedia.org/wiki/Endosymbiont :
> Two major types of organelle in eukaryotic cells, mitochondria and plastids such as chloroplasts, are considered to be bacterial endosymbionts.[6] This process is commonly referred to as symbiogenesis.
Symbiogenesis: https://en.wikipedia.org/wiki/Symbiogenesis #Secondary_endosymbiosis ... Viral eukaryogenesis: https://en.wikipedia.org/wiki/Viral_eukaryogenesis :
> A number of precepts in the theory are possible. For instance, a helical virus with a bilipid envelope bears a distinct resemblance to a highly simplified cellular nucleus (i.e., a DNA chromosome encapsulated within a lipid membrane). In theory, a large DNA virus could take control of a bacterial or archaeal cell. Instead of replicating and destroying the host cell, it would remain within the cell, thus overcoming the tradeoff dilemma typically faced by viruses. With the virus in control of the host cell's molecular machinery, it would effectively become a functional nucleus. Through the processes of mitosis and cytokinesis, the virus would thus recruit the entire cell as a symbiont—a new way to survive and proliferate.
T-Cell # Activation: https://en.wikipedia.org/wiki/T_cell#Activation
> Both are required for production of an effective immune response; in the absence of co-stimulation, T cell receptor signalling alone results in anergy. […]
> Once a T cell has been appropriately activated (i.e. has received signal one and signal two) it alters its cell surface expression of a variety of proteins.
T-cell receptor § Signaling pathway: https://en.wikipedia.org/wiki/T-cell_receptor#Signaling_path...
Co-stimulation : https://en.wikipedia.org/wiki/Co-stimulation :
> Co-stimulation is a secondary signal which immune cells rely on to activate an immune response in the presence of an antigen-presenting cell.[1] In the case of T cells, two stimuli are required to fully activate their immune response. During the activation of lymphocytes, co-stimulation is often crucial to the development of an effective immune response. Co-stimulation is required in addition to the antigen-specific signal from their antigen receptors.
Anergy: https://en.wikipedia.org/wiki/Clonal_anergy :
> [Clonal] Anergy is a term in immunobiology that describes a lack of reaction by the body's defense mechanisms to foreign substances, and consists of a direct induction of peripheral lymphocyte tolerance. An individual in a state of anergy often indicates that the immune system is unable to mount a normal immune response against a specific antigen, usually a self-antigen. Lymphocytes are said to be anergic when they fail to respond to their specific antigen. Anergy is one of three processes that induce tolerance, modifying the immune system to prevent self-destruction (the others being clonal deletion and immunoregulation ).[1]
Clonal deletion: https://en.wikipedia.org/wiki/Clonal_deletion :
> There are millions of B and T cells inside the body, both created within the bone marrow and the latter matures in the thymus, hence the T. Each of these lymphocytes express specificity to a particular epitope, or the part of an antigen to which B cell and T cell receptors recognize and bind. There is a large diversity of epitopes recognized and, as a result, it is possible for some B and T lymphocytes to develop with the ability to recognize self.[4] B and T cells are presented with self antigen after developing receptors while they are still in the primary lymphoid organs.[3][4] Those cells that demonstrate a high affinity for this self antigen are often subsequently deleted so they cannot create progeny, which helps protect the host against autoimmunity.[2][3] Thus, the host develops a tolerance for this antigen, or a self tolerance.[3]
"DNA threads released by activated CD4+ T lymphocytes provide autocrine costimulation" (2019) https://www.pnas.org/content/116/18/8985
> A growing body of literature has shown that, aside from carrying genetic information, both nuclear and mitochondrial DNA can be released by innate immune cells and promote inflammatory responses. Here we show that when CD4+ T lymphocytes, key orchestrators of adaptive immunity, are activated, they form a complex extracellular architecture composed of oxidized threads of DNA that provide autocrine costimulatory signals to T cells. We named these DNA extrusions “T helper-released extracellular DNA” (THREDs).
FWIU, there's also a gut-brain pathway? Or is that also this "signaling method" for feedback in symbiotic complex dynamic systems?
From https://en.wikipedia.org/wiki/Complex_system :
> Complex systems are systems whose behavior is intrinsically difficult to model due to the dependencies, competitions, relationships, or other types of interactions between their parts or between a given system and its environment. Systems that are "complex" have distinct properties that arise from these relationships, such as nonlinearity, emergence, spontaneous order, adaptation, and feedback loops, among others. Because such systems appear in a wide variety of fields, the commonalities among them have become the topic of their independent area of research. In many cases, it is useful to represent such a system as a network where the nodes represent the components and links to their interactions.
Graph, Hypergraph, Property graph, Linked Data, AtomSpace, RDF* + SPARQL*, ONNX, {...}
> The term complex systems often refers to the study of complex systems, which is an approach to science that investigates how relationships between a system's parts give rise to its collective behaviors and how the system interacts and forms relationships with its environment.[1] The study of complex systems regards collective, or system-wide, behaviors as the fundamental object of study; for this reason, complex systems can be understood as an alternative paradigm to reductionism, which attempts to explain systems in terms of their constituent parts and the individual interactions between them.
A multi-digraph of probably nonlinear relations may not be the best way to describe the fields of even just a few electroweak magnets?
> As an interdisciplinary domain, complex systems draws contributions from many different fields, such as the study of self-organization and critical phenomena from physics, that of spontaneous order from the social sciences, chaos from mathematics, adaptation from biology, and many others. Complex systems is therefore often used as a broad term encompassing a research approach to problems in many diverse disciplines, including statistical physics, information theory, nonlinear dynamics, anthropology, computer science, meteorology, sociology, economics, psychology, and biology.
... Glossary of Systems Theory: https://en.wikipedia.org/wiki/Glossary_of_systems_theory
Talking about parts of a mechanism in terms of "agency" is always a metaphor: A cogwheel or a transistor or a microchip doesn't "know" either what it's supposed to do. However, what is the case is that those parts are designed specifically to emphasize or to suppress particular physical effects.
And this kind of "design" can be found in cells and proteins as well - not by any kind of designer but through evolution of the whole organism and storage in the DNA.
I also believe this is the fundamental difference between an ecosystem and an organism: In an ecosystem, each part evolves on its own and the whole system is simply the result of all interactions. In an organism, the evolution of individual cells is constrained. It's only the oragnism as a whole that evolves. This means that all the chaotic interactions between the different parts of the organism aren't completely random either, because all those parts have a common playbook.
The evolution of the organism has tuned the interactions between the different parts in such a way that they result in particular outcomes - which increase the fitness of the organism as a whole.
E.g., from the POV of a white blood cell, it really may just be a selfish predator, however the way it is attuned to particular kinds of "prey" and the way other molecules and up- or downregulate its aggressiveness is not simply by chance.
You’re right though, we need to be careful that those maps don’t get confused with reality and end up constraining thinking and meaning.
Evolution on the level of multicellular organisms happens on the organism level and not on the cellular level (except in case of cancer) and so multicellular organism cells have incentives to do what is best for the organism as a whole, (and the organism's offspring) and not for the particular cell.
Hormones being passed between different parts of the body seem to be the way most communication happen inside the body, and it's definitely not in any cell's long term interest to ignore those signals. Even if the signal orders the cell to shrivel and die.
The only way for the DNA in a cell of a multicellular organism to survive long-term, is to create an entirely new organism, and there is a lot of order in the body to make sure that the vast majority of cells that don't fall in line, are killed very, very fast.
That's a bit of a leap.
The order and organisation of the human body is beyond every technology we have ever developed to date.
We discover what appears to be disorder in a healthy, non-aberrant system and make leaps to justify its disorder. Using the same philosophy that brought in the "junk dna" theory, we then settle the on acceptance of it being a mishmash of cobbled together mutations. But then as the years go on we find another level of order in that "chaos" and we're humbled again.
>but isn't it wondrous that from this emerges a complexity that can say "I" and has consciousness of self?
You're right, it is wonderous, and if we assumed order first, I suspect we'd look harder for it and find it faster than assuming chaos so early every time.
But that's exactly what the field of biology (and every other science) has been trying to do for 2000 years. We keep coming up with flawed analogies for systems that are inherently chaotic. Chaos can follow from simple rules, which is the entire basis for Chaos Theory.
That doesn't mean that there aren't rules, it means that the amount of predictions we can make about the system are limited and that the system may arbitrarily behave 'erratically' or non-deterministically, which biological systems often do! (i.e. the scales that biologists and microbiologists are primarily looking at).
The fact that there is a resulting, large-scale purpose emerging from it is an 'accident' of nature, in as much as that behaviour is not intentional, it is not created with a will or intent for those specific effects, but pure causality and the evolutionary fact that systems without those characteristics either could not propagate in the environment, or could not support other systems like itself to propagate.
To beleive there is chaos at some level of this extremely predictable system, you would have to have a system that starts with simple rules (chemistry), evolves chaotically, but has extreme order emerge from that mathematical chaos.
Flawed analogies are the result of improper understanding and the need for explanatory tools and models, but that's always going to happen as facts are revealed over time.
The answer isn't just to assume they're chaotic systems, but instead to accept that we don't fully understand all the systems and forces in play and keep searching for truth.
I don't think that's true. Signalling is important for multicellular coordination which can improve the fitness of the individual cell.
Sonigo seems to work in fetal MRI since a long time.
Kupiec seems to have not published scientific articles in biology since 2000, and his work have not been much cited. For example only 19 citations for "A Darwinian theory for the origin of cellular differentiation".
Are you aware of recent publications on the theme "We may be ecosystems of individually oblivious and dumb little cells"?
Thanks!
As in - “I want X” where the I identifies w the wanting lets the wanting take charge.
Same with recognizing oneself as an ongoing singular personality.
ever changing identification with various things perceived as self.
That doesn't stop it from explicitly having the specific design that fulfils that function though.
In the 1800’s when ‘fields’ were the new thing, folks assumed cells (or, more generally, tissue) has invisible vital forces that dictated morphongenesis etc.
With the development of steam, internal combustion, etc, living systems were viewed in terms of energy and chemical reactions.
Then, electronics... with digital, everything — from DNA on down — was viewed as, essentially, a computer program.
Now, as we’re getting more comfortable with chaos and complex inscrutable systems (such as neural nets and the like), we view the mess of proteins less like a lock-key and more like a dynamic complex system.
Not being critical... but, it’s worth noting the source of these analogies.
I don’t know if there was much of the “dynamic complex system” stuff in the 1800s. (What a terrible way to describe it... but, I think you know what I was saying.)
The theme seemed to be striving towards simplification. That is, as Newton transformed the convoluted epicycles and platonic spheres and all the other bizarro theories explaining astronomical movements down to F=MA with a nice simple inverse-squared law tossed in, I think scientists writ large believes a similar simplification would occur in other fields. This was justified to some degree; chemistry was beautifully simplified in a short time. As was, to some degree, medicine with the advent of germ theory.
But, biology seems immune.
I really don’t think many biologists were thinking in terms of complex dynamic systems. (Ironically, Turing — a computer guy — was with his paper on reaction/diffusion equations.)
This dominates in fields where the specialists tend not to post here (molecular biology) and gets shot down rapidly in areas where there's more people with domain expertise present (semiconductor manufacturing).
It's a tech startup forum: the whole concept is based on this theory and the appeal depends heavily on ignoring the exceptionally high failure rate of start ups.
A new scientific truth does not generally triumph by persuading its opponents and getting them to admit their errors, but rather by its opponents gradually dying out and giving way to a new generation that is raised on it. … An important scientific innovation rarely makes its way by gradually winning over and converting its opponents: it rarely happens that Saul becomes Paul. What does happen is that its opponents gradually die out, and that the growing generation is familiarized with the ideas from the beginning: another instance of the fact that the future lies with the youth.
As someone said, "Nothing in Biology Makes Sense Except in the Light of Evolution". If there is a way to select a mechanism that gives a real advantage to the organism, then it doesn't matter which bucket it falls into.
PS: I was also amused by the lack of sinusoids and an abundance of sigmoids in biochemistry.
In a way that is still true, but its not one message per messenger molecule. The message is intimately connected to what other messenger molecules are around, what are they bound too, what composition of receptors are on the cell surface, what are those receptors connected to, what secondary messages are being sent intracellularly and what messages have the cells received previously.
As we have understood the hormones passing loud, clear and overruling messages (like e.g insulin and thyroid hormone) we start discovering the much more specific and context-dependent hormones. And those are going to have effects that are much more dependent on the cellular state, and so are much more difficult to understand.
It's extremely complex, because the state of the cellular machinery is huge, and quite a lot of things we can't really observe directly.
It is beautiful work, but this breathless coverage really ignores that these properties have been previously characterized in other receptor signaling families like FcRs, cytokines, FGFR, TGFb, etc.
There is no upper limit to the complexity that biological systems are willing to use. They only have to work just well enough not to interfere with reproduction. Also: That endocrinology is even meaningfully possible to do is astonishing.
How does "analog" rule out "circuit".
^This is the algorithm they describe. They make it sound like there is some mystic computation going on. This is how biological computation networks work. A lot of the complexity is just what’s needed to get an analog system to perform digital computation.