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Why are there two replicase proteins translated from tobacco mosaic virus RNA?
I’m trying to understand how TMV is expressed and have read (here) that there is a large and small form of the RNA-dependent RNA replicase. These are translated from the same region of the genome, the larger arising from read-through of a leaky stop codon.
Why are there two forms of the replicase? My first impression was that each might produce a sub-genomic RNA, one for the movement protein and one for the capsid protein, but can find no reports confirming this.

Many proteins are made up of multiple subunits (look at pretty much any viral capsid protein for instance).

Is it possible that the subunits may have a function different from that of the completed protein? The link I put in the question states 'the small replicase is involved in replication and acts as a suppressor of RNA silencing' - I'm not sure if 'the small replicase' refers to a small subunit or the completed replciase.

Yes and no, both together make the RdRP in full, but one will be the replicase and one have other functions such as capping of transcripts, binding etc. Both will likely have several functions that do all the combined work of the RdRP.

So they are subunits that together have RdRP function, but work independently?

I have edited your question removing all reference to subunits. Subunits occur in proteins with quaternary structure — they are constituents of a larger molecule. There is no (or little) evidence that this is the case here. Certainly the word "subunit" does not appear on the page you reference. This is relevant to their function.

@bob1 Do you have any evidence for your statement "both together make the RdRP in full"? I find none in my reading (see my answer).

@David - it is called the replicase large subunit. If you follow the link and look at the information provided it says Replicase small subunit: is a methyltransferase active in RNA capping and an RNA helicase. and provides a reference. This protein, like many RdRPs, is a heteromer, and there is quite a bit of evidence for these in many species of viruses. You are welcome to add this into your otherwise excellent answer if you like. The small subunit also does host RNA silencing suppression

@bob1 — I need a reference from a research paper, not from a database compiler who may or may not know nothing about the biology.

@David See the reference I linked at the word reference

@David also try this one.

@David for heterodimerism this one

@bob — I've updated my answer regarding this.

Short Answer
As of 2021 the rationale for the production of two proteins from the Tobacco Mosaic Virus (TMV) replicase gene is incompletely understood. The two proteins share some activities but not others, and although they appear to co-operate in the replication process there is a ten-fold excess of the smaller relative to the larger.
Longer Answer
“Why is there a 126-kDa and 183-kDa form of the TMV RNA-dependent RNA replicase?”
My answer is based mainly on the review by Buck (Phil. Trans. R. Soc. Lond. B (1999) 354, 613–627), but includes material from some later sources (e.g. Malpica-López et al. (2018)). Many relatively recent papers related to the replicase (e.g. this from 2008, and this from 2012 tend to avoid this question, confining themselves to describing the properties of the two proteins. The main points are:

Both the TMV-encoded 126-kDa and 183-kDa proteins are required for maximum efficiency of TMV RNA replication. The full-length protein is absolutely required; preventing the production of the smaller protein reduces the replication rate to 20% of normal.
The rate of read-through of the stop codon is about 10%, so that ratio of 126-kDa :183-kDa proteins is 10:1.
The read-through portion of the 183-kDa protein contains amino-acid motifs characteristic of RNA- dependent RNA polymerases (RdRps) and hence the 183-kDa protein is likely to provide the catalytic activity for the synthesis of TMV RNA from NTP substrates.
“The C-terminal domain of the TMV 126-kDa protein is helicase-like. Although helicase activity has not yet been demonstrated for the 126-kDa protein of any tobamovirus, these proteins contain six amino-acid motifs, which are highly conserved in known helicases, such as the translational initiation factor eIF-4A.”
“The TMV 126-kDa protein contains two domains. An N-terminal domain with amino-acid motifs and predicted secondary structure typical of S-adenosylmethionine binding proteins, methyltransferases and guanylyltransferases is probably required for synthesis of the 5' m7GpppG cap structure. The TMV 126-kDa protein has been shown to have guanylyltransferase activity.”
The 126-kDa protein has activity in silencing host anti-virus suppression. The 183-kDa protein lacks this activity, suggesting a difference in conformation relating to the region responsible.
There is evidence for association of two forms of replicase in the replication of membrane-bound viral RNA. However no direct structural information (e.g. X-ray crystallography, cryo-EM) is available for a complex with or without the RNA.

The only suggestion that Buck makes is that as helicase activity is required for two separate purposes — to unwind double-stranded RNA during replication, and to remove secondary structure from single-stranded RNA when this is used as a template for multiple copies of the complementary strand —  the two forms of the replicase may have a different substrate specificity in their helicase activity.
Own thoughts
It is commonplace that the constraints on eukaryotic mRNA translational initiation and the small size of viral genomes have resulted in viruses adopting different strategies for maximizing their coding potential. Read-through is not unique to this class of viruses. I imagine that the replicase preceded the readthrough, in which case one wonders whether the original enzyme was a homo-dimer, which has been superseded by a hetero-dimer with similar protein–protein interaction. The problem here is that the contemporary enzyme has only one active site. Clearly, structural information is needed to address these possibilities.
Footnote: Nomenclature
The original question and some sources (mainly in structural biology) refer to the 126-kDa and 183-kDa forms as subunits of the replicase. Most virological sources do not employ this description, which I think is misleading because it ignores 90% of  126-kDa protein which cannot be involved in replication and therefore does not function as a replicase subunit. It also suggests a level of structural analysis that does not exist. Although replicase enzymes often have several subunits, they are generally structurally distinct. The situation with TMV is different.

Thanks for clearing up the misconception - the page I linked does state 'small replicase subunit' in the genome diagram which threw me off but after reading the attached literature I agree that it's not appropriate to consider the proteins to be subunits.

Ah. Fair enough. I just read it and did a text search. The authors of the page obviously chose their words more carefully than the author of the diagram (although in a diagram one is short of space, so sometimes one does that sort of thing).

The RNA-dependent RNA polymerase of the Tobamoviruses exists as a heterodimer expressed by read-through of the RdRP portion of the genome (open reading frames 1 and 2). The products of these ORFs are two proteins of 183 kDa (large replicase subunit) and 126 kDa (small replicase subunit), with the 126 kDa being produced approximately 10x more than the 183 kDa form. The functions and sizes of the various proteins are described well in Watanabe et al., (1999):

The genome of tobacco mosaic virus (TMV) consists of a single-stranded RNA molecule of about 6,400 nucleotides in length with positive polarity, which encodes at least four polypeptides: 126- and 183-kDa proteins required for transcription and replication (hereafter referred to as the 126K and 183K proteins, respectively), a 30-kDa (30K) protein for cell-to-cell virus movement in infected plants, and an 18-kDa protein for virus coat formation. The sequence of the 126K protein is encoded by the 5′-proximal region of the viral genome and includes the methyltransferase and RNA helicase motifs, while the 183K protein is a read-through protein of the 126K open reading frame (ORF) and contains, in addition to the above two motifs, the RNA-dependent RNA polymerase motif. The RNA polymerase is considered to be involved in both transcription and replication (8). From sequence analysis, it is believed that the viral RNA polymerase contains the 183K protein as a catalytic subunit, but the precise molecular compositions of transcriptase and replicase have not yet been determined.

A common feature of RdRPs in RNA viruses is that they exist as heteromers. A very well known example of this being the RdRP of influenza virus (-ssRNA), which exists as a heterotrimer consisting of the PB1, PB2 and PA subunits produced from the eponymous genome fragments. However, (many) other examples exist in the virus world, including in another plant virus genus Potyvirus, which, in common with Tobamoviruses and 90% of plant viruses, is a positive sense single-stranded RNA virus. The features of the  Potyvirus RdRP have just been published, and to quote the linked article (and references therein):

The RdRp–RdRp self-interaction seems to be a common feature for positive-sense, single-stranded RNA viruses, including insect-, animal- and human-, and plant-infecting viruses [38,49,50,51,52,53]. The dimerization or oligomerization of RdRps may increase the stability of these enzymes and protect against degradation.

As you can see from the information provided in the top quote, the functions of the different subunits of the protein are different but complementary. The 126 kDa contains a helicase and methyltransferase motifs, while the 183 kDa functions as the polymerase as well as containing the same helicase and methyltransferase motifs. Lewandowski and Dawson (2000) found that the 183 kDa subunit was capable of performing all the functions listed above, acting as the full RdRP, but with the 126 kDa subunit those functions were performed ~10 times faster. They also found that mutating a base in the helicase domain of the 126 kDa (183 kDa supplied by a helper virus that only expresses the 183 kDa form) resulted in no replication of the RNA with the mutant 126 kDa indicating that this protein is essential to RNA replication. It should also be noted here as per comments, that the evidence for heterodimerism of the two forms is not in the form of a crystal structure, but in a 1:1 stoichiometry in immunoprecipitation as discussed in the Watanabe paper linked above. To my knowledge no-one has produced a full crystal structure of the RdRP of any Tobamovirus.
However, as you might have noticed when you looked at the information on the link you provided, that there seemed to be only about 4 ORFs, and a small number of proteins produced, and you might be thinking something along the lines of

"how does a virus manage to work when it only produces so few
proteins?"

The answer to which is viral proteins perform many functions (this feature isn't specific to viral proteins). In particular, the small subunit (126 kDa) seems to act as a suppressor of the host silencing RNA system (siRNA). siRNA systems in plants function a bit like an immune system response - they signal within the cell and extra-cellularly to induce a viral RNA degrading response, so that the virus can not easily spread or establish itself in the host. I would speculate that what better place to suppress siRNA functions than at the site of viral RNA replication itself.

It should be pointed out that influenza virus is a completely different type of RNA virus, with a segmented genome. The RNA polymerase subunits are the products of separate segments are produced in similar amounts. Their relevance to the situation in TMV therefore not escapes me.

While there does seem to be evidence that both the smaller and larger proteins are part of the replication complex (e.g. co-immunoprecipitation), I don't see any direct evidence here that "The RNA-dependent RNA polymerase of the Tobamoviruses exists as a heterodimer ..."  It certainly may, but the wording "subunit" to me implies obligatory binding to perform its function. The smaller protein also seems to be synthesized in 10x greater amount than the larger protein.  It makes sense to me that the smaller protein could function on its own and may also bind to the larger protein.

@Armand well, those that study the protein themselves call it a heterodimer. It does have 1:1 stoichiometry in the IP, which is pretty strong evidence that it is existing as a heterodimer. It is called the subunit as it is transcribed from the same ORF unit on the TMV genome I suspect. No-one knows why 10x amount produced. It is definitely the large product that contains the RdRP bit.

@David I did point that out -ssRNA tells about the form of the genome (negative sense single stranded RNA), agreed it doesn't tell about the host(s), but I think most people recognize that flu doesn't infect plants. TMV and related viruses are in their own family, so there isn't anything exactly similar. If you like I can provide examples from +ssRNA, and dsRNA and non-segmented genomes too. The idea was that heteromerism is a common feature of RdRPs. I'll edit that to explain more clearly.

Re: "They also found that mutating a base in the helicase domain of the 126 kDa (183 kDa supplied by a helper virus that only expresses the 183 kDa form) resulted in no replication of the RNA with the mutant 126 kDa indicating that this protein is essential to RNA replication."  I think their inference was that the 126kDa acted on the RNA strand it was synthesized from ("in cis") so that the defective 126kDa was blocking replication of "its" RNA. The other experiment showed replication even without the 126kDa (at 10x reduced level), indicating the 126kDa was not "essential" to RNA replication.


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Calcium ions and bacterial transformation
What is the mechanism by which calcium ions and heat treatment allow the bacterial membrane to become permeable, allowing the uptake of plasmids?

DNA has an overall negative charge. The phosphate heads of the lipid molecules that make up the cell membrane, along with the LPS molecules on the outer membrane, are also negatively charged. This means the plasmid is normally repelled by the cell membrane.
What Ca2+ ions do is shield the negative charges on each side, making the overall situation electrostatically neutral.
This site has a nice animatic for this process: http://www.dnai.org/b/index.html

Thanks owlofathena

There are two things that need to be corrected in your answer. The first is that the effect of calcium is on the bacterial cell wall, not the cell membrane. The second is that "lipid" should be replaced with the specific membrane constituent of Gram-negative bacteria — lipopolysaccharide. There is a short Wikipedia entry for calcium chloride transformation.

You're right that I should have included LPS along with phosphate groups as contributing to the negative charge on the cell surface. That was sloppy of me. Edited. Thanks!

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Why isn’t prokaryotic mRNA modified post-transcriptionally like eukaryotic mRNA?
Eukaryotic mRNA is subject to addition of a methyl-guanosine cap at the 5’ end, addition of 100-200 adenosines to the 3’ end, and splicing. Why don’t these occur in prokaryotes? Is it because there is no exonuclease and intron in prokaryotes?

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Before posting a question it is important to make sure it is scientifically correct and clear. Your title referred to post-translational modification and there was no mention that you are talking about mRNA. Having corrected that, we see that 1. you are asking about three distinct post-transcriptional processes, 2. It is not clear what you mean by "why" — do you want to know the function of each (which are described in any text) or some basic reason why mRNA (and its translation) has evolved differently in eukaryotes or prokaryotes? The latter can only be speculated on.

Does this answer your question? Why do some bad traits evolve, and good ones don't?

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qPCR precipitation
I have performed DNA precipitation using two methods on an amplified 194 bp PCR product:

using a PEG method
with just cold 80% ethanol

PEG worked much better for me.
Can the same methods be applied to qPCR products? If not, could someone propose a way of doing that? I am in the exploration stage, and I am trying to learn different experimental techniques.

You need to provide some more information: What is your PEG protocol? How big are the qPCR products you want to precipitate? How much yield do you expect (this can make a big difference in the methods you can apply)?

@Chris thanks for your reply.  To answer your questions. 1) First stage, 1:1 Peg/ PCR Product volume and two washing stages with 75% ethanol. At the end of each stage, I performed spinning at 4oc / 15000rpm for 15 mins, disposing of the supernatant, and finally, letting the pellet dry (open tube lid for 15 mins at room temp). 2) The qpcr product is also 194bp. 3) The yieldiest, the better. I just want to practice.

I would say, in general the answer is yes, with caveats.
Firstly, remember that the optimal amplicon size for qPCR is small, so you can expect lower yields.
Secondly, what is the primer concentration that you use in qPCR? If the primer concentration that you found to be optimal for the purposes of quantification is low, then the amount of the final product will be that much lower, as at some point, qPCR will run out of primers to produce new amplicons.
Thirdly, if you’re using probe-based qPCR, remember that you might have non-specific amplification there that doesn’t show up on the amplification plots, because there is no probe hydrolysis when the non-specific product is amplified. If you’re using DNA-binding dye-based qPCR and your melt curve gives you a single peak, you can be relatively sure that you have just the one PCR product (although, theoretically, you could still have two that just happen to be of the exact same size).
A tip I can offer is that for the precipitation of tiny amounts of DNA (or RNA) it is a good idea to add some molecular biology grade glycogen (or glycoblue, which is glycogen stained blue to make the pellet more visible) – provided your downstream applications aren’t glycogen-sensitive. Although I only used glycogen in isopropanol/ethanol precipitations, I’m not sure whether / how it would interact with PEG.
Hope this helps.


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Arrangement of Amino Acids in the Protein alphabet
I am a software engineer with little knowledge of molecular biology. However I am trying to understand some bioinformatics computer code where the protein alphabet appears to be represented as the following string, with each of the twenty amino acid constituents of protein:
ACDEFGHIKLMNPQRSTVWY

The code appears to define a second string in which the first is reordered as:
DEKRHNQSTPGAVILMCFYW

I am not sure of the biological significance of this. Does this reordering represent some specific interaction between these molecules?

Welcome to Biology.SE. Have you looked at a table of amino acid properties? There are many ways of grouping amino acids, so if it isn't documented why that order is being used I doubt anyone can give you a definitive answer beyond the trivial 'ordered by physicochemical properties'.

@tyersome But the mapping given by the OP doesn't appear to be based on physicochemical properties at all?

@user338907 — What makes you say that? DE = "acidic", KRH = "basic" etc. (see also acvill's answer), you seem confused there is no mention by the OP of this being a mapping ...

What is the context? HPLC? Mass spectrometry? 2D gels? Sucrose gradients? Protein folding? What kind of analysis?

OP is probably referring to this.

That is exactly right @voile
I have been looking at the DeepSequence paper and its implementation where you have related protein sequence aligned with each other and one is trying to develop a statistical model over their distribution.

I rephrased the question to align it to the accepted answer and to avoid a biologically misleading title. Although not a Python devotee, looking at the code in the link given by @Voile it would appear that I am incorrect in my comment that these are not strings. The answer would seem to be that the second string has been reordered on the basis (better a particular assignment) of amino acid properties. Why strings are being used in this way is not evident to any molecular biologist, or anyone else without analysing the code.

@Luce Thank you for your contribution. As the algorithm for the paper you refer to is neither standard or self-evident, I for one would find very useful if you could provide an answer explaining it.

@David So I analyzed the code a bit and this reordering thing seems to be a red herring. Must be hangover of some old code as it does not seem to be used anywhere...

@Luca — Strange. I'll have a look at it myself perhaps. I am having to work on someone else's Django code at the moment, so I might as well try to suss out the Python. If it beats me I have friends I can lean on. This whole thing would have probably been better on SE Bioinformatics, although I don't go there much.

Ah right...yes, did not know about that SE!

As suggested by tyersome's comment, the amino acids are grouped by their physiochemical properties. Let's add some commas:
DE,KRH,NQ,ST,PGAVIL,MC,FYW

aspartic acid (D) and glutamic acid (E) are acidic
lysine (K), arginine (R), and histidine (H) are basic
asparagine (N) and glutamine (Q) are amidic
serine (S) and threonine (T) are hydroxylic
proline (P), glycine (G), alanine (A), valine (V), isoleucine (I), and leucine (L) are aliphatic
methionine (M) and cysteine (C) are sulfur-containing
phenylalanine (F), tyrosine (Y), and tryptophan (W) are aromatic

My source is this graphic.

Thank you! Lots to take in!

I am the person who came up with that reordering and I can confirm that acvill is correct. Specifically, the hope was that in heat maps relating the sequence to other properties like colours would show up in clusters. It actually does not work that great but it's the best you can do arranging them in one dimension.

I have deleted my previous comment about strings as it transpires, to my surprise, that the computer code contains the two 20 amino acid sequences as strings. So your answer might be modified to say that "the second string contains the 20 amino acids arranged so that those of similar physiochemical properties are grouped together". The reason for constructing such strings can only be discerned from an understanding of the computer algorithm.

@David I will contact the authors and update the thread.


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What is bacterial (prokaryotic) cell division called?
Eukaryotic asexual cell division is sometimes referred to as mitosis, although this is more strictly used to refer to the specific stage at which “the replicated chromosomes separate into two new nuclei”.
The term is specific to eukaryotic cells, as prokaryotic cells have no nucleus. Is there a corresponding more specific term technical term that applies to prokaryotic cell division?
I thought this might be related to “binary fission”, but an internet search indicates this can be applied to eukaryotic organisms, such as starfish and other echinoderms.

Comments are not for extended discussion; this conversation has been moved to chat.

Fission, binary fission, cell division: these are all used more or less as synonyms for prokaryotes. "Fission" and "cell division" are more general, because they include mechanisms resulting in more than two resulting cells or an asymmetric division. As a supporting example from the literature, consider this paper:
Angert, E. R. (2005). Alternatives to binary fission in bacteria. Nature Reviews Microbiology, 3(3), 214-224.
Right in the title: "alternatives to binary fission", where binary fission is taken to be the standard prokaryotic division strategy, and in the abstract:

Whereas most prokaryotes rely on binary fission for propagation, many species use alternative mechanisms, which include multiple offspring formation and budding, to reproduce

The same terminology is used for organelles in eukaryotes.
Mitosis itself also involves "fission", and though the term isn't used as often with eukaryotes it does come up in some cases, like in contrasting "fission yeast" (Schizosaccharomyces pombe) from "budding yeast" (Saccharomyces cerevisiae).
Terminology in biology isn't always strictly standardized. Standards tend to proliferate and language itself is not strict. In biology there is a tendency to conform with the terminology others have used in order to keep consistent in the scientific record in which publications build on previous work; there's little motivation to generate a new term to refer specifically to prokaryotic division if existing language used to describe it is sufficient. It's rare that there would be confusion between fission of multicellular organisms like echinoderms and fission in single cells, so there's no need for a separate term. If you're having trouble with your search results, you could try adding other keywords like "bacteria" or "prokaryote" to focus your results, or using excluded keywords with the minus sign, like:

"binary fission" -echinoderm

which on a search engine like Google to only return results without the word "echinoderm" in the result; testing that myself in a Google search only excludes about 10% of the total, though. If you're using Google, I wonder if you've also recently searched things about echinoderms and that's influencing your search results. You can try using another search engine that doesn't track your past like duckduckgo, or using Google's incognito mode to not use your history in your results.

I'm not sure that a discussion of search engines is relevant to your answer, and the specific context from the comments suggests the poster needs different advice. If he wishes to find English terms when his computer defaults to German he would be advised to use Firefox as a secondary web browser and set its primary language to English (while retaining German in a different primary browser). Then he is likely to see English terms. 2. He can search Wikipedia in German and then switch to the English version in the left column. I use these techniques with the various languages I work in.

I think your answer would be improved by a linguistic explanation of the meaning of the basic terms, "fission" and "binary fission", neither of which are Anglo-Saxon in origin. The Wikipedia article on the subject states "Binary fission means 'division into two'", and reference to dictionaries hardly extends the meaning of "fission" beyond "division".


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Would it be possible to genetically modify a plant to produce usable antibodies? And if eaten would they be used?
I am thinking of a project where i would Gene edit a plants cells to produce anti bodies that humans could use. Does anyone know
A. what genes to modify?
B. Would the antibodies be usable after ingestion?
C. What plants should be used?
(I know next to nothing about botany)

Possible duplicate https://biology.stackexchange.com/q/56131/27148

Welcome to Biology.SE. This is not simply an answer site, but instead a site that promotes self-learning with some expert help. Consequently, questions that show little or no prior research effort are off-topic on this site. In addition, questions must be focused — you have three distinct questions. Please [edit] down to a single question, tell us where you've looked for answers (including links to related questions on this site), what you do know about the topic, and where exactly you still have questions. Please take the [tour] and consult the [help] starting with [ask] for details.

To answer the "plants producing antibodies" part:
Yes.

in 1989 scientists developed a technique to genetically alter a
tobacco plant so it would produce monoclonal antibodies

Researchers had to adjust the West Nile virus antibody to adapt it for production in Nicotiana benthamiana, a relative of tobacco:

"We altered the genetic coding of the antibody slightly, not changing
its parts but using alternate forms of the coding for those parts to
maximize the plant's ability to produce it," says co-senior author
Qiang Chen, Ph.D., of Arizona State. "We also stabilized the antibody,
preventing copies of it from being degraded inside the plant cells.
Together, those two techniques increased our average antibody yield by
60 percent above any previous efforts."

Although, the study acted as "proof of concept", the antibodies in question were only a partial success:

They found that one important receptor was binding appropriately, but
the strength of a second receptor's bond was lowered.
"This results from the fact that plants combine their proteins with
slightly different sugars than mammals," says co-senior author Michael
Diamond, M.D., Ph.D., professor of medicine, of molecular microbiology
and of pathology and immunology at Washington University. "We're
already working on genetically modifying the plants to humanize the
sugars the plants combine with the antibody's proteins."

The (successful) release and usage of ZMapp in 2014 against West-African Ebola virus outbreak virus furthered the public awareness of the technology.


text:
Why is ATP hydrolysis to ADP, rather than ADP hydrolysis to AMP, used to drive biochemical reactions?
ADP has two phosphate groups, and can be hydrolysed to AMP in a reaction which involves a similar free energy change to that of hydrolysing ATP to ADP.
Why is the latter reaction, rather than the former reaction, coupled to energetically unfavourable reactions to provide an overall reaction with a negative change in Gibbs Free Energy?

I have edited the question to change it from one of fact (that the poster could have checked) to one of evolutionary biochemistry, which I think is more interesting.

Ah sorry, in my original question I wasn’t implying that ADP->AMP wasn’t as energetic as ATP->ADP, I was asking about the evolutionary biochem question to which you corrected it! Thanks!

The larger molecule (ATP) is easier to handle in biological systems.

Summary
The original question was edited — with the approval of the poster — so that in brief it now asks:

Why is ATP hydrolysis to ADP, rather than ADP hydrolysis to AMP, the
  normal way in which cells drive reactions which alone involve positive changes in Gibbs
  Free Energy?

The scope of this is wider than that originally assumed in the answer from @user1136, but he has also contributed to this answer by his comments, which I have incorporated into my revision.
To my knowledge there is no generally-accepted provable answer to this question (as opposed to listing advantages for the system as it works today). What I shall do is present a hypothesis that could explain this situation. The fundamental idea† of this is that:

The contemporary use of ATP rather than ADP in energy transfer
  reactions evolved from a preference for NTPs, rather than NDPs, as the
  precursors of RNA synthesis. This preference was a result of the fact
  that the conversion of NTPs to NMPs and pyrophosphate could prevent
  the reversal of this (and other) synthetic processes in a way that conversions  liberating phosphate could not.

AMP, ADP and ATP: Standard Free Energies of Hydrolysis

There is general agreement that the values for ∆G°′ (standard free energy change at 37˚C) for the hydrolysis of the terminal phosphate bond of ATP (β-γ) and ADP (α-β) are similar. (The following are from J.L. Jain, et al.:
ATP → ADP + Pi  –7.3 kcal/mol
ADP → AMP + Pi  –7.3 kcal/mol

Hence, there is no intrinsic energetic difference that might explain the preferential use of ATP over ADP as an ‘energy donor’ in biochemical processes, i.e. it is not evident why e.g.:

Glucose + ATP → Glucose 6-phosphate + ADP

and not

Glucose + ADP → Glucose 6-phosphate + AMP

And, as @user1136 mentions, there are examples where the energy of the hydrolysis of ADP to AMP can be used to ‘drive’ other reactions. He mentions polynucleotide phosphorylase, to which I would add  adenylate kinase, as this is not a synthetic process and is pertinent to the energy metabolism of nucleotide phosphates:

ADP + ADP ⇄ AMP + ATP

The introduction of AMP into the discussion raises the question of the value of the ∆G°′ for the following reaction:
ATP → AMP + PPi

Many texts quote a value only slightly greater (ignoring the minus sign) than those for phosphate release (the one cited quotes –7.7 kcal/mol), but a 1995 review of the situation in the Journal of Biochemistry suggests that the difference is actually greater: –10.9 kcal/mol, as opposed to –7.8 kcal/mol for the hydrolysis of ATP to ADP and Pi.
The relevance of this is considered in the next section.
Biosynthetic processes and ATP
It seems to me that the example of polynucleotide phosphorylase is especially pertinent because it is a biosynthetic process in which the nucleotide monophosphate is actually incorporated into the product.

[AMP]n + ADP → [AMP]n+1 + Pi

However this ADP-driven non-template dependent synthesis of polynucleotides is not model for template-dependent RNA synthesis, one reason being that it can also operate in the reverse direction as a phosphorolytic 3ʹ to 5ʹ exoribonuclease reaction:

[AMP]n+1 + Pi → [AMP]n + ADP

Irreversibility is an important feature of template-dependent synthesis of RNA¶, and it is thought that the key to this is that fact that ATP is the substrate and is cleaved between the α and β phosphates liberating pyrophosphate rather than monophosphate.

[NMP]n + NTP → [NMP]n+1 + PPi

The reason generally proposed to explain why this reaction is irreversible is that in the cell pyrophosphatase hydrolyses the pyrophosphate to phosphate in an exothermic reaction. However the problem in evolutionary terms is that pyrophosphatases would have to evolve before this would work. However, if the ∆G°′ for pyrophosphate release has a greater absolute value than that for phosphate release, this in itself would affect the equilibrium of the reaction in a manner favourable to synthesis, albeit at the greater effective cost of an extra ATP. The later evolution of pyrophosphatases would have served to reinforce and enhance the irreversibility.
The Hypothesis
The hypothesis is that nucleoside tri-phosphates developed early in evolution to provide a means of making nucleic acid synthesis essentially irreversible by a mechanism that generated pyrophosphate. As the example of polynucleotide phosphorylase shows, nucleoside di-phosphates do not allow this.
A priori it would seem that there is no reason why ATP rather than ADP should be preferred for coupling biochemical reactions. However, if one accepts the argument that ATP synthesis was required for nucleic acid synthesis, there would seem no reason for having a set of reactions generating ADP for other purposes. The energy of hydrolysis of ATP to ADP in such reactions would, in any case, have to be utilized, otherwise it would represent a net loss. Why go any further?
It may have been that ATP was preceded in evolution by an an earlier ‘energy donor’. However I would suggest that once a mechanism evolved for synthesizing and using ATP (and other NTPs) for synthetic purposes, it was more efficient to use this for metabolic purposes, largely displacing any previous energy donor molecule.
† Footnote 1
I have touched on this very tangentially in my answer to a quite different question about ATP. The common idea, however, is that the purine and pyrimidine rings of NTPs serve no purpose in energy transfer, but are a relic of their requirement in RNA synthesis, where the NTPs are not merely providing energy, but are incorporated into the RNA product.
¶ Footnote 2
RNA and DNA synthesis are not the only synthetic processes in which this strategy for irreversibility is adopted. The tRNA amino-acylation reaction — essential for protein synthesis is as follows:

Amino Acid + ATP → Aminoacyl-AMP + PPi

And the first step in glycogen synthesis is the formation of UDP-glucose:

Glucose 1-phosphate + UTP → UDP-glucose + PPi

@user1136 — Thanks for that — have downloaded the paper and will read it. Sounds the sort of thing that must have been discussed in TIBS at some stage. It is interesting in that it would provide less reversible phosphodiester bond formation without the hydrolysis of pyrophosphate, which one might suppose developed subsequently in evolution to lock things down. I'll revise my answer when I have a moment.

This is amazing, exactly what I was wondering!

Just updated as promised. To try to make the argument easier to follow I relegated certain points to footnotes. Happy to be informed of any typos or mistakes.

It can, and a very famous example is polynucleotide phosphorylase, an enzyme of great historical importance in the elucidation of the genetic code.
That said, it is very uncommon, and polynucleotide phosphorylase is the only example that I know of (but other users may be able to provide additional examples).
There is certainly no thermodynamic reason why the 'high-energy' bond of ADP cannot be used as a source of free energy.
Polynucleotide phosphorylase was discovered in Ochoa's laboratory by Mairanna Grunberg-Manago. The story goes (from memory) that Ochoa was very dismissive when Grunberg-Manago told him that the enzyme uses dinucleotide phosphates, rather than trinucleotide phosphates, and he told her that her conclusion was impossible. He later realized his mistake and apologized, and the biosynthetic activity of the enzyme provided a simple and elegant method for making short RNAs that were used to unravel the genetic code.
(I do not have the source of the above story 'to hand' (as I am on holiday). Perhaps someone can help me with a more authentic account of the story? Otherwise I'll 'dig out' the original source in the coming days).

Wow, that's really cool! If there is no thermodynamic reason, is it just by chance that life didn't really evolve to use the ADP->AMP pathway that much?

ATP can be hydrolyzed to AMP and pyrophosphate and the pyrophosphate is then subsequently hydrolyzed to phosphate. This is used by some enzymes to ensure the irreversibility of their reactions.

To be clear, I wasn’t critiquing your answer but rather adding some additional information that might be helpful to... someone.

@SullyChen — I don't think so. See my answer. BTW user1136, could you consider changing your name to something more memorable.

ATP -> ADP is easier to break than ADP -> AMP. I dont think i can explain why without invoking third-year chemistry notions of electron orbitals ...
Conceptually, the terminal phosphate link on the triphosphate is more unstable than the terminal one on the dipeptide, and so breaking this bond and liberating this bond energy to do work is easier, and the amount of energy is a small and useful amount. Breaking high energy bonds is harder, and if the energy released is in excess of what is need it can cause undesired side reactions.
Metabolism is step-wise to keep the unit of energy at appropriate level.

Please quote standard Gibbs Free Energies of hydrolysis to support your statement. And perhaps you would like to explain what dipeptides have to do with this.


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Why does oxidative phosphorylation require complexes 2 and 3?
I am learning about oxidative phosphorylation in cellular respiration now and do not understand the roles of complexes 2 and 3 in the process. Specifically, my textbook says that 2 and 3 pump H+ out into the inter-membrane space, just like complex 1 does.
Complex 1 pumps out the H+ from NADH, and I suppose that 2 would be needed to pump out the H+ from FADH2, but then why do we need complex 3? All the H+ has been pumped out already--there's none left!
Also, if this understanding were correct, there would be no purpose for the chain that started with NADH to go through complex 2 at all (because it already went through 1, as opposed to the chain starting with FADH2).
Thanks in advance for any clarification you can give.

Complex II does not pump H+. What textbook are you using?

"Chemistry: The Central Science, 13th edition".

The numbering of the complexes in the respiratory chain is confusing, as it creates the impression that the chain is structured like
Complex I $\rightarrow$ Complex II $\rightarrow$ Complex III $\rightarrow$ Complex IV
... but this is wrong. There are in fact several ways of feeding electrons into the respiratory chain. They all begin with one enzyme E that oxidizes an electron carrier in the mitochondrial matrix, such as NADH, FADH2, or ETF (electron transfer flavoprotein) and transfers electrons to coenzyme Q, which is then processed by Complex III, after which electrons are handed on to Complex IV. Both complex III and IV pump protons. But there are several options for the first enzyme E:

Complex I (NADH dehydrogenase). This handles all electrons from NADH (from many sources in oxidative metabolism) and is typically the major source of electrons in the chain. It is the only enzyme E that also pumps protons itself.
Complex II (succinate dehydrogenase) accepts electrons from succinate (a step in the TCA cycle).
ETF dehydrogenase accepts electrons from reduced ETF, notably from fatty acid oxidation.
Glycerol-3-phosphate dehydrogenase accepts electrons from cytosolic NADH (from glycolysis) via the glycorol-3-phosphate shuttle.

There are more alternatives, but I think these are the most important ones. So you are absolutely correct that when NADH is the substrate, Complex II is not involved. There is in fact not one respiratory chain, but several possible chains with different starting points E,
E $\rightarrow$ Complex III $\rightarrow$ Complex IV
You might think of this as a "fan in" structure where the various enzymes E all converge on Complex III. (I don't have the energy to draw this :)
As for the proton pumping at Complex III, it is not the case that the H$^+$ pumped are exactly those derived from NADH --- the system is more complicated than that. The respiratory chain(s) convert chemical energy from the redox reactions into potential energy (a proton gradient), but most of the H$^+$ pumped are obtained from the mitochondrial matrix. The exact number of protons varies depending on the substrate: for example, the 2 electrons donated by NADH at Complex I is sufficient to pump up to 10 protons. Actually, the stoichiometry is not fully understood, and there isn't really an exact integer number of H+ pumped, because this pumping is an imperfect physical process --- there is leakage, protins slipping back into the matrix etc.

Complex 1 pumps protons, but Complex 2 does not. Both, however, take electrons from the electron carriers (NADH, and FADH2) and transport them inside the membrane to Complex 3. At Complex 3, the electrons are transferred via the Q-cycle to Cytochrome C which resides on the exterior of the membrane. In the process of transferring the electrons to Cytochrome C, Complex 3 also pumps protons. Cytochrome C moves from Complex 3 to Complex 4, where Oxygen functions as the final electron acceptor, while more protons are pumped.
Also a little clarification, Complex 1 and Complex 2 both donate the electrons to coenzyme Q 10/ubiquinone which is solubilized in the membrane. Complex 1 does not donate its electrons to Complex 2. Coenzyme Q/ubiquinone is what enters Complex 3.
Edit:
Complex 2 only accepts electrons from succinate oxidation to fumarate. ETF, and Glycerol-3-Phosphate dehydrogenase function much like Complex 2 in that they donate electrons to coenzyme Q without pumping protons. However, unlike Complex 2, these two enzymes are not trans-membrane proteins. ETF is associated on the matrix side of the inner mitochondrial membrane, and Glycerol-3-phosphate is associated cytosolic side of the inner mitochondrial membrane.

I think this is inaccurate on Complex II, it is not a generic acceptor of reduced FAD. As I understand it, complex II contains a bound FAD cofactor, but this functions like prosthetic group and is exclusively devoted to oxidizing succinate; it cannot accept reduced FAD from other sources. FAD from fatty oxidation, for example, goes via ETF dehydrogenase.

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At what point during an organism’s lifespan do mutations occur?
I’m a software developer and I’m implementing something called a Genetic Algorithm. I would like some input on when during an organism’s lifespan mutations occur.
Genes mutate throughout the lifetime of an organism. When do the bulk of mutations, which would effect the offspring of an individual, occur? Do most mutations happen at conception and early adolescence, or do a significant number happen between adolescence and parenthood?

it is not so much when as to which cells, only mutations to germ line cells get passed on the the next generation and they can happen any time. https://en.wikipedia.org/wiki/Germline_mutation#:~:text=A%20germline%20mutation%2C%20or%20germinal,together%20to%20form%20a%20zygote.

@John I suppose that it varies between the sexes (in humans at least), since males only produce sperm during puberty, whereas females produce eggs effectively from birth, right?

Are you asking just from curiousity, or because you intend to make your implementation mimic life?  If the latter, my advice is not to bother: life is not the optimal way to implement GAs.

Well, in general, mutation happens after selection, and before fitness evaluation in a GA. I was curious if there was any biological basis for this. Seems like, based on MikeyC's answer, it does make sense to to do mutation before calculating fitness.

I'm assuming this question is primarily interested in heritable mutations, given the evolutionary nature of the link you shared. Only mutations in germ cells are heritable, so it will vary between males and females.
Female germ cells are formed in utero. Oogenesis in humans and is pretty much finished by 20 weeks gestational age (there's some debate about this, but it seems to be the current consensus view). So any heritable mutations would need to happen during gestational period. Note that that gestational age number probably varies quite a bit for different animals, but I think it's generally completed before gestation is completed (in mammals at least).
Males produce gametes via spermatogenesis continuously throughout life. So, for modeling purposes, you could probably use the age at which they conceive (though the sperm actually take a couple of months to mature).
One thing I'm unsure about is whether or not aging in the male affects the mutation rates in sperm, but might be something for the OP to look into.


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CML (Chronic Myeloid Leukemia) and blast cell percentage
I'm trying to understand the oncogenesis of CML. I have a question about CFC cells and blast cells. Are those the same? I know that in the chronic phase of CML there is a blast percentage of 1-10% of blast cells in the blood. Considering that the total amount of WBC is around 1x10–11 cells/l. That means the blast cells should be around the same order of magnitude. Looking on research articles I found that the amount of CFC (which contains according to my understanding all of the blast cells) are only 1x10–8 cells/l. Thus comprising around 0.1% of the blood count.
What cells can be considered as blasts? Only the myeloblasts? Are all blast cells CFC cells?
I also know that the average value of CFC cells in the bone marrow is around 10–5 cells, so how can they be 10–9 cells?
Reference:
https://pubmed.ncbi.nlm.nih.gov/9922073/

Not to be rude, but are you sure you read the article?  Figure 1 describes the CFU ontology and defines CFC as experimentally-determined CFUs.  Table 2 describes the relative number of each CFU per 10$^5$ marrow cells.  Those numbers are much closer to your 0.1% figure than the 1-10% value expected during chronic-phase CML.  Re: your final question, leukemia is pretty much defined by immature cells leaving the marrow, which would elevate the PB levels.  Ta-da!

I did read the article, but I'm learning about leukemia to make inter-disciplinary research, it's not my field of expertise. I am pretty confused about the percentages. If the CFC build up <1% of the cells in the bone marrow and immature blast cells are contained within the CFC compartment, how can they be present at 10% in PB? The only possible solution for me is: The 10% blast cells compromises not only the CFC but other types of cells. Which other types of cells? It seems that every article assumes a definition of blast cells I just don't find anywhere. Thank you for your help.


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Are the bacteria in the stomachs of unborn babies beneficial?
Babies are born with bacteria in their stomachs. I heard on The radio that when a child is given antibiotics for the first time unique bacteria in the stomach are destroyed and cannot be replaced. Is this true, and, if so, does this have negative effects on the health of the newborn?
Closely Related, but different: What bacteria do unborn babies contain?

It's a fascinating topic! While most of the bacteria known to colonize babies comes from the vaginal tract during birth and then later, through breastfeeding, although there is evidence to suggest that microbial colonization may begin before birth.
Regarding what these bacteria are, our microbiomes are composed of probably hundreds of species of bacteria from at least four major phyla: actinobacteria, proteobacteria, firmicutes and bacteroidetes (see the review for more on them).
As for taking antibiotics, I find it highly unlikely that taking antibiotics would completely destroy any native gut flora species. I certainly can't find any evidence to suggest that that might be the case. In general, when we have to take antibiotics, the offending bacteria are a relatively small population, compared to our native species and are less well-adapted to our body environment. Antibiotics work with our own immune defenses to clear our system of pathogenic species. Antibiotics also hurt our native flora, but less so than the ones that make us sick.
As for your last question regarding health, I wouldn't exactly say that having a microbiome promotes better health, so much as that your microbiome is critical for survival and health. There are actually nutrients that we need for survival that we cannot digest without our microbiota and a wide number of diseases, from immune disorders to potentially depression, can arise from an unhealthy microbiome.
As a fun bit of trivia to ponder in parting, our bodies are composed of 90% bacterial cells by count. Sweet dreams...  :-)

The 90% bacterial cell number is most likely too high by an order of magnitude. See this paper.

I think you missed one important part of the question - the claim that antibiotics destroy bacteria in the body. They don't - not by far. They can affect the balance of bacteria (some are more affected by that particular antibiotic than others), and they reduce their populations and do a bit of selection, but they simply can't kill all of even one kind of bacteria. If they could, antibiotics would cure any bacterial infection instantly, which simply isn't the case - they just tip the fight in your favour. Not to mention that many parts of the body aren't easily accessible by antibiotics.

Interesting fact : Knowing that a baby born by caesarean is not likely to come in conatact with useful microbes of the vagina of the mother, Rob Knight, a microbiologist applied them on his baby with a swab from his wife's vagina !

Good point, @Luaan! I definitely missed that. Thanks for adding to it. In future, I'll try to keep my answers to daylight hours, when I'm most awake. ;-)

Your answer has some errors (probably just phrasing) in it. For example, babies are not born colonized with all sorts of interesting bacteria. They acquire them at birth, which is very different (also stated clearly in the paper you cite.) This is a science site. Accuracy is valued.

@anongoodnurse, which of the sources are you referring to? I'll of course correct any errors, or just remove the answer if it doesn't stand up, but in the first  reference, the authors state: "It was previously thought that the in utero environment was largely sterile and that a fetus was not colonized with bacteria until the time of birth. Recent studies suggest the presence of a microbiome within the placenta as well as fetal meconium, suggesting that the colonization process begins well before delivery." This suggests that colonization begins prior to birth.

Suggests is the key word. The preceding statement is thought to be correct: "Colonization of mucosa in the digestive, respiratory, urogenital tracts, as well as the skin begins at, or perhaps even before, the time of birth when a newborn is exposed to a mother’s microbiota." There aren't really good studies yet about in utero gut microbiomes, but a lot to suggest otherwise at this time. If you have a some good studies to support your statement (there wasn't any reference cited in that article), I'm very interested in reading them. Thanks.

@anongoodnurse - fair point. I've edited my answer to better reflect the ongoing research into pre-natal bacterial colonization. Also to address a point raised earlier, by Luaan.

@biogirl He also convinced four other moms to do the same, apparently. There is also this recent paper claiming that OR dust might seed the infant microbiome, but I always worry about contamination in these really low biomass studies.

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text:
Have the potential therapeutic applications of cell fusion between cancer cells and neural cells been investigated?
Studies have appeared on the possible role that cell fusion plays in the formation of certain cancers. For instance, Sitar et al. (2019) have looked into the process of cell fusion in the formation of erythroleukemia.
However, research has also been done on the potential therapeutic effects of cell fusion to tumour immunotheraphy, see e.g. this article by Pedrazzoli et al. (2011) and this one by Sullivan and Eggan (2006). For instance, in the former an article by Guo et al. (1994) is mentioned in which researchers fused B-cells with carcinoma hepatoma cells to create a vaccine, which resulted in hybrid cells that lost their tumorigenicity and became immunogenic.
I am interested in a particular type of heterotypic cell fusion. More specifically, I am curious whether biomedical research has been done on the potential therapeutic applications of fusion between neurons and different types of cancer cells. My reasoning is as follows: neurons in the brain do not renew themselves through cell division processes that occur in many other parts of the body. So if neural cells fuse with cancer cells (that grow and divide more quickly than normal cells), the resulting hybrid cell might have lost some of its carcinoid properties - including its tendency towards rapid proliferation.
Question: has any research been done on the potential therapeutic applications of cell fusion between neural cells and cancer cells? If so, can you point me towards a relevant reference?
Note 1: I am a mathematican, not a biomedical/pharmaceutical scientist or a biologist. If my reasoning seems seriously flawed, please enlighten me on the matter. I did try to perform a literature review and hope this question is appropriate for this venue.
Note 2: This question was also asked on Medical Sciences Beta SE a few months ago. A user on that venue suggested I'd ask it over here, as s/he asserted there are more experts related to the field on this SE page.

This is a site for questions about biology, whereas yours is about history, at best, or an attempt to start a discussion, at worst.

@David I've added the "Literature" tag to make it clear this question is a reference request. If no papers on the topic exist, an answer explaining the plausible reasons behind that would suffice from my point of view.

Tags do not determine suitability of questions for SE Biology. Any User with a certain reputation can invent a new tag. The description of the purpose of the site in the [Tour] and the Help on asking questions does. That makes it clear that this is a question and answer site about problems in biology. A reference request is not a problem in biology.

@David I think the question is okay, it shows some prior research, though like any similar question it's far harder to provide an answer that says "no, this idea doesn't make a lot of sense" that fits our site guidelines.


text:
Oncological applications of a leadership detection algorithm for moving cell populations
In the article ``Detecting switching leadership in collective motion" by Butail and Porfini (2019), the authors propose an algorithmic method to automatically detect leaders among groups of moving animals. The leaders are the invididuals within this group whose movements largely direct the movements of their followers. At the same time, the movements of the followers do not affect the leader's movements.
While tracking animal leadership seems interesting and useful to me in some research or conservation contexts, I have another possible application of this algorithm in mind. I believe this algorithm may also be employed to detect leader cells among cancer populations. Previous academic research has indicated that certain cell types among cancer clads during metastasis (spread to a secondary site within the host's body) act as leaders. For instance, in the work of Saénz-de-Santa-María et al. (2020), the authors show that the presence of leader mesenchymal cells is significantly associated with metastasis development, recurrent disease, and low overall disease survival in head and neck squamous cell carcinomas.
Moreover, in a review article by Qin et al. (2021), the authors note the importance of both leaders and followers in collective cell migration. The leader cells are identified as specialized front cells that assume a ``finger-like" structure. The follower cells comprise the majority of the collective, and are located in the cell reservoir. The authors note that recent studies suggest that not only leader cells, but also follower cells become specialized during the polarization process that enables collective migratory properties. (More information about the role of cell polarity in collective migration can be found here.) Both leader and follower cells are depicted in the image below, which can be found on page 1267 of Qin et al.'s article.
$\qquad \qquad \qquad \qquad \qquad $
Various techniques from automated image analysis have already been employed to spur oncological research. For instance, van Ineveld et al. (2022) describe a number of 3D imaging methods that drive cancer discovery. These include light sheet technology to study blood and lymphatic vasculature. This can be useful, as blood and lymphatic vascular systems provide gateways for whole-body tumour dissemination. Other techniques include whole-body 3 imaging techniques (including CUBIC, 3DISCO, and DeepMACT) allows for the study of late manifestation in cancer, which enables quantification of metastasis. In yet more recent work by Holme et al. (2023), the authors describe a technique to automatically track cell migration in phase contrast images - as opposed to fluorescence images.
I highly the suspect the leadership detection algorithm developed by Butail and Porfini can play a role in cancer research. It can automatically detect leader cells from a series of images of moving cancer cell populations. Unfortunately, I am not a biologist, but a mathematician. I thus find it hard to pinpoint exactly how this algorithm can propel cancer research forwards.
Thus, my question is:

What biological, clinical, or pharmacological applications does a functioning leadership detection algorithm for migrating cancer cell populations have in oncological research?

I don't know that it does - there's no conscious decision in cells migrating, so the "leadership" is unlike that found in a game of soccer/football.

@bob1 True, but cells don't make conscious decisions about most of the things they do, right? Yet it is of importance to be able to understand what mechanisms lie behind cell behaviour, in order to drive biology and pharmacology forwards

How do the papers cited in Qin et al. (2021) identify leaders? Is their method easy or difficult? What sort of data do you need to apply your algorithm? Hours of invasive live-cell imaging? If it's easy or your method is hard, what's the point of an algorithm?

@BryanKrause I've tried contacting a number of the authors cited by Qin et al. Many appear to be busy at the moment - it's still close to the start of the academic year. I believe an algorithm can save time - especially in the long run, when it is improved upon in various various ways (detection of multiple leaders, 3D detection instead of 2D, etc.). It can also potentially identify the moment at which cells become leaders - thus providing more insight in the process of cancer metastasis

@MaxMuller Where are you going to get the 3D data from? You should read the methods sections rather than trying to contact authors.

@BryanKrause There are more and more 3D imaging methods that are employed in oncological research. For instance, in the paper "3D imaging for driving cancer discovery" (2022) van Ineveld et al. name a number of techniques that allow for three dimensional imagery of the human body for cancer research, including light sheet technology, whole-body imaging (CUBIC, 3DISCO, DeepMACT), confocal and multiphoton microscopy, and multi-marker imaging.

@MaxMuller Don't you need 4D imaging?

@BryanKrause Light sheet technology has been applied at a high temporal resolution to be able to observe movements in 3D within organisms, see e.g. "High-contrast single-particle tracking by selective focal plane illumination microscopy" by Ritter et al. (2008)


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Complete human rDNA sequence
I've been trying to retrieve the complete human rDNA sequence (non-spacers and spacers), which should be about 43-kb in length using Biomart, NCBI, and rnacentral, but I have only been able to find the 13-kb non-spacer sequence. Are the spacer regions not yet sequenced due to difficulty in sequencing a repetitive region? Thanks for your help.

Managed to find the complete sequence of the repeating unit:
https://www.ncbi.nlm.nih.gov/nuccore/U13369

In 1.1 version of (since that version) "Complete genome" assembly of homo sapiens (never achieved before) compared to 1.0 (previous version) 5 last gaps (all somehow in the rDNA) were fixed and now it all is there!
https://genome.ucsc.edu/cgi-bin/hgTracks?genome=t2t-chm13-v1.1&hubUrl=http://t2t.gi.ucsc.edu/chm13/hub/hub.txt
https://www.ncbi.nlm.nih.gov/assembly/GCA_009914755.3
Delta from 1.0 version is there https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/changes/v1.0_to_v1.1/v1.0_to_v1.1.chain and delta from patch 13 of GRCh38 is here: https://t2t.gi.ucsc.edu/chm13/hub/t2t-chm13-v1.0/hg38Lastz/t2t-chm13-v1.0.hg38.over.chain.gz

To the best of my knowledge, of the estimated  500 copies of rDNA repeats in the human genome only 1 and half repeats has been sequenced and published. Mammalian rDNA repeats are hard to clone and appear unstable in yeast and e coli.

Great, that's useful to know. I assume that there must be mutations in at least some of the noncoding regions that would enable positional information for certain sequences.

Yes, there must be sequence variability in the non-coding region. However as rDNA arrays are rather unstable and recombine within a yeast or ecoli host. Hence isolating rDNA repeat array and making a rough map of rDNA repeat arrays is next to impossible.

Reference in support of this assertion please. I thought methodological developments in sequencing meant that this situation could be dealt with.

Welcome to the "gaps" in human genome. Parts of the genome of eukaryote that are very difficult to explore must less experiment with. Here is a reference but it does quite cover recombinational instability of repeat arrays that prevent other methods to study them.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5098217/


text:
What is the primary energy source for sprouting plants?
To what extent are young plants powered by the potential energy stored in the seeds and when does solar energy take over? Are there other energy sources involved?
I was observing sprouts in a germinator [is this a word?], pushing up the lid after being left alone over three-four days. As this is a considerable amount of work (for such young plants) I wondered how long the plant can access the original energy stored in the bean/seed and how it compares to the amount of energy it can get. As you can see in the picture, the sprouts have only access to water and some sunlight.
I suspect the potential energy it draws somehow decreases monotonically (perhaps linearly, quadratically, exponentially?) over time, while the solar energy pics up.
Is this mental model correct?
I'd appreciate an answer that a non-expert can understand.

I think these were radish sprouts, but my question is more general.

This depends largely on the plant, some seed stores can last a very long time, but a few general trends can be discussed.
sprouting plants run off stored carbohydrates in the seed, they are using respiration, photosynthesis begins as soon as they are able and they will switch over to it as quickly as possible it is however gradual as the plant never stops using respiration it just starts using photosynthetically produced sugars instead of stored ones. The stored energy will run out so the faster a plant can stop relying on it the better, so even a small production is helpful, you yest it is a gradual process, even if it is a fast gradual process ins some plants.

Your first question has an easy answer.
Q: "when does solar energy take over?"
A: as soon as a green part of the plant receives sunlight. Chlorophyll is the main light-harvesting pigment, and responsible for the green color of the plant.

Clearly. But is it the primary power source for the early development? The surface area of the plant is comparably small and it's just beginning to develop leaves.


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Is there any example, where cooperative behaviour of predators induce fear in prey population?
I am basically from math background and doing Ph.D in mathematical biology. So I am not so efficient in biology. But my problem based on cooperative behaviour of animals during hunting which is related to the animal behaviours in ecology.
We know that different animals show cooperative behaviour during hunting (or, group hunting) such as wild dogs, lions, chimpanzees, birds, spiders, crocodiles etc.
We also know that fear of  predator (predation risk) reduces the  growth rate of prey population. Now, I am looking for
example(s), in which prey population does not fear predator but cooperative behaviour of predators induces (creates) fear in prey.

Are you asking for exemples when a particular prey species is "normally" not afraid of predators, unless/until the predators displays a (cooperative) behaviour to induce fear?

@fileunderwater  Yes, you got my point. Could you please give me any example related to this phenomenon?

Are you asking a question about prey psychology or prey behavior?  i.e. is it "fearful" behavior that is your focus?

Maybe relevant, in relation to fear: https://biology.stackexchange.com/questions/42497/are-there-any-animals-that-gradually-approaches-the-predator-to-search-for-food/42499#42499


text:
What is this plant's scientific name?
This is the picture of a tree in my college's botanical garden.
First I thought it to be a banana tree for its leaves but then seeing its lower part, I don't think it is a banana tree. So what is it's scientific name? I am just curious. Is it any hybrid or something like that plant?
Edit: This tree is from Bangladesh in South Asia. This tree is approximately 9-10 feet (I think, I cannot go near the tree). This picture is from Spring season.

Please [edit] your post to provide your location and the approximate size of the plant. See here for guidelines for writing well-received [tag:species-identification] questions. Thanks

The name of this plant is:
Ravenala madagascariensis
Check: wikipedia

It is not a banana . I have seen them but don't know the name.

@blacksmith37 edited my answer

@Muath It's plant not planet


text:
Growth rate oscillation in the a population of non-interacting bacteria
I have come across this theoretical paper claiming that if you start a batch culture from a single E. coli cell, the exponential growth rate of the population defined as $$k = \frac1N \frac{dN}{dt}$$
could oscillate for as long as 30 to 40 generations. In this equation, $N$ is the number of cells, and $\frac{dN}{dt}$ is the rate of change of the number of cells with time.
My question is:

Have these oscillations been ever observed? This seems like a very simple experiment. Looking for references.

Edit: As mentioned in the paper, the "oscillations are hidden to the optical density measurements which provide a proxy for the total mass of the population" and not the number of cells.

The theoretical article concerns growth rates of single cells. There are many studies that model cell cycle as a non-linear oscillator (see Tyson and Novák, 2015).
However, growth rate measurements in microbiology are usually done on cell populations consisting several cells. You generally do not observe any oscillation because:

Cells are not synchronized
There can be variations in growth rate of different cells because of noise
The measurement time points are much larger than the period of oscillation

Some of these reasons are already mentioned in the paper you linked (Jafarpour, 2019).
I do see some ups and downs in the growth rate in my own data; E. coli growing in LB in a 96 well plate.

X-axis is the time in seconds; measurement was made every 15minutes. Y-axis denotes difference in OD between two consecutive measurements. The different colors are biological replicates. However, I cannot say that this is the kind of oscillation that Jafarpour talks about. It appears more like stochastic fluctuations in growth rate or measurement errors (they are also not damping by the end of growth).


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DnaA binding energy to E coli genome
I have been told that DnaA binds strongly to DnaA boxes on the E coli genome, but binds weakly to 8 out of 11 sites near ori. I want to know more quantitatively what strongly and weekly mean. Are there order of magnitude estimates of binding energies of DnaA to various locations on the E. coli genome?

I would suggest searching the literature for answers, I didn't instantly find binding energies but I could readily find dissociation constant estimates.

@MaximilianPress Thank you, this is helpful. I had done a quick search and hadn't found anything, but I wasn't searching for dissociation constants, which is equally useful. Feel free to post this as an answer, and I will accept it.


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genetic variance
A.Very very few traits have their variance explained only by the genetic variance,
B. even fewer are explained only by variance at a single locus and
C. yet even fewer have a locus that show a simple dominance / recessivity pattern.

What does genetic variance mean in (A)? does it imply that environmental factors are at play
So does (B) mean that mutliple genes affect traits?
Does (C) mean that multiple alleles are at work as opposed to simply 2 alleles?

by the way, i'm not a science student, so explaining it in simple terms would be appreciated. thanks.

I understood your question because I wrote the answer from which you took the quotes and I saw you having misunderstanding but no one else will understand your question. I am sorry if I am being too pedantic with you today. Can you please 1) use > symbol at the beginning of a quote to highlight it is a quote and 2) indicates where your quote is from.

FYI, when you think an answer answered your question, you can click on the checkmark next to the answer.

What does genetic variance mean in (A)? does it imply that environmental factors are at play

Yes and other things. For more information, have a look at Why is a heritability coefficient not an index of how “genetic” something is?

So does (B) mean that mutliple genes affect traits?

Yes, often many loci are involved in explaining the phenotypic variance.

Does (C) mean that multiple alleles are at work as opposed to simply 2 alleles?

multiple alleles or some other relationship between the two alleles than recessivity/dominance (such as additive, underdominance or overdominance, incomplete dominance). There might be epistasis among loci too.

Thanks Remi, I appreciate the answers and will follow the posting protocol in a better way. I read the above captioned post and it went over my head. In a nutshell apart from genetic and environment factors, do you have a list of other factors at play in affecting traits?

The "What is heritability coefficient not an index of how 'genetic something is?" post  expounded on the concept of genetic variance. In essence, the two factors that affect trait phenotype is environment and genetics.

Genetic variance, environmental variance and other things as explained in the section Other sources of phenotypic variance


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Why do we value species that are on the brink of extinction?
As I understand, biodiversity has two benefits:

Species might be a functional part of the ecosystem, e.g. balancing other species' numbers or beeing part of the foodchain.
Species with diverse abilities make sure that "life as a whole" can adapt to changing environments.

These hold true for most species currently alive. For species that have only a few thousand or even a few dozen exemplars left, neither function seems to be achievable. Yet there is a wide consens in protecting such species - what's the reasoning?

The concept of benefit depends upon what we ethically judge to be good. In those terms, biodiversity has other benefits (and, arguably, drawbacks) that are very unrelated to biology such as an appreciation for richness and pretty landscape for example. A sense of guilt and melancholy toward extinct species plays a big role in what species we decide to protect as a society. Hence, the reasons for protecting a species go way beyond biology and those reasons cannot be discussed on a biology website only.

I'm voting to close as off-topic because the question asks for justification of political decision that go beyond the field of biology.

This seems like a question for philosophy or political policy, not biology

I agree with all the comments above, but also think it is a valid question. Besides the value of biodiversity for both ecosystem function and aesthetics, the use of species as indicators of whole ecosystems, and the moral values we impose upon ourselves, it can also be said that we can never know if a species may hold some property that we will need for our own survival.


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human sight at 1000x while looking into the mirror
I noticed that my eyeballs have the ability to see in what appears to be 1000x.
Setting the conditions: Look into a mirror while in a well lit room. (for me the lighting in my living room as opposed to the bathroom was not as direct and offered a better focus)  Position your face with your nose touching the mirror. Look at the twinkle of light that reflects off your eyeball. Stay focused on that twinkle with both eyes. Now, pull your face away from the mirror in order to focus your vision.  Position that twinkle of light directly to the center of your eyeball.
At this point that twinkle of light starts to look like a patch of cells under a microscope.  My left and right eye are different images.  My question: Am I looking at the cellular array that makes up my retina?   Eric McBrearty

What color and shape is the image? Red equal spaced cells? A different visual effect at 1000x is If you look up into the blue sky long enough, and with enough attention, you should be able to see tiny blue-white dots flashing around the sky.The phenomenon was so well-known that it acquired the nickname "blue-sky sprites," and they're actually white blood cells moving through your eye.

Not sure why this is gathering close-votes as "personal medical question". This is a common phenomenon that many people have noticed and has a non-personal  answer to it. com.prehensible alludes to a similar phenomenon in his comment above. I vote to keep open, and I hope someone takes the time to write a good answer here :)


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The role of atomic theory in biology
Feynman writes, in his Lectures on Physics Vol. 1, Chapter 1:

The most important hypothesis in all of biology, for example, is that everything that animals do, atoms do. In other words, * there is nothing that living things do that cannot be understood from the point of view that they are made of atoms acting according to the laws of physics.* This was not known from the beginning, it took some theorizing to suggest this hypothesis, but now it is accepted and it is the most useful theory for producing new ideas in the field of biology.

He would have written this around 1961-1963. Was he right then and/or is he right now? Is what he says applicable for the entirety of biology (say evolutionary theories) or only for a subset of biology?
Would Feynman have been referring to a few specific advances or to the general state of biology at the time?
Please note that this question comes from an (interested) amateur to both physics and biology, I hope the question is appropriate for this site.
Edit: Perhaps this will clarify the intentions behind my question:
I would be interested to know how much atomic theory actually helps biological research. For instance, it often happens that the specific low level details are not necessarily important for explaining the high level theory. A nice example is abstract algorithms vs implementation in programming languages vs hardware implementation. Is this the case with biology or do the details of atomic theory matter? For instance, have advances in physics led directly to new biological discoveries?

Did the original claim repeated In other words twice or is it a typo?

Yes it is still true for all of biology, of course physics has expanded a bit, and likewise we have discovered cases of biology exploiting these new parts, for instance photosynthesis might involve quantum tunneling.
Feynman's quote basically restating that there is no magic or supernatural aspect to biology, no vital essence or spirit required to explain how it works or seperate living matter from non-living, it is all just chemistry and physics. The most complex chemical process ever discovered but still just chemistry and physics. Of course he does not mention chemistry becasue of course chemistry is just physics as well, the laws of physics control both, so saying it is a result of atoms obeying the laws of physics expresses both.
He is saying biology is still obeys the laws of physics and are made of atoms, this is true for all of biology, but as Feynman points out took some time to be accepted, keep in mind this is the time of the Miller–Urey experiment which showed organic molecules could form through entirely non-biotic means, which was not as widely accepted at the time as many think, especially to a general audience. Many similar discoveries a t the time were showing the same thing, there was nothing special about biological molecules or their interaction. things like evolution is the inevitable result of the interaction of basic properties (reproduction and heredity)just as a salt crystal is the inevitable result of the interaction of charge of sodium and chlorine. Vitalism still hung around in the popular mind and a few corners of academia at the time Feynman was growing up so taking a few moments to help dispel this notion in his lectures makes a lot of sense, especially given how much advancement was done by abandoning it.

@charles I have read it actually, and explaining what the quote means is important for understanding its application, you seem to be reading far too much into the quote.

Your last paragraph is the kind of thing I was looking for. I would also be interested to know how much atomic theory actually helps biological research. For instance, it often happens that the specific low level details are not necessarily important for explaining the high level theory. A nice example is abstract algorithms vs implementation in programming languages vs hardware implementation. Is this the case with biology or do the details of atomic theory matter? For instance, have advances in physics led directly to new biological discoveries?

that is two separate questions which would be far better answered as there own formal questions. A formal questions they will also be educational for us all, as I suspect others will have farm more examples that i can provide. .


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Why does this genetic pedigree show an autosomal dominant allele at one generation but not another?
Questions 186-188 of the GRE Biology Practice Test are prefaced with this genetic pedigree:

Questions 186-188 refer to the following pedigree for the inheritance of a very rare human disease over three generations.

It looks like the allele that caused the "affected" phenotype was dominant because Generation II showed a 3/4 probability of having the phenotype, and it looks like it was autosomal because it affected males and females roughly equally. This is confirmed by the answer to Question 186 ("Which of the following is the most likely mode of inheritance for the disease trait?") which is "(D) Autosomal dominant".
However, why don't the offspring 1, 2, 3, 4, and 5 in Generation III show a similar rate of expression?

Don't pay attention to probability in pedigree analysis. The number of offspring is too small. Just look for things that can't happen and use that to rule out modes of inheritance

@DeNovo I guess that makes sense, but questions 187 and 188 (see link in the question) talk about probability, so how do i go about answering them?

I don't see those questions quoted here, but that's usually a two part question. Part one may require you to determine an inheritance mode, or most likely inheritance mode from a pedigree. Part two may then require you to demonstrate some additional knowledge about that inheritance mode (e.g. what is the probability that the offspring from this individual and that individual will express some trait).

Why don't the offspring 1, 2, 3, 4, and 5 in Generation III show a similar rate of expression?

Because there are only 5 individuals in that list. The entire generation III involves 8 individuals (all the offspring of one affected and one unaffected parent). The entire pedigree involves 12 offspring of an affected and unaffected parent.
When you look at III 1-5, you see 1/5 affected (0.20).
When you look at III 1-8, you see 3/8 affected (0.375).
When you look at all offspring of an affected and unaffected parent, you see 6/12 affected (0.50).
As you increase the number of offspring you consider, the proportion affected gets closer to the expected value of 0.5. Given a very rare autosomal dominant condition (i.e., I-2 is most likely heterozygous), this is exactly what would be expected. You may have to look at fruit flies, or some other prolific organism, to see it quite so clearly. Mendel looked at tens of thousands of pea plants, if I recall.
Generally, you shouldn't use the proportion of offspring that show a trait to rule out any particular mode of inheritance, especially if you're looking at a small number of offspring. You can state the probability of a particular child expressing a mendelian trait. That doesn't mean a small sample won't deviate from that probability.
You can read more about this in chapter 7 of Thompson & Thompson Genetics in Medicine.


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Why is cDNA usually lacking in terminal sequences of the template mRNA?
It appears from presentations I have attended that cDNA often lacks terminal sequences (usually 5′) which have not been copied from the mRNA. This puzzles me a lot, but I have not been able to find the answer as the focus of most of the sources I have consulted seems to be the principle, rather than practicalities.
Does reverse transcriptase just fail to finish copying the mRNA sequence, and if so, why? Or what is there some other problem? ?

I have edited your question to show you the sort of style that is preferred here to help you frame any future questions. First describe the background, and then state the question clearly, indicating why you have been unable to find the answer yourself, as @uhoh has mentioned. Try not to personalize it. Our aim is to provide answers to questions of general interest that will be useful for others besides the poster.

Traditionally cDNA cloning used an oligo(dT) primer that binds to the 3′ poly(A) tail of a mRNA and extends towards the 5′ end of the mRNA.
What makes it difficult for the reverse transcriptase to copy right to the 5′ end is the fact that this has secondary structure which has to be unwound. This is a general feature of eukaryotic mRNAs, as evidenced by the fact that in the initiation of translation during protein biosynthesis there are specific factor(s) to perform the unwinding in an ATP-dependent manner.
In addition, during the subsequent steps to prepare the second cDNA strand, trimming of the 3′end of the single-stranded cDNA can occur. Various strategies are now employed to avoid this.

As far as truncations at the 3′end, I am not sure there is anything specific one can say — at least I do not know of anything.


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Vision and signal through the nervous system: Is it Frequency Shift Keying?
I have questions regarding the signal between the retina and other parts of the brain. There are two types bipolar cells which are excited by light or darkness to the retina.
Question: Do these form different signal frequencies over the nerve channels?
This is my understanding from resources.
Wikipedia states:

Retinal ganglion cells spontaneously fire action potentials at a base rate while at rest. Excitation of retinal ganglion cells results in an increased firing rate while inhibition results in a depressed rate of firing.

It’s my understanding the photoreceptors in the eye have an opsin pigment molecule which experiences a change in geometry when an electromagnetic wave passes through, pushing on the photoreceptor’s body.  A potential difference in voltage occurs which causes the photoreceptor to release glutamate, an exciting neurotransmitter, or GABA an inhibitory one to the electric synapses of the bipolar cells via synapses.
One type of bipolar cell gets excited by light while the other inhibited.  Either one releases a neurotransmitter to the synapses of an ion channel.  The ion channel creates potential difference, sending a signal or action potential through from the soma, to the axon, to dendrites and to its receptor destination. The above quote suggests that the action potential is “frequency shit key” modulated, with a baseline frequency, then a higher or lower frequency depending on presence of a particular light wavelength.  The photoreceptor outputs an exciting neurotransmitter with no light, inhibitory with light.

In the edit, you've added a couple of other questions, we deal with single questions, one per post. Ideally you can place the others in their own threads, and link back here to the place you've shown your researches.

Frequency-shift keying is an electronic communications approach, part of a broader set of frequency modulation strategies for conveying information.
These strategies relate to the difficulty in communicating over what is really a single available physical channel: the electromagnetic spectrum. If you're communicating by radio or other similar frequencies, you can't really sort out an individual signal from all the background except by knowing something about its structure and using that structure to filter out the noise.
It seems like you're trying to apply what you've learned about these forms of electronic communication to brains. However, none of that is necessary in brains, because each neural process represents a separate physical channel. There's no need to encode and decode signals that way: communication within the nervous system is massively parallel.
Sometimes "rates" and "frequencies" are interchangeable concepts, but not here. When people talk about a "firing rate", they literally mean a rate: discrete events. See for example "rate code". More action potentials means more neurotransmitter release at the end of an axon. No frequency encoding or decoding is necessary. Different messages are conveyed through different "cables". This is also called the "labeled line principle" or theory: the idea that information in nervous systems is conveyed largely based on the physical structure of where it comes from and where it transmits to. There is no difference in the electrical properties of an axon conveying information about one part of the visual field versus another, except that they are connected respectively to a part of the retina and a part of the brain each also dedicated to processing information about that part of the visual field.

Thanks, I wasn't aware of how parallel the axons were and ion channels.  So everything comes in parallel from the bipolar cells after the retina?  I also understand there is multiple layers in geniculate which may do some signal processing between both eye images for a side itself before reaching the visual cortex.


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Quantifying species detection probability using sign surveys as a function of distance in known occupied sites
I ran a pilot study to determine the probability of detecting a rare African small carnivore using scat (feces) detection dog surveys to assist with future population monitoring and occupancy surveys. A primary objective is to determine the search effort (in kms traveled with sniffer dog) needed to have a 95% probability of detection. I trained two dogs over two seasons and tested the method on a telemetry monitoring site and all surveys were within known home-ranges from four collared animals (true site occupancy is known). Rectangular walking transects ranged from 1.6 to 3.2 kms in length. We recorded distance from start of transect to each scat found. We found 112 scats ranging from 0-5 per transect. Species ID was confirmed through DNA barcoding, I intended on doing individual ID, but could not get lab funding, thus only have species detections. I am a field biologist and it has been quite a few years since my MSc. I am struggling to find examples that are similar to my data structure and aims for guidance. Resources for direction or suggestions for data structure and programs/packages would be useful.

Welcome to the site. May I recommend that you take a [tour] and visit the [help] for more information on this site and about composing a good question/answer.

I'm assuming that you are looking to be able to detect unknown populations of this animal? If so, it seems to me that to get a 95% level you would need to test this on areas which are outside as well as inside known ranges, unless the animal has some very specific environmental requirements for habitat. Did you see this one? https://onlinelibrary.wiley.com/doi/pdf/10.2981/wlb.00393

This might be a better for fit for CrossValidated, or for the r-sig-ecology@r-project.org mailing list. Are you essentially trying to compute the expected effort required to detect at least one scat during a set of surveys?

I will check those lists thank you. I only surveyed in known HRs to control for Occupancy to evaluated detection probability (prob of detecting at least one scat) as a function of effort (in kms moved) and influence of co-variates (dog, weather etc). Thus as distance increases, detection probability should increase. I also want to do the same with spotlight distance sampling (visual observation). The goal is to provide survey recommendations for EIAs and presence/absence surveys to develop habitat suitability models.


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Does eating bananas help digestion?
I don't know what I am asking is silly or not, but I have always heard that eating a banana after a meal helps in digestion.
Some people says before food while others say after.
Is it a fact or some silly myth?

I just ate bananas on their own by a 300km bicycle tour, and they did not help by the digestion...

This question is on-topic I think but it would also be a very good fit on skeptics.SE if you can prove it is a notable claim.

This question appears to be off-topic because it is better suited to Skeptics.SE

I have heard same for Papita.

Bananas seem to contain lots of dietary fiber that help move consumed food through the intestines (popular article) thereby promoting digestion. Whether one should eat bananas before or after dinner is probably a debatable subject (Yahoo forum).


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How do I perform recurring pattern mining or regular expressions of nucleotide sequences?
I am interested in performing nucleotide sequence pattern-mining (regular expressions) which is 12 characters (sequences) in length from a dataset. Is that possible to script using MATLAB?

Dont use MATLAB for this.. it is too damn slow for these stuff.. Add more details on what do you want to search exactly and what is your input file like.

You can use Perl, Python or Awk for this kind of stuff (all of them have regex searches). Awk is my favourite; it is fast and doesn't require too much of code writing.

Alternately you can use R (search for regular expressions in R language), which allows you to construct your mining results in a format of a table, which each column containing the data you are interested! there are many packages in R that allows you to process many data types. I would say R is worth the investment to learn for any future data analysis. I use the RStudio to interact with the R language software.

For python, the Bio.motifs package from BioPython could be useful: http://biopython.org/DIST/docs/tutorial/Tutorial.html#sec244

With awk it is as simple as this (Assuming that the sequences are in fasta format and the sequences are not interrupted by line breaks):
awk -v p=<some_patttern> '/>/{name=$0} !/>/{
    s=$0
while (match(s,p)){
       print name,substr(s, RSTART, RLENGTH)
       s=substr(s, RSTART+RLENGTH)
    }

}' fastafile.fa

This script will print all matches for a pattern in a given set of sequences.I cannot explain how this script works in this forum; Stackoverflow would be more suitable for that.

I'm no expert in MATLAB but I know that it is possible to do regular expressions in MATLAB with the general rules explained here. However there are alternative approaches and softwares you could use to achieve this with softwares that are freely available and quite powerful in performing such functions. Although I'm aware that perl and python are the programs of choice for regular expression analysis; however I would urge you to consider the R language. R allows you to construct your mining results in a format of a table, which each column containing the data you are interested! there are many packages in R that allows you to process many data types. I would say R is worth the investment to learn for any future data analysis. I use the RStudio to interact with the R language software.
The best place to get help for MATLAB or R is the http://stackoverflow.com which you can sign on with you current account. In fact I have asked a few questions there on regular expressions and the community is very helpful however ensure that you show your attempt at the problem and where you are stuck in order to get a constructive responses!