CharonY

Considering the large amount of wrong statements in the OP, it is obvious that someone should read up on the stuff that we know.

With paper pulp I assume that the enzymatic reaction will not be terribly efficient. The easiest way is probably rough filtration and then to treat the supernatant of the mixture with Bendict's reagent (the quantitative version potassium thiocyanate). That should be readily available. And then quantification with either titrating or spectroscopy, depending on what is available (and with proper calibration curve as per hypervalent_iodine's suggestion).

IMO joining a big name group is likely to be of more importance than joining a big name school (though the former are probably found in higher concentrations in the latter).

The way I understood it, a big issue would also be how the gel was applied. I assume that after that the overall sterility is not really an issue. Also working at a Bunsen, while generally a good idea, can also do more harm than good, if done incorrectly. This is mostly due to the air circulation created by the flame.

The ligand is an umbrella term for non-covalently bound compounds to enzymes. Based on that, where would you see the difference between those two? With regards to allosteric regulation, would you care to give an example of how you understand what allosteric regulation is and the precise role of cofactors (especially with regards to the regulatory function)? To give some more context: cofactor is a more specific term (though it is sometimes used in a somewhat loose fashion). Also the terms holo and apo-enzyme are relevant here.

Are you referring to speciation? In that case, yes, kind of. It is proposed that the change in surface sugars at some point may have led to genetic incompatibilities thus separating populations with different surface decorations over time. Note that genetic incompatibilities also exist within a species. It does not necessarily lead to a change in evolution speed. However, it could shape population composition. Just to clarify, the sugar in question is part of the decoration of cell surfaces (part of the glycosylation of surface proteins, for instance). Certain modifications would be identified as foreign and hence, trigger immune responses.

Ligand is a more general term refering to a compound that binds to a given enzyme. It could be a substrate, but also have regulatory roles, for instance. A cofactor refers specifically to a compounds that are part of an active enzyme.

Actually it would have been a simpler experiment if you had just used your finger (without application of additional bacteria) before and after cleaning the hands with the gel.

1) Depends on the method of freezing and the number of bacteria, but mostly yes. Repeated freeze thawing can kill some off, but many will survive. 2) I think the pH in the stomach is on average above 1 but again, it depends on how many are sent through. There are pH resistant strains, but even sensitive ones might survive the passage, only with a much lower yield.

Ah, I see what you mean. You are correct that few yeasts are strongly proteolytic. I only remember that (way way back) we used a strain to demonstrate proteolytic activities (though not on gelatin). Something like strain 1532 or 1352 is in my mind, but my memory may be totally off.

If the fungus degrades the gelatin you are not better off than with (mostly) liquid medium, regardless of the purity of your strain. However, there are different Saccharomyces strains, some of which are able to liquefy gelatin, some which are not. So you could be lucky. There are a number of protocols that utilize autoclaved gelatin. However, it is possible that there differences in the heat stability of available gelatin types.

Wow, that is an old thread. However, (as mentioned above) gelatin usually does not work well with microbes since most are able to degrade it and thus liquify the plates.

From what I have heard it appears that the career path in biomedical engineering is somewhat less clear (considering that it is a relatively new discipline). For pharma students there are the typical options that still exist. Biomed engineering sounds fancy, but jobwise they still lack their own strong niche. Due to the dual nature of it, they tend to be less specialized and especially in research positions more biological or more engineering-oriented disciplines are better established and have an edge there. Engineering as a discipline is very diverse, though and there are plentiful established subdisciplines apart from biomed, obviously. At this point it would be best to figure out where your priorities and interests are.

Ribozymes, not ribosomes. Ribozymes are essentially RNA molecules with catalytic properties (i.e. independent of proteins). Also you got it backwards in terms of efficiency. Now, due to complex cellular systems the required mechanisms are in close proximity (including specialized compartments, when thinking about eukaryotes and to a certain extent prokaryotes, too). Just putting everything into a big pot would dilute everything. There is no strong consensus how early proto life could have been. Many favor a nucleic acid system, though there are proponents that postulate peptides as early replicating units. The mix of the two is almost certainly something that evolved later.

It is more a matter of convenience. You could clone it into the MCS, but then you are limited in how you can clone in the subsequent protein to create the fusion. But functionally, if you get the stuff in frame into the construct you should be fine.

Normally you would want to clone the PTD in first and the create or clone in an MCS after that. That way the plasmid is more convenient to clone fragments into. Also you would want to avoid cutting out the PTD when using restriction enzymes. So often e.g. a PCR construct with the PTD is created that can be ligated into the original vector, often in a way that does not result in a restriction site (unless you want to be able to remove the PTD sequence, then it should be a enzyme not present in the downstream MCS).

The evidence (e.g. DNA codons) strongly suggests that all known organisms (i.e. including archea and bacteria) share a common ancestor. It is of course possible that several proto-life forms evolved but only one group survived. Current mobile genetic elements depend on relatively highly complex protein systems to facilitate their spread. Early mechanisms were likely much simpler (more in the form of ribozymes, for instance).

What is a good strategy to derive physiologically relevant answers from omics based experiments. More specifically what would be the ideal workflow to reduce false-positive detections in quantitative analyses on the one hand and derive predictive models on the other. Also what do you think are the implications of population averaging in proteomic samples?

After a few hours you will experience wonderful diarrhea.

Actually this is close to the standard theory for the origin of eukaryotic cells. In fact, the similarities found between archaea and eukaryotes was one of the big problems placing archaea properly in a taxonomic model. Current assumption based on molecular data posits that early eukaryotic cells were derived by association of distinct archaeal and bacterial partners. Also note that archaea and bacteria are both prokaryotes.

The important bit is generally that the whole construct is in-frame. I.e. if you translate it, you should get the correct overall AA sequence. Small aberrations are often not avoidable, but especially in those linker regions they tend not to be crucial (though as usual with recombinant protein expression there may be exceptions). If the additional base pairs result in frame-shift, the whole thing won´t work, obviously.

That is interesting. While I knew that Northerns and Westerns are derived from Southern, I was not aware that they are not capitalized (in publications they generally are). As a comment to the blot: the process takes at least two steps. The first is a standard gel as described above. In the second step (the actual blot) the proteins are transferred and immobilized on a membrane. On this membrane immunoreactions against target proteins are carried out, detected and quantified (if applicable). Molecular compositions are not detectable by these means. The method gives two information. 1) Molecular weight (as assessed by the gel based separation) 2) reactivity to antibodies in question (technically presence of epitopes).

I have not read the papers, but often it does not make much of a difference whether the start codon is introduced or not. Sometimes the additional methionine (especially the sulfur residue) may prove to be problematic, but usually one just has to clone in-frame. The UTR obviously has to be removed, otherwise you would introduce some random aa sequences.

Flu vaccines are usually live or inactivated viruses. I.e. they require the strain to develop a vaccine. [The selection of the strains for the seasonal vaccine is based on known spread. IIRC H1N1 (the one that caused a pandemic 2009) was in the 2010 and 2011 vaccine. For some reasons I overlooked that you actually cited that from the CDC website] The first step is usually isolating a new strain from the wild and then develop a vaccine. Having e.g. identified crucial parts of the genome for the spread between humans as a template, can improve the detection, as well as monitoring of spread. It can also accelerate the production of attenuated viruses (though that is usually not the most time-consuming part). With the average of 50%, do you mean how much of the population is being vaccinated? A quick google search shows that in the US the average is indeed below 50%. Though it varies a lot and of course it depends on local rate that determines spread and especially death rates. Elderly and children are most susceptible and here the question is how high the vaccination rate is in a given school, for instance. However, for vaccination morbidity rates are often not a good measure as the goal is usually to limit spread. The reason why H1N1 caused a pandemic (whereas other strains did not) was the lack of immunity within the populations.

That would be quite an extensive list. I am afraid that for a true exhaustive list you would have to got through lots of reviews. Also note that many differences are only inferred e.g. by identifying expression differences. They may not be "true" differences or false positive detection. Also, individual differences may not account for much alone (only in conjunction with other changes). These are among the reasons why diagnostic biomarkers are so hard to validate for cancer.