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Why aren't mitochondria and plastids considered symbiotes of eukaryotic cells?
Mitochondria and plastids have their own DNA, their own membranes, and their reproduction is not tied to the reproductive cycle of the host cell. However, they are considered to be organelles rather than a separate species in symbiosis with eukaryotes. Granted, mitochondria and plastids are incapable of living outside their parent cells, and likewise eukaryotes are incapable of surviving without the help of mitochondria and plastids. But this is also true of many other symbiotic pairs in Eukarya. So where does the distinction lie? What makes mitochondria and plastids organelles rather than separate organisms?

Something to do with the lifecycle maybe? It is an interesting question. Perhaps it is because mitochondria are inseparably tied to the host cells mitotic cycle? A bacteria in a symbiotic relationship with a plant would have a distinct lifecycle... although I'm sure there would be examples where the distinction is less clear...

In my naivety I think that Richard Dawkins has given the perfect answer in the last chapter of The Selfish Gene. It’s indeed (solely, he argues) a function of their life cycle. Mitochondria may be able to reproduce independently, but their proliferation is bound to their hosts.

I would say it has to do with the amount of mitochondrial or sequence that has been transferred to the host genome. As a consequence of all this information stored in the host genome, mitochondria cannot reproduce without the host. In this way, they are not their own organisms, but rather organelles.
Over evolutionary time, the line between organelle and intracellular endosymbiont gets blurry, but in their current state, mitochondria are organelles.
The same goes for for plastids, in general.

I agree with this answer. Symbionts are distinguished as separate complete organisms in some stage, despite their need of other to survive.

Ninety percent of a mitochondrium's proteins are coded in the nucleus.


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Does Amphibian embryo's blastocoel become a primitive yolk sac without yolk?
The mammalian blastocoel becomes yolk sac without yolk according to my professor. I have not found any evidence that such a thing happens in amphibians like frog.
I need to be able to compare and contrast cleavage and formation of blastula in amphibians and in humans.
My thoughts raised another question.
My friend says that blastula exists only when blastocoel exists.
2. Is the thing without blastocoel but with yolk sac the blastula?

Amphibians are produced externally so they do not get proteins and ATP from the mother during their maturation and differentiation. This means that they must have some way to get those things to protect themselves and survive.
The way that they get these things is yolk. Amphibians start to have yolk-filled endoderm during blastulation, [page 9, Gilbert, Developmental Biology].
I am considering the frog here as an example of amphibian. To know that things need energy to survive and that they must get it somewhere, you can deduce this solution. So nutrition and external "hatching" or development outside of female is the key here.
The overall answer to the question:
The organism must have a yolk sac, since it has yolk.
The second question seems to be an idealized one.
Without blastocoele but with yolk-sac suggests me that the blastocoel has developed already to yolk-sac. If that is the case, then I would call the thing gastrula, since for instance some species' ectoderm develops into yolk-sac. I assume that the question refers with "yolk-sac" to complete yolk-sac, not to the developing one during gastrulation.
If it is about developing yolk-sac, I would say that the cell is still blastula but is developing to gastrula. The yolk sac is not ready until gastrulation is complete.

I'm not overly convinced about getting ATP from yolk.  Perhaps glucose or other respiratory substrate but cellular metabolism is still internal?

@RoryM You are correct. I am not either overly convinced about getting all of the ATP from yolk, probably some - do not know, need to verify. There must be glucose around to get it the most of ATP. Cellular metabolism should be internal, since no mother around, but do not know about possible bacteria or other culture helping the thing. - Need to verify.

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Synthetic biology using existing cells
I was watching the video at this link:
http://www.bbc.co.uk/news/science-environment-17436365
The speaker says that a cell is taken and its original DNA content is stripped out and replaced with synthetic DNA.
Does this mean scientists are not able to create a synthetic cell yet? Is this why they use existing cells, stripping them out and replacing the DNA?

Related question?  http://biology.stackexchange.com/questions/406/can-scientists-create-totally-synthetic-life/407#407

The J. Craig Venter Institute recently has indeed created a synthetic, self-replicating cell (see the press release). So it's definitely not impossible to create completely synthetic cells for use in synthetic biology, but that doesn't mean it makes much sense to do so. E. coli in particular have been used as bench tools for decades: lots of protocols exist for using them in the lab, their genome has been extensively sequenced and is well studied, and they're cheap. I'm not a bench biologist anymore, but I'm guessing these are the reasons they stripped living bacteria and replaced their DNA rather than trying to build a completely synthetic microbe from scratch.

@leonardo Good point. I guess there is some room for debate as to how truly synthetic the JCVI microbes are.

May also find V.natriegens interesting. It's not as well documented as E.coli but makes for a good teaching subject because of its rapid growth (Td ~ 10min).

There is this guy, Martin Hanczyc, working on protocells to better understand how the beginning of life occurred. He makes synthetic protocells. They don't have any DNA in them but they are pretty cool and maybe the beginnings to making synthetic cells. Perhaps once science has figured out how cells began and their very minimal needs they can create completely synthetic cells.
http://www.ted.com/talks/martin_hanczyc_the_line_between_life_and_not_life.html
Also, just thinking, what would we consider completely synthetic cells? If we took synthetic protocells and they eventually evolved into a cell with DNA would that still be synthetic?

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What is a coupled reaction and why do cells couple reactions?
I was wondering what exactly a coupled reaction is and why cells couple them.  I read the wikipedia article as well as several others, such as life.illinois.edu but I still don't get it.  Could someone explain it to me?

Think of this: would you rather take a can of fuel and burn it or take a can of fuel, put it in a car and let it burn (in a controlled way) in there?

It's pretty simple. A reaction occurs that releases energy (like ATP losing a phosphate to become ADP + Pi). If this is uncoupled, the energy will merely turn into heat. If it is coupled, then it can be used to fuel some other process. For instance, if you couple the ATP -> ADP reaction to a certain protein, the energy can be used to modify the shape of that protein.

A reaction where the the free energy of a thermodynamically favorable transformation, such as the hydrolysis of ATP, and a thermodynamically unfavorable one, are mechanistically joined  into a new reaction (or may be envisaged to be so joined) is known as a coupled reaction.
To put it another way, two or more reactions may be combined mechanistically such that a spontaneous reaction may be made 'drive' a non-spontaneous one,   and we may speak of the combined reaction as being 'coupled' (see, for example, Silby & Alberty (2001), quoted below). The combined reaction may be catalyzed by an enzyme, in which case the 'thermodynamic push' is provided by the coupling agent (such as ATP) and the 'kinetic push' is provided by the enzyme.
We need to take into account a very important point. As pointed out by Atkinson (1977),  the coupled reaction is a different reaction to the reaction we are trying to 'drive', with different overall stoichiometry and hence a different overall equilibrium constant (Atkinson, 1977, p52).
A coupled reaction does not "push a reaction past its equilibrium" (see Atkinson, 1977, p52). No enzyme, for example, can push any reaction past its position of equilibrium. This is forbidden by the second law. (If your favourite kinetic mechanism does not obey the second law there is, as Eddington put it, "no hope"). An enzyme (or enzymes) can however, cause a reaction to proceed further than it normally would by catalyzing a different reaction (or series of reactions).
Perhaps (in lysine biosynthesis from aspartate), nature requires the the (NADH-linked) reduction of a carboxylic acid to an aldehyde, a reaction normally considered  irreversible. And lets spell this one out: the equilibrium constant for a reaction such as the following:
        NADH + carboxylic acid = NAD+ + aldehyde        (1)
greatly favors aldehyde dehydrogenation so much so that the left-to-right transformation has never (to the best of my knowledge) been demonstrated (more on this below).
Lets first phosphorylate the carboxylic acid using ATP as coupling agent to give aspartyl-phosphate (aspartate kinase):
         aspartate + ATP = aspartate-4-phosphate + ADP        (2)
Now let's reduce the 'activated' acid (aspartate-4-phosphate) using NADPH as electron donor, where the equilibrium constant of the following reaction is  very much to the right  (aspartate semialdehyde dehydrogenase):
  aspartate-4-phosphate + NADPH + H+ ⇌ L-aspartate 4-semialdehyde + Pi + NADP+
So we have got our product (the aldehyde) from our 'starting material' (the carboxylic acid), but at the 'expense' (as we would see it) of  ATP hydrolysis.
We may think of the above reactions as being 'mechanistially coupled' by the formation of aspartyl-phosphate such that the overall equilibrium constant for the following reaction is much more favourable than that of Eqn (1)
  aspartate + ATP + NADPH + H+ ⇌ L-aspartate 4-semialdehyde + Pi + NADP+
Or, perhaps in more abstract terms, the coupled reaction may be represented as folows:
  carboxylic acid + ATP + NADPH + H+ ⇌  aldeyde + Pi + NADP+
The reduction of a carboxylic acid to an aldehyde has been given a thermodynamic 'push' by the coupling agent  (and a kinetic 'push' by the enzymes).
Before we move on to some specific examples let's consider three further points.
(i) What makes ATP a good coupling agent? To again quote Atkinson (1977, p48), a good coupling agent has two requirements: firstly, it must be thermodynamically unstable. That is, it must be "far from equilibrium in terms of some useful conversion" (Atkinson, 1977, p48). The hydrolysis of ATP nicely fills this criterion. Secondly, a good coupling agent must be kinetically stable. Again ATP 'fits the bill': solutions of ATP in water are stable (Atkinson, 1977, p48).
ATP (-39.7 kJ/mol), of course, is not the only useful coupling agent, or even the 'best' one. phosphoenol-pyruvate (-61.9 kJ/mol) , creatine-phosphate (-43.5 kJ/mol)  and acetyl-phosphate (-43.1 kJ/mol) are others. The figures in brackets refer to free energy of hydrolysis and are taken from Silby and Alberty (2001, p 282).
(ii) The coupled reaction need not involve direct hydrolysis of coupling agent. Any reaction in which ATP is converted to ADP has received a 'thermodynamic push equivalent to the free energy of hydrolysis of ATP' (Atkinson, 1977, p49). In essence, the concept of a coupled reaction is an abstraction, created by us for our convenience.
(iii) To state the obvious, a coupled reaction is exactly that: coupled.  The coupling may be 'chemical', as in many of the examples below, or may be conformational (as in ATP synthase), but there must be in some sense a mechanistic joining into a new (real) reaction. Two reactions occurring in isolation, even if one is ATP hydrolysis, are not coupled.
Specific Examples
An example of a coupled reaction is the  glyceraldehyde-3-phosphate dehydrogenase (EC 1.2.1.12; GAPDH) reaction [see here] .
 Glyceraldehyde-3-phosphate + NAD+ + Pi → 1,3-diPhosphoGlycerate + NADH + H+
We can think of this reaction in terms of two separate reactions which are coupled mechanistically by the enzyme. (i) The NAD+ linked oxidation of an aldehyde to a carboxylic acid (the aldehyde dehydrogenase reaction) and (ii) the phosphorylation of a carboxylic acid. (Like ATP, a phosphorylated carboxylic acid may be considered a 'high energy' compound, that is one where the equilibrium for hydrolysis lies very much to the left in reaction 2 below).
Reaction 1
 RCHO + NAD+ + H2O → RCOOH + NADH + H+
Reaction 2 (Pi is inorganic phosphate).
 RCOOH + Pi → RC(=O)(O-Pi) + H2O
As stated above, the NAD+-linked oxidation of an aldehyde (reaction 1) is practically irreversible. That is, at equilibrium it has proceeded almost totally to the right. As stated above, the position of equilibrium of reaction 2 lies very much to the left.
How can one 'drive' the formation of a phosphorylated carboxylic acid by coupling it to the (spontaneous) NAD+-linked oxidation of an aldehyde?
A simplified version of the GAPDH reaction is as follows (a more complete mechanism, supported by a lot of experimental evidence, may be found in Fersht (1999), which I quote below).
Step 1.  Formation on an enzyme-linked thiohemiacetal.
 E-SH + RCHO → E-S-C(R)(H)(OH)
A sulphydryl on the enzyme (part of a Cys residue) reacts with the aldehyde group on the substrate to give a thiohemiacetal.  (In the representation above, groups in brackets are all connected to a single (tetrahedral) carbon atom).
Step 2. The thiohemiacetal is oxidized by enzyme-bound NAD+ to a thiol-ester (the key step).
 E-S-C(R)(H)(OH) + NAD+ → E-S-C(=O)(R) + NADH + H+
This (enzyme-bound) thiol-ester is a 'high energy' intermediate wherein, it may be envisaged, the free energy of aldehyde oxidation has been 'trapped'.
The final step of the GAPDH reaction is now spontaneous (proceeds to the right).
Step 3. Attack on the thiol-ester by inorganic phosphate (Pi is inorganic phosphate)
E-S-C(=O)(R) + Pi → E-SH + R-C(=O)(O-Pi)
Thus, the free energy of NAD+-linked aldehyde oxidation has been 'sequestered' and used to 'drive' the thermodynamically unfavourable phosphorylation of a carboxylic acid, by coupling the two reactions via a ('high energy') thiol-ester: the coupled reaction is a different reaction.
The 'thermodynamic price' is that the GAPDH reaction (unlike NAD+-linked aldehyde oxidation) is freely reversible: the coupled reaction has a different overall equilibrium constant.
As stated above, this is a simplified version of the GAPDH reaction.  The (tetrameric) enzyme contains a tightly bound NAD+ for a start, and this needs to be taken account of.  A fuller account may be found in the following reference:

Fersht, Alan. (1999) Structure and Mechanism in Protein Science, pp 469 - 471, W.H. Freeman & Co.

For a fuller treatment of coupled biochemical reactions, see

Silbey, R.J. & Alberty, R.A. (2001) Physical Chemistry (3rd Edn) pp 281 - 283.
Atkinson, D. E. (1977) Cellular Energy Metabolism and Its Regulation.
Academic Press, New York

Pyruvate kinase (EC 2.7.1.40) [see here] is another great example of a coupled biochemical reaction.  In this case the reaction is almost irreversible in the direction of ATP synthesis!
The standard transformed free energy (ΔGo') for the hydrolysis of phosphoenol-pyruvate (PEP) to pyruvate and phosphate is ~ - 62 kJ/mol.  This represents an equilibrium constant of about 1010 in favour of hydrolysis! (see Walsh, quoted below, pp 229-230).
For comparison,  ΔGo' for ATP + H2O → ADP + Pi is about - 40 kJ/mol.
Thus the pyruvate kinase reaction may be viewed as a coupled biochemical reaction where the free energy of PEP hydrolysis is coupled to (almost irreversible) ATP synthesis.
Why does PEP have such a large negative ΔGo'? The enol form of pyruvate does not exist in appreciable quantites in aqueous solution at pH 7 (Pocker et al., 1969; Damitio et al., 1992).  PEP may be considered a 'trapped' form of a thermodynamically unstable enol which is released upon hydrolysis, thus 'pulling' the equilibrium to the right. (see Walsh, quoted below, p 230, for a more thorough explanation).
Personally, I have always considered the reaction catalyzed by PK to be pretty amazing.
Edit
In response to this question on the standard free energy of hydrolysis of phosphoenolpyruvate (PEP), I'll add the following.
The thermodynamically stable form of PEP in solution at 'physiological' pH is the enol form.  That is, the enol from predominates.
PEP hydrolysis may be formally divided  into two parts:
(i) the hydrolysis of the phosphate ester to give the enol form of pyruvate,
followed by (ii) tautomerization to the (thermodynamically stable)  keto form of pyruvate (Chiang et al., 1992).
Thus it is the enol form of PEP that predominates in aqueous solution at pH 7, but pyruvate exists predominately in the keto form under similar conditions.
In their in-depth study, Chiang and co-workers attribute 47% of
the free energy liberated by  the hydrolysis PEP to the ketonization of the enol form of pyruvate, and
conclude that "nearly half of the high energy content of this molecule resides in its masked  enol function" (And of course, they mean 'high energy' in the Lipmann ('squiggle') sense, that is PEP has a high standard free energy of hydrolysis).
We need to be careful with the following and acknowledge that the language is somewhat loose: we may
think of PEP as a molecule where the thermodynamically unstable form of pyruvate (the enol form)
is 'trapped' in a (thermodynamically stable) phosphate-ester linkage, which will be 'released' on hydrolysis. And to emphasize, the thermodynamically stable form of PEP is the enol form.
IMO, Chiang et al. (1992) is a very nice paper that rigorously backs up conclusions with strong experimental evidence, but it is surprising that they did not quote Walsh
 who (again, IMO) is the first to give the correct explanation?
References

Chiang,Y., Kresge, A. J. & Pruszynski, P. (1992) Keto-Enol Equilibria in the Pyruvic Acid System: Determination of the
Keto-Enol Equilibrium Constants of Pyruvic Acid and Pyruvate and the
Acidity Constant of Pyruvate Enol in Aqueous Solution  J. Am. Chem. Soc. 114, 3103-3107
Damitio, J.,  Smith , G.,  Meany , J. E.,  Pocker, Y. (1992).  A comparative study of the enolization of pyruvate and the reversible dehydration of pyruvate hydrate
J. Am. Chem. Soc.,  114, 3081–3087
Lipmann, F. (1941). Metabolic generation and utilization of phosphate bond energy.  Adv. Enzymol. 1, 99 - 162.
Pocker, Y., Meany, J. E., Nist, B. J., &  Zadorojny, C.  (1969) The Reversible Hydration of Pyruvic Acid. I. Equilibrium Studies.  J. Phys. Chem.
76, 2879 – 2882.
Walsh, C. (1979) Enzymatic Reaction Mechanisms.  W.H. Freeman & Co.

Oxidative Phosphorylation

Perhaps the most important coupled reaction is that which occurs in oxidative phosphorylation where the oxidation of  fuels via the respiratory redox chain is coupled to  the  'synthesis' of ATP.
I have 'steered clear' up to this point, as it is a very complex area and difficult to do justice to in a few lines.
In the chemiosmotic theory of oxidative phosphorylation (due primarily to Peter Mitchell)  electron transport via the respiratory chain to molecular oxygen creates a proton  gradient across the inner mitochondrial membrane by pumping protons outwards. This proton gradient, or protonmotive force, is used to 'drive' the following  reaction to the right:
ADP + Pi ⇌  ATP + H2O
This is commonly referred to as 'ATP synthesis' but, more correctly perhaps, it  maintains our coupling agent  "far from equilibrium in terms of some useful conversion" (Atkinson, 1977, p48), that is far from equilibrium in the hydrolysis of ATP.
Although all of oxidative phosphorylation may be considered a coupled reaction, all that will be (very briefly) looked at here is the reaction catalyzed by ATP synthase, which may be considered to catalyze the following coupled reaction.
 ADP + Pi + H+(Out) ⇌ ATP + H2O + H+(In)
This is an example of vectorial catalysis, but it is much more. The ATP synthetase has been described as a "splendid molecular machine" (Boyer, 1997b).

It is an example of sequential, cooperative catalysis between 3 active sites where the the release of products (ATP) at one site is dependent on binding of substrates (ADP and Pi ) at another.
It is an example of indirect conformational coupling where the proton gradient effects the release of of tightly bound ATP by eliciting sequential conformational changes in all active sites .
It is an example of a binding-change mechanism, where the proton gradient is responsible release of ATP from the enzyme, but plays no role in its synthesis.
Perhaps most dramatically,  it is an example of rotational catalysis, where the indirect rotation of a protein subunit brings about the sequential conformational  changes in the active sites.

Much of the mechanism of ATP synthetase is due to Boyer: this includes the prediction of rotational catalysis and the formulation (and defense) of the binding-change mechanism (see Boyer, 1997a,b). For some nice dynamic diagrams on the mechanism of action, see this SO answer.
Perhaps the most important considerations from the standpoint of the present discussion is the subtlety  of the coupling effect or 'mechanistic joining': it is brought about by a conformational change due to rotation of a protein subunit, and it is mediated though the dissociation of ATP from a subunit and not through its 'synthesis' from ADP and Pi at an active site.

[Aside] In a most famous experiment, rotary catalysis was 'physically' demonstrated by Kinoshita and  co-workers by attaching an actin filament to the rotating subunit of the enzyme and viewing under a fluorescent microscope (see here), which showed that rotation is anti-clockwise (viewing the enzyme from the 'membrane' side) when the enzyme is hydrolyzing ATP. A nice YouTube video, which seems to be base on the original Noji experiment, may be found here .
References

Abeles, R.H., Frey, P.A. & Jencks, W.P. (1992) Biochemistry.  Jones & Barlett, Publishers.
Boyer, P. D. (1997a) [Nobel Lecture] Energy, Life, and ATP (pdf available here)
Boyer, P. D. (1997b) The ATP Synthase. A splendid molecular machine Annu. Rev. Biochem.  66, 717–749
Mitchell, P. (1978) [Nobel Lecture] David Keilin's Respiratory Chain Concept and Its Chemiosmotic Consequences (pdf available here)
Walker, J. E. (1997) [Nobel Lecture] ATP Synthesis by Rotary Catalysis (pdf available  here)

A clear, comprehensive answer filled with examples. +1.

The answer was automatically converted to CW because you edited it more than 10 times. This is meant to discourage trivial edits to bump the question. I reverted CW in this case, as most edits were substantial.

In a coupled reaction energy required by 1 process is supplied by another process. For example: glucose + phosphate becomes glucose.6.phosphate. This is an endergonic reaction and the energy is supplied to this reaction by another reaction which has to be exergonic reaction i.e. ATP which can become ADP+energy.

Coupling process by which two or more chemical reactions depend on each other through energy once one is exothermic another is endothermic, one produce product or intermediate which is used by the another
Examples glycolysis and citric acid cycle , phosphorylation and dephosphorylation in steps of glycolysis and many other

Welcome to BiologySE! Please elaborate your answer a little bit (explain terms, format the text appropriately for reading, maybe some images?) and provide references for your claims and to give access for further reading sources to interested people.


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How do proteins and genes participate in learning?
I am a computer scientist that studies biology and bioinformatics.
In the last weeks, I have been trying to study new research directions, and I would like to deepen my knowledge on the role and behavior of genes and proteins in learning.
By learning, I mean the human process: the information I is absent at time T, and present at time T+1.
I would like to study more this problem, and I am wondering: how do proteins and genes behave during learning?
I have read that proteins that participate in learning are called marker proteins. Is it true? Which role do they have?
Where could I find some resources to study this fascinating problem?
Thank you very much!

The storage of memories in cells is rarely thought of on the protein level of the cell.  Cells are usually given a developmental state, but no memory.  A cell may become a liver cell, cancerous, or diabetic, but this is not memory, but a physiological change in the cell which is usually not reversible to a previous state.
For example cancer treatments are entirely focused on identifying the cancerous cells and killing them.   Internally the genomes of cancer cells often have deletions and duplications.  They are cancerous, they have not learned to be cancerous. Though not as dramatic, it is now thought that cellular differentiation which creates different types of cells is heavily influenced by epigenetic modification of the genome; the DNA is marked by methyl groups which dictates the state of the cell by modifying the gene.  This is mediated by proteins for sure, but is quite complex and not well understood at this time. Epigenetic markers can even change gene behavior between generations of offspring as well, though that is not usually called memory.
How is information stored in the brain?  This is thought to be reflected in the organization of the neurons in the brain.  There are many kinds of neurons.  They can be distinguished by the sorts of axons and dendrites that emanate from the cell body.  They can also be distinguished by the chemical variety of neurotransmitter they use (there are a score of different molecules).  So to a great extent the type of cell and the specific proteins it chooses to use to mediate information is very important.
That being said, information is currently thought to highly related to the placement of the axons and dendrites connecting the neuron to sometimes scores of other cells, sometimes touching the cell body, other times other dendrites or neurons.  As neural activity ensues, the cells will reconfigure their connections by physically moving them.
More recently, investigators have tried to understand the genes which internally modulate the neural signals within the cells.  This nobel prize lecture discusses how the CREB/MAPK pathway can modulate Long Term Potentiation - the shape of the neuron response to a signal over time (days or hours).
Taken as a whole, you can see that memory is likely to be stored on several levels at once - the kinds of cells (dictated by differentiation) involved, structural arrangement of the neurons (axons and dendrites connecting to various cells and places on cells), as well as internal signaling circuitry that generates and modulate the electrical and chemical activity within the cell.
"Marker protein" only refers to a protein that you can follow to see some sort of activity in the cell. A typical example is Green Fluorescent Protein, which is colored, fused with a protein of interest.  It has no specific meaning regarding learning I think.

Thanx, interestin' answer. Could you indicate to me some online resources to deepen these themes?

I would choose just one of these angles to take up first.  Here's an online MIT class on learning and neuroscience http://ocw.mit.edu/courses/brain-and-cognitive-sciences/9-03-neural-basis-of-learning-and-memory-fall-2007/

Right now the neurophysiology of memories and feelings are hot and doing big things.  Here is a blog post on erasing a fear memory in a mouse. http://cellularscale.blogspot.com/2012/04/erasing-memories-cell-by-cell.html

Thanks again. May contact you privately for further detail discussion? Here's my address davide.chicco(AT)gmail.com

If you're interested in understanding the maintenance of state, history, and information, I would look at hysteresis. The classic biophysics model for studying hysteresis has been the Lambda phage which has been extensively detailed in Mark Ptashne's A Genetic Switch


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Bicoid regulation of hunchback
I'm learning about development via the example of Drosophila embryogenesis. I understand that bicoid regulates hunchback, among other genes. My question whether the regulation is direct or indirect? In other words, does the level of bicoid directly govern the expression of hunchback, or are there steps in between?

These two papers[1] [2] argue that bcd is a direct activator of hb, although be aware that this does not rule out downstream events feeding back to further activate  hb. (In fact, given the complexity of the embryonic gene network, it is likely that both mechanisms have a role.)

Struhl G, Struhl K, Macdonald PM. 1989. The gradient morphogen bicoid is a concentration-dependent transcriptional activator. Cell, 57(7): 1259-1273, doi:10.1016/0092-8674(89)90062-7.
Driever W, Nüsslein-Volhard C. 1989. The bicoid protin is a positive regulator of hunchback transcription in the early Drosophila embryo. Nature, 337: 138-143.


text:
In the vacuum of space would death be instantaneous?
I was arguing with my colleague about this matter (I'm not going to mention which side I fall on).
Would death be immediate in the vacuum of space? For example, if I was suddenly teleported into the vacuum of space would I die straight away? Or would I experience a suffocating sensation?

Sounds like a perfect candidate for http://what-if.xkcd.com/! :)

Please see skeptics for an answer: http://skeptics.stackexchange.com/questions/8521/would-a-humans-blood-suddenly-boil-or-eyes-body-explode-in-a-vacuum

Nope, you wouldn't die instantly. While explosive decompression has never been tested on humans (for obvious reasons), the dangers of a vacuum have mostly to do with the pressure differential between your body and the now pressure-less void around you. The most fragile parts of the biological system would be the lungs and ears, and the instantaneous transportation would cause a severe case of the Bends if you were rescued quickly enough. You would pass out within a few seconds stated by NASA when an experiment went awry, and death might be from lack of oxygen to the brain, although after a few minutes everything bad starts to happen so nobody really knows what you would die of:

At NASA's Manned Spacecraft Center (now renamed Johnson Space Center) we had a test subject accidentally exposed to a near vacuum (less than 1 psi) in an incident involving a leaking space suit in a vacuum chamber back in '65. He remained conscious for about 14 seconds, which is about the time it takes for O2 deprived blood to go from the lungs to the brain. The suit probably did not reach a hard vacuum, and we began repressurizing the chamber within 15 seconds. The subject regained consciousness at around 15,000 feet equivalent altitude. The subject later reported that he could feel and hear the air leaking out, and his last conscious memory was of the water on his tongue beginning to boil.

"While explosive decompression has never been tested on humans..." Love it!

not until somebody does the test with a chimp first

Not tested under controlled conditions, but there was the Byford Dolphin diving bell accident - 9 atm to 1 in under a second, four souls lost.

If an astronaut were teleported into space without her spacesuit/helmet, she would feel a suffocation feeling, likely making breathing motions even though there is no air to breathe.  She would also feel her sweat, saliva, tears, mucous, and any other water on her body boil off, though her body would maintain blood pressure, at least until her heart stopped. She would be unconscious within 15-20 seconds and dead within 90-120 seconds.

Please provide some references to support your answer.

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Is Aspergillus clavatus an unicellular organism?
I could not find the piece of information form Burton Human Parasitology -book and not by Google.
Yeast is divided to two phylums: one of them is Ascomycota.
Aspergillus clavatus belong to the given phylum.
Yeast is unicellular.
So it is possible that Aspergillus clavatus is unicellular.
Can you tell whether the Aspergillus clavatus is an unicellular orgarism or not from the following picture?

I need to find unicellular parasites that cause damage of brain. The fungus causes patulin so hemorrhaging of brain, but should still be unicellular to meet the criteria.

You're right in saying that yeast is single celled.
However, moulds are described to be filamentous fungi that are multicellular. The filaments of the mould give colonies "a woolly, fluffy, or velvety appearance, sometimes punctuated with a granular or powdery aspect that is produced by the formation of asexual reproductive structures"(1).
Aspergillus is such a species. The filaments are called hyphae. In Aspergillus, hyphae have divisions or walls which separate it into multiple cells. This is called septate hyphae.

McPherson, et al. Henry's Clinical Diagnosis and Management by Laboratory Methods. 22nd ed. 2011. Saunders.


text:
What role does a protein's size have on protein-protein interactions?
Protein-protein interactions are when two or more proteins bind together, possibly for some important biological function.  Recently, I'm starting to look more into proteins, and in particular, networks related to proteins, such as protein-protein interaction networks.  I found myself thinking about the following question:

Question:  Does the relative size of two proteins significantly affect how likely they are to interact?  Does it affect how they interact?

It would be plausible for me to download a protein-protein interaction network, and calculate their relative size from the proteins' PDB files.  However, I predict that the results from such a computation would not offer much insight into why (or why not) the protein sizes affect binding.

Do you mean size in 3D space or mass?

I meant in 3D space, although, now that you mention it, it would also be interesting to consider mass instead.

Protein interactions occur mostly (if not all) through residues that are on the "surface" and exposed to the milieu in which they exist, be it cytoplasmic or extracellular. So, a naive thought would be to guess that a greater surface area means a greater swathe of exposed regions and probable interacting parts. One protein can bind many others, even simultaneously, through different such interaction surfaces. However, other factors also determine whether a given set of two proteins interact, most important being where they localize in a given cell. If one protein is nuclear but the other on the plasma membrane, it is highly unlikely that they ever interact even if thermodynamics highly favors complex formation. Interaction between two proteins also depends on their respective conformations, which can further be regulated by events such as post translational modifications (eg., phosphorylation by a kinase), bound nucleotide state (eg., GTP vs GDP in a G protein). Last, scaffolds can also sequester and organize protein clusters together spatially and increase the probability of them interacting. All put together, I think it is highly unlikely that just looking at 3D surface area of a protein will say much about its "interactability" with other proteins.

@gkadam is correct and quite exhaustive. There are a lot of things that can affect protein binding, and many of them have little to do with the protein itself, but instead where it is and what else it is doing.
All other things being equal, smaller proteins will form networks more quickly than larger ones for kinetic reasons.
Size differences don't affect how likely two proteins are to interact by itself. Big proteins and little ones interact all the time.

Sir what are the things that effect protein binding? Is there an exhaustive list of it??

If there is it would be a medium size textbook. pH, temperature, saltiness, conformational changes, adaptor molecules, and the identity of the proteins are the big contributors, but there are many many more.


text:
Is there a way to see what representations are currently displayed in PyMOL?
I am using PyMol to visualize .pdb protein structures.
I show/hide representation a lot, and sometimes I get confused with what representations are currently displayed. So I end up with doing a lot of hides (basically trying to hide each representation).
Is there a command which shows me what representations are currently used.
For instance if I have used
show ribbon
show lines
show mesh
hide lines

and than use some sort of showRepresentation
it will return me ribbon, mesh

If you do that via the context menu on the sidebar, there is an option "show as" that will remove the previous representations and only show the new one.

You can use "as" to switch to a particular style (http://pymolwiki.org/index.php/As
):
as cartooon, 11AS and chain a

You can also hide everything, to remove all representations (http://pymolwiki.org/index.php/Hide):
hide every, 11AS and not (n. ca+c+n and resi 5-10)

I'm a fairly expert user of PyMOL and I've never seen an API exposed which will show you what representations are being used. That's not to say that it doesn't exist, there are a variety of undocumented features and commands still.
The problem is it isn't as simple as ribbon,mesh.  Every single atom can be displaying any combination of representations, so as an API call or command, it would have to return the status of every atom in your selection. If the displayed representations are exposed somewhere they're probably in a very low level format like that, and not of use unless you're a programmer.


text:
Is "computational biology" different from "bioinformatics"?
Are "computational biology" and "bioinformatics" simply different terms for the same thing or is there a real difference?

Probably better to ask them directly :) http://www.biostars.org/
Actually there are few questions going into that direction already: http://www.biostars.org/search/?q=computational+biology

Thank you! I'm glad that someone recognizes that there is a difference http://meta.biology.stackexchange.com/a/169/389

@Chirag And between the answers and comments, we're lucky enough to have 4 alternative definitions for everyone to choose from!

@bobthejoe I don't think anyone has suggested there is no differences, but getting the community to agree on exactly what those differences are is an exercise in futility.

@Chirag Why did you roll back Daniel's edit, it was a more grammatically correct version?

@jonsca The idea is to ask not just what is the difference but also to ask whether the is a difference in first place...

@jonsca I made it unambiguous :)

@Chirag It was more the sentence structure I was taking issue with, which wasn't that big of a deal, I was more curious as to why you decided to roll it back.  The "biology" versus "chemistry" issue wasn't as bothersome.  Anyway, I think it's fine now.  One of your answers still uses the term "computational biology", but I think it all still makes sense.

Wait...when did this question become about chemistry?

@DanielStandage replaced biology with chemistry by mistake... my bad.

I found this post by Russ Altman quite good.  Below is his opinion about the two similar but distinct fields:

Computational biology: the study of biology using computational
  techniques.  The goal is to learn new biology, knowledge about living
  sytems.  It is about science.
Bioinformatics: the creation of tools (algorithms, databases) that
  solve problems.  The goal is to build useful tools that work on
  biological data.  It is about engineering.

Just as a note:
This is just one persons opinion and I have heard many other definitions for both of these terms.  For example, one person I know mentioned that he believes computational biology is concerned with very theoretical research such as NP-hardness (ie. articles published in the Journal of Computational Biology). Other people think that bioinformatics is an applied field that is essentially using already published tools.

This is perhaps the most closest you can ever get to the definition of this field. :)

As informative as this answer is, keep in mind that many (talented) scientists will disagree, or at least have a slightly different answer.

Would bioinformatics not be more about the use of tools to solve statistical problems than the creation of such tools?

I don’t think this definition is commonly agreed on. Where we work, most people are self-proclaimed bioinformaticians (heck, we even have it in the institute’s name) but according to this answer they’d be classified as computational biologists. They may also do the latter (because the topics are usually intrinsically linked) but the focus is definitely biological study, not development of tools.

@KonradRudolph: Again the goal of my answer was not to give a concrete definition hence why I gave an additional note showing other people have varying opinions on what they are.  The definitions are going to be very institute / lab specific depending on what their research topics and goals are.

I think this question is on topic here, although yes you would definitely get a lot of answers  at BioStars. But consider this from the bioinformatics tag wiki on this site.

Bioinformatics is a broad field that interfaces a variety of life
  science disciplines (biology, genetics, biochemistry, biophysics, etc)
  with a variety of quantitative sciences (mathematics, statistics,
  computer science, engineering, etc). Bioinformatics techniques
  typically involve developing and applying software and algorithms to
  computationally intensive biological questions, such as those common
  in structural biology, genomics, sequence analysis, and systems
  biology.
Some scientists draw a distinction between the term bioinformatics and
  computational biology. While these areas indeed broad and diverse,
  these distinctions in terms are not consistent or well-defined.

Case in point: @GWW's answer cites two different definitions, while another has already been suggested in response to his answer (as a comment). More definitions are sure to come from additional answers, comments, and edits. None of these definitions are necessarily wrong, but in the same way none are "right" as there is no objective way to determine which of the definitions is "better" than the others. If you were to ask 5 experts in the field, you are likely to get 5 different definitions.

There must be an option to choose multiple answers :)

@Chirag Well, unfortunately there are many "good" answers to this question...which is kind of the point.

+1 but I shall contest that the formation of that tag was contested (by myself) http://meta.biology.stackexchange.com/q/168/389

Computational Biology - usually involves creating a model (software or other logic) where you attempt to shed light on some process of biology by building information flows using known physics/chemistry/biology --- (how to cells divide ? -> build a biomechanic model of mitotic spindles ...) --- You are building up complexity in your model to simulate biology to ever increasing levels of accuracy
Bioinformatics --> measure biology then analyze the data --- biology already has the complexity --- You are attempting to understand this complexity by identifying patterns in measurement data
Both of these fields drive research efforts to create better sensors used to measure biological processing

I think there is no general agreement on what is computational biology and what is bioinformatics, so the answers are bound to vary, depending on the field and the background of the person. Let me list a few options:
They are the same
There is a good reason to think that these terms are used interchangeably, particularly in the academic environment. Moreover, while the two terms co-exist in English, in some other languages/countries only one of them exists, used to convey both meanings: e.g., in French one can say bioinformatique/bioinformaticien(ne), but there is no translation for computational biology.
Computational biology is a method, bioinformatics is a tool
Some people, more prone to treating the figures of language literally, would say that computational biology is about mathematical approach to biology, whereas bioinformatics is doing these computations in a computer. This approach seems to lack nuance and broad knwoledge, but it is surprisingly common even among the experts.
Bioinformatics is about sequencing
If one looks for a job outside of academia, bioinformatician in a job description usually means somebody who can process sequencing data, i.e., trim, clean, assemble/map genomes, calculate the differential expression, etc. Biostatistician usually describes someone involved in experiment/study design and the subsequent data processing. Computational biologist occasionally surfaces as a term in job descriptions coming from big research labs, meaning that the job description is rather vague - these are usually R&D jobs.
These are two broad and overlapping domains of knwoledge
As I mentioned in the beginning, people working in a narrow domain would tend to equate the two terms. However the range of computational disciplines related to biology is very broad: some of them are more naturally associated with bioinformatics than the others. The following list is definitely incomplete, but should give the idea:

Processing and analyzing sequencing data
Protein and RNA structure modeling
Biostatistics (study design, analysis of non-sequencing data, etc.)
Population genetics
Epidemiology
Mathematical ecology

To summarize: there is no definitive answer to the question, but there is a lot to learn by exploring it.


text:
How are proteins formed?
Somewhere, I have read that we need to consume proteins to make amino acids to make new proteins. What does it suggest? How do we make proteins from proteins?

I suggest you have a read of the articles on protein and protein metabolism on Wikipedia :) (http://en.wikipedia.org/wiki/Protein_metabolism) This is a really broad topic and it's best if you study it up yourself.

Let me know If I'm right with the phrase "proteins that we consume form new proteins that are different". I'm looking for a simple explanation.

Essentially, yes, "proteins that we consume form new proteins that are different".
The processes are each of them topics for themselves. In short, consumed proteins are digested by peptidases (enzymes) in the stomach, breaking them down into their consituent amino acids. These are absorbed in the gut and transported in the blood to all cells. These take up amino acids and attach them to tRNA molecules which are used in translation to form new body proteins.

Very elegantly worded.

You ingest daily dietary protein which your body hydrolyzes to get all the building blocks for other proteins (amino acids).
Also, from diet you can get essential amino acids that cannot be synthesized de novo by the organism which is more economical than amino acid synthesis. Other amino acids can be constructed by metabolic processes.


text:
Can the third sex be categorized as Male or Female?
Hijra are people who have a penis (not sure if sexually active) but look much like a female (perhaps for some feminine biological property). Wikipedia says they are "physiological males who have feminine gender identity"
Also, I just came to know there are some more types of third gender people.
Now, is there really any BIOLOGICAL third gender which cannot be categorized as male or female? Or its always possible to categorize them to male or female?

When dealing with humans, there are only two Biological genders as defined by the presence or absence of the Y-Chromosome. If the Y-Chromosome is not present, or through some process gets totally deactivated, the human will appear and function as a Female.
XX = Female
XY = Male
XXY = Male (Klinefelter's Syndrome)
XYY = Male (Aneuploidy - Normal Functioning Males)
XXX = Female (Aneuploidy - Normal Functioning Females)
X = Female (Turner's Syndrome - Generally infertile, other issues)
Y = Fatal (The Y-Chromosome is drastically smaller than the X-Chromosome, which contains many necessary genes)
XXYY = Male
...
The list goes on, since there have been records of up to XXXXX.
If there is a Y-Chromosome present, the human born will be male.
However, that is not to say that a person cannot psychologically identify as something else. It's also worth noting that the majority of known species are asexual and do not have genders, and that those which do have genders do not always follow the same rules (Fruit Flies, for instance, use the ratio of genes to determine sex).

That one is really a nice answer. I did not take biology in school (planned to be engineer) but I did know about X-Y chromosomes. However, I always thought its only XX and XY!

How do you deal with XX males without SRY gene and with infertility?

@Remi.b -- The missing SRY gene in a phenotypical male with XX chromosomes is a really interesting exception to the general rule I described above. Thanks for bringing it up in the comments! I didn't know it existed.

I think you might be confusing sex and gender. The terms are often used interchangeably, but strictly speaking, they have different biological meanings. Sex refers to the biological categorization based on genetics, reproductive organs, or similar things, whereas gender is based on social identity.
For humans, there are only two sex chromosomes, X and Y, and they determine the male and female sexes. But there are many situations that don't fall under the XX/XY categorization, and people with these conditions are usually referred to as intersex. These can include conditions such as congenital adrenal hyperplasia, androgen insensitivity syndrome, and 5-alpha-reductase deficiency. So in short, there is no biological third sex, but that doesn't mean you can always categorize a person as biologically male or female.
As you quoted, the hijira are usually physiologically male but have a different gender identity.

Yeah, I was not aware of the difference between gender and sex. But I mentioned Biological Gender which IMO implies the technical term sex as you explained. Thanks for explaining the distinction.

As I read the Wikipedia article you reference, its useful to remember that conventional chromosomal definitions of gender, the genitals are soft tissue which has many recorded morphological abnormalities.  hermaphrodites and a spectrum of tissue shapes do occur to the extent that the conventional gender identity is not acceptable.
Physiological definition of gender, despite the chromosomes do need to be medically and socially addressed.  I am not sure that all these 'intersex' people really should be grouped into a single 'third sex', but some way of recognizing their essential human rights should be out there in my opinion.

Adding to @MCM answer, there are also chromosomal crossover that might happen between non homologous. You can have some of the genes of Y chromosome going to X chromosome or elsewhere, for instance, further expanding the possibilities for different sexualities...

There is an actual third gender. That is true hermaphroditism. Some humans are true hermaphrodites. The most common cause of this? 2 eggs fusing, 1 male and 1 female before they start differentiation.
These have both male and female characteristics and so they can't be classified as either male or female.
Here is my source:
https://en.wikipedia.org/wiki/True_hermaphroditism

Do you have a source for this?

Yeah I just now added it

From your source: "There are no documented cases in which both types of gonadal tissue function."  Based on this, human "true hermaphrodites" can always be classified as either "reproductively male" or "reproductively female", never a mix.

Hermaphrodites don't occur in humans — you may be confusing this with intersexuality. 2) Eggs don't have a sex and I don't think there's ever been a record of an egg containing an Y-chromosome so this doesn't seem to make any sense. 3) if you have evidence that two egg cells have ever been observed to fuse and lead to a viable child please post it here – since even small trisomies are typically fatal or in rare cases only have severe developmental problems (e.g. Down's syndrome) the current understanding is that a triploid human is not possible.


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Why are there exactly four nucleobases in DNA?
Does someone know why DNA is composed of four nucleobases? In particular, is there an explanation for the number? Why four and not two, or eight?

this just in - two new bases added to E coli (X and Y) do reproduce. http://www.wired.com/2014/05/synthetic-dna-cells/  not clear on how much adaptation is needed to make X and Y work to code for genes.

A now deleted answer put this down to an argument based on amino-acid coding in codons but, as pointed out by Konrad Rudolph in a comment, arguments based on codons cannot be correct because the 4-base system likely pre-dates the evolution of protein translation.
So why four?
I suggest that it comes from a combination of factors which make it a 'just right' fit for RNA-based replicators: more would be bad, and less would also be bad. The four bases are able to copy with high reliability because two features combine to exclude mis-pairings: there are two size classes - meaning any purine-purine or pyrimidine-pyrimidine pairing results in incorrect separation between the strands, excluding A-G and C-U bonds; and there are two classes based on number of OH-bonds - which limits the potential for A-C and G-U bonds. More bases must, inevitably, weaken the strength of these exclusionary approaches and increase the number of mispairings. RNA world replicators will have lacked the sophisticated repair and error checking mechanisms of modern lifeforms so this increase in mispairings would likely not be corrected.
Of course, a two base system would be even more capable of reducing errors. I suggest that the advantage of the four base system is that it allows for much more complex 3-dimensional structure to form in RNA and thus enabled a broader range of catalytic capabilities. I've only considered even-numbers because only even numbered systems could use the Watson-Crick style of base pairing.
I'd also suggesting reading Eörs Szathmáry's 2003 paper on this very question.
Addendum
A group in California has just published a paper in which they successfully added a third base pair stably into DNA. I think this could shed some light on why four - you can read about it here or get the full paper here (Nature, so pay walled).

Here is a possible answer given by this paper:
http://www.ncbi.nlm.nih.gov/pubmed/16794952
or
http://www.math.unl.edu/~bdeng1/Papers/DengDNAreplication.pdf
It gives a Darwinian explanation to the question. It approaches the problem from Claude Shannon's theory for communication. It treats DNA replication conceptually and mathematically the same as a data transmission. It concludes that the system of four bases, not two, not six, replicates the most genetic information at the shortest amount of time.
The communicational analogy goes like this. If you have two data transmission systems, one can transmit, say, 1 MB per second, and the other can do 2 MB per second but cost less than twice as much. The answer is obvious you will buy the second service for a higher rate per cost. As a data service, it does not care what information you consume -- it can be spam, video, audio, etc. All that matters is the transmission rate. As for DNA replication, it is like a data transmission channel when one base is replicated a time along the mother DNA template. It too does not care whether the process is for a bacterium genome, or a plant, or an animal genome. The pay-off is in information and the cost is in time. Unlike your abiotic communication varieties, time is both the sender and the receiver of all messages of life, and different life forms or species are merely time's cell phones. So if one system can replicate more information in a unit time than another, the faster one will win the evolutionary arm race. A prey operating on a slow replicator system will not be able to compete with nor to adapt to a predator operating on a fast one.
Now because the A-T pair has only two weak hydrogen bonds but the C-G pair has three, A and T take a shorter time to complete duplication than the C and G do. Although the replication time is short in some fraction of nano second, but the time adds up quickly for genomes with base pairs in the billions. So having the C-G pair may slow down the replication, but the gain is in information. One base pair gives you 1 bit per base information. Two pairs gives you 2 bits per base information. But, having more base pairs may eventually run into a diminished return in information replication rate if the new bases take too long a time to replicate. Hence the consideration for the optimal rate of replication measured in information bits per base per time. Without information there would be no diversity, no complexity. Without replication in information there would be no life.
Using a simple transmission/replication rate calculation by Shannon you can calculate the mean rate for the AT-system, the CG-system, the ATCG-system, and for some hypothetical 6-bases, 2n-bases system whose new bases take progressively longer time to replicate. The analysis shows the ATCG-system has the optimal replication rate if the CG bases take 1.65 to 3 times longer to replicate than the AT bases. That is, a base-2 system replicates its bases faster but does not carry more information to have a higher bit rate. Likewise, a base-6 system has a greater per-base information but replicate slower on average to end up with a suboptimal bit rate.

According to a comparison from the paper, the base-4 system is about 40% faster than the  A–T only system, and 133% faster than the G–C only system. Assume life on Earth started about 4 billion years ago, then the A-T only system would set back evolution by 1 billion years, the G–C system would do so by 2.3 billion years. For a hypothetical base-6 system, it would do so by 80 million years. In other words, life is where it should be because the base-4 system is able to transmit information through the time bottleneck at the optimal  bit rate.
In conclusion, life is to replicate the most information with the shortest time, and the base-4 system does it the best. If ever there were other systems they would have lost the informatic competition to the base-4 system from the get-go. Darwin's principle works at life's most basic and most important level.
There are other explanations, all non-Darwinian. Most are based on the base's molecular structures. But these types of explanation border on circular argument -- using observations to explain themselves. They also face this catch-22 problem since there is no way to exhaust all possible bases for replication. However, such lines of exploration are fruitful regardless because more knowledge the better. But without taking information and its replication into consideration it is hard to imagine a sensible answer to the question.

Welcome to Biology SE. It would be great if you can expand your answer to include a summary of the main points. We can't count on the link being there forever.

you can edit your answer. (see the link under your post.)

Cool explanation.

"and for some hypothetical 6-bases, 2n-bases system whose new bases take progressively longer time to replicate." - This assumption seems hard to justify.

There is a chemical dimension to this question too.
If you look at the Watson-Crick Base pairs you can see that there isn't a lot of wiggle room:

The nucleotide bases have 2 or 3 hydrogen bonds.  It's probably not sterically reasonable to have 4.
That means there are only a limited number of ways the base combinations can be complimentary and also specific as they form the double helix.  Since A->T and T->A hydrogen bond patterns take up both donor-receptor combinations there is one possible 2 H-bond pairing.
There are 2 ways to configure the three hydrogen bond bases I think, so perhaps six is possible, but I'm guessing that if you expand the base pairing repetoire, one could start to lose specificity.  As it is, if you play with nucleotides enough, you can make non Watson-Crick base pairs and probably lose some of the confidence you have exact 1:1 matches between complimentary base pairings.   Wobble Base pairs in RNA and  Hoogsteen Base Pairings can already be demonstrated to allow triple helixes and non-perfect match RNA helices.

Theoreticaly from pyrimidines and purines together
they are 6 Base Pairs = 12 Bases possible...
IF the nucleobases are evolved from only pyrimidines and NOT purines
THEN they are only 2 Base Pairs = 4 pyrimidines Bases possible!!!...

The 4-bases DNA system with A-T bonds and C-G bonds is the one that evolved to be used by most living creatures on Earth, as mentioned in other answers, because it can encode a triplet table of bases for all aminoacids used, allowing for some aminoacids to have more than one triplet code. There are though slight variations of the system: even though the A-T and C-G bonds don't change, the nucleotides can be modified to mark areas of the genome in what is part of the epigenetic code. The most common modification is adding methyl and 5-hydroxymethyl molecules to the bases, although more modifications are still being discovered.

Disclaimer: I am not a biologist or a chemist or an information theorist. I just want to toss out a perspective which I've sort of pieced together from the various answers here, but which I don't really see expressed in any one answer.
Namely, I think it's easy to imagine that 4 base pairs is the result of a trade-off between having many base pairs and having few base pairs. That is, it's essentially the result of an optimization problem. There are some advantages to having more base pairs, and some advantages to having fewer base pairs, and 4 is simply the best trade-off between them. As with any optimization problem, the result is likely quite sensitive to exactly how we frame the question -- exactly what environment the 4-base-pair system evolved in, what role RNA played in life at that point, exactly how we quantify the benefits and drawbacks of various base pair systems, etc. And perhaps the 4-base-pair system initially evolved in one environment, while later rising to dominate other competing systems in a quite different environment -- in which case the question is even more complicated.
Likely, many of these modeling questions are uncertain enough at present that it's impossible to confidently "run the optimization problem" and trust the output. But probably the first step would be to try to enumerate as many as possible of the competing factors at play. Let me attempt that, with help from the previous answers here:
Reasons to prefer fewer base pairs

Fewer base pairs means fewer possible "mispairing" pathways, potentially decreasing mutation rate

Fewer base pairs also means that only the "best pairs" need be used, again potentially decreasing mutation rate.

Fewer base pairs simplifies the process of acquiring or synthesizing the base pairs in the first place.

May affect speed of transcription.

Reasons to prefer more base pairs

More information stored per unit mass / volume.

Potentially increases range of structures which can be built directly from the genetic material.

May affect speed of transcription.

I'm sure there are many other factors to consider.
It's unclear to me whether anything quantitative can be said said about these opposing forces with enough confidence to really "run the optimization" and trust the answer.
And of course, there's presumably a lot more to say about the space over which we're optimizing -- exactly which "base pairs" conceivably could be used in the first place, as other more qualified people have already addressed.

Because four is the minimum possible number. If there is no push to make a system more complex, it will never assemble.
One might then argue that a similar system could have been built only using two bases.
Fine.
Try it out.
You will miserably fail. Sure you can make a DNA strand containing adenine and thymine only. But who would be stopping guanine and cytosine from forming and joining some deoxyribose then? How would you manage information storage, preservation and transfer then?
Base pairing - no matter how complex might look - is the simplest way to safely store information at the molecular level so that it could be handled for transfer and translation somewhere else. The spatial combinations of hydrogen bonds that can be established between pyrimidine and purine derivatives are only two.
For replication purposes you need a further symmetry breaking, which leaves you with two bases, one on each strand of a DNA double helix.
Two times two is four.
P.S.: By the way, who on Earth told you that there are exactly four nucleobases in DNA? Tell them they probably forgot methylcytosine! The term "methylation" is just an excuse to avoid admitting that DNA uses five bases instead of four. Open your mind.


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If life is discovered on another planet, will it likely be classified using the current domain/kingdom/phylum system?
This may be a stupid question showing my lack of understanding of taxonomy, but I was wondering if the current classification system we use contains broad enough categories to include new life forms, if they are discovered on other planets?  Would this depend on whether or not the new organisms could be shown to be evolutionarily related (eg have DNA), or are the highest levels of organization independent of relatedness and more dependent on physical similarity?

This is actually kinda interesting, because I asked a similar question on worldbuilding (the answer was about the same).

Background
There are basically three highest taxonomic levels: bacteria, archaea and eukaryotes. Many sources distinguish only prokaryotes and eukaryotes, subdividing prokaryotes into bacteria and archaea. Other sources posit archaea as a third domain on the highest level. That's a long debate though and fortunately not the topic here.
By appearance, the dual-domain system makes more sense because archaea and bacteria look very much alike under a microscope, and can both be clearly distinguished from eukaryotes (which have membrane bound nuclei). At the same time, comparing genetic structure and the protein machinery that interacts with DNA, eukaryotes and archaea are very similar and bacteria are clearly different from both of them. This demonstrates how appearance and molecular organisation have been typical criteria for distinction between branches of the evolutionary tree.
There are, however, many features that even those three most basic branches of life share, and they are in no way simple or few in number. For example, all extant life uses DNA to store genetic information and proteins for almost all processes governing the various reactions going on at any time in a cell. However, RNA for example is able to perform both the information storing function of DNA as well as the catalytic functions of protein. This just shows how the principles behind life are not unique to the molecules in use now, and extraterrestrial "life" may work by the same principles on an entirely different molecular basis.
Extraterrestrial life
If you want to know whether life found on another planet could be fit into our current classification system, the answer would be: No, most likely it will not be classified using the current domain/kingdom/phylum system. This is because our system describes evolutionary descendency, so unless this newly found life shares some common ancestor with an organism on earth, it would have to be classified in an entirely new system. (Of course this is subjective as you may find it more likely that it does share a common ancestor [Panspermia], while I personally find it more likely that life would have evolved entirely separated on this other planet seeing as we haven't heard of any life within reasonable distance.)
However, it is possible that this new life will follow the same evolutionary rules such as natural selection, and similar evolutionary pressures may drive to evolve similar properties. It may then be possible to draw parallels to characteristics of the current classification system, especially based on molecular function, and possibly appearance (micro- and macroscopically).

I disagree. Our current classification system is based on classifying evolutionary history from a single common ancestor, not function. Function is used to assess evolutionary relationships.  Excluding panspermia, any extraterrestrial life would represent a completely unique evolutionary history and could not be classified.

Valid point, does that sound better? I have to say that this made me realise the question could stir discussion more than encouraging an objective answer, so may be a candidate for closing.

Yeah I think that captures it.  I am not sure this question is more contcontroversial than phylogeny in general :)


text:
Tool for nucleotide alignment with all nucleotide codes (e.g. R, Y, W, S, etc.)?
I have a vector sequence and would like to find the following nucleotide sequence in it.
AASYWSRA

This query sequence uses several degenerate symbols, defined as:

S = C or G (Strong)
Y = C or T (pYrimidine)
W = A or T (Weak)
R = A or G (puRine)

(See this page for a complete description of the IUPAC nucleotide codes.)
Is there a tool to align this sequence with the vector and find all the possible sites?
EDIT: I found this website but couldn't find any of the resources helpful. Maybe one of these will work but I found most of them too complicated. If you know which one will work and explain how to use it I will be grateful.

I could've sworn NCBI BLAST can do that? Have you tried it?

If you're looking for an exact match, you don't really need a complex aligner. Perl regular expressions are pretty powerful at string transformations or conditional matching of substrings. For example, to find all matches of AASYWSRA in a nucleotide sequence $seq, you can do:
@matches = $seq =~ m/AA[CG][CT][AT][CG][AG]A/g;

The [] brackets are known as Perl character classes, which allow different characters in a position.

I've never utilized the feature, but I know Vmatch allows you to define your own alphabets and symbol mappings, which should allow you to handle the IUPAC ambiguous nucleotide symbols. The default alphabet/mapping may even include these symbols.

Unfortunately, vmatch treats the letters in symbol mappings as equivalent (e.g. S = C). It does not handle that S can be C or G. The symbol mapping is intended for handling case (e.g. t = T) or to group similar amino acids.

I have used MAST to search for particular motifs in a sequence.
From the MAST intro page, it looks like you'll have to reformat your motif a little, but it should suffice for your purposes:

Motifs are represented as position-dependent scoring matrices that
  describe the score of each possible letter at each position in the
  pattern.

Here is more info on formatting, which also indicates that the alphabet you use will be interpreted correctly.


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tools to reconstruct the transcriptional regulatory circuits?
What are commonly used tools to reconstruct the transcriptional regulatory circuits that govern diverse cellular responses and what input data sets do they accept?

Inferring transcriptional / regulatory networks from empirical data is an active area of research, and to my knowledge there aren't many mature tools for this type of analysis. I see mostly mathematicians, statisticians, and engineers working on this problem, probably because of the intense quantitative theory involved. Even if mature tools do exist, I doubt they're tailored for the typical biologist--more likely, they are geared toward scientists with a more quantitative background.
That being said, I am aware of 2 or 3 pieces of software that may provide a starting point for the curious or the adventurous: AIRnet (described here), iBioSim (described by Barker's PhD thesis, currently the second hit on this Google search), and maybe Ingenuity Pathways Analysis (which requires a paid license). The only one of these tools I've even tried to use is iBioSim, and at the time (2 or so years ago) it was a very kludgy process.

I'd like to add regulonDB which is not as integrated, but has a tremendous map of the e coli regulome which would be useful for any bacterial model.
I agree with @DanielStandage that this is not a well understood and there don't even appear to be standard representations for this sort of data.

The Systems Biology Markup Language (SBML) is the closest thing to a standard representation out there, but it's been adopted about as widely as every other XML-based bioinformatics format I've encountered.


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TFBS predictions for yeast and pombe?
Are there any resources out there for TFBS (transcription factor binding site) predictions for the yeast (S. cerevisiae) and S. pombe genomes? Even if these are only de novo predictions, I would like to have access to them.

This question is quite old, but I think it might be useful to mention this:
You can also look at RSAT (Regulatory Sequence Analysis Tools):
go in the Fungi portail, in "motif discovery" choose "oligo-analysis"; there you can predict putative TFBS from upstream sequences for example. It detects repeated motifs. To be more specific of Saccharomyces cerevisiae or S. pombe, select these species in the "Background model" section.

Try YEASTRACT http://www.yeastract.com/

YEASTRACT (Yeast Search for Transcriptional Regulators And Consensus
  Tracking) is a curated repository of more than 48333 regulatory
  associations between transcription factors (TF) and target genes in
  Saccharomyces cerevisiae, based on more than 1200 bibliographic
  references. It also includes the description of 298 specific DNA
  binding sites for more than a hundred characterized TFs.


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Example(s) of reduced rate of mitotic progression?
Most species complete mitosis, and in particular the process of chromosome condensation, rather quickly, in a matter of minutes. Are there any known species that undergo mitoses with substantially reduced kinetics (on the time scale of hours), particularly with respect to the processes of chromosome condensation (prophase through metaphase) or decondensation (anaphase through telophase)?

don't know about mitosis but oocytes are locked in metphase for several years.. the second round of meiosis (gametogenesis) begins only at puberty.


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Finding DNA from Amino Acid sequence problem

My attempt: First I took the single letter AA codes and made them amino acids.  So, the first one is Trp which is 5'-UGG-3'.   From this I got the DNA sequence 3'-CCA-5'.  However, the correct answer (shown in red) doesn't have this sequence.  What did i do wrong?


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Mutation in axillary buds of trees overcoming self-incompatability?
I seem to recall from either reading or lecture that there have been instances of trees that are self-incompatible accumulating enough mutations in an axillary bud that the resulting branch was able to pollinate flowers on other parts of the tree. Unfortunately, I do not have a source for this information.
Are there recorded instances of this happening, or is this a figment of my fevered brain?

You may be remembering the line of work since reviewed here: https://www.nature.com/articles/hdy2013114 (Scofield DG. 2013. A definitive demonstration of fitness effects due to somatic mutation in a plant. Heredity 112:361–362.) Maybe you can clarify the question further, as well, if you are still interested one decade after the op?

Recently, samples from different parts of cottonwood trees have been sequenced (Nature News). The conclusion:

“The variation within a tree is as great as the variation across unrelated trees,” says Ken Paige, an evolutionary biologist at the University of Illinois at Urbana-Champaign, who led the team that made the discovery.

This doesn't say anything about overcoming self-incompatibility, and it probably depends on the mechanism of self-incompatibility if it can be overcome by accumulating mutations.

Going through my old Botany textbooks. It would appear that for at least one mechanism for self-incompatability, it would require between one and three de novo mutations. Perhaps for some mechanisms it would be more likely, and perhaps someone has come across this in the wild, but for now this works for me. :)


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Influence of alcohol on brain cells
As I am not related to biology, I would appreciate if you can keep your answers as simple as possible.
My question is about the influence of alcohol on the brain. As far as I know, drinking alcohol is killing cells in the brain. But is it linear? E.g. if I have 1.0 per mil and it kills 1000 cells will 2.0 per mil kill 2000 cells?
(An equation would be nice)
Thanks

It's definitely not linear (100% ethanol will kill all your brain cells, but 0.01% will kill far fewer than 1/10000 of neurons). Also, it will heavily vary according to your metabolism (broken down faster by alcohol dehydrogenase, etc.)

See also https://en.wikipedia.org/wiki/Neurotoxin#Ethanol

@Mechanical snail: "100% ethanol will kill all your brain cells" does not mean anything, it depends how much you ingest, how you ingest it, for how long and oh so many other variables.

I corrected the units in your question to per mil (I assume promil is the German spelling). I apologize if you meant another thing, in which case feel free to revert the edit!

@nico: 100% blood alcohol content.

@Mechanical snail: well, that is a complete different thing. 100% ethanol, means pure ethanol (i.e. not diluted with water)! Anyway, I got your point.

The situation is definitely an extremely complex one, and you should probably forget about having an exact equation to define it.
When talking about the effects of a substance on the organism there are several factors to take into account. These are generally put together under the term pharmacodynamics.
Some of the factor to take into account are:

The dose of the substance
The route of administration
The metabolism of the substance
The target organ

The problem is, not all ethanol you drink will go to the brain, and it will not necessarily go there immediately, or all at the same time. All of this will change the effects on the brain. Also, there are several confounding factors, some of which I have tried to list.
I have summarized here a few information about ethanol metabolism, taken mostly from Principles of Forensic Toxicology - Chapter 10 by Barry Levine and Yale H. Caplan
Ethanol is normally taken through drinking, which means that it will have to pass through the gastrointestinal (GI) tract (i.e. stomach and intestine) before getting into the bloodstream. This route permits practically 100% of absorption of ethanol in the body, with the major site of absorption being the small intestine, absorbing ~75% of a dose of ethanol. The rest will be absorbed in the stomach and in the other parts of the intestine.
The absorption in the GI tract is dependent on the type of beverage: for instance carbonated alcoholic beverages are absorbed faster than "plain" ones.
The alcohol content also is important: a very diluted drink is absorbed slower than one with 10-30% of ethanol, as the latter will generate a bigger concentration gradient between the GI tract and the circulation, so it will diffuse faster. However, >30% ethanol will enhance mucus formation, which will slow down absorption. Furthermore, absorption depends on the status of the GI tract: preexisting conditions (e.g. inflammation) can modify the rate at which the alcohol enters the bloodstream.
But, we are still far away from the brain! After being absorbed, ethanol goes into the vena cava, and passes through the liver, where it can be metabolized (destroyed) by an enzyme called alcohol dehydrogenase (ADH), which converts ethanol into acetaldheyde, effectively reducing the ethanol concentration in the blood.
This is a well-known phenomenon for many drugs, and it is called first pass effect
Importantly, the human stomach also expresses ADH, so this first pass effect can start even before reaching the liver! The effects of ADH in the stomach obviously depends on how long the ethanol stays in there. So, it will be lower for an empty stomach then after a big meal.
Food, in fact, is also a well known factor that reduces the amount of ethanol in the blood.
For instance, these graphs show blood ethanol content in four healthy subjects after a 10 hour fast (filled circles) or after breakfast (empty circles), after drinking the same dose of 0.80 g ethanol/kg body weight, in 30 minutes.

From: Food-Induced Lowering of Blood-Ethanol Profiles and Increased Rate of Elimination Immediately After a Meal - Jones AW and Jönsson KA - J Forensic Sci., 1994.
As you can see, eating strongly decrease the ethanol blood content. Also see how there is quite a bit of variation between the different subjects (if you open the paper you will also see the graphs from other 6 subjects).
Also, you can look for instance at this paper (just got a random study, there seems to be a ton of them around):
First pass metabolism of ethanol. - Lieber CS et al. - Alcohol Alcohol Suppl., 1994
Coming out of the liver, ethanol goes into the right side of the hearth, and from there to the lungs. This poses no particular issue for most drugs, but ethanol is volatile! So, part of the ethanol is released through respiration (in fact the "classic" way of saying if someone has drunk alcohol is to smell his breath). However, this only accounts for a minor decrease in blood ethanol levels.
Finally, ethanol can start going around the body. Being a water-soluble molecule it will tend to diffuse into water-containing parts of our body (i.e. you will not find much ethanol in fat), which include the brain.
In the meantime, however, the process of elimination has started: ethanol can be excreted in urine, sweat and breath, although the major route of elimination is epathic metabolism by ADH, accounting for >90% of ethanol elimination.
There is a neat formula to express all of this, called the Widmark equation:
$A=\frac{Wr(C_t+\beta*t)}{0.8z}$
where
$A$ = number of drinks consumed
$W$ = body weight (important because of the content of water in the body)
$r$ = Widmark constant (depends on sex, age, etc.)
$C_t$ = blood ethanol concentration at time t
$\beta$ = acohol elimination rate
$t$ = time since the first drink
$z$ = volume of alcohol per drink
You can find examples of this formula in this PDF about Widmark equations
And now to the brain: ethanol does indeed have various effects on neurons. Short term effect essentially involve depression of neuronal activity, ethanol being able to modulate GABA signalling in the brain. Long term effect range from reduced neurogenesis (i.e. birth of new neurons) to reduced volume of certain brain areas, probably due to loss of neurons, to inflammation in the brain.
Again, the situation is very complex and it depends on the frequency of drinking, the amount of each drink and many other factors. A single dose of ethanol will probably have irrelevant effects on your neurons... as the amount needed (in one shot) for serious neurotoxicity will probably send you into ethilic coma. The exact mechanisms for these effects are only partially known and very likely to be derived by the interaction of numerous diverse effects.
This article explains some of the mechanisms for loss of neurons in the cerebellum.
Mechanisms of ethanol-induced degeneration in the developing, mature, and aging cerebellum. - Jaatinen and Rintala - Cerebellum, 2008

These mechanisms include: (i) excitotoxicity; (ii) dietary factors, especially thiamine depletion; (iii) glial abnormalities; (iv) changes in growth factors; (v) apoptotic mechanisms; (vi) oxidative stress; and (vii) compromised energy production.

I will not go into the details of all of this, but it should be clear by now that all the things I mentioned so far (and many other factors I did not talk about) make it extremely difficult to give an exact quantification of the number of cells killed by ethanol. Surely the relationship is not linear, in fact, for instance, positive effects of small doses of alcohol have been reported numerous times.
A few more references on effects of alcohol on the brain:
Reduced neurogenesis
Long-lasting reduction in hippocampal neurogenesis by alcohol consumption in adolescent nonhuman primates. - Taffe et al. - PNAS, 2010
Adolescent binge alcohol exposure alters hippocampal progenitor cell proliferation in rats: effects on cell cycle kinetics. - McClain et al. - J Comp Neurol., 2011
Brain volume decrease
Decreased volume of the brain reward system in alcoholism. - Makris et al. - Biol Psychiatry, 2008
Amygdala volume associated with alcohol abuse relapse and craving. - Wrase et al. - Am J Psychiatry., 2008
Hyperhomocysteinemia as a new risk factor for brain shrinkage in patients with alcoholism. - Bleich et al. - Neurosci Lett., 2003


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Average face shape
I am doing face detection application where every face detected is inside a rectangle. The rectangle always contains some background behind the face and now I need to extract as much of the face as possible.
Also the method should be fast so I've decided to extract just some basic shape from the rectangle, like an inscribed circle. This circle unfortunately also doesn't fit so well. The best shape I've tried right now is ellipse:  (2*width of the rectangle)/3 x height.
So right now I am looking for some better ratio between the width and height of the face maybe the best would be if you could point me to some research papers.
Thank you.

According to an article in Vision Research Volume 50 issue 2 :

"The face’s vertical distance between the eyes and the mouth is approximately 36% of its length, and the horizontal distance between the eyes is approximately 46% of the face’s width."

The article can be found at:
http://www.sciencedirect.com/science/article/pii/S0042698909005045


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Why doesn't the avocado turn brown when it is kept with its seed?
Why doesn't the avocado turn brown when its kept with its seed?
What does the seed release that slows down the oxidation process?

This is actually only partly true: When you cut the avocado in half, only the part where the seed really sits stays green, while the surrounding cut area gets brown over time.
Avocados turn brown because of an enzyme called polyphenol oxidase, which oxidizes the green contents of the avocado upon contact with oxygen. The seed blocks the access to oxygen, thats why it helps here (but only where it makes close contact). See this and this links.
There are two ways of preventing the browning of cut avocados (besides avoiding oxygen contact): Use either lemon juice, which inhibits the enzyme (by chelating the metal ion from its active center) or keep it cooled to slow down the procession rate of the enzyme (which will only work for some time).

For some reason I was under the impression that lemon juice worked by lowering the pH to a sub-optimal level. What is it in lemon juice that is the chelating agent, I wonder?

It is the citric acid which has this property, see here.


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How can an albatross stay airborne for months?

Albatrosses, of the biological family Diomedeidae, are large seabirds allied to the procellariids, storm-petrels and diving-petrels in the order Procellariiformes. They range widely in the Southern Ocean and the North Pacific.

  Short tailed Albatross , Source: Wikipedia, DOR 16/09/2012

I read that albatrosses can stay airborne for up to a decade and that they can cycle brain activity between hemispheres. How do they do this feat, and how did they evolve this ability?
Possible points to consider:
immune system, predation, cycling solar output, weather, seasons...

Could you give a reference as to where you read this?  It's interesting!

@RoryM I heard about it in the great IMAX movie Legends of Flight (2010). Subsequently, I felt compelled to at least verify this online. Indeed, very interesting!

Albatrosses drink seawater; without this ability they could not be sea-bound for long periods of time. Regarding sleeping in the flight, I find this article convincing http://www.onlinemathlearning.com/animalfacts-albatross.html

I'm not really inside the field but few weeks ago I noticed a Plos One article that was dealing with this. Indeed albatross can fly for thousands of miles and this is possible at no mechanical cost, because they use a dynamic way of flight that takes the energy from wind (dynamic soaring) (ref-1). Their muscle-skeletal system further evolved so that no energy is required to keep open the wing.
In addition, when foraging, they minimize diving and landing activities because they follow Killer Whales, so that food is always in proximity. (ref-2) Very smart birds.
ref-1 Sachs et al., Plos One 2012
ref-2 Sakamato et al., Plos One 2009 both references are open access.

That article on dynamic soaring is fantastic.


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How do I view the simulated protein structure along with ligand in VMD?
I did a simulation of a protein-ligand complex, and it has stabilized after 5 ns. I have got the respective pdb files for every ns, but when I try to view in VMD (Visual Molecular Dynamics), I cannot see the ligand. How do I select the heteroatom in the graphical representation window? My complex has 1129 + 50(ligand atoms) but while loading it just shows the protein molecule(1129).

->www.biostars.org

After you load the molecule in VMD, from the menu bar select Graphics->Representations... In the box labeled Selected Atoms, type "hetero" and hit enter. You should now see only your ligand (and whatever other non-protein/DNA atoms that happen to be in your PDB file). Hit the Create Rep button, enter "protein" in the Selected Atoms box and hit enter (you can see a list of all the possible selection words in the Selections tab). You will now have a separate representation for your protein and your heteroatoms, and you can modify them with the other settings in the Graphical Representations dialog in order to make them visually distinct from one another.
If this doesn't fix your problem, open up your PDB file in a text editor and check to make sure that there are lines that start with ATOM or HETATM that correspond to the atoms in your ligand. If they aren't there, your problem isn't with VMD but with one of your prior manipulations.


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Survival of E. coli on agar plate at -20 degree C without glycerol stock
If I kept E. coli transformed with plasmid at -20˚C without making glycerol stock, will it survive? Actually I have kept it this way for 18 hours. What will happen with it? Will it grow in fresh media?

My guess is that you may be able to rescue something at this stage, but this is definitely not recommended for long-term storage. If you can't recover any living cells you should still be able to recover some plasmid from the cells for retransformation.

e coli are tough bugs.  they will last in the freezer for a while, but good experimentalists don't leave things like this to chance.  They live fine in a regular refrigerator for a week or more - no need to freeze.  replate and then transfer to glycerol asap.

Over time I suspect that ice crystals will form in the colonies from defrost cycles in the freezer and the moisture in the agar.  This will cause rupture of the bacteria membranes and over time may destroy the bulk of the bacteria cells.  The plates will also desiccate over time as well from the defrosting cycles of the freezer.  You may be able to leave them in the freezer for a while but I can't foresee them surviving indefinitely.
If the strains are really important I recommend just sucking it up and spending the small amount of time necessary to make the glycerol stock.  Glycerol is used in bacteria stocks as a cryoprotectant to prevent the crystallization of the stock.

Trehalose[1],[2] is the cryoprotectant used by bacteria to keep things going when all else freezes (or dries up), and they grow in it, too!

Trehalose accumulates dramatically in microorganisms during heat shock
  and osmotic stress and helps protect cells against thermal injury and
  oxygen radicals. Here we demonstrate an important role of this sugar
  in cold-adaptation of bacteria.

Kandror O, DeLeon A, Goldberg AL. 2002. Trehalose synthesis is induced upon exposure of Escherichia coli to cold and is essential for viability at low temperatures. Proceedings of the National Academy of Sciences USA, 99(15): 9727-9732, doi:10.1073/pnas.142314099
http://en.wikipedia.org/wiki/Trehalose