text:
Nitrogen deficiency and chloroplast function
Q. The formation of which of the following in the chloroplast is affected by a deficiency in nitrogen?
(a) Glyceraldehyde 3-phosphate
(b) Starch
(c) Enzymes
(d) Carbohydrates
My thoughts:
Nitrogen is used in both of chlorophyll and in converting carbohydrates into proteins so I am puzzled between glyceraldehyde 3-phosphate and enzymes.
However, glyceraldehyde 3-phosphate, starch and carbohydrates are nearly identical in this context and enzymes aren’t produced in the chloroplast either.

This site doesn’t provide a service for people to cheat on their homework.

This question was asked in a national Biology exam in my country and the majority are split between PGAL (nitrogen is used in chloroplast) and Enzymes (nitrogen is used to convert carbohydrates to proteins) so I wanted to hear other opinions. I’m still new here so I don’t know how this opposes the point of this page?

Please read the Help on answering Homework questions, of which this is an example. You are required to demonstrate that you have attempted to answer such questions yourself.

Does my recent edit make it acceptable?

Yes, except that the English of the question is incorrect. I assume it should be ( even though a little clumsy) “The formation of which of the following is affected…”.

Fixed, so, what do you think the answer is?

No idea. I don’t know what PGAL is. Does it contain N? Also, your title is sure to collect down votes. Change it to something like “Nitrogen deficiency and chloroplast function”.

phosphoglyceraldehyde

Ok. If only one is correct, the answer should be evident from my previous comment, assuming that they are all made in the chloroplast, which I cannot be certain about as I’m not a plant biochemist.

Chloroplasts, like mitochondria, contain DNA (in a circular chromosome) and the machinery for reading that DNA to produce RNA and protein. This chromosome encodes many enzymes involved in transcription and translation and also RUBISCO, which is one of the most important enzymes for life on earth!

so just to be sure, you're saying it's Enzymes?

I'm not saying anything about the answer. I have no idea what the question writer wants and think this is a badly written question. A nitrogen deficient plant will be be limited in the ability to make proteins and chlorophyll. I would expect that everything would be affected eventually ...


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Turnover number of the enzyme catalase
My textbook says that catalase is the fasting acting known mammalian enzyme and it can act on 40 million molecules of hydrogen peroxide per second.
Does that mean that is acting on that number of molecules during normal conditions or does it mean that one “act” takes one 40 millionth of a second?
This fact is truly incredible. The speed at which these molecules are clicking in and out of the active sites must be near light speed.

Yes, it means that each individual enzyme molecule, under ideal conditions, is able to perform its reaction in one 40 millionth of a second.
But, the reactants aren't moving at even close to the speed of light. 40,000,000 reactions per second works out to 25 nanoseconds per complete reaction ($2H_2O_2$ entry into active site, catalysis reaction, and $2H_2O+O_2$ leaving, clearing the way for the next set of reactants to bind). The speed of light is 299792458 m/s, which means it travels approximately 7.5 m in 25 nanoseconds. Catalase is about 6x10 nm in size. Even if the molecular reactants had to each travel 10 nm, that's still about 1 billionth the speed to light.

Wow , numbers both big and small are truly mind boggling in science.

That's one of the reasons we use scientific notation. 2.5e-8 seconds is a little easier to wrap your head around than 25 billionths of a second.

l upvoted your answer, but now think you have fallen into a trap over the speed of light. See my comment to the poster. Think about it. Even if you say that catalase is affecting collisions, the colliding molecules are not moving any faster, they are just colliding more frequently. Speed and catalysis are both rates but speed is distance per time, whereas catalysis is events per time.

@David I think you might have misunderstood the last part of my answer. I wasn't trying to conflate the act of catalysis itself with the speed of light. Based on the last sentence of the OP's question, I was just trying to show that even if the reactants had to travel the entire length of the enzyme to get to the active site in 25 nanoseconds (a much longer distance than they likely would have to travel in reality), they still would only be moving at 1 billionth the speed of light, which travels on the order of ~10m in the same length of time. Does that make sense?

Sure. But I'd like to make the OP think more carefully about his use of words in science.

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text:
Mutation rate breakdown by original and mutated nucleotide for Coronaviridae
In a discussion of the mutations S:Q677H and S:Q677P in SARS-CoV-2 it was mentioned that the mutations leading to this result are "against the tendency" of preferred mutations on the nucleotide level. It was also stated as a well known fact, that the rate of mutations depends on the original and mutated base.
So I'd like to know the mutations rates for all possible base pairs in Human Coronaviruses, or a pointer to reference where I can look them up. A less specific but still applicable reference is also welcome, as well as relative mutation frequencies given in some arbitrary units.
EDIT in response to comment by @David: This is the relevant part of a preprint by Hodcroft et al. on the top of page 5

The amino acid Q changes to H due to a mutation at nucleotide position 23593. Notably, in four of these six lineages, the mutation changes from G to U, whereas in the other two, it changes from G to C (FIG 2B). In contrast, the S:Q677P variant occurs by virtue of an A to C change at position 23592. All mutations leading to Q677H or Q677P involve transversions. Hence, their spontaneous occurrence is generally disfavored relative to transitions. In SARS-CoV-2 samples from human infections, A to C and G to C transversions occur at only ~10% the frequency of C to U transitions, while G to U mutations are more common, occurring half as frequently as C to U. (Wright, Lakdawala and Cooper, 2020) (Ratcliff and Simmonds, 2021).

EDIT 2: Learning more about the terminology, I am looking for a Nucleotide Substitution Model or a Mutation Profile in the described environment, especially in a best fit of the empirical data.

Please provide a reference for your assertions, and explain what you mean by source and target base, as the terms are unfamiliar, at least to me. Also let us know the results of your own attempts to answer this question.

The sun is shining for a change, and am going out for a walk, but it looks like a reference to a general difference in frequency of transitions and transversions, which has a straightforward structural basis. There may already be an answer on this topic here, but if not and nobody else does, I’ll post later.

Here is an answer to a question about transitions and transversions. Do you understand how the different in overall frequency of these types of mutations is a general thing and has nothing to do with the gene, in the first instance? If this answers your question, I would delete it. If not, explain what more you wish to know. But in any case remove the terms "source" and "target" — they are non-standard and IMHO badly chosen. "Original" base and "mutated" base is clear and unambiguous.

The linked question is a good resource, thank you for finding that one, but it does not go down to a quantitative level. I am interested in mutation rates occurring in the wild, not under some mutagene agents.

The general knowledge about transitions and transversions IS based on observations in what you term "the wild", as is knowledge about, for example, the greater mutation rate of  RNA viruses. The details of the mechanisms that explain these observations is necessary  for a rational scientific understanding of them. I suspect that you were unaware of this, in which case I think you would be better advised to do some serious reading in this area rather than responding with vague statements about "being interested in mutation rates occurring in the wild". And "target mutation" still doesn't work.

Does this answer your question? Transition/Transversion ratio

I finally found a paper with numbers, it is Host-directed editing of the SARS-CoV-2 genome by Tobias Mourier, Mukhtar Sadykov, Michael J.Carr, Gabriel Gonzale, William W. Hall, and Arnab Pain.
The authors give relative numbers in percent, so all mutations make up 100%. C>U is by far the most frequent one, making up 36.9% of all mutations, followed by G>U 17.6%, U>C 12.6%, A>G 10.9%, and G>A 10.6%. The rest are much rarer: C>A 2.6%, A>U 2.4%, A>C 1.6%, G>C 1.6%, U>G 1.5%, U>A 1.4%, and finally the rarest one, C>G 0.3%.

This one is specific to RNA mutations, and the article cited suggests some mechanisms responsible for the differences in the rates. Also read the comments below the question about transitions and transversions, in general transitions are more probable than transversions.

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Coronavirus lineages with amino acid insertions
Is there an overview over SARS-CoV-2 lineages that have some insertions in their genomes? Tools based on GISAID sequences do not show them.
I am aware of a few lineages with insertions

Mu with S:YY144-145TSN (part of lineage definition)
B.1.1.28 with S:ins214ANRN (as I understand, only in a subgroup of the lineage)
B.1 with S:ins214QAS (as I understand, only in a subgroup of the lineage)—now assigned the lineage B.1.639

I'm interested in lineages that occur in the wild, I am aware of some more insertions occurring in lab experiments.

Please check the meaning of Genetic Code in Wikipedia. What you refer to is called the “genome”. I have corrected this.

This is OK with me.

That's because handling insertions is a bit harder than point mutations and deletions.
With covizu I get this, unfortunately it doesn't tell us the insert and the translation. Hope someone can give a more comprehensive answer
    B.1.36.20 ['ins:29594:2']
    B.1.1.373 ['ins:28251:3']
    A.2.5 ['ins:22206:9']
    B.1.214.2 ['ins:22205:9']
    P.1 ['ins:28263:4']
    B.1.604 ['ins:28273:9']
    A.2.5.1 ['ins:22206:9']
    P.1.2 ['ins:28263:4']
    P.1.1 ['ins:28263:4']
    A.2.5.2 ['ins:22206:9']
    P.1.10 ['ins:28263:4']
    P.1.3 ['ins:28263:4']
    B.1.243.1 ['ins:28265:3']
    B.1.621 ['ins:21991:3']
    B.1.1.523 ['ins:26499:3']
    P.1.9 ['ins:28263:4']
    AT.1 ['ins:23599:12']
    P.1.7 ['ins:28263:4']
    A.2.5.3 ['ins:22206:9']
    P.1.4 ['ins:28263:4']
    P.1.10.1 ['ins:28263:4']
    B.1.621.1 ['ins:21991:3']
    P.1.11 ['ins:28263:4']
    P.1.10.2 ['ins:28263:4']
    P.1.8 ['ins:28263:4']
    P.1.6 ['ins:28263:4']
    P.1.5 ['ins:28263:4']

Thanks for the list, this is really helpful.

With the help of the list by @reuns, I was able to hunt down some of the mutations in terms of amino acids:

AT.1 has S:ins679GIAL S:N679K (found in a report from Public Health England)
A.2.5 has S:ins214AAG (usually, the insert can have another point mutation to S:ins214ASG, and it can occur reduplicated as S:ins214AAGAAG
B.1.214.2 has S:ins214TDR (found in a preprint by Gerdol on Recurrent Insertion Region RIR1, the preprint has some more rare insertions in the same region)

The insertions in lines P.* fall in the small gap between ORF8 and N and don't affect AAs, the insertion in B.1.36.20 falls in ORF10 that is probably not coding a protein.

For B.1.621 (Mu) it is ins146N. The insertion in P.1 (Gamma) is at the TRS, duplicating some part of it.

Then the game is to guess where the inserts (including a bit of 5' and 3' context) come from. I didn't find any match in Wuhan-Hu-1 and the matches in human mRNA are not too convincing. `>A.2.5
AGTGCGTGCGGCAGGCTATCTCCCTC

B.1.214.2
AGTGCGTACAGATCGAGATCTCCCTCA
B.1.604
CAAACTAATTTCTTTGGAATGTCTGAT
AT.1
AGACTAAGGGGATAGCACTTTCTCCTC
`

Is it necessary for such short insertions to come from somewhere, can't it be just random? But this is a completely different question ...

For the 12nt one yes, it must come from some mechanism. Most insertions in viruses are unexplained, but sometimes they are, for example some influenza furin cleavage site come from duplication of a motif, others come from host rRNA. It is still a bit mysterious for me and supposedly the 2.5 million SARS-CoV-2 sequences should improve a lot our understanding. The insertion in P.1 comes from duplication of a motif, at the TRS, binding to the 5-UTR, causing the discontinuous transcription / subgenomic mRNA.

On virological.org there are now some insertions with putative origins, either from the virus itself or from host RNA: https://virological.org/t/putative-host-origins-of-rna-insertions-in-sars-cov-2-genomes/761

Another paper on insertions: https://www.biorxiv.org/content/10.1101/2021.04.23.441209v2


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Could fingerprints potentially be changed using a gene gun?
Not to confuse with your "DNA fingerprint"  I've read surgery is readily used to not just remove but even to change people's prints through employing very small grafts between opposing hands.
About 5 years ago a Chinese group identified SMARCAD1 as a key player in the development of fingerprints. this was  discovered by generating gene expression profiles of people with a very rare condition called adermatoglyphia. These people have  no finger prints.
A gene gun, which uses micropartical bombardment is a technique that propels microscopic particles of heavy metals, coated with the gene of interest, "deep" into tissues.
If you were to alter the genetics of the epidermal stem cells, you could potentially permanently change the tissue that arises from those stem cells. Could this in principle work if over expression of SMARCAD1 resulted in remodeling of the prints or has other more important genes been shown since to be involved?
Do any model organisms have fingerprints, or a version thereof?
I know I'm fishing here, lots of questions. I thought it was an interesting topic and wanted to see what people here had to say.

People cannot change their fingerprints. It is possible to temporarily remove enough of the pattern to make the fingerprint useless for identification, but nothing more. Note that today, the fingerprint isn't the only evidence. Palm prints, especially the hypothenar eminence, is just as valuable. Even leather gloves can leave scientifically acceptable evidence in the form of skin prints.

@anongoodnurse you take your opposing thumbs, and perform 100 or so micro skin grafts between each thumb. If the graft takes, your going to perminantly alter your print. As I said this technique is already well described. Here's one example. http://www.csee.wvu.edu/~ross/pubs/FengJainRoss_AlteredFingerprint_TechReport09.pdf

@anongoodnurse I'm not asking about the surgery, what I'm referring to here is inducing local genetic changes of the  epithelium to eventually alter the print, we know there is a genetic component to finger print development. . Micropartical bombardment is a way of introducing foreign DNA into cells by propelling microscopic particles of heavy metals coated with the exogenous gene. During development differences in gene expression are what make tissues different. I think it's reasonable to assume that the cells under the ridges are genetically different from the found between the ridges.

A real gun would change your fingerprints much more efficiently.

Chimpanzees have fingerprints.  Next all you have to do is find the homologue of SMARCAD1 and let the animal testing begin!  But actually I doubt it will work.  This website goes into some depth and links some additional sources that show fingerprints are developed in the womb and are fully set by 6 months of gestation.
It seems likely that SMARCAD1 may have to do with having fingerprints or not, but not likely that it has anything to do with their composition.  It would be difficult for one gene to have enough variation to provide 6 billion variations in output.  You could hypothesize that it's a combinatorial output from other genes as well, but the studies linked above focus more on environmental interaction as the cause of variation.
I would guess that the patterns are set and no amount of gene therapy is going to change your fingerprints.  The simplest experiment would be to knockout the above gene in an adult for some period of time and see if the fingerprints fade.

More like 60 billion variations, since every fingerprint on every finger is different.  Once you realize that fingerprints differ on the same person from finger to finger...it's pretty easy to see that the exact pattern on each finger can't be genetically determined.

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Do we instinctially interpret birdsongs as a sign that there are no predators present?
I was outside today thinking how nice it was to hear the birds back from winter when I started thinking about the fact that we like bird song.  It makes us happy in a very basic level, the sort of level that usually implies subtle evolved instincts.  Thus I started wondering, why do humans all over the world naturally love the sound of birds?
The simplest explanation that came to my mind was because birds supposedly will flee or be quite when predators are around.  Thus the presence of birds singing may indirectly mean a lower chance of predation.  In other words it's less that were happy when birds are singing, as that were a little more on edge when they aren't singing.
However, that seems almost too easy an explanation.  Has anyone more intelligent then a random computer geek who's just happy to be away from the computer for a few hours put any more effort into considering this?  What is the generally accepted hypothesis?

I specifically don't really love bird songs (it is indifferent to me or sometimes quite irritating), I think I'm not the only one. Please don't think that I'm a horrible person. I just wanted to point out that your claims might be a bit wide....

Bird song appreciation is a thing that most (if not all) people experience at least some times and the question falls within the field of "evolution of behaviour" or more accurately "evolutionary psychology". I think it is a totally valid question.

I've never doubted that this is indeed a valid question. I just wanted to point out (with some self-irony) that not everybody loves bird songs. Nontheless this is an interesting question.

@poka.nandor sorry, your a horrible person and you will clearly be hunted down and burn on the stake any moment now  :)  yes I generalized a little bit, but I think the majority of people do in a way that suggest evolutionary influences, even if there are some (clearly horrible) outliers :)

I had a good laugh at your comment. Good to see that this site is full of joyful and friendly people. As i said earlier your question is totally valid in terms of what @Remi.b said.

There are plenty of birds that call and communicate in the presence of a predator, so I'm not at all convinced that we instinctual pay attention to their jabbering. Surely you learn that it's nice being in a park playing whilst the birds are tweeting.

Crows and gulls would probably also flee predators but their songs are definitely not really pleasant to listen to! I know it, they woke me up last week-end $\ddot \smile$. The canadian goose or the common starling (see here) are other examples of not really pleasant songs.
Too a selectionist view of evolutionary processes
It is important not to make the mistake to see anything as an adaptation (a result of natural selection only). Evolution is way more than natural selection and it encompasses tons of stochastic processes. This answer has a paragraph on the subject of not thinking of anything as a result of natural selection. This kind of over-consideration of adaptive processes in evolution is a common mistake especially when thinking about how human behaviour evolved.
Evolutionary psychology and evolution of appreciation of bird songs
The field of evolutionary psychology may interest you but note that it is a field that is sometimes still at the limit between psychology, philosophy and biology.
Appreciation of art as a by-product
Appreciation of art (like birds songs) and beauty is a pretty poorly understood subject yet. The first hypotheses came from Darwin and Gould. They pretty much argued that we enjoy sex, grasp facial expressions (kin recognition), have to like logical proof to appreciate learning and acquire language, efficient communication (cooperative hunting), appreciate put oneself into others thoughts (Machiavellian intelligence),  etc... As a result of those selection pressure, we may have evolved, so-called by-products. A by-product is a phenotypic trait that hasn't been directly selected for but that has been  selected via its correlation to some other phenotypic trait that is under positive selection and that is correlated. If this is true, then there would have a correlation between cognitive abilities and art appreciation and therefore a correlation between art appreciation and fitness.
Appreciation of art due to sexual selection
Some have argued that looking at the importance of art appreciation and intelligence in today's mate choice, it is likely that art appreciation may have been reinforced by sexual selection.
Either sexual selection may have reinforced a trait that was correlated to fitness ("evolution of appreciation of art as a by-product" hypothesis).
It is also possible that sexual selection may have selected for art appreciation without art appreciation being correlated with fitness but just because it asks for a big brain and lots of energy (brains consumes lots of energy) and being able to appreciate arts means that the individual has extra-energy to spare and is therefore very fit (handicap principle).

I understand your general point, but could you elaborate on what you mean by appreciation of beauty is due to having a big brain?

@dsollen It is a good point, it was indeed still unclear. I've been trying to develop the ideas a bit further. It is really not my field and I don't expect that my summary is a good review of the thoughts and evidences we have on the subject.

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How does HIV mutate into other strains while keeping their virulent phenotype?
How does a virus like HIV mutate into so many strains, and yet all of them are  harmful to our immune system? What gives this virus the ability to mutate so efficiently?

Others have already touched the important points. Consider this as a summary.

What gives HIV the ability to mutate?

All organisms mutate by two mechanisms:

Replication errors
Mutagenesis by physical/chemical agents that cause a chemical change
(lesion) on DNA

The main enzyme responsible for HIV replication is reverse transcriptase which makes a DNA copy of its RNA genome. All RNA and DNA polymerases make some amount of error but the error rate of reverse transcriptase is much higher than usual DNA-dependent DNA polymerases because it does not have a proofreading mechanism.

How does a virus like HIV mutate into so many strains, and yet all of
  them are harmful to our immune system?

As indicated in previous answers, the mutations will produce a virions with a spectrum of infectivity/pathogenicity (some can even be non-infective).
However, the immune system acts as a selective barrier which selects only those mutants that can survive (similar to what happens in evolutionary process of natural selection). The selected strains expand their population and that is how these strains get established.

What gives HIV the ability to mutate?
HIV is a single standed RNA virus. DNA is much more stable than RNA as it has a stronger backbone and it is typically double stranded. But HIV mutates at a rate far higher than just being a RNA virus. That's because it uses an enzyme called reverse transcriptase (RT) to build it's RNA genome from RNA bases.
RT is meant to copy the old HIV and make a new one but it does a rubbish job. Most the time it copies it well but every now and then (3 x 10−5 per nucleotide base) it puts in a random base. That might seem like a small rate but that's HUGE if that was coding our genome we would die (if we ever even lived). And since HIV's replication rate is enormously high, there's always going to be a range of good and junk HIV (but it's mostly just junk - next answer for why that's not a bad thing).
But that's not all, RT doesn't just use one old HIV to make a new one. It can use several different old HIVs to make a new one that's not only a combination of all the other ones but then add in the mutations from above, completely different.
So I get that there's lots of mutated strains all over the place. Surely that'd make them useless because the mutations are random?
Yeah they are random and yes that does mean some virus particles are useless. But it's very variable. There's ones which are greatly infectious, partly infectious, slightly infectious and basically junk. The body doesn't really know which ones are which and that's the beauty of it all. The body tries to fight all of them and has no clue which one to get. If it happens to target the greatly infectious one, the numbers of this go down but then the partly infectious one will become the most infectious one and the cycle continues. The junk HIV is basically just a sticky pool of most of the HIV particles that just gets the immune system going crazy and diverts it from the real threat.

Viral recombination produces genetic variation that contributes mostly to the evolution of the HIV-1 virus.
HIV being an RNA Virus utilizes  an enzyme called reverse transcriptase, which produces DNA from RNA. HIV also has two RNA genomes. After infection and then replication, which is catalyzed by reverse transcriptase, recombination between the two genomes can occur. specifically the single-strand (+)RNA genomes are reverse transcribed to form DNA. Then during this reverse transcription the nascent DNA can switch multiple times between the two copies of the viral RNA and multiple recombination occur throughout the genome. Furthermore, multiple events per genome may occur during each replication cycle, thus compounding the mutation.

Simple answer is that those mutations that create inactive virus, will never show up on screen, since it  will be asymptomatic. In same fashion if virus loses its ability to infect new target (via sexual contact or blood directly) it will show up only in first victim, so that effectively be a non-problem for society.
Addendum: I think I answered portion, starting with "and yet...", which seems to be most important in the question. I think that exact mechanism of mutagenesis must be covered in literature, if known. Also, it seems that since there are no vaccine for HIV, it's mutagenesis cannot be really "efficient", since it is not actively fighting anything.

First, you have to keep in mind that patients are not infected with a single strain. Because HIV is a chronic disease, and given its rapid mutation rate, it has enough time to evolve into a pool of enormous strains called "quasi species". So the virulence manifested is not virulence of individual strain, but the overall virulence of the quasi species.
Actually, because of its high mutation rate, HIV produces many failure strains. These strains are even unable to replicate and account for around half of its progenies! So they're certainly avirulent. But these progenies will die out very soon. However, HIV makes billions of copies per day. So there will always be fully replication competent and fully virulent strains. That's how its virulence sustains. So patients will always develop AIDS if left untreated.
Also, HIV may produce progenies with varying virulence. But the overall virulence is not determined by a single strain. And our immune system may serve as a natural selection. Only strains with good replication efficiency and immune evasion ability can survive. This may also explain how the virulence sustains.
Actually, there're a few people infected with Nef deficient HIV mutants. Nef is an accessory gene. HIV without it can still replicate but cause much milder disease. However, Nef is crucial to the immune evasion mechanism of HIV. So HIV strains without it are more likely be out competed by fully virulent ones.
I think influenza is another example. Influenza is also rapidly mutating, but its virulence varies greatly. From highly pathogenic avian flu to mild seasonal flu. I think the reason is that influenza don't cause chronic infection, so they don't generate quasi species, and there's no natural selection process. That's why the virulence of influenza fluctuates greater. Warning, this is just my guess.


text:
What is the basic structure of the nuclear lamina

What gives the nucleus
  its shape is a mesh of intermediate filaments called the nuclear
  lamina. It forms an interface between the chromosomes and the inside
  of the nuclear envelope. If these large protein fibres were to be
  temporarily separated into their component nuclear lamina, the nuclear
  envelope would pull away from the chromosomes and withdraw into the
  endoplasmic reticulum. Problem solved.

I am confused by the last sentence starting with "If these large proteins..." Could someone explain this in another way? I would appreciate any response. Thanks!

Can you articulate what exactly confuses you about the sentence?

This is a fair question, his text or source words it funny.
To keep it simple, the nuclear lamina is a network of filaments inside the nucleus and it includes the proteins associated with the nuclear membrane.
It's connected to the inner face of the nuclear lipid bilayer that makes up the nuclear envelope whereas the outer face is continuous with the endoplasmic reticulum.
Look at most any cartoon of a cell, it shows the nuc envelope attached to the ER, which it is. Makes up a big part of the cells endomembrane system.

I think in other words the author is trying to say if the lamina came apart, the envelope would essentially just be a continuation of the ER, as it's the lamina that essentially folds up that "portion of the ER membrane" up to create the nuc envelope.

This doesn't answer the question.

How is that? @OminousOwl

Watch this animation and you'll understand the general process of mitosis:
http://www.sumanasinc.com/webcontent/animations/content/mitosis.html

This doesn't answer the question

Okay, so your nuclear lamina is composed like so,

Source: Wikipedia
When cdc25 is upregulated between G2 and M, we see dephosphorylation of Cdk1 and it's subsequent association with cyclinB. Cdk1-Cyclin B activates the MPF, and the MPF initiates phosphorylation of the proteins called lamins. As the nuclear lamina depolymerizes, it's resorbed into the ER,

Source: http://www.jbiomedsci.com/content/16/1/96
What we find is that lamins actually help anchor heterochromatin (tightly packed) to the nuclear lamina, so when we phosphorylate the lamins, the heterochromatin is shown to move from the periphery to the more central areas of the nucleus. So we couple this uprooting of the chromatin from the lamins, and the resorption of the lamina to the ER through phosphorylation of the lamins during mitosis to broadly answer the question.

This answer has more details than mine, good answer.


text:
Heritable immunity and smallpox vaccination
As I understand it, lack of heritable immunity caused smallpox to wipe out certain communities of native Americans. If vaccination conveys heritable immunity to a population, shouldn’t this make vaccines unnecessary after the first generation?

Genocide is not a verb.  Nor does the death of a large number of people in a plague constitute genocide, whether it was the introduction of European diseases to the Americas, or the introduction of Asian or African diseases to Europe, e.g. the Black Death, the Plague of Justinian, &c.  You might also note that smallpox was endemic or epidemic in Europe and the Near East for centuries prior to the development of vaccination, regularly killing significant numbers of people.

Yersinia pestis was not a new European disease in 1300...

I have edited your question for logic (inserted “lack of”) and to make it conform to scientific and non-confrontational site style. As a new user to this list I would encourage you to take the Tour and read about asking good questions.

Guys, you are discussing with an anti-vaccine troll, as the original not edited question clearly shows.

@Chris I am not discussing with him, although jasmesqf is. I edited his question so that we can post a clear answer clarifying the confusion in the use of the term immunity and making the point that the immune response invoked by vaccines is not heritable. It is important, however, not to get side-tracked into answering questions about when bubonic plague appeared in Europe and to provide basic references in answers. I intend to reply  myself, to some extent duplicating what Bryan has said, but focusing on what I have just said, not accepting undocumented interpretations of history.

@Chris It may have been convenient to close this as a duplicate, but in my opinion it was wrong to do so. The question this is a supposed duplicate of is different and is a historical question which can only be answered in a speculative manner. It is extremely badly phrased and should be closed, rather than this question as now amended which asks a precise scientific question which can be answered clearly and unequivocally without any reference to historical events and for which an answer could be used as a resource.

@Chris: You are less charitable than I am.  I'm assuming s/he is just ignorant, or perhaps deluded by anti-vaccination propaganda, and so possibly could be educated.

@jamesqf I was just saying that discussion might be pointless. You are if course fine to do this (the question now is ok I think), but I will have an eye on this.

Vaccines are pointless?

No.
The heritable immunity you are describing is due to selective pressures on populations where individuals with certain alleles have a survival advantage in the face of particular pathogens. If a population is exposed to deadly diseases like smallpox and there are some individuals in the population who are more resistant, those individuals are more likely to survive to reproduce so future generations will have more resistant individuals. You could think of this as immune system "hardware."
Vaccines trigger the immune system's ability to recognize past infective agents and therefore mount a rapid specific antibody response when exposed to that pathogen again. You could think of this as immune system "software." This software that is aquired during the lifetime is not present in the genome of germ line cells and is not transmitted to offspring.

Is there any scientific evidence or specific mechanism(s) for what you a re saying

@user52352 You can read about the adaptive immune system starting with Wikipedia https://en.wikipedia.org/wiki/Adaptive_immune_system or any biology textbook. To learn about evolution and heredity you can start with https://evolution.berkeley.edu/evolibrary/home.php

Those don't seem to mention the genocide if the native Americans, or your hardware distinction whatever is meant by that


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Lysozyme amino acid sequence: N-terminal extension
I looked up the amino acid sequence of lysozyme here: http://www.biology-pages.info/L/Lysozyme.html
Then I crossed referenced that with the lysozyme sequence on UniProt: https://www.uniprot.org/uniprot/B8YK79
My question is why does the sequence on UniProt start with eighteen other amino acids before getting to the start of the sequence described in the first source?
The sequence on UniProt starts with "MRSLLILVLCFLPLAALG".  I know the M comes from the start codon in the gene for the protein, but where does the rest of this come from?

If you scroll down through the uniprot entry you will come to a section with the heading PTM/Processing.
From this you can see that the first 18 amino acids are a signal peptide.
You can learn more about signal peptides from any good introductory textbook covering cell-biology — alternatively Khan Academy is a good source for learning the basics.


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What is the genetic reason that this flower has petals of two different colors?
I have two different varieties of the flower, portulaca: one is bright pink, the other is pure white with pink specks at the centre. Recently a flower bloomed which had 50% of the former and 50% of the latter: both traits in the same flower. Is this an example of co-dominance or is there some other reason for it?

This can be a result of a somatic mutation, especially if the other flowers on the same plant don't have the same color pattern. Somatic mutations are not inherited for parent organisms but occur spontaneously in one of the cells in the body. If that cell then proliferates all of its descendants will have the mutation and new phenotype associated with it.
Look for example at Fig. 1 (c, d) in this article. Those peach flowers have similar coloration to the one on your photo.


text:
How many proteins could participate in a complex
Disclaimer: I’m a computer science student with minimum knowledge of biology.
I’m working on an algorithm to cluster proteins in Protein-Protein-Interaction Networks to find protein-complexes. While working on that I stumbled upon the question how many different proteins can be part of a protein complex. (I'll call this the size of the complex from this point.)
I started by counting the the participants from all Corum complexes.
I got sizes ranging from 1 to 143:
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 36, 37, 38, 40, 44, 45, 47, 48, 62, 68, 78, 80, 104, 143]
The distribution is skewed to smaller sizes with 3 participants counted 1465 times and most of the bigger sizes from around 30 counted 1 or 2 times.
{44: 1, 36: 1, 32: 1, 47: 1, 78: 1, 48: 1, 31: 1, 143: 1, 40: 1, 26: 1, 38: 1, 62: 1, 104: 1, 23: 1, 20: 2, 22: 2, 33: 2, 80: 2, 37: 2, 45: 2, 28: 2, 68: 2, 27: 2, 30: 3, 19: 3, 24: 4, 25: 4, 18: 6, 17: 11, 15: 19, 1 6: 21, 14: 23, 11: 25, 12: 28, 13: 30, 10: 55, 9: 57, 8: 72, 7: 83, 6: 100, 1: 127, 5: 237, 4: 499, 2: 1370, 3: 1465}[Sorry for not sorting...]
My main question from this first dip into data is, are there any assumptions to make about the size of complexes? Are these big complexes for example special cases and normally complexes are limited to a size of around n?
Is there maybe even an upper limit of participants in a complex?
Anything would be helpful for me to minimize runtime.

This is suggestion as to how you could clarify the question to help us help you, without your having to resort to socializing, as per my answer. Could you sort the non-redundant list by number of participants and then present us with say 20 entries that span your putative cut-off, just showing the number of participants and the name of the complex? That way the question becomes, can we apply some different descriptor to complexes above the cut-off, which you can use in your report. Btw. I downloaded one of the files. I would advise having only one instance of a complex, e.g. not mice and man.

Hi. At first thanks for the answer. I can do that, but it'll probably take me some time as I'm right now working at several different spots concerning this project.

[Was to slow to edit...]
Still I want to clarify more what my project is. The Idea is can we find protein complex candidates just by looking at the structure of PPI's. I'm especially working with quasi-cliques. So I try to find a configuration where my algorithm finds all known complexes and more. These extra findings are then seen as candidates. That's my reasoning for asking this question. The project itself is more like "Let's see what happens and if we want to further work in this direction" Also it's my bachelor thesis, so the scope is definitively limited.

The problem with coming into bioinformatics from a non-biological background is all too apparent in your question, and very real. You are dealing with a category of object called a protein complex, you suspect that it will be reasonable to exclude a proportion of them, but as you don’t really know what they are (other than at a basic level) you don’t understand the implications of doing so. As generally in such cases, you need to find an appropriate biologist to help you.
All I can do is try to make an analogy. Consider an entity that the biologist who knows nothing about computing calls a ‘program’. As a surrogate for the number of components, let us consider that it is written in Java and so that one can judge its complexity by counting the number of classes. (I know that the examples I am giving are not all normally written in Java, but in theory they could be.) I could write a simple program that just parses a file and outputs a second file in a different format. That would use very few classes (especially without a GUI interface). Then I might write a modest web application to query a database and return biological information to the user. That could have perhaps two dozen classes. A more sophisticated commercial web application would have more. And then we get into commercial desktop applications from the relatively modest utilities to the monsters like Microsoft Word.
But just classifying computer programs on the number of Java classes would have severe limitations, just as would an alternative approach such as programming language (python for scripts, C++ for large applications). What I would really need to decide is what kind of program to include or exclude.
Likewise with protein complexes. I am not familiar with Corum (I just checked the website on my phone) but one might assume that the protein complexes it contains range from basic enzymes and proteins with two different subunits (perhaps in two or more copies, generally in a regular structure) like haemoglobin or immunoglobulin G, through proteins that interact with several species and posses half a dozen different subunits, to what are in effect machines of greater or lesser complexity, like the ribosome, the two subunits of which may together have 70 to 80 proteins.
So, yes, it would be reasonable to exclude the relatively small number of very large complexes which constitute a class of “machines” (and your size distribution suggests where the cut-off might be). But for your work to be valid you need to know specifically what class of complex you are excluding so as to be able to state that you had deliberately decided to ignore large complexes like ribosomes, splicesomes etc. And name them.
It’s tough at the moment, I know, but in my opinion you do need to sit down with a biologist and have this explained in more detail, reviewing the names of the complexes in the Corum list that you are considering excluding.


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The Human Menstrual Cycle
1) What happens in the ovary and in the bloodstream that brings about this change in the uterus?
2) Why does the level of FSH decrease and remain at a relatively low level during the luteal phase of the cycle?

For 1 I was thinking: So estrogen levels increase and the follicle matures which first cause menstruation and then the lining reforms??
For 2 I was thinking: the follicle has already ruptured by the luteal phase

I addressed this topic in an answer to a related question. Although it’s a different question, I think both of yours are answered in the background I provided in that answer. (P.S. You need to specify what you’re referring to by “this” change in the first question - probably either a proliferative or secretory endometrium, or maybe menstruation? Or if it corresponds to the title, do you mean the entire cycle - “these changes”?)

Please expand on he abbreviation FSH

This sounds quite a lot like a homework/exam question, so I added the relevant tag.


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What cause the urge to inhale in humans?
The urge to inhale in humans result from
(a) rising pCO2
(b) rising pO2
(c) falling pCO2
(d) falling pO2
p stands for partial pressures. I am guessing the answer is falling pCO2.... but I wanted what is the answer and the reason for it?

It sounds like a homework question, so I added the tag. Feel free to correct me if I am wrong.

As a homework question, guessing doesn't suffice @MukilanSC

@skymningen This was not an homework question. It was a question given by my biology faculty and he said the answer was fallin pO2.. I wanted to know the reason behind this to counter my faculty and to make the class aware of the real reason.... So you are wrong and I did not violate the community guidelines?

In the help section on how to ask, the first sentence is "Have you thoroughly searched for an answer before asking your question? Sharing your research helps everyone. Tell us what you found and why it didn’t meet your needs. This demonstrates that you’ve taken the time to try to help yourself, it saves us from reiterating obvious answers, and above all, it helps you get a more specific and relevant answer!" You simply guessed. @rg255 is correct.

@MukilanSC I don't think we have a general difference here to distinguish between (written) homework questions and "classwork" or "in class" questions/ exam questions and so on.

The correct answer would be a) rising pCO2. The rising CO2 level in the blood causes an urge to inhale and take in more O2.
For how it works, this is controlled by respiratory center:

The respiratory centers (RC) are located in the medulla oblongata and pons, which are part of the brain stem. The RCs receive controlling signals of neural, chemical and hormonal nature and control the rate and depth of respiratory movements of the diaphragm and other respiratory muscles ... In healthy individuals the presence of elevated carbon dioxide levels in the blood is the stimulant that the RC responds to in order to signal the respiratory muscles to breathe. Chemoreceptors found in carotid bodies and aortic bodies are responsible for detecting decrease in blood pH by this carbon dioxide.


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Can you get enough water by eating only fish?
Scenario: In a boat in the middle of the sea, no freshwater or food stores, no desalination equipment, no rain, but you can catch fish and eat it raw. Can you get enough water this way to survive, let's say for 14 days? (Enough clothes to protect against cold, shade available)
2, 000 g of raw Pacific cod contains 1,650 mL water, 350 g protein, 2,200 mg sodium (source: usda.gov)
By my calculation, you would need to excrete 2,800 mL of urine to excrete urea from protein metabolism (8 mL urine per 1 g protein; source: nap.edu), so after eating fish you would be in the negative water balance for more than 1,150 mL solely from urea.
My questions are strictly about fish as a water source, not about other water sources or survival time:

Does protein really expel so much urine that makes fish an inappropriate source of water?
Any other appropriate source of water from fish, apart from eyeballs? Can you somehow squeeze the water from fish?

small hole in your scenario - if you can cook fish, you should be able to boil seawater and condense the steam for desalinated water :)

I edited: No cooking, raw fish.

note protein levels in fish blood vary by quite a lot. so it depends on the fish in question.

If you have a man in a box scenario where you only look at numbers, the answer is, no, he won't last 14 days.[1]
The difficulty with this question for me is that the body doesn't always behave the way it's supposed to. The 3-3-3 rule (3 minutes without air, 3 days without water, three weeks without food) and the "100 hour rule" (4.166 days) aren't absolutes.[2] Some people die in hours, some 10 days. The variables are too great.
Guinness World Records puts the record for survival without water at 18 days[3] by an 18 year old male forgotten in a cell by the police. But he was in a cool basement, and licked the walls which had a small amount of moisture on them. Had he been sweating or 2 decades older, he probably wouldn't have lasted as long.
Water requirement under extreme circumstances varies. How much clothes is your male wearing? Does he have shade? Where in the ocean is he? How inactive can he be? Can he oil his skin with fish oil? But mostly, does he have a still suit (j/k)? These things all matter.
Eating protein without water isn't wise. Carbs are better, but your guy doesn't have them. The better thing for your guy, who can certainly live for 14 days without food, is to suck the water out of the fish, and what he can't suck out, wring out at the end. If he has access to the whole fish, the eyeballs and the spine also have water in them.* The body has all kinds of homeostatic mechanisms to preserve fluids, including continuous secretion of ADH (Anti-Diuretic Hormone), osmoreceptors and baroreceptors to regulate fluid volume and how much water is lost from the kidneys.[4] He'll suffer terribly; fluid will be sucked out of his joints and cells and his blood urea nitrogen will go up and his kidneys will be damaged, he'll hallucinate, he'll need hospitalization, but might he live? If he is young, healthy and hydrated going in, and other factors (a tarp for shade, etc.) mitigate his water loss, I think the answer is yes, he might.
*In 1953, a French physician and sea survival expert, Alain Bombard, set sail in a Zodiac inflatable dinghy with the only food and water officially sealed to discourage himself from using it. He started immediately with drinking small amounts of seawater, and would suck water from fish, and, if he had any fresh rain water, would eat raw fish. He sailed from Minorca to Barbados, eating supplied food and water only once. His rival survivalist, another physician, Hannes Lindemann, contested Bombard's claims, but did well at sea as well.
[1] The Biology of Human Survival : Life and Death in Extreme Environments
[2] Dehydration
[3] Andreas Mihavecz
[4] Fluid Physiology, Ch. 5, 6

Human eyeballs contain more than 98% of water, so I assume something like this would be in fish, so yes, this can be a water source. The water from "spine" would be cerebrospinal fluid (?), which content would be similar to plasma (lot of sodium), so not sure how effective in hydration.


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Why is hydrogen to oxygen ratio used to compare energy storage efficiency?
I came across an article that says that lipids are more efficient energy storage molecules compared to starch because lipids have higher “hydrogen to oxygen ratio”.
I do not understand how “hydrogen to oxygen ratio” equates to more efficient energy storage.
I am guessing that since energy production have to do with reducing NAD+, so “hydrogen to oxygen ratio” is a measure of the ability to reduce NAD+. And since NADH is then later used in oxidative phosphorylation in mitochondria to produce energy currency ATP, “hydrogen to oxygen ratio” is a measure of the potential amount of ATP the molecule is able to produce. And thus it is a measure of energy storage efficiency.
Is this correct?

Answer
In my opinion:

The original poster’s overall interpretation of the statement in the article (as
reported) is most likely correct.

Problems with original statement
Although the statement may be clear in context, I would rephrase it because of two specific objections I have to it. These are:

“Energy storage efficiency” in isolation is ambiguous. It is not clear whether it refers to storage per unit mass or per unit volume, both of which may be considerations for living organisms.
“Hydrogen to oxygen ratio” is an imperfect heuristic for the reduction state of the carbon backbone.

I would also be specific in naming the lipids involved in ‘energy storage‘ — there are other lipids (e.g. steroids) that are not used as energy stores.
So my restatement (adapted from Berg et al. ‘Biochemistry’) would be:

Triacylglycerols are more concentrated stores of metabolic energy than
polysaccharides such as starch or glycogen because they are more
highly reduced. The energy yield per gram from the complete oxidation
of triacylglycerol is over twice that from polysaccharides (38 kJ/g
cf. 17 kJ/g).

Comments on restatement

I have avoided the use of the word ‘efficiency’ for reasons of lack of precision,
already mentioned. In general I deplore its use in biology, partly
because it is seldom defined, and partly because it generally
involves the implicit assumption that the most ‘efficient’ is the
‘best’. If this were so in the current case, potatoes would be bags of oil.
There are other factors that contribute to the concentrated nature
of triacylglycerols for storage of metabolic energy. These include
dehydration and lack of branching (important for reducing the
volume).
It is important to talk in chemical terms — i.e. about oxidation and
reduction. I reproduce below part of a diagram I used to use for teaching
which summarizes the relationships between metabolic intermediates
of different oxidation states.
The above diagram shows the limitations of the heuristic of
“hydrogen to oxygen ratio”. The pair on the left (which might be found in
saturated v. unsaturated fatty acids) both have the same H:O ratio
(infinity) but are in different states of reduction.
It may be better (at least in abstract) to consider carbon atoms as the basis on which to
compare the oxidation states of different metabolites, rather than
weight, which is influenced by the oxidation state itself.


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How do ribosomes interpret stop codons as selenocysteine and pyrrolysine?
How does the protein synthesising machinery determine that UGA and UAG in mRNA should be decoded as selenocysteine and pyrrolysine, respectively, in certain circumstances, rather than as stop codons?

Summary
Reassignment of an UGA codon as a selenocysteine codon is thought to involve the interaction of obligatory secondary structure elements called selenocysteine insertion sequences (SECIS) with the dedicated translation elongation factor that presents a unique tRNA aminoacylated with selenocysteine to the ribosome. However the location of these elements and their specificity differ between prokaryotes and eukaryotes. Less is known about the less common reassignment of UAG to pyrrolysine, but some organisms may employ similar mechanisms to those involving selenocysteine, whereas others may almost completely avoid the use of UAG as a termination codon.
Preliminary — Presentation of selenocysteine to the ribosome
Although the question specifically relates to the translation of erstwhile termination codons, it is worth mentioning how selenocysteine (Sec) is presented to the ribosome.
     In most species a specific tRNA — tRNASec — is aminoacylated with serine catalysed the standard seryl-tRNA synthetase. The Ser-tRNASec is then converted to Sec-tRNASec — in Escherichia coli, by the product of the SelA gene.
    Whereas all other charged elongator tRNA species are brought to the A-site of the ribosome by the same elongation factor (EF-Tu in prokaryotes, EF-1 in eukaryotes), there is a specific elongation factor for binding Sec-tRNASec.
Reprogramming UGA codon as a selenocysteine codon
The reprogramming of UGA as a selenocysteine codon requires a stem–loop secondary structure — the SECIS — in both prokaryotes and eukaryotes. However there are differences in how these operate. Quoting from a Nature News and Views piece written in 2007:

In bacteria there is a site-specific recoding signal embedded in mRNA that flags a nearby UGA codon as encoding selenocysteine rather than stop (Fig.b). In other organisms, ranging from worms to mammals, a recoding signal located outside the coding part of the mRNA (Fig.c) signifies that all UGA codons in its mRNA specify selenocysteine (one essential human mRNA has ten UGAs).

The mode of action  of the SECIS elements is envisaged as interaction with the Sec-tRNASec-specific elongation factor, as in this illustration from Ch 13 of Molecular Biology by Clark et al.:

A shortcoming of this cartoon, is that it fails to show that in prokaryotes the SECIS element encompasses the UGA codon. This is important as it may indicate that  termination factors are prevented access to the UGA by secondary structure, which the Sec-specific elongation factor is able to unwind. (In eukaryotes there may UGA codons may also be made inaccessible by local secondary structure.)

However sequence context effects have also been suggested.
Pyrrolysine
The situation for pyrrolysine (see, for example, Ambrogelly et al. (2007)) differs from that for selenocysteine in that it is synthesised before it is charged to a specific tRNAPyl in a reaction catalysed by a specific pyrrolysyl-tRNA synthetase. The reassignment of UAG to pyrrolysine was thought to involve a change (or almost complete change) in the genetic code of certain archaea in which it is found, with UAG not or rarely being used as a termination codon. However, according to the Nature News and Views article aleady cited, this is not the case for other organisms, in which I am unaware of the mechanism of reassignment.

In bacteria during translation what happens to the codons present downstream to the SECIS sequence? Can the ribosome easily skip over that sequence to the remaining codons?

@trinitrotoluene — The orthodoxy is yes. Once a secondary structure is unwound the ribosome keeps it apart. This was deduced early on from studies of the translation of small RNA phases, where one AUG could only be translated if other parts were displaced. Although far more sophisticated techniques are available to follow translation today, I’m not aware that they have been used for this problem. But I haven’t trawled through the recent literature. I may check it out in the next few days.

Ok, thank you so much. Just a few more follow up questions. After the SEICS element is unwound is it also translated? Do Bacteria need one SEICS element for each UGA codon?

@trinitrotoluene — If the SEICS element containing a Sec UGA is unwound, sure, it will continue to be translated until it gets to the “real” stop codon. And yes, unlike eukaryotes, bacteria appear to need a SEICS element for each UGA.

Ok, thanks for clearing my doubts.


text:
Do DNA viroids exist?
Viroids are described as short circular ssRNA with no protein coating.
Are there any analogous infectious particles that contain DNA instead of RNA?
If DNA viroids do not exist, is there an obvious reason for this?

The definition on the Wikipedia page you recite uses the language 'no protein coating' as opposed to 'protein coating'.
A protein coating would make it a virus.
No protein-coating would make it a Viroid.
As far as we know DNA Viroids do not exist. But this is an advancing field of research and it depends on what structure of genetic material you are referring too.
The general different types of genetic material include - but are not limited to:
Single-stranded DNA (ssDNA),
Double-stranded DNA (dsDNA),
Single-stranded RNA (ssRNA),
and double-stranded RNA (dsRNA).
There is more information on Classes I and II DNA viruses here:
https://www.ncbi.nlm.nih.gov/books/NBK21523/
If there were no DNA viruses without a protein coating - what is the reason?
Viroids only infect plant cells.
It may be that Viroids route of entry via microscopic junctions between plant cells (Plasmodesmata) are only large enough to fit single stranded genetic material. Therefore allowing ssDNA and ssRNA, but not dsDNA and dsRNA to act as plant cell infectious agents.

Welcome to SE Biology. I think, as a non-native speaker, you are on shaky ground criticizing the use of the word "particle" by the poster. The definition from Oxford Languages is "a minute portion of matter", which in no way implies a container. I would delete your first two paragraphs. Also questionable is your remark "it depends what you mean by DNA". DNA is unambiguous. The strandedness and cicularity of DNA may vary, but it is all DNA, and it is clear that the poster wishes to know whether an entity composed only of DNA with no associated protein can exist as an infectious agent.

@David thank you for your response. I made your changes. I hope we can get on in the future here at SE.


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Regulation of Glycolysis and other pathways at ‘irreversible’ reaction steps
The hexokinase, phosphofructokinase and pyruvate kinase steps of glycolysis (1,3 and 10, below) are the only ones that are irreversible, and are also the steps where glycolysis is regulated.

Is it necessary for a regulatory step in glycolysis to be irreversible, and if so does this apply to metabolic pathways generally?

Is this a homework question? What is your basis for the generalization from one pathway — namely glycolysis? What have you done to try to answer this question yourself?

@David I rephrased it-please ignore that generalization. I've tried to find an explanation on Berg's 7th ed. Biochemistry. It (and Mathews' Biochemistry from which my course's lectures are taken) states that the reactions are essentially irreversible on physiological conditions, and go on explaining the control on these reactions' enzymes. We've been told at our course several times (with no explanation) that regulation of pathways usually occurs at irreversible steps.

This is not a homework question; I want to know if and why this is true, and if not are there any counter examples some of you may know.

Ok. I'll answer your question over the weekend if nobody else has stepped in first. Too busy with other things tonight.

As far as glycolyis is concerned, the answer is straightforward. In certain cells and tissues there is a pathway working in the opposite direction — gluconeogenesis — in which the ‘irreversible’ steps of glycolysis are, in fact (and of necessity), reversed by a different enzymic reaction in which the position of the equilibrium is in the opposite direction.

Obviously if it is metabolically appropriate for glycolysis to occur it is inappropriate for gluconeogenesis to occur. The only way of turning e.g. glycolysis off while at the same time turning gluconeogenesis on is by regulating the activity of the different enzymes at these three steps.
Glycolysis is, therefore a special case in sharing many reactions with another pathway working in the reverse direction. What about pathways in which the interconversions only proceed in one direction. Classic examples are biosynthetic pathways that are regulated by what is known as ‘feedback’ or ‘end-product’ inhibition. An example (for which I happen to have my own diagram) is the synthesis of isoleucine from threonine in bacteria:

When the concentration of isoleucine increases to a certain amount (sufficient for the cell’s needs) this inhibits the enzyme threonine deaminase, preventing the wasteful conversion of threonine to isoleucine.
The main point is not the position of equilibrium of the threonine deaminase reaction (I haven’t checked it yet) but that it is the first unique step in the synthesis pathway. Hence regulating this step prevents the unnecessary removal of threonine in a way that does not allow the wasteful accumulation of intermediates.
Moral
There is an old party game in which you pass a pair of scissor to your neighbour saying “I pass you these scissors crossed” or “I pass you these scissors uncrossed”. The initiates then tell you whether you have performed the operation correctly. The uninitiated player assumes that what is important is whether the scissors are crossed. In fact, it is whether or not your legs are crossed. Beware of false associations.

This is useful information, but there is also a different aspect on the question. Regardless of the pathway, I think the thermodynamics of an irreversible reaction make it a good candidate for regulation, in general. I believe this is related to the fact that a reaction with a large free energy difference can "drive" a pathway, while an equilibrium reaction cannot. This is explored in Metabolic Control Analysis, see https://en.wikipedia.org/wiki/Metabolic_control_analysis  I am not an expert in this stuff though ...

After consideration I deliberately avoided posing the question of whether all regulation steps in biosynthetic pathways  (e.g. theonine deaminase, above) are thermodynamically irreversible, partly because I did not know if this is so, and partly because I regard it as subsiary to the question of where to control a pathway. For example, if in all cases the first commited step in biosynthetic pathways were irreversible one would conclude that evolution pressures had selected from alternative chemistries. A good question but one I can't answer. The evidence interests me more than theory, though.

@Roland Thanks that's a nice way of looking at it.

@David This might be a digression but are there other criteria for which steps should be regulated other than the first unique ones?

@idnap — not that I can think of, although others may. I could envisage a situation where A ⇋ B → C ⇋D etc. in which B → C is regulated rather than A ⇋ B. If the A ⇋ B reaction didn't require energy or reducing power (e.g. an isomerization) and the equilibrium was midway between the two it wouldn't really matter if the next step were regulated. As A was drawn off in some other direction, B would be converted back to A. Can't think of any examples off the cuff.

@David I understand. Thanks a lot for all your help


text:
Scoring matrices (BLOSUM & PAM) in BLAST and other sequence-comparison programs
The Wikipedia page on BLAST states that:

The scores are created by comparing the word in the list in step 2* with all the 3-letter words. By using the scoring matrix (substitution matrix) to score the comparison of each residue pair, there are 203 possible match scores for a 3-letter word. For example, the score obtained by comparing PQG with PEG and PQA is 15 and 12, respectively with the BLOSUM62 weighting scheme.

I do not understand how they got a score of 15 for PQG v. PEG. What is a scoring matrix, how is it computed, and how is it used?

Step 2 on that page is Make a k-letter word list of the query sequence: “Take k=3 for example, we list the words of length 3 in the query protein sequence (k is usually 11 for a DNA sequence) sequentially, until the last letter of the query sequence is included”.

Hi Vandana - thanks for your question and Welcome to BiologySE! You may want to add some links to your question so that everyone can follow. The more descriptive you can be with the question the better the answer you may get from the community.

This has got nothing to do with BLAST per se. Read about BLOSUM and PAM matrices.

The two most common families of scoring matrices are BLOSUM and PAM. Each of them has a score for every possible alignment combination between the 20 standard amino acids1. They both do more or less the same job but have been derived using different approaches.
BLOSUM matrices

(image taken from Wikipedia)
The BLOSUM matrices are built from actual alignments between very conserved regions of protein families. The score for a given pair of amino acids aligning with each other is the log-odds score measuring how often this particular alignment is found and how often it would be expected to be found by chance:
$$ S_{ij} = \left ( \frac{1}{\lambda} \right ) \left ( \frac{p_{ij}}{q_i * q_j} \right )$$
Where $p_{ij}$ is the probability of finding the two amino acids $i$ and $j$ aligned to each other in a homologous sequence and $q_i$ and $q_j$ the background probability of finding the amino acids $i$ and $j$ in any protein sequence. The $\lambda$ is a scaling factor set to ensure that the matrix contains easily computable integer values.
In simple words, the BLOSUM matrices give you a score based on how often the alignment you observe in your sequences is found in alignments of similar sequences.
There are several BLOSUM matrices which have been computed using proteins of more or less sequence similarity. The most commonly used one is BLOSUM62 which was built using alignments between proteins of $\ge 62\%$ sequence identity. This is a nice middle ground and will do for most cases. If you are comparing proteins that are very closely related, you might want to use a matrix based on more similar sequences such as BLOSUM90 (built from sequences with $\ge 90\%$ sequence sequence identity) and for less conserved proteins, you might use something like BLOSUM45 ($\ge45\%$ sequence identity).
PAM matrices
The PAM matrices are built using a different approach. First, a global alignment (as opposed to the local ones used in BLOSUM) of of a set of sequences sharing 85% sequence identity is computed. Next, a score for the alignment of all possible pairs of amino acids is calculated based on its observed frequency in the aligned proteins. Then, the scores are extrapolated to alignments of different sequence similarity using mathematical tools. The PAM matrices assume a model of protein evolution and score the alignments based on that model.
The PAM-I matrix is the only one that was actually built from real alignments. The rest were obtained by  multiplying PAM-I by itself N times. In PAM, unlike in BLOSUM, the higher numbers correspond to greater evolutionary distances between proteins.

With all that in mind, the scoring matrices are used by BLAST to calculate the score of the alignment. You can think of this score as the sum of the scores of each individual pair of aligned amino acids in your BLAST result.
Useful references:

http://statgen.ncsu.edu/st590a/notes/76_ST590A_100509.pdf
https://en.wikipedia.org/wiki/Point_accepted_mutation
https://en.wikipedia.org/wiki/BLOSUM
http://www.ncbi.nlm.nih.gov/pubmed/21356840

1The non-standard amino acids Selenocysteine and Pyrrolysine are not included in any matrix I know of, probably because they are too rare for any reasonable conclusion to be drawn from statistic analyses.

A scoring matrix is used to compute a score for finding identical 3-letter words or similar 3-letter words that takes into account the liklihood of one being related to another. Although these matrices are empirical, they encompass factors like the number of mutations required (which is why there are different matrices for different extents of divergence) chemical/functional similarity, rarity etc. This produces a more accurate measure of relatedness than the naïve alternative of scoring all perfect matches the same and assigning no score to mismatches. Thus, it will allow better choice of the high-scoring segment pairs (HSPs), referred to in the article you cite.
As @WYSIWYG mentioned, such matrices are used generally in programs comparing sequences, not just BLAST, and there are two main matrices in use — the PAM matrix and the  BLOSSUM matrix — each well documented on-line.
Addendum: Blosum matrices
In response to an overlapping question that is likely to be marked as a duplicate I make two further remarks regarding the Blosum matrices.

There is a more extensive mathematical account of the derivation of the Blosum matrices in a set of slides from Columbia University. I suggest that one starts reading from the page starting “Henikoff and Henikfoff(1991)”.
The BLOSUM-45, BLOSUM-62 etc. matrices have been carefully prepared for sets of sequences with characteristics required by the approach. All one needs to do is decide which one is most appropriate to the sequences one is comparing — for example a higher number will be more appropriate for ‘mammalian v. mammalian’ than for ‘mammalian v. bacterial’. However in multiple sequence alignment (MSA) a position-specific dynamic scoring matrix is often used: after each sequence is aligned, the matrix is recalculated to take into account the actual matching pattern observed at each position. See, for example, this paper by Panchenko and Bryant.


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Genome and Proteome
Due to the dynamism of protein expression, a genome can give rise to different proteomes, but could we say that a proteome comes from different genomes?

Do you mean this in a hypothetical sense, or if it has been observed?

Related: Why is there more variation in proteins than genes?

Yes, different genomes can produce the same proteome.
Imagine a genome that only has a single protein-coding sequence (without splicing isoforms), the rest of the genome is simply regulatory sequences. Whatever those regulatory sequences may be, as long as that single protein is expressed, it'll be the same proteome.
If you consider a single nucleotide difference enough to say two genomes are different, then there are probably quite a lot of different genomes on earth that produce proteomes identical with at least one other genome.

In my opinion a proteome doesn't just which sequences are present, but also how much of each sequence. And you also overlooked the modifications to the proteome which might not be of biological origin but could have biological consequences.

Would you say that affects whether or not different genomes can (theoretically) produce the same proteome?

No, if you want to have a generally valid statement. You can not say: "that a proteome comes form different genomes".
The official (MeSH) definition of the term "proteome" is:
The protein complement of an organism coded for by its genome.
https://www.nlm.nih.gov/cgi/mesh/2016/MB_cgi?mode=&term=Proteome&field=entry

Correct answer according to the phrasing of the question, which aims for "is it generally true" rather than "is it possible" (which I assumed was the question in my answer).

Taking the first two answers into context, you cannot say given two proteomes that they came from different genomes, but as stated above in the first answer, if you consider a single base change to constitute what is a different genome then yes you probably have a lot of different genomes producing the same proteome.
There are a few fallacies here.
Firstly you cannot say based on a single base change that they are different genomes, Consider this, if your body is constituted by 10^13 cells, then from the time you were a zygote, with each turn in replication the replisome constituted by the DNA polymerase, introduced a few mutations in the genome.
Why you ask?
Because the fidelity of polymerase delta is 10^6 meaning that every one million bases it will introduce a mutation (link explaining differences between different types of mutation). But hold on, there are a few repair machanisms involved, this raises the aggregated fidelity to 10^9. Which means that every 1 billion bases you can expect to find a mutation in the sequence.
Are these all different genomes? No, of course not.
These are  somatic mutations which are aggregated over the course of a lifetime. This is why we age, why we get cancer, and why we ultimately die.
Now consider this, your body is constituted by cells which are somehow different from each other based on their DNA sequence, they are also differently specialised to perform different tasks. These specialised subsets among those 10^13 cells produce different subsets of the entire proteome which as a cumulative whole represents the entire proteome of the organism.
Are they producing different proteomes? No, they are producing a subset of a larger whole superset, but the proteins produced are at different levels by all these cells. If you are interested, you can take a look at single cell sequencing
So I hope you understand that the question you asked has few underlying considerations which must be accounted for.
Next coming to the question at hand? Can we start from two proteomes which are the same and say they came from two different genomes even if you ignore the second answer above? Nope.
This is because of how proteins are translated. You can check out the  reference translation here. Translation, the process which converts RNA to protein exhibits codon degeneracy a feature where amino acids are coded by two or more three letter combinations called codons, making the process of translation very robust to DNA mutations.
So finally, to make a very long answer short. Can we start from a proteome and say they came from different genomes? No


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Why do we get 'bags under our eyes'?
Why do these circles form around the eyes if somebody is tired? And why does fatigue express itself around the eyes this way? Can I get eye bags very quickly in another way?

http://www.todayifoundout.com/index.php/2014/06/causes-dark-circles-eyes-sleeping-people-really-tired/
http://www.top10homeremedies.com/how-to/how-to-get-rid-of-dark-circles-fast.html

It's considered a requisite on biology.se that at least some reading/research is carried out and presented with your question. Otherwise it will be closed as homework. The site tour and the help center  provide guidance on how to use this site. Please take a few minutes to read about the kind of questions which are on topic here

I edited your wording. I wasn't entirely sure what you meant with your last question "How can I get it really fast?", so I re-worded that sub question as best as I could. If you are unhappy with the edits, feel free to change or roll back.

I'm sorry I had to change the title from 'why do we get eye bags'

I know that dark circles and bags are two different things with different causes, the dark circles are mostly related to breathing problems while the bags are related to fluid retention, although these answers don't satisfy me which is why I'm still researching.

A possible answer for the first image may be that if you sleep badly you release more of the cortisol stress hormone, which breaks down your skin collagen across your entire body, which makes your skin thinner and reveals the blood behind the dark circles with a dark blue tint.

According to the Mayo Clinic website:

As you age, the tissue structures and muscles supporting your eyelids weaken. The skin may start to sag, and fat that is normally confined to the area around the eye (orbit) can move into the area below your eyes. Also, the space below your eyes can accumulate fluid, making the under-eye area appear puffy or swollen. Several factors can lead to this, including:

Fluid retention due to changes in weather (for example, hot, humid days)
hormone levels or eating salty foods
Not getting enough sleep
Allergies or dermatitis, especially if puffiness is accompanied by redness and itching
Heredity — under-eye bags can run in families

Of the list above, the most common reason is likely heredity.
Sources:

Mayo Clinic, as linked above
http://www.allaboutvision.com/cosmetic/puffy-eyes.htm

http://health.howstuffworks.com/skin-care/problems/beauty/what-causes-bags-under-eyes.htm Good answer +1

@CRags Thank you! I appreciate the feedback-- good or bad! I read that article as well, it was helpful.

authors: Георгий Цакелиди


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Are stem cell lines cryogenically preserved or commercially available like HeLa cells are?
There are HeLa cells, which were taken from sick cancer patient and now is growing worldwide in different laboratories for experiments. HeLa cells can be kept because they are immortal and so they are an instance of immortal cell line.
What about stem cells? They are also immortal. Such cells can be taken from normal healthy person and also kept forever. Do scientists do this? Why don't we hear about it then? For example, they are distinguished in Wikipedia article, referred above.
Are there some special properties of stem cell lines, making them different? For example, being low differentiated they may be useless for experiments.

Firstly they are not cancererous as other cell lines. Secondly under the right circumstances (cell niche, growth factors etc.) you would have an unlimited supply of normal healthy cells. Also because they are undifferentiated they are used for unravelling the components necessary for differentiation commitment to certain lineages.

This is too long for a comment, so I have to write it in here:
Mostly this is because other cell lines are more practical in the lab.
Stem cells are much more tricky to maintain - especially if you want to keep their stem cell properties. They only grow very slow, tend to differentiate when they get too much stress, cellular signals and so on and need special media (these need to be defined, so that they are not containing factors which promote differentiation for example).
For everyday experiments (like expression profiles, experiments on the effects of certain substances on the growth, gene expression or whatever of cells) "normal" cell lines are much more suited as these are much easier to keep in the lab using standard media. Additionally,experiments can be more easily repeated and reproduced, since these cells should behave always the same.

I would the to stress the 'should' in your last sentence, as it not uncommon for cell lines to be contaminated, mislabelled or wrongly annotated. (see article in Nature last week: http://www.nature.com/nature/journal/v520/n7547/full/nature14397.html)

This is written under the premise that the cell lines are identified by suitable methods and that this identity is controlled regulary.

Thanks. But from my point of view, keeping stem cells are of specific interest. For example, we can observe the process of aging, since some of aging theories say about stem cells depletion or damage. What if stem cell cultures live no more than 100 yrs? This would discover explicit lifetime limit hidden somewhere inside them...

There is a limit for normal somatic cells - it's called the Hayflick limit which happens due to the fact that the telomeres get shorter with every division and at some point active genetic regions will be shortened. However, this does not apply to stem cells (at least to current knowledge which is pretty solid here) as these cells have an active telomerase.


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How does one calculate how to dilute a solution to working strength?
If I'm loading a 3.5ul PCR onto an agarose gel, how do I calculate how much of the 6x loading dye to add?

Since its 6x (6 times concentrated), you have to dilute it 1:6, so you add 1ul of 6x dye for every 5ul of reaction.
5 +1=6ul final volume
6ul final volume / 6x concentrated = 1x working concentration
Now the dye is diluted down to a 1x(working) strength.

You want to dilute concentrations to 1x, therefore a 1:6 ratio for dye:reaction.


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How does alternative splicing work?
I am trying to find out what controls what exons are spliced out, and I keep coming across the term cis regulator, but I cannot seem to find a clear explanation of what happens...
Thank you in advance :)
EDIT: to clarify, I have tried to read the Wikipedia article on alternative splicing and I get the main idea (some exons being cut out of the mRNA with the introns to produce the mature mRNA, I think...) but I don't understand the 'mechanism' section, I.e. What controls which exons will be cut out? And what enzymes 'splice' the mRNA- how do they do it in the right place, and stick the mRNA together again?

Just to be clear, do you want to know how alternative splicing works? Have you tried reading the Wikipedia article on it? Can you tell us, what you don't understand more specifically? Actually this is pretty broad...

@Chris thank you for your reply! I have tried reading the Wikipedia article- I get the main idea of alternative splicing (some exons being cut out of the mRNA with the introns to produce the mature mRNA, I think...) but I don't understand the 'mechanism' section, I.e. What controls which exons will be cut out? And what enzymes 'splice' the mRNA- how do they do it in the right place, and stick the mRNA together again?

Can you add  this comment into your question? It would make it much clearer.

21joanna12, look into snRNPs.  These are parts of the splicosomal apparatus and some of them (the U1 and U2, U11 and U12 snRNPs) are also the guideposts that bind near the splice junctions at the end of introns.  These help guide the splicing apparatus to the splice sites. There are also proteins that bind RNA and interact with the splicing apparatus to switch alternative splicing, such as SP proteins.
https://en.wikipedia.org/wiki/SnRNP
https://en.wikipedia.org/wiki/SR_protein
https://en.wikipedia.org/wiki/Exonic_splicing_enhancer
Here's a recent review that might serve as an entry into the literature: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4232567/

I'm a little familiar with U1 - U6 because I just read a paper on splice switching oligos to control splicing of a defective dystrophin gene to skip a frame shift mutation. But I haven't heard of U11 or U12. I still don't understand how cells select specific alternative splicing patterns to produce a specific protein. Could the pool of miRNAs produced by a cell affect alternative splicing in a manner similar to splice switching oligos just by binding to certain splice sites and forcing the spliceosome to find a different site?

There are two sorts of spliceosomes.  The major spliceosome uses the U1 and U2 snRNPs and the minor splicosome uses the U11 and U12 snRNPs.  It is binding of the splice-regulatory proteins that influence where the splices occur.  I have not heard of RNA directly influencing splicing patterns.  I'm very aware of the DMD splice switching using Morpholino oligos - it has great potential as therapeutics for genetic diseases.

The oligo-based methods of altering splicing can take two different approaches.  The most common strategy is to use an oligo to block the binding site of a guidepost snRNP (U1 or U2, U11 or U12).  The other approach is to block the binding site of a regulatory protein, preventing that protein from docking with the pre-mRNA.  It is the latter approach that is interfering with the mechanics of alternative splicing.  The former method, blocking snRNP binding, can cause skipping of an exon that is never skipped by "normal" alternative splicing mechanisms.

And if that exon contains a frameshift or bad stop codon, skipping it can create a protein that retains enough function to still work. Now if we can just get some good delivery methods for getting the oligos into cells.

user137, the arginine-rich peptides, such as (RXR)4, are pretty good.  Moulton HM, Moulton JD. Morpholinos and Their Peptide Conjugates: Therapeutic Promise and Challenge for Duchenne Muscular Dystrophy. Biochim Biophys Acta. 2010 Feb 16. [Epub ahead of print]. http://www.sciencedirect.com/science/article/pii/S0005273610000520

Along the same lines, this published yesterday.  Betts CA, Saleh AF, Carr CA, Hammond SM, Coenen-Stass AM, Godfrey C, McClorey G, Varela MA, Roberts TC, Clarke K, Gait MJ, Wood MJ. Prevention of exercised induced cardiomyopathy following Pip-PMO treatment in dystrophic mdx mice. Sci Rep. 2015 Mar 11;5:8986. doi: 10.1038/srep08986.    http://www.nature.com/srep/2015/150311/srep08986/full/srep08986.html

A review by Penalva and Sánchez explains one example of how alternate splicing is regulated at the molecular level.  There are other possible mechanisms that I am only vaguely aware of.
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/12966139/
Sex determination in Drosophila melanogaster is largely controlled by a cascade of alternate splicing events.
In a brief (and admittedly incomplete) summary, the product(s) of one gene (RNA binding protein) recognize a particular splice site in a downstream transcript.  On binding, that site is no longer available as a splice acceptor site and the splicing mechanism is "forced" to work with the next available acceptor site.  This leads to the excision of the former exon, which has now become an intron.
This process is represented graphically in the above cited review in Fig 3A where female/functional Sxl product (when present) blocks another RNA-binding protein (U2AF) which is involved in default splicing, and tells it to move on to the next available acceptor site.  (I would like to include Fig 3A here but don't know how.  Perhaps this will help: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC193869/figure/f3/)
Sex-lethal gene product exists in male- and female-specific forms, produced by (who would have guessed?) alternate splicing of the Sxl transcript.  The male-specific transcript has an early stop codon and yields a non-functional protein. The female form modifies splicing of the transformer gene product to produce a female-specific (functional) version of the transformer mRNA.  The unmodified (male) version again produces a non-functional protein.  The female-specific version of the tra gene product (wait for it!) modifies the splicing of the doublesex transcript to produce a female-specific doublesex protein.  The unmodified/default splice dsx transcript produces a male-specific protein.  These male- and female-specific proteins lead to male- and female-specific expression of an array of genes further downstream.  By the way, the Sxl gene product not only affects the tra transcript but it also modifies the splicing OF ITS OWN TRANSCRIPT to keep Sxl expression going after its initial onset.  It also plays a role in setting the overall level of X-chromosome transcription to achieve "dosage compensation".
Hope this helps.

the product(s) of one gene recognize a particular splice site in a downstream transcript. On binding, that site is no longer available as a splice acceptor site and the splicing mechanism is "forced" to work with the next available acceptor site.
But what determines which splice site is chosen? Suppose pre-mRNA has exons 1,2,3,4. What determines that in one scenario exon 2 will be skipped, whereas in another scenario exon 3? Do we need a different RNA binding protein for each exon of each pre-mRNA molecule? Or can the same RNA binding protein interact with multiple exons, if yes, how?


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COPI/COPII proteins and kinesins/dyneins
I am considering the transport of protein from ER to Golgi, and have read that this involves the COPII protein coat. I have also read that this is a form of anterograde transport, and elsewhere that kinesins are responsible for anterograde transport as they move from the negative to positive  (outside) poles of the microtubules.
Thus it seemed to me that the kjnesins carry the COPII vesicles carrying proteins from ER to Golgi.
However a Google search of the terms 'kinesins' and 'COPII' together did not seem to yield anything about kinesins carrying COPII.
On the other hand in this article it links COPII with dynsctjn, which I have not heard of before.
Does someone know the link between COPI and COPII transport, and/or retrograde and anterograde transport, with the microtubule motor proteins kinesin and dynein? Where do dynectins come into this? Do they bind the vesicle to the dynein or are they a different type of motor protein? If it is the first case, then why is this transport termed anterograde if it does not use kinesins? Are the terms anterograde and retrograde not directly related to kinesin/dyneins use?

The link in your question doesn't point to any article.

@canadianer Apologies . It seems I did not copy the end of the url link.  I have corrected this now. Thank you for letting me know@

Interesting question. The term anterograde refers to movement in the forward direction. In the context of vesicular trafficking, anterograde refers to (1) movement from the site of protein synthesis in the rough endoplasmic reticulum (RER) towards the Golgi and then (2) movement from the Golgi towards the final destination in the cell.
Both processes rely on microtubules for transport. Microtubules are polar and radiate from the microtubule organizing center (MTOC) with their (+) ends directed towards the periphery of the cell:

There are two broad classes of molecular motors that facilitate directed movement along microtubules. Kinesins are generally (+)-end directed motors whereas dyneins are (-)-end directed:

These images should already give you a hint. Your question may have arisen due to the assumption that the ER is centrally located near the MTOC with the Golgi somewhat peripheral. This is incorrect. In reality, the Golgi complex is actively clustered near the MTOC by movement on microtubules. Furthermore, the ER extends along the microtubule network towards the (+)-end periphery. Taken together, it is evident that microtubule (-)-ends are located near the Golgi and transport to it from any part of the cell, including the RER, requires the (-)-end directed motor dynein. Subsequent anterograde transport from the Golgi to a specific destination in the cell, or through the secretory pathway, requires the (+)-end directed motor kinesin. Retrograde transport from the Golgi back to the ER would also use kinesin:

The article cited in the question (which I also reference in this answer), mentions that COPII vesicles are coupled to microtubules via dynactin. Dynactin is a protein complex that is used to both activate and adapt cargo to dynein (ie COPII vesicles are coupled to microtubules via a dynein/dynactin complex):

Thank you for your reply! Just to make sure I understand correctly, for a secreted protein they would be carried by dynein from the ER to Golgi and then by kinesins from the Golgi to the cell surface membrane? Also, dynactin was entitled in the article as the way COPII bind to the microtubule. What is this third protein?

@21joanna12 Yeah that sounds right to me. I'll edit my answer shortly to address dynactin.


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What impedes the understanding of genotype/phenotype relationship without statistics?
Most genetic research tries to establish a relationship between a certain genotype and certain phenotype.
To me this is like trying to understand a system as a black box, where you try to establish a relationship between a certain input and an output. It seems unnecessary to me because it seems possible - even tough extremely complex - to establish a more mechanical relationship between the box’s system and its environment and make a mechanical model that would always be correct about the box’s outputs based on a combination of inputs.
What is the missing link that impedes science from creating a model of genetics that is 100% certain of the resulting phenotype based on a genotype? Is it just lack computing power due to the complexity of understanding genotype/phenotype as mechanical system instead of probabilistic one?

Perhaps you could clarify what you understand phenotype to mean, and what the determinants of a phenotype are.

The actual answer to this is in your question: "possible - even though extremely complex". Complexity both limits the current level of any science (as in, the more complex the system the more time it takes for scientists to figure it out. Consider the time it took between discovering DNA and sequencing the human genome for example), and even the level of understanding humans could ever realistically achieve (because chaos theory issues). But I think a good answer to this question would give examples of the current state of the science in terms of the mechanical genotype-phenotype relationship.

Many genes are not associated with phenotypes. Your question is not expressed in a contemporary manner. I have answered on the assumption that, in plain English, you want to predict what a gene does.

I’m not sure that this question is suitable for this list, which is intended for questions from students of biology, not questions from students of the physical sciences who would like biology to fit into the sort of framework they understand. However…
First, genetics has been variously defined throughout history — Wikipedia currently has “Genetics is a branch of biology concerned with the study of genes, genetic variation, and heredity in organisms”, but I do not think current research is concerned with “establish(ing) a relationship between a certain genotype and certain phenotype”. Phenotypes are not where it’s at.
I stand to be corrected, but I think the question behind the post can be put simply as:

Why can’t we predict the function of a gene and its product from the
  DNA sequence?

And the answer is simply:

Because the DNA sequence does not provide enough information for us to
  do that. For the benefit of the physical scientist I’d say it’s like trying to determine the value of several unknowns with an insufficient number of simultaneous equations.

Let me use some analogies to explain further.

It’s like trying to assemble IKEA furniture without instructions.
Or, worse, it’s like trying to determine the function of a single component of IKEA furniture without even knowing whether it’a part of a Rågifarsok or a Nässeltrjik.
Or someone thinking that the instructions for a Nässeltrjik will tell you how to build a Rågifarsok.
Or, if you don’t do IKEA, it’s like a person transported in time from the middle ages trying to guess what the blueprint for an internal combustion engine means.
Or for the same person to guess what a screwdriver does.

That’s why biology is an experimental science.


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How many plants or trees should one plant to take carbon dioxide from atmosphere?
I'm interested on computing things. I know that some biologists have done mathematical modelling. Has anyone took any calculations on the following?
How many trees or plants should one plant such that those plants takes more $CO_2$ from atmosphere than human uses in his or her life? Feel free to make reasonable assumptions.