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Once food has been properly cooked is it absolutely safe?
If you properly cook food (let's say in the oven for 2 hours) will there be no risk left? no pathogen will survive this?

Depends on what you consider "food". ;)

Some pathogens are more harmed by heat than others, some are obliterated at 80, 110. Some pathogens require large numbers to hurt you, a couple of tired E-Coli will not harm at all, but a mass of them is dangerous. generally you can boil water for 10 seconds at 100 degrees and it is considered sterilized, in fact that's how they sterilize orange juice, they pass it through a pipe and boil it for a minimum time, say 10 20 seconds.

Also depends on the elapsed time between cooking and eating.  Leaving cooked stuff in the refrigerator for a few weeks is probably not a good idea.  Nor is cooking stuff like meat that's started to smell...

You won't be able to eat the food at a temperature that is even close to reducing pathogens. So in any case, the time it spends cooling down will always be time which allows potential pathogens to grow.

No, no food is ever 100% safe, Prions for instance can survive anything short of incineration, spores can land on food in the transition from oven to wherever, some bacterial spore can survive high temprature, ect.

Oven does not sterilize!
High temperatures like the one you get in a normal oven (250 degrees Celsius) can kill a great deal of microorganisms but not all of them.
Also, consider that spores (including bacterial spores) can survive to extreme temperatures.
Lab-grade sterilization is obtained by high temperature, at high pressure and high humidity conditions. Have a look at this web page to get a glimpse.
So, even though you can reach high temperatures in a modern oven, you miss the high pressure and uniform humidity needed for a proper sterilization.
Also, as already mentioned by @John, it depends on what you mean for safe. 1) your food can be contaminated with toxic molecules and they may not be degraded by temperature alone, so even if you get a microbiologically clean food, that doesn't make it necessarily safe. 2) Many reactions occur during the cooking process, some of them may lead to accumulation of toxic products like acrylamide, in such a case, cooking make your food less "safe".
Here some literature on the topic:
http://www.annualreviews.org/doi/pdf/10.1146/annurev-food-041715-033144
http://science.sciencemag.org/content/301/5635/934
http://aem.asm.org/content/71/7/3556.full
http://www.sciencedirect.com/science/article/pii/S1878614611001164
https://www.readbyqxmd.com/read/16672493/high-pressure-mediated-survival-of-clostridium-botulinum-and-bacillus-amyloliquefaciens-endospores-at-high-temperature
Just to be clear, I didn't find any scientific paper describing any organism able to survive at 250 C. However 1) it has been shown that spores may survive to dry heat much better than wet heat and some microorganisms have been described to be thriving at more than 120 C. 2) The oven temperature is not the same of the food temperature, in many cases such a heat does not reach the "food core". 3) Unless you cook under a fume-hood, your food gets contaminated as soon you open the oven door.

Any refs for the claim that some microorganisms can survive 250°C even as spores?

I have one https://cals.arizona.edu/PLP/courses/plp329/sporeref.pdf  pg. 552, it's only about B. subtilis and it was tested only up to 160 C. I am checking for more...

-1 This paper gives the well known value of 120°C of wet heat (the one also used in cooking) needed to kill spores of Gram-positive bacteria in reasonable time. This is where the autoclaving temperature comes from.

To autoclave, you need pressure as well. Without it, you will not get any sterility. I assure you, I deal with microbiology all day long and I am doing it for more than 10 years. If you autoclave bacterial medium without setting the right pressure, you will see molds growing into perfectly sealed bottles in a few weeks. The same occurs if the humidity is too low. Temperature alone is not enough. Look at the plot on pg 552, dry heat for 1h at 160 C and still you don't kill all the spores.

@har-wradim:  250°C oven temperature does not mean  250°C food temperature, especially if you're cooking something large.  A turkey, for instance, is considered "done" when it reaches an internal temperature of about 75°C, which takes several hours.

No.
Staphylococcal food poisoning is super common.  The bacteria that cause it are killed by cooking but if they have a chance to grow and make their toxin before they are cooked, the toxin is not destroyed by cooking and can make you sick.  I think this type of food poisoning constitutes most cases where you throw up and have diarrhea about 6 hours after you eat but you rally within 2 days.
From linked source (CDC)

People who carry Staph can contaminate food if they don’t wash their
  hands before touching it. Staph can also be found in unpasteurized
  milk and cheese products. Because Staph is salt tolerant, it can grow
  in salty foods like ham. As it multiplies in food, Staph produces
  toxins. Although Staph bacteria are easily killed by cooking, the
  toxins are resistant to heat and so cannot be destroyed by cooking.
  Foods at highest risk of transmitting Staph toxins are those that
  people handle and then do not cook. Examples are sliced meat,
  puddings, pastries, and sandwiches. Food contaminated with Staph toxin
  may not smell bad or look spoiled.

No for several reasons.
If poisonous bacteria previous got into the food, there could be poisons left over that cooking isn't guaranteed to get rid of.
Some bacteria pack themselves into spores when they are cooked. Spores are incredibly hard to destroy. You might consider irradiating them. A common way to counter this: cook food, let it cool (prompting the spores to unpack themselves), then cook it again.
Then you have the risk of "kitchen-to-table" contamination where the food gets contaminated after cooking and cooling due to poor hygiene practices.


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Distribution of nutrients throuought a drink made of plants?
In an attempts to eat my veggies for the day in one shot, I blended together a bag of salad with some water. The mixture separated by density, a thick top layer containing the bits of leaves, and a bottom layer of just juice. My question is: how many vitamins and nutrients are actually found in the top layer compared to the bottom, and how efficiently would the body process them?

I removed the sentence about you throwing up in case this appears to be a personal medical question to some people. I don't think it really is myself.

@dd3 that's ok I still got a good answer.

If we assume the drink was very well blended most of the water-soluble vitamis (B and C) as well sugars could dissolve in the juice. Fiber would mostly remain in the plant debris. Oils and fat-soluble vitamins (A, D, E, K) would form their own oily layer or be found in an emulsion with the fruit juice.

source: Stack Exchange

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Precursor miRNA and a mature miRNA
What is the main difference between a precursor miRNA and a mature miRNA?
It is often the case that we have more than one precursor miRNA but only one mature miRNA.  The miRNA-seq data contains only precursor miRNAs, so I was wondering if we could use the expression of the precursor miRNA as the expression of the mature product or not?

precursor miRNA is ~70mer RNA with a stem loop structure. It is cleaved by dicer to generate one or two mature miRNAs (from one or both the 'arms' of the stem ; called 3p and 5p which are ~22nt long). Refer to this review. (It is an old one and some facts might have changed, but the basics are there.)
Yes, there can be different precursors giving rise to same mature form. There are a few cases like that (check for entries like mir-x-y [where y can be 1,2,3,...], in miRbase).
Usually pre-miRNA is shortlived and is immediately converted to mature form. Therefore, in small RNAseq data, most miRNA reads (more than 90% [at least that's what I get]) come from mature form (pre reads would be longer [after adapter removal] and will contain sequences not retained in mature form). Most algorithms select for the mature reads.
It is difficult to determine which precursor gave rise to a certain mature miRNA, using an RNAseq data. The usual practice is to assign the average read count to each locus. E.g., for a mature form that has 3 precursors, each precursor is assigned 1/3 of the total mature reads. However, in most RNAseq experiments, the objective is to obtain the mature miRNA profile and which precursor gives rise to it becomes immaterial.

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What do you call the non-Wild Type allele?
Can I have a list of suggestions, such as the mutated allele, other allele, etc. ? Are there any blatantly missing ones on my short list?

List-type questions don't work well here. Your question is a bit borderline, so we'll see what everyone else thinks. One that you are missing is mutant allele.

If not wt then it is a mutant.

Usually its major allele and minor allele.  When you hear this language, you feel that the major allele is the 'wild' type, but its more precise to avoid 'wild'.
This language avoids the question of which one is 'wild' since different populations may have different ratios of the two.

This is a nomenclature I have almost only heard in bioinformatics context. In most biological literature I have generally seen "wild type" vs "mutant". Although the point about the different population is true one may argue that using major and minor brings confusion as the same allele can be major in a population and minor in another...

how do they know which allele is wild type?  you would only know if you were doing an experiment where you created the mutant yourself I would think.

I am not saying that wt/mutant is a better nomenclature in absolute, just that it is - probably for historical reasons - the one most commonly used (the wild type nomenclature if you wish :P). In general you would use wt for the allele most abundant in the general population.

Wild type refers to the phenotype of the typical form. Normally it is wild type is being compared to a mutant allele because the allele is not longer typical. So the answer would an allele that is not typical which, in most cases is a mutated allele.


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General undergraduate zoology textbook recommendation?
I am very interested in zoology,and I want to study zoology in my spare time.
Any undergraduate level zoology text book recommendation?

This is a rather broad question. In an attempt to narrow things down: Are there specific areas of zoology in which you are interested?  Are there specific types of textbooks that you like more than others (or what do you not enjoy in a textbook)?

@dd3 general introductory level zoology textbook

I used Zoology by Miller and Harley in my undergraduate years and I found it to be an engaging, informative text book.

LIFE : The Science of Biology by Sadava & Hills & Hellar & Berenbaum


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What is the appropriate blender speed to maximize nutrition and digestion of fruits and vegetables?
Blender companies state that a blender for smoothies should have speeds of at least 30000 rpm. They argue that only at 30000 rpm are cells of fruits and vegetables sheared enough to maximize nutrition and ease of digestion.
Would blending at lower speeds, such as 20000 rpm, be sufficient?

Could you explain what chlorophyll has to do with your question?

Sounds very much like a marketing ploy...

You might start by asking the company where they got their numbers and if they have published citations or data to back up their claims. They're making two claims, first that 30k rpm is necessary to shear cells, and second that shearing cells is desirable and improves the nutritional properties of the food.

Related: http://cooking.stackexchange.com/questions/22639/how-important-is-rpm-in-a-blender

@dd3 thanks for editing. Chlorophyll has nothing to do with it

This is better suited for [cooking.se]

I'm guessing that what they mean by 'maximize nutrition' for digestion is that they are assuming that the cells are broken open.  This would make the co-factors we call vitamins, protein and sugars freely available to the digestive system and more easily absorbed.
I think it is a marketing literature claim, though the blender may have some valid advantages... details below.
Stainless steel waring blenders used to be typical pieces of lab equipment which could be used to homogenize tissue to extract proteins or DNA from tissue.  These blenders would typically run from 10k-30k rpm.  The web search for 'cell lysis blender' gives lots of examples of prepping DNA from plants at these speeds, but they don't complain for speeds towards the lower end of the range.  A reputable looking example in my short search: This paper for tomato fruit cell wall preparations doesn't even give a speed the blender might have run at.
Cell lysis in the literature is not precise - the cell toughness, the strength of the tissue around it and other such factors all come into play.  Putting woody stems into your blender and those cells won't really get opened up at all.  Also in the cell literature cell lysis buffers may have detergents or other chemicals (the reference above is done in 50% ethanol) to weaken the cell walls.  Not exactly what you'd want to use if you were making a health drink.
In experiments they have to contend with oxidation that happens when the cells are broken open with all the air whipping through the mixture.  This is one reason you don't see blenders in labs to much anymore - hydraulic presses, sonicators, and bead beaters have taken their place - they have less aeration in the mixture and also deliver more power so that they can break open yeast and bacteria, which blenders really can't.
So there will be some vegetables where the cell walls won't break open and all the nutrients won't be so easily accessible.  It must help to be running at the top end of the range, but there will always be some vegetables which won't be broken open.  For most things like bananas and apples it sounds like you'll get similar benefit with other blenders too.  Just have to think about how much more are you paying for that extra 10k of rpm I guess.
Is there a benefit to breaking open the cells and letting all the nutrients (as well as cell waste) break out into solution?  It might give you a quick pulse of nutrition when you drink, but I'm pretty sure all the cells of a piece of fruit or vegetable will be pretty much broken down and extracted by the end.  On the other hand, it sounds like it will save the digestive system some work...  So there's that question too.

Very nice but... how does all of that compare to the effects of HCl in the stomach? If HCl breaks apart food anyway (which it does...) the advantage of a >30K rpm blender are small or non-existent at all.

you are correct I think. I've read that you actually don't need to chew your food.  Including the action in the intestines, the conventional answer is that the digestive system does eventually break down all the nutrients you take in.    Still, its not completely equivalent - it must be less work for the digestive tract if all the nutrients are in a juice than if you swallowed a bunch of cherry tomatos in their skin.

sure I agree with that, but I was more puzzled by the fact that a 20K rpm blender would be worst then a 30K rpm one...

Probably not a lot worse.  I should have said that I think the differences are marginal, though its reasonable to assume that 30k will get a bit more than 20k. When I say a bit, it might be 80% vs 70% of cells.  Not a big difference with many fruits and veggies.  Most tissue will be liquified nicely at 20k if not completely. Running longer will lyse more cells, but will also heat the sample as well as oxygenate it, which can oxidize the contents.


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What would be the best design for spike-and-recovery and linearity-of-dilution validation experiments in one 96-well ELISA plate?
I have searched in the web for a detailed explanation of doing such validation experiment, but unfortunately couldn't find a satisfactory one. I came across the following sources:

Thermo Scientific Tech tip #58: IMAHO, well written description, but still there are some issues
Pros

Clear on describing terms and straight forward calculations
Troubleshooting of the results is outlined

Cons

Not designed to be performed in one 96-well plate ELISA
No mention of any acceptable criteria for the both validation tests
No mention of blank

Quansys Biosciences: a practical design to implement
Pros

Both spike-and-recovery and linearity-of-dilution experiments can be performed in one 96-well plate ELISA
Justified introduction of the endogenous sample, which is diluted the same amount as the spiked sample
Addition of blank
Mention of acceptance criteria for both types of experiments

Cons

No mention of troubleshooting
a little bit messy plate design

R&D spike and recovery protocol: a brief one but useful
Pros

Clear on design
Mention of acceptable criteria at least for the spike recovery 80-120%
Mention of blank
Hint about possibility of using diluted neat sample until it gives reading

Cons

One sample was used for assessment and not averaging on 3 samples at least
No mention for any criteria for linearity of dilution

Issues/Questions
    - Q1: How can we combine the two experiments into one plate to spare samples, and materials?
    - Q2: Can we dilute sample with assay diluent instead of sample diluent?
    - Q3: In case low sample material is there, can we skip the neat sample and add 1:2 diluted one instead to spare material?
    - Q4: In preparing spikes in Thermo Scientific tech#58, why was it 10µl spike stock solution added to 50µl sample? what governs this addition, is there any ratio to stick to here or arbitrary ratio? Can we add 90µl sample and 10µl stock solution?
Please feel free to expand sources, or questions, and of course answers are more than welcome to achieve the following aim:

The best design for both validation tests (i.e., spike-and-recovery and linearity-of-dilution) in one 96-well plate ELISA that will use the minimum amount of sample material as possible with explanation of calculations based on averages and clear troubleshooting plan

PS: I am short of reputation to add important tags to enhance searching, e.g.: ELISA, validation

This is quite a few questions. I understand why you asked them all together, but if there is not much of a response, you might consider asking separate questions.

Welcome to the site @doctorate. I agree with dd3 above; there are many questions here, so it's possibly difficult for one answer to address them all. It seems like your last request is actually is the question: "What is the best design for spike-and-recovery and linearity-of-dilution test in one 96-well plate ELISA...". I'd suggest leading with that, and then provide the results of your own research. It gets to the point more quickly, and those with knowledge can read on.

@dd3, my concern is that when these questions will be separated and answered individually, the answers can easily be misleading, out of context, and not taking advantage of the different approaches being aggregated into one place, it is a stack exchange after all.

Understood. The new title makes the question much clearer.

Background:

There are a lot of recipes to extract protein from human tissues out there, but all of them boil down to one thing; preserving the tissue proteins as much as possible while obtaining a reasonable yield for downstream applications, using extraction buffer, extra techniques, and by adding protease inhibitors
ELISA is one of the those downstream applications that you might be interested in, but one important question? is the sample matrix that you have already obtained valid for the ELISA assay? keep in mind, your sample is not serum, it is a mixture of tissue, extraction buffer, and protease inhibitors, and other things as well
Two known assays are usually performed to address the above question. These are, spike-and-recovery (SAR), and linearity-of-dilution (LOD), and these two assays are specific to the analyte that you want to measure in your samples, e.g., cytokines, factors, Igs, etc...and specific also to the tissue, and assay kit as well
Often times, you are interested in performing these two assays with minimum resources as much as possible, i.e., less time, less kit materials, and, most importantly, less sample material. This can be quite challenging and it depends on many issues that is out scope of this post to discuss them all
If you are interested in performing these two assays using only one 96-well ELISA plate and examine validity of different sample matrices, sample buffer (lysis buffer or sometimes called extraction buffer) for a certain analyte, say X, then this scheme below is for you:

Technical Notes:

In this scheme, recovery is examined in 3 types of solutions; assay buffer, sample buffer and samples. These are different in their complexity. Typically, the assay buffer is usually optimized to detect the standard protein provided with the commercial kit
The idea of spike-and-recovery is that you add a certain amount from standard stock solution into the wells containing the solution to be tested (e.g., sample buffer or samples) and measure them, to see whether you can recover that amount again, and how much you can recover from it in %. If, for any reason, you couldn't recover that amount in comparison with a control well, where that same amount was added into assay buffer, then this means that something in the test solution is not in favor of the assay. The specific amount you add into the wells is called spike, and it should be the same amount across all tested wells (try to be consistent). Make sure that the added amount when diluted in the well, its final concentration should still be measured by the assay and lie inside your standard curve. E.g., if your standard curve is from 4- 4500 pg/mL, and each well has 100µl of sample, if you want now to add spike into that sample well, you may add whatever amount you want that will still give you at the end a reading inside the standard curve, you may choose to add 10µl from the highest stock which is 500pg/mL, so you end up here with 1/10, that is 50pg/mL, which is fine as it lies inside the 4-500pg/mL range. Alternatively, you can add 50µl sample + 50µl spike (500pg/mL) and would end up with 1/2 dilution (which is the same in this scheme), that is 250pg/mL, which is also fine. So it is up to you to choose, keeping in mind the final concentration should lie inside your standard curve
For the linearity-of-dilution, it is obvious that you need a high concentration solution that you can make two-fold (or whatever fold you like) serial dilution from and its reading should still lie inside the standard curve. The best candidate for this is the high spiked wells. The LOD would tell you about the effect of different dilutions on the precision of the assay
For SAR and LOD you will get at the end an average percentage from 3 samples at least (calculation example will be provided later), I added a fourth sample, but this fourth can be a different sample type, say samples from tissue culture, so it is up to you to re-design this scheme and be innovative
Choosing the best dilution is not an easy task, it is not without compromises sometimes. For example, if you have a harsh sample buffer, you may not have good recovery at 1/2, 1/4, 1/8 dilutions of the sample buffer in assay buffer, whereas almost good recovery is achieved at 1/16, then this dilution factor is most probably the one you should go for in your assay. On the other hand, 1/16 might not be detected by your ELISA assay, which is limited by its sensitivity. Here, the E wells can give you a clue whether you detect something in these unspiked samples or not, that's why I recommend you include at least one sample of high expected value of the analyte in question (this is not easy sometimes to predict) in this scheme, here this is sample 3. One more thing, if you get good recovery at 1/16 DO NOT go to 1/32 or 1/64, as it is obvious that with these higher dilutions you are reducing the chance of the analyte's detectability as it is limited by your assay's sensitivity
In most of the cases, you will see that the dilution factor of good recovery of the sample buffer in columns 3 and 4, will coincide with that of the spiked samples in columns 5, 7, and 9. This will give you the assurance that you are in the right direction. If sample 4 is extracted by a different sample buffer, then it is clear that should not expect to end up with the same dilution factor (please, be more reasonable!)


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Why can myopic eyes focus on nearby objects, but not on distant ones?
In myopic eyes, far away objects get blurry. I understand that myopia means that the focus of the lenses concentrates light at a point in front of the retina, thus by the point the light rays reach my retina they've already spread apart so they aren't coalescing on the same point as they ought to.
My question is, why is it that this deficiency only apparently manifests itself when things are far away?  Why is it that the focusing of light in front of the retina doesn't cause the same blurry vision up-close as it does far-away?

There are four common refractive errors, namely nearsightedness (myopia), farsightedness (hyperopia), astigmatism (Fig. 1) and presbyopia.

Fig. 1. Refractive errors. source: Excimer Ophthalmologic Clinic
myopia (nearsightedness): The eye ball is too long, or the cornea too steep, causing light to focus in front of the retina and making distant objects appear blurry.
hyperopia (farsightedness): The eye is too short, or the cornea too flat, causing light to focus behind the retina and making near objects appear blurry.
Astigmatism: is caused by an irregular cornea or lens, causing images both near and far to be distorted or blurry.
Presbyopia: a common age-related problem that is caused when the natural lens in the eye loses its elasticity, making it difficult to focus on near objects (hyperopia).
Focusing of the retinal image is mainly regulated through the process of accommodation (Fig. 2). Accommodation is mediated mainly by changes in the shape of the lens. A more globular lens results in a larger refraction of the light to focus on near objects. A flat lens refracts light less and is suited for focusing in the distance.
The lens is held in place by the suspensory ligaments. The ligaments in turn are attached to the ciliary muscle (Fig. 2). When the ciliary muscle contracts, it shortens. This effectively moves it closer to the lens and so any tension in the suspensory ligaments is released as the ligaments go slack.  Slack ligaments mean the lens adopts a more globular shape.
When the ciliary muscle relaxes, this changes its position to increase the tension in the suspensory ligaments. Taut suspensory ligaments (caused by the relaxed muscle) will pull the lens into a long thin shape.

Fig. 2. Accommodation. source: PMG Biology
In the case of myopia, objects in the far distance are blurry. Objects far away tend to send near-parallel light rays onto the lens and the lens needs to be maximally flat and hence the ciliary muscles should be maximally relaxed. If in this case the image is still in front of the retina, the lens cannot relax any further and hence the image is blurry. Because there is enough dynamic range for the ciliary muscles to contract, there is not any problem with objects close by, because the lens is perfectly capable of assuming a concave (fat) shape.

It took me about three read-throughs to understand, but great answer.  The sentence, "If in this case the image is still in front of the retina, the lens cannot relax any further and hence the image is blurry." really drove it home.


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How do we know that dinosaurs were related to lizards and/or birds?
Do we clearly know what the living closest relative of the dinosaurs are? And connected to the first question, in scientific manner how do we know these relationship between extinct species and living ones?

In general the answer is always the same: you construct a phylogenetic tree. In order to locate different species on this tree in relation to each other, you use various features to compare which species are more similar to each other than others.
The best way of doing this is by comparing their DNA sequence, especially orthologous genes (i.e. genes common to the species compared).
Unfortunately, genetic sequences usually aren’t available for extinct species. You can still compare homologous features though. For instance, the class of mammals are all characterised by the possession of mammary glands. Similarly, all vertebrates have a vertebral column and all aves are feathered, warm-blooded, egg-laying vertebrates.
The collection of many such features from fossile records allows the creation of more or less detailed phylogenies. The Wikipedia explanation mentions several transitional fossil forms which trace the evolution from dinosaurs to modern birds via several intermediates. All of the inferences are based on anatomical resemblance.
This may sound weak evidence but in fact anatomical homology has proved to be sufficiently accurate in constructing other phylogenies, where we have been able to verify the correctness using genome comparison data. So while there is much uncertainty about the precise branching point of birds from dinosaurs (or maybe archosaurs), there is near-certainty that the common ancestor of birds and dinosaurs was, in fact, an archosaur.

Tolweb.org is a website that offers a good summary of our current knowledge of the phylogenetic tree. You (The OP) might want to have a look to it.

Extending Konrad Rudolph's answer, research has been conducted into reconstructing the phylogenetic tree via protein sequence data of the T. rex (one of the latest living dinosaurs):

C. L. Organ et al, Molecular Phylogenetics of Mastodon and Tyrannosaurus rex, Science 320 (2008), p. 499.

They use a variety of standard methods for the phylogenetic analysis.  The real challenge was collecting protein sequence data for the T. rex (which has been extinct for ~65 million years).  They succeeded in collecting and sequencing collagen α1(I) from Mastodon and T. rex, and compared it to the same protein in extant species.
They write:

Despite missing sequence data, the mastodon groups with elephant and the T. rex groups with birds, consistent with predictions based on genetic and morphological data for mastodon and on morphological data for T. rex.


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ATP cost for gene expression
How would you estimate the number of ATPs required to transcribe, export and translate a single eukariotic protein?

Is this in bacterial or human? Transcribing a pre-mRNA and splicing are significant contributors to this energy cost calculation. Don't forget charging of tRNAs with amino acids.

Thanks, edited the question: I was thinking about eukariotes.

I'm assuming this wouldn't take into account the ATP cost of transcribing / translating / regulating any of the proteins required for transcription / export / translation?

@GWW, No: I assume the cell contains already all the required machinery.

The cost of transcribing and translating a hypothetical average gene in yeast has been calculated as 551 activated phosphate bonds ~P per second (Wagner, 2005).

The median length of a yeast RNA molecule is 1,474 nucleotides, and
  the median cost of precursor synthesis per nucleotide (derived from
  the base composition of yeast-coding regions) is 49.3 ∼P. With a
  median mRNA abundance of R = 1.2 mRNA molecules per cell and a median
  mRNA decay constant of dR = 5.6 × 10−4 s−1, the mRNA synthesis costs
  calculates as 49.3 × 1,474 × 1.2 × (5.6 × 10−4) = 48.8 ∼P per second
  and cell. This is a fraction 48.8/1.34 × 107 = 3.6 × 10−6 of the total
  RNA synthesis cost per second. The median length of a yeast protein is
  385 amino acids, with a combined biosynthesis and polymerization cost
  of 30.3 ∼P per amino acid. The median abundance is 2,460 protein
  molecules per cell. No currently available data allows a meaningful
  estimate of the median protein half-life, but a protein of an
  intermediate half-life (see below) of 10 h (decay constant dP = 1.92 ×
  10−5 s−1) yields an overall synthesis cost of 30.3 × 385 × 2,460 ×
  (1.92 × 10−5) = 551 ∼P s−1.

For your question about a single gene, the cost would be 49.3 * 1474 ~P for the mRNA and 30.3 * 385 ~P for the translation, which would result in around 84 thousand ~P. This is probably a very misleading statistic as you can transcribe multiple proteins from a single mRNA.
How the cost of mRNA synthesis and translation are calculated is described in detail in the paper. A large part of the cost comes from the synthesis of the basic building blocks, the nucleotides and the amino acids.

Wagner, A. Energy Constraints on the Evolution of Gene Expression. Mol Biol Evol 22, 1365-1374 (2005).


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Career progression through biosafety levels?
Does a career in infectious disease typically progress through biosafety levels, or do people select one and specialize their training in procedures specific to those hazards?
That is, say Dr. Kliener wants to work on TB (BSL3). Does he first on have to work on MRSA (BSL2), which he has no interest in, just to build up experience? Or could he simply learn everything there is to know about TB and BSL3 lab procedure, don hairnet and gown, and get to work with someone who has experience under those conditions?

As far as I know, the higher biosafet levels (3 and 4) need a special training. For the BSL 2 labs I have worked in, you need a proper training (technician or any relevant study as biology, biochemistry and so on) so you know how to act and behave in the lab. And of course you need some introduction (rules and safety for the lab).

BSL 2 access requires a 1-2 day course, which is training generally offered by the institution.

I have found that BSL2 access tends to not be highly regulated. Some of the BSL2 labs I have worked in did not even require 1-2 days of training, while others did. In any case, the current policy at my current institution is that BSL3 access is denied to anyone who does not possess an undergraduate degree, and those with it must apply for and take a course.

There is major jump in the risk to researchers between BSL-2 and BSL-3. BSL-2 laboratories are very common in part because potentially infectious viral vectors are commonly used in molecular biology.

My short answer would be no, careers of people who study pathogens requiring biosafety training are not focused biosafety level.
More broadly, the people I know who study infections diseases are not motivated by the biosafety levels of their infections organisms. Rather, they are motivated by biological questions and their research that often require higher biosafty for their labs.
For example, the researchers featured in a recent (July 2015) National Geographic do not study Ebola because they want to work on a BSL-4 level virus. Rather they want to about learn about the disease from both a basic science and applied human heath perspective.
Your hypothetical Dr. Kliener would not work his way up the biosafety chain as a conscious. Let's say a young Mr. Kliener always wanted to study human health. He probably would have started doing research in a BSL-2 facility as an undergrad research assistant (See BSL-2 requirements here. As a grad student, he might have worked at a BSL-3 lab if he choose a good program while spending years focusing on a specific pathogen or system. By the time he became because a PI, he would have needed to find a BSL-3 facility for his research. He worked his way up, but not because he wanted to study dangerous pathogens. Rather his research question guided his path.
Other career tracks could end up using a BSL-3 facility, but not necessarily need the stop at a BSL-2 facility. For example, a hypothetical Dr. Fish may have started off loving the outdoors. She studied limnology as an undergrad and grad student and did not step foot inside a lab. However, when she began working as biologists for a state conservation agency, a novel fish virus emerged. She now is tasked with studying it. Her agency trained her to work in a BSL-3 lab so she could culture fish with their virologists.

Here's a nice little walk-through by the CDC on Biosafety levels. Biosafety level reflects that potential risk microbes used (or potentially present in the case of human tissue samples) in the laboratory present to researchers. http://www.cdc.gov/training/QuickLearns/biosafety/
BSL-1 is for very low-risk organisms, like non-pathogenic E-coli. You can work with these guys on an open bench with minimal protection gear and be at little to no risk of disease.
BSL-2 is for low-risk organisms, like Staphylococcus, where risk of infection is low and/or infection is not likely cause serious consequences to researcher well-being. (Some dangerous blood-borne diseases can be worked with at BSL-2, because the additional pre-cautions do not impact transmission, which would only be likely to occur after a needle-stick or similar inoculation with infectious material).
BSL-3+ Labs are much less common, have much stricter requirements on facility structure and security and on researcher's protective equipment and procedures.
BSL-3 is for dangerous microbes that can be transmitted by aerosols, such as Tuberculosis.
BSL-4 facilities are rare, require expensive training and equipment and are used for deadly, exotic microbes, like Ebola.


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Why and how does complexity usually tend to increase through time?
The question of complexity is classic in the very first lectures of evolutionary biology where the teacher usually tries to tell the students that complexity does not necessarily increase and that humans are not more complex than other organisms.
My questions are:

Why does complexity tend to increase through evolutionary time?
What are the different hypotheses to explain this pattern?

When writing "Mass extinction" on google image, we find many graphs displaying the number of families (or other taxa) through evolutionary times with the five mass extinctions. What would it look like to draw such graph replacing the family richness in the y-axis by :

Mean complexity among all living things?
Complexity of the most complex taxon?

I suppose that anyone who wishes to answer to this post will necessarily need to define the words "complexity". He or she might define it in terms of number of genes, number of metabolic pathways, length of DNA sequence, number of cell types, some kind of index taken from information theory. When asking my questions I had in mind a definition close to "number of genes" or "number of metabolic pathways".

I'm not putting this as an answer because I have no references, if I find any we'll see. I can see two reasons why complexity would increase in evolution (not the only two possibilities mind). 1) Plain diffusion: as life diversifies a range of complexity develops, and since life started at the lower bound the upper bound can only go up. And 2) the environment is complex, being able to act in specific ways in specific circumstances can promote survival, complex behavior means complex structure, so complexity is adaptive in some(many) cases, so evolution will promote complexity in those cases.

Having posted that I'm not convinced "complexity" as defined by "number of genes" or "number of metabolic pathways" HAS increased that much since, say, the Cambrian. "Number of genes" is probably capped by mechanisms like Müller's Ratchet anyway, and most of the ways around that haven't changed since Eukaryotes became a thing. We all know how potatoes have more genes than humans and such trivia. Metabolic pathways might be another story depending on how it's defined (C4 does date from the Oligocene), but what we perceive as "complexity" in Eukaryotes isn't about metabolic pathways.

I have just putted a revised edition to the answer of your question but I fear you (biologists) may take it to be "too philosophical" for you people so I will put it simply here-the reason (the answer to question why) complexity is increasing is the more complex organisms inhabit an ecosystem the more niches for ever more complex organisms they create and the mechanism of complexity increase (the answer to the question how) is the drive of these new complex organism to adapt to the new niches provided by the previous complex organisms. How is this answer?

@Yordan Yordanov, This answer, like many like it, insufficiently answers the question.  It's basically saying the 'need' or 'benefit' of more complexity creates more complexity.  This isn't a valid mechanism.  The 'benefit' of my smart phone being smarter does not explain the mechanism for making it smarter.  I feel a better answer needs to be given.

I think I can understand your point. You're referring to my second point the answer to the question how, right? I think everybody can agree on the first point the answer to the question why is it provides self-sustaining process-more complex organisms make more niches for other more complex organisms and it is this organisms-ecosystem interaction which causes the proliferation of complexity through time. Just like the smarter your smartphone gets, the smarter you want it. It is a self-sustaining process, you see? The moment you want smarter phone and the conditions allow it to get smarter it

is you who provide "the drive" for the smartening of your phone-you say you will pay money for smarter phone, so the company producing it wants to invest in technology to make it smarter and the result is the development of ever more smarter phones. I call this self-sustaining process (philosophically you can define it by saying-it is the reason for itself). My point it complexity generation is also such self-sustaining process-the more it generates the conditions for more of it arise. So once a certain amount of organizational features is reached the accumulation of new ones becomes

self-sustaining and the process can go on forever or until the conditions of the environment allow it. It is the reason behind complexity. The second part is the more "tricky" one and I agree may be I had to develop it further in my answer but as you can see it is already well too long. "The trick" consists of making the definition of complexity itself dependent on adaptability of the organism. If we define complexity as the increase of variation driving adaptability with the emergence of new organization, then it is organization itself driving the ability to make new organization.

Your smartphone isn't alive but can you consider would it have had the organization it has today if there weren't many generations of "ancestors" before it where all the features needed to make it as smart as it is today weren't tested. You can also say your smart phone now is a testing ground for the smart phones of the future, too. Nobody knows where the smart phone's design would go but you can bet it will be based on the models we use today. How is that not a reasonable argument? Then, it's the same for Life and complexity-trying to adapt to new environments organisms must try many new

organizational features and sometimes the new environment they adapt to forces them to generate ever more new organizational features which in turn can form the environment to provide space for more new organizational features and so on in a self-sustaining process like the one I discussed answering the first part of the question however by including the adaptability argument I can in a way "close" the question by dissolving it with the definition of complexity(yes, I know, such thinking isn't very popular in biology). How that isn't an answer?

@Yordan Yordanov,  Not quite.  I'd summarize your first half more succinctly: more complexity comes because there's always room for more complexity.  That may be 'the drive', but that's not a mechanism.  Pontificating at length on the smartphone analogy misses the point:  ENGINEERS are the mechanism.  Remi.B asks an excellent question, and this "because there's room for improvement" style answer again doesn't identify the mechanism.

I don't think Remi.B's question is good at all and I think I provided good enough (although somewhat too long) answer to it. He actually asks a whole bunch of questions and at the end of it all puts what can be considered basically a philosophical question about the definition of complexity all with the rest. I think this is definitely not what you do when you want to know more about complexity in biology. And I think I manages to answer his main point. Yes, it is true I can expand more on the mechanism point and write something about the particular instances of complexity he is mentioning

but there can you imagine how huge would this answer get. I am at a dilemma here-if I write all I know about the issue my answer would go in the size of a small book (no, not even a paper sized answer will be enough) and the creators of this platform had explicitly stated it isn't for extended discussions or vague and/or long answers. Even my answer now as it is too long. Yesterday I tried writing shorter answer but someone just told me it isn't succinct the way it was. If I'm going to answer all of Remi.B's question than this is definitely not the right platform! And I can't do anything

about it. The way I see it there are 2 ways out of the situation-either Remi.B would come and make this question shorter and more precise (e.g. for example, with talking about a particular instance of complexity like the number of genes, of metabolic pathways, the mean complexity among all living things, the complexity of the most complex taxon, etc.) or he can try "breaking up" this question into a series of questions (I even suggest creating special tag-complexity) each dealing with an individual issue of complexity. Then we can all answer them in paragraphs with reasonable length.

But I can talk so much more about the issues mentioned here that this comment section will get the size of a book here, so I suggest you if you would like to continue the discussion on the topic to go into special chat room for the issue. Do you agree?

If you want to join the discussion you can go here http://chat.stackexchange.com/rooms/54964/complexity-in-nature

I've voted to close because it is not clear what is meant by complexity. Complexity has specific definitions in different subfields of biology. I think you need to pick one and stick with it in order to get a good answer. The top voted accepted answer is more of an explanation of complexity definitions rather than an answer to the question.

@James I totally disagree. Perhaps a lexicon update would help us all, no matter how meta...

This is actually a very interesting yet difficult question to give a single precise answer to. I will try and summarize for you a "meta answer":
Complexity Science Some consider complexity not to be a Biological topic as such, since it is a property that accumulates in non-biological systems e.g. economics, technology, music, language - in fact anything that "evolves" through time. This new field of science is called "Complexity Science" or "Complex Systems" and is primarily a field of mathematics or information theory: Complex systems
Complexity in Biology What I can say is that these kinds of questions have started an almost new field in Biology, called "diversity evolution", here is a very interesting paper: Diversity Evolution.
Defining Complexity You were right to mention Complexity first needs to be defined, and as an early field of science this is where much focus has been recently. There are quite a few definitions but it is perhaps too controversial to list any particulars... HERE is a whole UCL lecture dedicated to defining Complexity!
Topics of Complexity Science I have written enough, so perhaps this lovely diagram of the topics of Complexity Science will be of some help:

Thanks for your answer. From your answer I understand how broad is the science of complexity and I understand that the tendency for complexity to increase does not exist only in biological evolution but also in the evolution of music, technology, economics and other. It is very interesting. It does not answer to why complexity tends to increase (in the biological system) and how it evolved through the past time. I realize that the question might be a hard one! I'll wait to see if someone have some hypotheses for this increase and for past patterns.

"economics, technology, music, language" are all biologic, since they exist inside biological organisms. If you want to talk about complexity outside of biological realm, you can consider physics, chemistry, minerals, crystals, etc.

The phenomenon of increasing complexity is natural puzzle for everybody studying biology, because "nothing in biology makes sense". Stuart Kauffman shifted the emphasis from complexity to order, and this is IMO the right observation: chaotic systems are more complex in thermodynamic sense, while biological systems occupy a thin niche on the border of chaos. There are many ideas in this book but, unlike the famous manuscript which title Stuart has apparently followed after, there is no satisfactory and compelling answer to that question yet.

I think there is a way to tackle the issue however it requires a lot of work on the "edges" of what we consider science and philosophy (and their interaction with each other). I can propose you a suggestion but it is my own research, so it can be quite controversial and please, bare with me.
First the big question here-what is complexity can have multiple answers upon the definition you use. But definitions aren't the subject of biology but of philosophy. And in philosophy whole fields of study can simply dissolve if their definitions prove unsatisfactory. So, one can argue there isn't anything like complexity in Nature and every single time this word is used we can find some problem defined in the terms of some science where the word complexity is missing. One can argue if we can do this for all cases the word complexity is used, then, there truly isn't such a thing like complexity in Nature, but rather it is an artificial human language construct and as such has no objective base in reality. I refer to such cases as "denial by definition".
Pay attention that even the very word "Life" itself can be the subject of "denial by definition" and if it is indeed denied, then how about the rest of biology? So, the "denial by definition" can be serious issue for many problems in biology, not just complexity. In order to avoid it the only way to proceed would be to find one or more universal characteristics behind what we can call complexity having common origins. It is the origins which are important because they can provide us with a common mechanism behind the process and thus give us a way to put "flesh" on the word complexity by denoting the same effect under different circumstances. If you can make such a dictionary definition of complexity than you can relate it directly to the mechanism creating such effects and show its use is more than a convenient semantic coincidence but there are some real scientific implications for your question.
Now, such an effect should have its defining cases-these circumstances when what you are trying to show exists as more than just a convenient word and emerges as a real world characteristic of the system. Then the problem is transferred from one of philosophy to one of science and you can have your definition of complexity. Then, complexity is equated to what characteristics emerge in the system with the advent of new processes taking place in it. I believe such a solution to the problem of the definition of complexity provides best use for science because it turns the problem of defining complexity into the problem of the emergence of properties when new mechanisms appear in the system. I know may be the philosophy is too much for you but can you understand me?
If we follow through these assumptions then complexity arises in the system only when we can show direct link between the emergence of new characteristics of the systems (things that can describe it) and new processes in it. Then we can conditionally define "simplicity" as the state when both the characteristics of the system and its organization are unchanged, some "unrelated states" when the system can accumulate new characteristics or organization without one changing the other and complexity only when change in the characteristics relates to change in the organization and vice versa. I know this definition may sound quite "obscure" for biology because it doesn't specifically prescribe genes, or proteins or metabolic pathways or anything for that matter but, please, consider some examples. If a new metabolic pathway arises do the number of genes remain the same? What about their organization? What about the way their organization is itself organized? However, if an animal adapts for a new environment does it always implies some "fundamental" changes in its anatomy and physiology or does the simple change of "minor details" suffice to make it fit for its new niche? In the first case you can say there is a remarkable increase in complexity, while in the second you can claim just "a simple adaptation". In order to connect the increase in adaptive variation and the organization generating it one needs to know the mechanism beyond both, which as you can see returns us back to the point already discussed in the "denial by definition" problem. If there is an increase in the number and/or interconnectedness of such mechanisms one can make the point the two are pretty much connected with each other and prove the point such a definition can be taken as the definition of complexity in biology. Then, the "denial by definition" argument automatically dissolves by itself and such a definition of complexity can be accepted as a working one. On the other hand if there isn't any relationship between the generation of new mechanisms in the living world and an increase in the connection between variation and organization we should be able to see examples of increased variation without new organizational features and the vice versa. However, I think we can easily prove that in the living world in order to increase the potential variation any lifeform can have, the number of its organizational features should also increase and the vice versa. Can you imagine spiders evolving into diverse families and species without their ability to weave webs? Or the evolution of the higher plants without the evolution of leaves? Or the evolution of new bacteria without the evolution of new metabolic pathways? And so on and on. I believe you can readily see the point that every time adaptive variation becomes able to widen its scope one can see the corresponding emergence of new organizational features. I believe you can easily make the case for the opposite argument, too-that new organizational features always increase the ability of the organism to vary and therefore to take over new niches. I wouldn't be giving examples for the sake of shortness here but I believe you can see my point. New organizations widens variation and new variation allows better adaptability. Of course, new organization isn't always required by the organism to adapt to new niches, but new organization always arises and stays in evolution to make the organism fit for new niches. My argument is that this relation is the mechanism connecting adaptive variation and the increase in the number of organizational features and it by itself is the definition of complexity one should adopt in biology. Thus, complexity can be defined as the increase in organization driving the increase in the potential (here potential is key word because one can make the case new organisms with new organizational features can have lesser ability to vary than their ancestors, and in fact we can see that there is the trend the more "complex" the organism is the more are those features which remain conservative through its further evolution, but if we consider the overall ability of the new organism to evolve ever newer and newer forms we can see more complexity actually generates more variation because the ability of the ancestor to vary was limited by its organizational features while the evolution of newer features means they can add more possible routes evolution can use-"the trick" isn't to consider the overall ability of the ancestor to evolve on many potential routes but the net gain available to vary more organizational features give on the routes of its descendants which has to be greater than the ancestor according to this definition) variation which can be used to adapt to new niches. If I have to "translate" it in a more "layman" (e.g. non-philosopher) terms complexity is the increase of possible routes evolution can take on when new organizational features emerge. It means the emergence of new organization have to always generate more variation which can be used to adapt to new niches and the ability of the organism to widen its adaptability must always come with the emergence of new organizational features. If we adopt this definition then organization and adaptation become fundamentally linked by definition and we don't have to search for the cause of either any more. The significance of this definition is that then this isn't mere "play of words" to define complexity any more, this is viable scientific hypothesis! We can prove the statement: " Every time new organizational feature appears more variation increasing the ability of an organism to adapt is also generated and the vice versa." by observation of our data. If you can provide even a single example of an organizational feature appearing "just by accident" with no extra ability to vary generated by it, then, you have your proof the above statement is wrong! One can argue philosophy is mere "play of words" where you can choose different conflicting "opinions" about a certain question and make the case they can be both correct depending on your point of view, but science isn't. It means the moment you can make a statement that can be put to the test by observations of reality this isn't philosophy any more-it's science! Do you understand my point?
If this definition of complexity allows us to make statements about the observable universe, then, this isn't any more some "philosophical definition", it is verifiable scientific hypothesis which can be put to the test. It means we were able to "export" a question out of philosophy and "import" it into science. And this is an achievement!
Then, this definition can serve as the base for viable scientific investigation. Now, the questions is "Why and how complexity usually tends to increase through time?", right? (This is the last revision I'm using here-I don't remember exactly what was the previous one but I'm certain the topic is still about the reason (why) and the mechanism (how) complexity is increasing through time. Correct me if I'm wrong, please.) Therefore, our investigation requires what we deem as complexity to be able to increase through time for a reason (the "why" part) and with some common mechanism (the "how" part). Do you agree? The definition I already made the case for connects the increase in complexity (as the appearance of new organizational features) with the variability of the organism which in turn serves as the source of adaptability. Therefore, the reason why new organizational features should appear in the organism (and therefore, define this as an increase in complexity) is its adaptability. If the above hypothesis that the appearance of new organizational features and the generation of new variability for new adaptability holds (which is how we defined complexity), then, the reason for the appearance of more complexity (by definition) is the very environment the organism needs to adapt to. The reason fro complexity is none other than the reason for evolution itself-the drive to always increase its number. But in the particular case for complexity it is the fact that the environments presents to the organization of the organism new challenges its current form isn't able to adapt to. This is why the organism evolves some extra organizational features  it can use to cope with these challenges. Now, I know may be this isn't the answer you were looking for when you specify about the genes or the proteins or whatever, but it is a viable answer of the question you posted. The term "new organizational feature" can represent wide range of possibilities-may be a new gene, may be new metabolic pathway, may be some new mechanism for the regulation of gene expression, may be the development of some new organ or gland in the organism, may be the development of new hormone and so on. As you can see the list is endless but this is exactly what the answer of your question is. Different environments force organisms to develop different organizational features which we deem as an increase in complexity. It is us who think of complexity as some "global move" of Life to more and more organization, but are you sure that Life itself thinks the same way (we if assume that evolution is intelligent)? Put yourself in the shoes of the evolving organism. Why do you need to evolve? Because you "feel like" you have to become more "organized" or because you simply must in order to survive the new environment? What do you think evolution would answer you if it could speak? It is us who think complexity is some "grand move" of Life to become more and more organized! From the point of view of the organism themselves Life is just Life as "usual". They simply want to survive and reproduce any way possible. Some of those ways involve "minor changes" well within the organizational features of the organisms themselves under their current level of organization, but some require what we (not the organisms themselves) can call as "giant leaps" or "quantum jumps" in evolution. Do you think the first fish to start to evolve into a land based animal wanted to walk? Or it simply wanted to be able to move on the ground to be able to escape drying ponds? What about the first reptile to be able to evolve into birds? Do you think it wanted to fly or to escape predators in the air? How about the first ape to become human? What did it want-to become an intelligent being able to change the world or to be able to gather into more compact and well organized groups to find food and fend off predators better? I think the examples are endless here, too. The point is the environment itself sometimes requires organisms to get new organizational features to survive in it, not that there is some "grand mechanism" or "tendency" of Life to get more "organized". If such "great tendency" is to be assigned then it has to be to the environment itself, not to the organisms! One can make the case the more organisms an ecosystems has and the more are their interactions among themselves the more new niches this ecosystems can offer to new organisms which in turn can develop new organizational features which can produce new organisms which can offer yet other new organisms more new niches and so on in an ever expanding self-sustaining process. Here is a nice reason for complexity, isn't it? The argument can be further extended for organization itself. If new organization (which is required by the diversifying environment) can bring about more diverse environment which can in turn bring about the emergence of niches requiring even more organized organisms and so on in a self-sustaining manner, then, in a way the mechanism to bring about ever more complexity in the world. But, remember, this is not depending on the organism itself, but on its environment. The question of "Why does complexity usually tends to increase through time?" is transformed into the question "Does the ecosystem itself require increase in complexity to develop further?" which as you can see are 2 very different questions. Then the focus fall not on complexity by definition but on the environment as a whole. And this is one very different question. And it is one we can have the answer to if we can know enough about the ecosystem this organism is in. Once again you can see how "superficially" "philosophical" questions can be transformed into distinctly different scientific questions if we can clarify our definitions and follow through the consequences of those. This is a particular approach I myself have developed but it isn't something accepted by the community, so you are free to disagree with my approach and answer.
As far as the mechanism part of your question is concerned I already "touched" on it when I defined complexity.By the very definition I expounded whenever there is an increase in complexity (e.g. the appearance of novel organizational features) there is an increase in adaptability it brings on. Therefore, the more complexity an organism accumulates the better it can adapt to particular conditions. The increase in adaptation means novel features it has and the novel features it has define complexity, therefore, one can argue adaptation driven by the accumulation of novel organizational features IS the mechanism of complexity increase. This is a "classical" case of the "denial by definition" argument I put on previously! If you say complexity increase is the adaptation by accumulation of organizational features, then the entire question "What is the mechanism of complexity increase?" which in turn can be equated to your question "How does complexity usually tend to increase through time?" simply dissolves or to put it in layman's terms-makes no sense at all.
I know it may seem like "too much philosophy" for biology but the thing is the arguments I put forward actually make sense if taken together and if you want to come to a satisfactory answer to your question (which itself isn't asked in a clear-minded manner according to me), then you need to take the steps I already described and "translate" it into questions which can be answered in more rigorous manner and if they are done (as I suggest here) may be you can agree you have your answer?
To conclude this all too long reply I would like to reflect on personal experience with both philosophers and biologists. My experience has been that both the philosophers don't want to reflect on the science biologists are trying to put on with their questions and the biologists don't want to reflect on the arguments philosophers are trying to put on when reflecting on the biological questions. In my mind this is what "the tragedy" of modern biology is part of because philosophy may be is able to provide answers biologists may find useful but they just aren't listening to them. On the other hand if biologist can "export" difficult to tackle in the modern biological paradigm questions to philosophy, than, may be, philosophers can bring on understanding and possible explanations biologists are just missing! It can be very fruitful relationship! But in order to do it one just has to listen to what the other has to say and this "listening" isn't something either side do very well in my mind. Thank you very much if you managed to endure long enough to get to here, I didn't intended to make this answer so long but as you can see the argument isn't easy to follow either.
Thank you very much for your patience.

I agree that a flimsy definition of complexity is what makes this question a challenge to answer. I think the idea of linking rate of changes in a system to the rate of new characteristics would answer questions about evolution. However, this is hard to quantify objectively & scientifically assess. Not only that but the scale of study required is well beyond what is currently available to scientific interrogation. Ultimately I'm downvoting because the answer isn't succinct, and doesn't attempt to answer the question, but rather comments on the definition of complexity.

@James, I revised my answer. At first I thought it will be one very long to write it here so I tried to present short arguments. But after I saw your comment yesterday I said to myself: "Why the hell shouldn't I write my entire point? If you desire the full argument, then you should get it." and here it is my full argument. I know it may be too long for this site but I downstated my point and used simple language so everybody can understand me. I even bolded the important points. Is this answer succinct? Does it attempt to answer the question?

IMO -1 rating is too harsh, so I corrected it. As for relating philosophers and biologists I think Bruce Alberts in "Molecular Biology of the Cell" captured it the best: "It was innovations in lense grinding, rather than any philosophical advance, allowed Hooke and Levenhook to discover previously unseen cellular world"

Biology arises when some molecules begin copying themselves with a certain amount of error: not too much error, or there would be no heritability; but SOME error, or else there would be no evolution at all. Copying, copying, a few molecules become a multitude, and evolution spreads in all directions, to the more and to the less complex. But when a new level of complexity arises, it usually allows a new size, and a bigger organism can, for instance, eat a smaller organism. Once this level is achieved, it tends to be mantained. Again some copies will lead to smaller lineages, but the big ones have founded a niche that will not disappear by itself (it may take an asteroid). So, looking up close, evolution leads to diversity, not only to higher complexity. But since small complexity already existed, and bigger complexity is something new, we tend to perceive evolution as creating complexity - which is not a false point of view.

I think you are conflating complexity with a necessary increase in size and with speciation, which wasn't the point of the question.

The question was "why and how does complexity increase"? I explained it. Size and speciation are part of the answer. We needed eucariotic cells to get bigger cells. Bigger cells were mantained because they lived in a new niche, where competition couldn't expel them. We needed three germinative layers to have bigger and more complex animals. Size and complexity are like the egg and the chicken, they generate each other.


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What causes tissues manifest the various forms that they do?
A heart (or any other organ) is comprised of a group of cells. To the best of my knowledge, the growth of a heart depends on cell division. However, cell division by itself doesn't seem to explain why heart cells collectively manifest the form of a heart.
What causes tissues to manifest the various forms that they do?

Are you asking about how heart or any other organ forms, including how it assumes its geometry? That question would be too broad. You should narrow down the question to a specific aspect.

@WYSIWYG It seems to me that if tissue grows by cell division, all tissue should form a blob (or maybe an approximation of a circle if it were growing on a flat surface). However, organs grow into specific forms, not just blobs. It seems to me that the cells would have to coordinate their positions with each other in order to do that, which seems absurd to me. Nevertheless, something must organize the cells. I mean to ask what organizes into the forms exhibited by (for example) organs? Is that a sufficiently determinate question?

Okay... so add these details to your question. Clarify that you are interested to know how the cells get arranged in a certain structure. Since this is a general question you should expect only a general answer.

This is a subject of active research. All the cells in the zygote are identical up to 8 cell stage. At the next division resulting in 16 cells formation it is called a morula.
The zygote has totipotent cells meaning each cell has the ability to develop into full organism by itself if it separates from the zygote (this is how identical twins are born).
Human zygotes are totipotent till at least 4 cell stage. In other primates experiments have demonstrated totipotency upto 16 cell stage.
The totipotent cells differentiate into pluripotent cells and then into various distinct cells belonging to different systems. This process is very complex and a lot of embryological factors and chemicals come into play.
The embryonic factors cause migration (called embryotaxis) and differentiation of the embryonic cells. Some of the factors are sonic hedgehog, wnt, insulin like growth factors, Hox, etc...
Different factors cause differentiation into different cell lines. These factors also cause the organs to attain specific shape and structure, thus the heart is shaped as a heart and the liver is shaped as a liver and so on.
Once the cells differentiate into a particular line, the stem cells of that region generally differentiate into that particular line due to the paracrine influence in that locus, even though these stem cells can differentiate into other cell lines when appropriately stimulated (thus demonstrating pluripotency). So intestinal stem cells would differentiate into goblet cells, surface epithelial cells, Enterochromaffin cells, etc... which are present in that locus.

For more see here:

http://www.sciencedirect.com/science/article/pii/S009286740800216X
http://www.embryology.ch/anglais/iperiodembry/controle01.html
https://www.bio.cmu.edu/labs/ettensohn/pdfs/dvg22746-2.pdf


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Spider Identification Michigan
This was taken in Ann Arbor, MI.  It looks a bit different from the wolf and grass spiders I'm used to seeing.  Anyone know  what this might be?
edit: Per request, I've uploaded a better picture.  Actually, it's the same picture, but I postprocessed the first image quite a bit to ease identification.  The second one is not post processed but (hopefully) clearer.
Processed image:

Unprocessed image:

the camera focused on the trash instead of the spider. Do you happen to have a better image?

Unfortunately stack overflow optimizes it a lot when I upload, and the quality suffers.  Let me try Dropbox.  Just a moment

Also consider switching your camera to a non-lossy format for future use, if possible.

@jzx - Can this be done on the iPhone 6 - do you know?

What was the real color of the leg's stripes?

@Ilan:  I don't know if you can see it on your screen - but the actual image color of the non-processed image is pretty close.  Something like a medium-to-light brown.

I am not an expert by any stretch of the imagination, but I think  the lighting is pretty different in my examples. There are about 70 kinds of spiders generally in the U.S. The shapes are important, as are the habitat, the  presence or absence of a web (fishing spiders don't usually make webs), an egg sack, etc.  Narrowing things down significantly, this is my best guess . The eye pattern would help a lot.

I can't tell how big your spider is. :( But I agree, it's probably not a wolf spider. (The fourth pair of legs is the longest in the wolf spider
I think it might be a fishing spider (Dolomedes tenebrosus). They do hang out in man made structures and are the most common fishing spiders found.

Fishing spiders are similar to the larger wolf spiders in size, shape, and coloration. Species in the genus Dolomedes are called fishing spiders because most live near water and have been reported to catch small fishes and aquatic insects from the water as they walk on the surface. The species Dolomedes tenebrosus is more frequently associated with wooded areas (it would be more accurately classified as a tree-dwelling spider) and is a common household invader in these locations. It occurs from New England and Canada south to Florida and Texas.

The stripes on the legs are characteristic, the shape and size ratio of the thorax and abdomen are right, and they are smaller than their giant cousins that catch minnows (!). The coloration on the abdomen can vary. The females are 1.5 to 2.6 cm *about an inch) in length; males are smaller. The legs of both male and female are banded with alternating brown/black, scalloped rings on the femurs and reddish-brown/black rings on the tibia. Seeing an eye pattern and/or a good side view would help.

This is a great answer.  Unfortunately - he has been released into the world, so I can't get any better pictures.  The only thing that makes me question (not disagree) whether this is the  right guy (or gal) is lightness of the hair on your guy.  There are a million different reasons that that could explain that  that are unrelated to anything biological, but it seems to me, mine is quite a bit darker.  I'm certainly no expert, so I'd definitely defer to your wisdom here.  Thoughts?


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Where do the electrons and protons formed from biological reactions go?
In a reaction like disulphide bond formation protons and electrons are released. These particles are presumably damaging in high levels. What systems are in place to prevent a build up of electrons and protons?

I've reproduced the diagram that you linked to. It shows the oxidation of a pair of thiols to create a disulphide. What is missing from this scheme is the accompanying oxidising agent. So for example this could be carried out without catalysis in a reaction with molecular oxygen, in which case hydrogen peroxide would be formed. So the electrons and protons have ended up on the oxygen.
In a biological system this oxidation would usually be carried out by an enzyme, in which case the oxidising agent would probably be FAD (flavin adenine dinucleotide) or NAD+(nicotinamide adenine dinucleotide). These are by far the most commonly used redox cofactors. In a typical eukaryotic cell these would end up either (a) being reduced either by the mitochondrial electron transport chain (in which case the ultimate electron acceptor would again be oxygen); or (b) when they were used as a reducing agent in a metabolic reaction.

Additionally often Glutathione (either oxidized or reduced depending on the reaction) is part of it.

@Chris thanks, I forgot about glutathione. Of course the diagram could actual be the oxidation of glutathione!


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Why are transmembrane proteins difficult to crystallise?
I know that in vivo there are a lot fewer transmembranous proteins in general, and that they are produced at a lower rate than their free counterparts. This is mainly because transmembrane proteins are only required in a 2D space on the membrane rather than a 3D cytoplasmic or extracellular space. This (again, very broadly speaking) means that the probability they will interact with their target is higher.
I also know that this is one of the reasons that producing crystals for X-ray crystallography is notoriously difficult for transmembrane proteins. What are the other reasons that make transmembrane proteins typically tough crystallisation candidates?
What specific part of the crystallisation process yields such poor success rates of transmembrane protein structure elucidation?

high hydrophobicity is one factor

There are several factors that make obtaining crystal structures from membrane proteins more difficult.  In brief, nearly every stage of obtaining the structure via crystallography is more difficult.
First: protein expression.  Large amounts of pure, well-folded protein are required and this is much more difficult to achieve than it is with a soluble protein. Since membrane proteins are bound within a membrane, the mechanisms to translate the peptide into the membrane and to fold the protein in the membrane are different.  They may involved folding factors which are only available in a particular compartment of the cell (making bacteria impossible as a system of expression).  In high amounts in the cell, their hydrophobicity might tend to result in clumps of unfolded protein instead of gobs of membrane-associated protein.
Next: Purifying the protein is more difficult.  The expressing cells are usually broken open in the presence of detergent to get the proteins to float around as individual proteins in detergent micelles.   The wrong detergents might break up the membrane protein and it may lose its fold - the concentration of detergent must be carefully managed and kept at optimal levels or the micelles might break up and the protein will be ruined.
Crystallizing the protein is quite a bit more difficult too.  Membrane proteins in detergent micelles which may or may not be charged themselves look like oily blobs with hopefully a domain or two of folded proteins sticking out of them.  Compared to a soluble protein with a nice ordered surface in every direction instead of a detergent micelle which might undergo a phase change at high concentration or by the addition of a salt or change in pH, membrane proteins take a task that might take thousands of trials and adds new dimensions to worry about.
The proteins are 2D-like, but the crystals still have to be 3D for crystallography to work usually.  Protein crystals are small, but those derived from membrane proteins - which tend to organize into planes like the membranes they inhabit - are often thin, which can make them too delicate and small to get a good set of data even from synchrotron beams.  As a result, the crystals are commonly too small or thin to use at first, requiring extensive optimization after the first crystal are found.
In a few cases some membrane proteins have been solved with 2D crystals using electron microscopy on crystalline arrays of porins and rhodopsins in membranes. That was a ton of work but they were the first membrane protein structures by years and years.
Not to make all this sound impossible - once you have crystals, they can usually be improved; there are good starting points to crystallization and purification with detergents.  It's just that a process which can already take quite a bit of time (years) and can sometimes end in frustration takes even longer and is less certain with a membrane protein.

.. i have to say it doesn't matter so much anymore - cryo EM will do most of these structures...

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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Can proteins move outside cells?
I am trying to learn about basic cell biology, and have what is probably an extremely simple question.
So this is how I understand it so far:
Proteins are made from amino acids. This process is called protein biosynthesis, which is carried out by the ribosomes. So proteins are made by the ribosomes in every single cell.
So are the proteins made by the ribosomes to stay in the cell? Or can a protein move to other cells, and if so, what's the reason behind it?

Yes. All proteins actually begin to get synthesized on cytoplasmic ribosomes but if they are going to be used for extracellular purposes, they are tagged and whole ribosome is taken to ER where protein synthesis is completed. The proteins are exocytosed with help of Golgi body, the post office tagging and packaging organelle (the Golgi body packages these proteins into the vesicles that fuse with the plasma membrane).
Examples of this process are: the pancreas secreting insulin for blood sugar control, digestive enzymes for digestion, the immune system telling the body there's a bacterium we must fight it and calls more immune cells (cytokines). Most proteins of course stay in the cell, and are necessary to make the cell or carry out metabolism or DNA transcription.

Extremely good answer which really helped. Thanks!

My pleasure Lars!

Thanks Alan :) how did I forget Adrenaline is a steroid hormone...

Other examples are neuropeptides produced by neurons in the brain (e.g. endogenous opioids, various neurohormones such as GnRH, GHRH, vasopressin, oxytocin etc etc)

Collagen and elastin are other examples of extracellular proteins.

I would like to complement dd3's answer a bit. It is about bacteria

Bacteria secret enzymes outside. The bacterial membrane has import size limits and it is necessary for them to chop the big molecule into smaller pieces before import. Examples are glycoside hydrolases and protease. Bacteria take part in the clean-up after the annual algal and jellyfish bloom. It is especially important for the jellyfish because they have few predators and if it were not for the bacteria, their gelatinous body will pile up at our sea bottoms.
Bacteria release protein toxin, either to defend, or use to recognize the host if they are symbionts.
Gram-positive bacteria use peptide as autoinducer to do quorum sensing.
Last but not least, bacteria sometimes form aggregates. The glue among them is chemically very complex (in other words, we don't know exactly what it is). It is believed sugars are there and, proteins too.


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Does NADH inhibit gluconeogenesis?
I was told in a physiology lecture that alcohol inhibits gluconeogenesis because 'NADH produced from ethanol catabolism leads to product inhibition'.
But is NADH not a reactant coenzyme of gluconeogenesis? It would make more sense if NADH inhibits glycolysis by product inhibition.
So, what is wrong here? Or is it because of some other reason why alcohol inhibits gluconeogenesis and leads to hypoglycemia?

Yes, this is the effect of metabolizing ethanol and also the reason why excess ethanol can lead to hypoglycemia.
Ethanol is oxidized by the alcohol dehydrogenase to acetaldehyde. This reaction consumes one molecule of NAD+ per molecule ethanol oxidized:
Ethanol + NAD+ <=> Acetaldehyde + NADH + H+

Acetaldehyde is oxidized by the acetaldehyde dehydrogenase in a second reaction in the mitochondria to Acetyl-CoA, which produces another molecule of NADH:
Acetaldehyde + NAD+  + CoA <=> Acetyl-CoA + NADH + H+

If you now take a look at gluconeogenesis, there is one critical step which needs NAD+: the oxidation of lactate to pyruvate by the lactate dehydogenase which then cannot be processed into oxalacetate, phosphoenolpyruvate and so on.

Adding excess NADH shifts the reaction equilibrium completely to the side of lactate and also leads to the production of additional lactate, leading to hypoglycemia and lactic acidosis. Excess NADH from the ethanol oxidation inhibits the oxidation of fatty acids in the liver - this process also generates NADH for the production of ATP. NADH signals this process that enough energy is available in the cell. And finally excess NADH also inhibits the malate dehydrogenase reducing the amount of oxalacetate for gluconeogenesis further.

Good explanation

Partially correct. Please allow me to explain. It is mentioned above: "shifting the equilibrium to the production of additional lactate, leading to hyperglycemia..."
It's true that excess NADH production as a result of alcohol consumption inhibits oxidation of lactate to pyruvate via lactate dehydrogenase. But, this leads to HYPOglycemia, not HYPERglycemia, because lactate is not adequately converted to pyruvate to meet the body's metabolic demands.
What are the repercussions?
Less pyruvate created ---> less of its conversion to oxaloacetate, which under normal conditions, would usually traverse across the mitochondrial membrane into the cytoplasm to be converted to PEP via PEPCK. Less oxaloacetate as a result of less pyruvate being shunted towards the gluconeogenesis pathway ultimately leads to HYPOglycemia.
Although ethanol on its own (like if you were to drink grain alcohol) would result in a drop in blood sugar, and this is ESPECIALLY a danger for individuals with Type 1 diabetes. Beer, wine, and common spirits rarely cause a drop in blood sugar because they also provide carbohydrates. These carbohydrates help to maintain blood sugar, if not elevate it on a binge.

Welcome to SE Biology.  I think hyperglycemia was probably just a typo in @Chris post.  It would probably be better to just edit the accepted answer to correct the mistake.

You can simply correct typos in answers. As I have no corrected mine (thanks for spotting it), your answer is obsolete.


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What is a bacterial biofilm?
Bacteria produce something called a biofilm.
I have found a few definitions; some say it is a complex of live and dead bacteria and others say it is a layer on cell wall.

What is it made of?
What is its purpose?
How do we combat biofilms when we encounter them?

Why would you want to combat them universally?  Some do us harm (e.g., the plaque on our teeth) but most are essential for the functioning of the biosphere.

Hi Kenny. I dont. I just like to know about them universally ;)

Aside from the actual microbial cells themselves, biofilms are a slime matrix made of a variety of substances, including DNA, lipids, proteins, and other signaling molecules, but the major component is something called extracellular polymeric substance (EPS), also known as exopolysaccharides.

Succinoglycan from Sinorhizobium meliloti
These are high molecular weight extracellular (exo) polymers (poly) of sugars (saccharides) linked together into long linear or branched chains, which can be modified by moieties such as phosphate, sulfate, acetate, and succinate. As the biofilm forms (below), channels can form in the EPS to facilitate nutrient uptake and distribution, hydration, and inter-cellular signaling such as quorum sensing. Biofilms are often composed of multiple species of microorganisms, from bacteria and archaea to fungi and algae, with the social (and physical) structure dependent on the species that compose it.

Bacterial biofilms are a bunch of bacteria that have attached themselves to a surface or to each other as a floating mat to form a solid phase community.  Its not seen in the lab so much, but they are common in nature.
The bacteria not only adhere to the surface, but each other through a matrix of polymers they secrete.
The bacteria in a biofilm are often resistant to chemicals, heat, acid and other changes in the environment.  Its a practically universal trait and its generally assumed that any bacteria can form a biofilm.  Dental Plaque is a biofilm.
Getting a biofilm eradicated can be a lot of work because the bacteria are sequestered in the matrix and somewhat protected.  Scrubbing or chemicals are usually used.

I'd add that Variovorax (http://www.jgi.doe.gov/sequencing/why/100320.html) is a biofilm producer that grows biofilms nicely in the lab.

just saw this now - a major regulatory switch that causes biofilm formation was discovered. http://www.sciencedaily.com/releases/2013/04/130412132413.htm

also FYI E coli can form biofilms... http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2864707/

biofilm is a sort of bacteria's small attempt towards multicellularity.. biofilm is not just a layer of bacteria.. it is a system in which different bacteria can assume different roles

indeed it has structure and different individuals appear to have different roles (or at least genetic activity).  E coli form bacterial slugs as well... See Howard Berg's work.. :)


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Doesn't osmosis violate the law of conservation of energy?
Osmosis seems very counter-intuitive to me. I will try to explain my doubt with the following thought experiment:
Consider a huge container divided into two by a semi-permeable membrane. We add equal levels of water on both sides. On one side, dissolve some sugar. After some time, there will be a net movement of water to the sugar containing side of the container. This will increase the level of water on one side and decrease it on the other. If we create a huge hole in the membrane (large enough for both water and sugar molecules), then water will rush from one side to the other, equalizing the levels. If we were to somehow place a turbine at this hole, we could generate quite a bit of energy. Where did this energy come from?

Liked the way you presented it

I'm no thermodynamics expert, but Ill have a go at this.
The energy comes from the original set up, in which you have created a low entropy state. As the diffusion of water molecules equalises their concentration across the membrane so the entropy of the system will increase. This translates to a negative free energy change. That manifests as potential energy stored in the hydrostatic pressure resulting from the changes in volume, which in turn is available to turn the turbine.
So in the case of an experiment of the type described, the energy is derived from the experimenter who sets up the experimental situation in the first place.

Small Addition: free energy changes and the reaction spontaneity is governed by ambient conditions. The semi permeable membrane poses an energy barrier. Given this barrier, osmotic motion, brings down the free energy by entropy maximization (as Alan Boyd said).


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Is there any other function of DNA?
We all know that DNA acts as a genetic molecule. Does DNA have any other function in the cell other than being a genetic material and carrier of information?

In eukaryotes DNA has a structural as well coding function. Parts of chromosomes called centromeres bind to proteins and form a scaffold which helps chromosomes attach to each other and correctly segregate during division. Technically this is still related to the transmission of genetic information though.
Since RNA can act as an enzyme (the so-called ribozymes), scientists have hypothesized that DNA can also have an enzymatic function, but no such function has been found in nature. Artificial DNA enzymes (deoxiribozymes) have been designed to cleave DNA, covalently modify proteins, ligate RNA molecules, and even catalyze reactions between small molecules. See this lab's website.

as far as i know DNAzymes are purely synthetic.. Are there natural DNAzymes too ??

No, there are only synthetic ones

I want any other function inside living cells. Is there any ?

From what I researched, no

DNA has the following functions other than genetic material :

It can function as a molecule that attaches to TLR ( Toll like Receptor ) on or in cells and so  can contribute to innate immune response.
It can act as carbon source. ( We have nucleases enzymes in our intestines.)
It can be structural component of biofilms.
It can also influence pH in cells as it is an acid.
It is a structural component of neutrophil extracellular traps to wrap up microbes.

Please feel free to correct any errors I have made.

DNA has been shown to be important for biofilm formation in certain bacteria.  This is extracellular DNA that comes from cell lysis.

Interesting! Can you give a reference?

Heres the first one I could find that is open source, but if you search "extracellular DNA biofilm" in google theres loads of papers on it: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0016861

Yes, maintenance of the genome.  But not DNA specifically, but DNA and all of its associated proteins.

Could you give a bit more detail here? It's hard to tell what you're referring to.


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Detecting Introns and Exons
I know that when RNA is transcribed from the original strand of DNA it contains introns and exons, and that the introns are spliced out of the strand to provide genetic diversity. However, what I don't understand is, how does whatever is doing this splicing know whether the section it is reading is an intron or an exon? Are there start and stop codes like there are for polypeptides, or is it determined by epigenetic factors like methyl markers? Or is it neither?

Quick answer: we don't really know.
As WYSIWYG said, splice sites do have a sequence signature. The image below (taken from [1]) shows the consensus for human acceptor and donor sites:

In the images above, the size of a nucleotide represents its frequency at that location. As you can see, there is a clear signal around the splice sites and this signal is used by various programs that do splice site prediction. What is not quite clear yet is how the cell recognizes these signals. Sometimes a "perfect" (identical to the consensus) splice site is ignored by the cell in preference to one that we would consider "worse". This is further complicated by the presence of various downstream and upstream signals such as splicing enhancers, silencers and structural elements (loops, hairpins etc) in the mRNA molecule.
So, to answer your question yes there are start/end markers for introns/exons but they are far more complex than the simple START and STOP codons of transcription. We know know a lot about it but we still don't fully understand the details of splicing.

References
Brent MR, Guigó R., Recent advances in gene structure prediction, Curr Opin Struct Biol. 2004 Jun;14(3):264-72.

There are some signature sequence which mark intron-exon boundaries. Usually introns start with a GU and end with an AG. But this feature per-se is not sufficient for splicing; there are other cis-elements such as exon/intron splicing enhancers/silencers [ESE/ESS; ISE/ISS]. Refer this article.
Also, there are protein regulators of splicing such as SR proteins; other proteins such as Fox-1/2 can control alternate splicing events.