Biomolecular Machines (split)

Perception = reason?

From my Oxford Concise:

Perception - the ability too see, hear or become aware of something through the senses

Reason - the power of the mind to think, understand and form judgements logically


Bacteria know that they are too small to make an impact individually.

was taken from what I assume to be a scientific publication, I would interpret the statement litterally (not metaphorically). So clearly the implications of the statement are the following:

The bacterium -

  1. by perception, is aware of its size
  2. by reason, realizes that its diminutive proportions cannot make an impact
  3. by reason, figures out that this is a problem
  4. by reason, comes up with a solution to the problem

Maybe at a stretch the bacterium can be argued to perceive, but I’m doubtful about the reasoning bit.


Reasoning…perhaps not, that seems way too teleological not? Or is it?
How about molecular autonomous agents?

Intelligent? There is no universally accepted definition of intelligence, so lets go with what there is…
Look at artificial intelligence for example (excuse the wiki if you don’t mind).

For AI, the following characterstics have been identified or associated with “intelligence”.

  1. Deduction, reasoning, problem solving
  2. Knowledge representation
  3. Planning
  4. Learning
  5. Natural language processing
  6. Motion and manipulation
  7. Perception
    8 ) Social intelligence
  8. Creativity
  9. General intelligence

Compare the systems and machinery within cells to any intelligent AI system.

1) Deduction, reasoning, problem solving
Deduction: No
Reasoning: No
Problem solving: Yes. E.g. (from Nature;Vol 446;12 April 2007: Quantum path to photosynthesis)

[QUOTE]Elsewhere in this issue, Engel et al. (page 782) take a close look at how nature, in the form of the green sulphur bacterium Chlorobium tepidum, manages to transfer and trap light’s energy so effectively. The key might be a clever quantum computation built into the photosynthetic algorithm.

[QUOTE]The process is analogous to Grover’s algorithm in quantum computing, which has been proved to provide the fastest possible search of an unsorted information database.
And in the same issue: Evidence for wavelike energy transfer through quantum coherence in photosynthetic systems.

[QUOTE]When viewed in this way, the system is essentially performing a single quantum computation, sensing many states simultaneously and selecting the correct answer, as indicated by the efficiency of the energy transfer.
Wait for catcalledjesus to say something lol…

Deduction: No
Reasoning: No
Problem solving: Yes. (not quantum mechanically yet…)

2) Knowledge representation
Default reasoning and the qualification problem: No?
Unconscious knowledge: Perhaps. Stored in any or all of the cellular codes?
The breadth of common sense knowledge: No.
Default reasoning and the qualification problem: No
Unconscious knowledge: Yes. The software contains the stored information
The breadth of common sense knowledge: No

3) Planning
Cells: Yes, from post here and here:

[QUOTE]We question whether homeostasis alone adequately explains microbial responses to environmental stimuli, and explore the capacity of intra-cellular networks for predictive behavior in a fashion similar to metazoan nervous systems. We show that in silico biochemical networks, evolving randomly under precisely defined complex habitats, capture the dynamical, multidimensional structure of diverse environments by forming internal models that allow prediction of environmental change. We provide evidence for such anticipatory behavior by revealing striking correlations of Escherichia coli transcriptional responses to temperature and oxygen perturbations—precisely mirroring the co-variation of these parameters upon transitions between the outside world and the mammalian gastrointestinal-tract. We further show that these internal correlations reflect a true associative learning paradigm, since they show rapid decoupling upon exposure to novel environments.
Microarray transcriptional profiling was employed to determine whether gene expression correlates with the observed global cellular state and physiological responses. And indeed it does.
From the study it was determined that anticipatory transcriptional reprogramming occurs in response to aerobic and anaerobic environmental changes and these anticipatory transcriptional reprogramming events are as a result an “associative learning” paradigm. Is this an example of harnessing random variation and selection that allow for predictive transcriptional reprogramming in response to environmental change that gives the illusion of foresight? Creativity?

And for this: Scientists Show Bacteria Can ‘Learn’ And Plan Ahead
AI: Yes if instructed to.

4) Learning
Cells: Yes: Scientists Show Bacteria Can ‘Learn’ And Plan Ahead
AI: Yes, certain artificial neural networks are capable of this.

5) Natural language processing
Cells: Yes and no. Yes because cells are able to communicate and process information from themselves and other cells (autocrine, paracrine, endocrine etc). No, cells do not consciously talk
AI: Yes and no. Yes because certain programs can interpret human language and systems of various platforms can communicate (Linux to Mac etc). No, AI does not consciously talk.

6) Motion and manipulation
Cells: Yes, chemotaxis…controlled movement.
Directed movement of organisms without a nervous system.
AI: Yes

7) Perception
Cells: Yes, cells communicate with the environment through surface receptors and relays information through signal transduction which in turn affects gene expression and protein activity.
AI: Yes

8 ) Social intelligence
Cells: Yes, even bacteria interact with other bacteria and can even mimic a multicellular organism through quorum sensing.
AI: Perhaps? AI neural networks?

9) Creativity
Cells: Yes, harnessing random variation and selection to adapt. Controlled cytosine deamination and subsequent repair mechanisms determine the type of random mutation to occur. Not directed mutation, but an active search of random space for a solution. Your immune system also does it.
AI: Perhaps? An example?

10) General intelligence
Cells: No (Only in humans so far)
AI: No

When compared to our own engineered AI, even the simplest lifeforms’ machinery outperforms it hands down.

Mmmm … interesting points all.

There was a young coccus called Fred
who, when considering the life that he led,
without baby-blue eyes
and of diminutive size,
kept tossing and turning in bed.


You dropping your little turds around here again?

I notice that you have conveniently excised your Wikipedia definition of intelligence - was the highlighted bit a teensy-weensy problem for you LOL? -

Intelligence (also called intellect) is an umbrella term used to describe [b]a property of the mind[/b] that encompasses many related abilities, such as the capacities to reason, to plan, to solve problems, to think abstractly, to comprehend ideas, to use language, and to learn.

As stated elsewhere:

“… I did glance through all that - speculative kite-flying of the worst ( read “hidden religious agenda” ) kind. No brain = no mind = no consciousness = no intelligence. Unless your beloved cells have brains hidden in their arses or somewhere.”

Or, of course, they have Bebeh Jebus up their arses, directing operations.
:stuck_out_tongue: :stuck_out_tongue:

Still no answer.


Defecatory Fatalist Manifesto: Point 3…

Anyway, let’s look at the teleological adaptation of the immune system:
Putting cytosine deamination to work: How the immune system exploits the optimal properties of the genome for antibody diversification and immune function.
The effect of cytosine deamination on a random pool of amino acids and how it might facilitate evolution has been described. The optimal features of the genetic code are exploited by the vertebrate immune system by putting cytosine deamination to work. Antibody diversification is crucial in limiting the frequency of environmentally acquired infections and thereby increasing the fitness of the organism. Initial diversification of antibodies is achieved by assembling variable (V), diversity (D) and joining (J) gene segments (V(D)J recombination) by non-homologous recombination. Further diversification is carried out by somatic hypermutation (SHM) and Class Switch Recombination. Central to the initiation to these diversification processes is the activation-induced cytosine deaminase (AID) protein. AID deaminates cytosine to uracil in single stranded DNA (ssDNA - arising during gene transcription) and is dependent on active gene transcription of the various antibody genes. The induced mutation is resolved by at least 4 pathways (Figure 1):

  1. Copying of the base by high-fidelity polymerases during DNA replication.
  2. Short-Patch Base Excision Repair (SP-BER) by uracil-DNA glycosylase removal and subsequent repair of the base.
  3. Long-Patch Base Excision Repair (LP-BER)
  4. Mismatch repair (MMR)

Link to big picture

Figure 1: Activation induced cytosine deamination and the pathways involved in resolving the induced mutation. 1) Normal DNA replication results in a C:G→T:A transition. 2) Successful SP-BER resolves the mutation, however the recruitment of error-prone translesion polymerases results (e.g. REV1) in transversions (REV1; C:G→G:C) and transition. 3) LP-BER can also resolve the mutation, however recruitment of low-fidelity polymerases (e.g. Pol n) also causes transition and transversion mutations. 4) MMR repair can also resolve the mutation, however the recruitment of low-fidelity polymerases through this pathway is a major cause of A:T transitions.

AID causes somatic hypermutation and its activity is limited to the certain genetic regions of the immune system. When the system runs unchecked, mutations might be introduced into proto-oncogenes, resulting in possible cancerous growth. The system is controlled (Figure 2). The activity and gene expression of AID is controlled. The type of error-repair pathway and the subsequent recruitment of various low-fidelity polymerases determine the type of mutations after the repair process and these also seem to be controlled. Current research focuses on the mechanisms of control of downstream repair pathways and why this system is selectively targeted to the small region of antibody genes.

Figure 2: Controlled variability of somatic hypermutation.

Thus, the immune system exploits the properties the genetic code and controls random variability. This system is not only limited to vertabrate. Cytosine deamninases are found in bacteria as well. Error-prone repair systems are also present together with an optimal code. In this case the optimal properties of cytosine with regards to evolution and how it relates to the code.

Peled JU, Kuang FL, Iglesias-Ussel MD, Roa S, Kalis SL, Goodman MF et al. The biochemistry of somatic hypermutation. Annu Rev Immunol. 2008;26:481-511.

Teng G, Papavasiliou FN. Immunoglobulin somatic hypermutation. Annu Rev Genet. 2007;41:107-20.

Goodman MF, Scharff MD, Romesberg FE. Abstract AID-initiated purposeful mutations in immunoglobulin genes. Adv Immunol. 2007;94:127-55.

Basu U, Chaudhuri J, Phan RT, Datta A, Alt FW. Regulation of activation induced deaminase via phosphorylation. Adv Exp Med Biol. 2007;596:129-37

You are the only one who minds wiki, when it doesn’t suit your agenda. ::slight_smile:

When compared to our own engineered AI, even the simplest lifeforms' machinery outperforms it hands down.
Only in your head and by quotemining scientists.

Unless you’ll provide the peer reviewed paper where any biological or life science scientist makes a case for “intelligent” cells. Won’t hold my breath.

Found any computers or any other of our own engineered AI systems that make other computers or AI systems so that they in turn can succesfully make more computers AI systems?
Interesting don’t you think?
Bacteria as computers making computers.

Don’t hold your breath waiting for any biological or life science scientist making a case for “non-intelligent” cells either ;).

Aaanyway, enough about intelligence… More biomolecular machines :D.

A little about RNA splicing machinery: [URL=]Possibly the most complex macromolecular machine in the cell[/URL]

What is RNA splicing?
Many human genes (±94%) contain exons (the DNA sequences that code for amino acids). These exons can be spliced together to form different types of proteins from a single gene.

How is it controlled?
Extensively and exquisitely controlled.

How common is it in humans?
Human Genes: Alternative Splicing Far More Common Than Thought

[QUOTE]ScienceDaily (Nov. 4, 2008) — Scientists have long known that it’s possible for one gene to produce slightly different forms of the same protein by skipping or including certain sequences from the messenger RNA. Now, an MIT team has shown that this phenomenon, known as alternative splicing, is both far more prevalent and varies more between tissues than was previously believed.
Thus, the same gene can result in different functions, depending on the functionality and control of the RNA splicing machinery.

Is it important?
Of course: Humans And Chimps Differ At Level Of Gene Splicing

What happens if the machinery malfunctions?
Quality control systems are in place.
RNA Biology Finding Makes Waves By Challenging Current Thinking

[QUOTE]ScienceDaily (Jan. 23, 2008) — Case Western Reserve University School of Medicine researcher Kristian E. Baker, Ph.D. challenges molecular biology’s established body of evidence and widely-accepted model for nonsense-mediated messenger ribonucleic acid (mRNA) decay with a new study. With her collaborator, Ambro van Hoof, Ph.D. of The University of Texas Health Sciences Center, Baker directly tested the faux 3’ UTR model and proved it could not explain how cells recognize and destroy deviant mRNA. This landmark discovery will redirect mRNA research and expand opportunities for new discoveries in understanding the cells’ ability to protect itself from these potential errors.
Present in yeast…

But how prevalent is this kind of machinery?
Visualizing The Machinery Of mRNA Splicing

[QUOTE]ScienceDaily (Apr. 8, 2008) — Recent research at Yale provided a glimpse of the ancient mechanism that helped diversify our genomes; it illuminated a relationship between gene processing in humans and the most primitive organisms by creating the first crystal structure of a crucial self-splicing region of RNA.

[QUOTE]This work, published in Science, highlights a 16-year quest by Anna Marie Pyle, the William Edward Gilbert Professor of Molecular Biophysics & Biochemistry at Yale, and her research team into the nature of group II introns, a particular type of intron within gene transcripts that catalyzes its own removal during the maturation of RNA.

Group II introns are found throughout nature, in all forms of living organisms. Although much has been learned about their structure and how they work through biochemical and computational analysis, until now there have been no high-resolution crystal structures available. The resulting images have provided both confirmation of the earlier work and new information on the three-dimensional structure of RNA and the mechanism of splicing.

One of the most exciting aspects of this work was that we did not need to do anything disruptive to these molecules to prepare them for structural analysis, said Pyle. The molecules showed us their structure, their active site and their activity – all in a natural state. We were even able to visualize their associated ions.

According to Pyle, the crystal structure revealed some unexpected features – showing two sections that were most implicated as key elements of the active site and strengthening a theory that the process of splicing in humans shares a close evolutionary heritage with ancient forms of bacteria.
Forms of this machinery present all the way down to bacteria :cool:.

Here is a video describing the process.

Yawn “Well, I can’t explain it, therefore a greater intelligence must be at work.”

What a tired little joke.


How much straw can this bunny handle?

Aaaanyway. More machines ;D.

Design Features of a Mitotic Spindle: Balancing Tension and Compression at a Single Microtubule Kinetochore Interface in Budding Yeast

[QUOTE]Accurate segregation of duplicated chromosomes ensures that daughter cells get one and only one copy of each chromosome. Errors in chromosome segregation result in aneuploidy and have severe consequences on human health. Incorrect chromosome number and chromosomal instability are hallmarks of tumor cells. Hence, segregation errors are thought to be a major cause of tumorigenesis. A study of the physical mechanical basis of chromosome segregation is essential to understand the processes that can lead to errors. Tremendous progress has been made in recent years in identifying the proteins necessary for chromosome movement and segregation, but the mechanism and structure of critical force generating components and the molecular basis of centromere stiffness remain poorly understood.
During cell division, DNA is replicated and commitment to this process is started during the G1/S phase. During the S-phase, DNA is replicated and cells grow (take up energy) in size in order to provide enough energy for daughter cells. Transition from the S-phase into the G2 phase is characterized by the completion of the replication process and initiation of the mitotic spindle apparatus. It is during this phase that accurate segregation of duplicated DNA is crucial in order to prevent downstream aberrations.
Parts of this apparatus include:
Spindle Pole Bodies (microtubule organizing centers): Responsible for organizing microtubules into two poles.
Microtubules: Tubelike polymer structures playing an essential role in the structure of the spindle formation as well as providing conduits to transmit information.
Microtubule Motor Proteins: Including kinesin and dynein motors: These motors are required for bipolar spindle formation, spindle positioning, metaphase spindle stability, and anaphase progression.
Microtubule-Associated Proteins: Regulates microtubule polymerization dynamics. (rescue vs catastrophe).

Each time this apparatus is assembled it goes through the following checkpoints before initiation of mitosis (final stage cell division):

  1. Spindle formation
  2. Establish correct connections between chromatids, microtubules, spindle pole bodies and motor proteins.
  3. Recognize and correct incorrect attachments
  4. Regulate microtubule dynamics

Other processes check and control DNA integrity, and only once the the integrity and structure of DNA is intact, does it signal for the mitotic spindle aparattus to initiate mitosis.

All this happens while the cell monitors nutrient availability and other stress signal in order to correctly respond to stress situations. The cell division can be shut down for repairs and if repairs are not succesful or stress sitations are too much, the cell goes into conservation mode (autophagy) or self destructs (apoptosis or necrosis), depending on the environmental signal.
All exquisitely controlled processes present in all eukaryotes.


And just as I say that, I see these have been moved here ;D All fair in my opinion. He has been given a chance to expound on this and I think it is pretty clear that the idea is not to expose us to good science.

That others saw this independently is gratifying.

Phrony, what you are doing, is lying. These good people here saw right though you. I stand vindicated. :stuck_out_tongue: