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What insect is this?
I found it in Russia.

Where do they usually live? What do they eat?
Full length is approximately 2 cm.

Terrestrial crustacean

Seems to be it's a Woodlouse!
http://en.wikipedia.org/wiki/Woodlouse

And, of course, whatever it is it isn't an insect.

Indeed, by true definition you are looking at a crustacean instead of an insect. The differentiation can be made because crustaceans are biramous, meaning their "legs" have two segments instead of the typical one in most insects.

@MichaelCannon.. arachnid perhaps ??

@WYSIWYG it has 12 legs, arachnids have 8 by definition. The woodlouse/pill bug is in the subphylum of Crustacea.

and interestingly, woodlice are said to be delicious in a soup!

This is a terrestrial isopod crustacean called a woodlouse (colloquially referred to as pill bugs, potato bugs, roly-pollies, sow bugs, etc.).

There are over 5000 species in the world with at least 64 in Russia (see Kuznetsova & Gongalsky 2012).
Habitat:
Woodlice are typically found in damp, dark places -- in the soil, under rocks/logs/debris, etc.

Living in a terrestrial environment, woodlice breathe through trachea-like lungs in their paddle-shaped hind legs (pleopods), called pleopodal lungs. Woodlice need moisture because they rapidly lose water by excretion and through their cuticle, and so are usually found in damp, dark places

Description:
As with all Arthropoda, the woodlouse is a segmented animal with a rigid exoskeleton and jointed limbs.

However, this is not an insect! Insects have 3 pairs of legs while isopods have 7 pairs of legs.

The extended uropods on your specimen as well as the pereon-pleon junction, number of antenna flagella, etc. all are important for IDing to species. (E.g., see here).
Note: although many people associate these arthropods with the ability to roll up into a perfect ball, only woodlice in the genus Armadillidium and in the family Armadillidae can roll up into an almost perfect sphere as a defensive mechanism.
Diet:
Woodlice are generally detritivores, meaning they eat decaying organic matter.

Citations:
Kuznetsova, Daria M., and Konstantin B. Gongalsky. "Cartographic analysis of woodlice fauna of the former USSR." ZooKeys 176 (2012): 1.


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Why does the PR form of phytochrome exist?
I know how it gets converted because PR is more stable and when there is neither red or far red light PFR naturally converts to PR. But what is the point of it? If PFR is the biologically active one why didn't evolution just make one pigment, PFR. At night neither is active so PR again has no point, in the morning PR gets converted to PFR. So why do we need a PR?

First off, "evolution" doesn't necessarily lead the most efficient system for anything - it works with what we already have.  Once something has evolved, it might not go away, if there is no particular harm to having it around. You might take a look at the evolution tag, as other people have asked similar questions about the "usefulness" of biological mechanisms and molecules.
Aside from that, having both isoforms is important for the detecting the color of light. When Pr absorbs red light, it gets converted to Pfr, and when Pfr absorbs far red light, it gets converted to Pr.  The ratios of Pr to Pfr allow plants to determine light levels and adjust their growth accordingly:

Sunlight has a R:FR ratio of 1.2

Light under a canopy of leaves has a R:FR ratio of 0.13

Light under 5 mm of soil has a R:FR ratio of 0.88

A higher proportion of FR light allows plants to detect when they are
shaded. Plants adapted for growth in full sun will display greater
stem elongation when they are transferred to shade.  They also develop
smaller leaves and less branching.  This change is due to greater
proportion of Pr to Pfr.

Seeds of certain plants require red light for germination; FR light inhibits germination.  Many small seeds with low amounts of storage reserves (such as lettuce) show such a red light requirement.
If these seeds they are buried below the level of light penetration in the soil, they do not germinate.
If they are shaded by a leaf canopy, causing a high proportion of FR, germination is inhibited, [as] Pfr is required for germination.

Source: Missouri Botanical Garden

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


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Reproductive isolation causing evolution
My course book says about reproductive isolation that it does not allow the interbreeding among the individuals of different species. It also says that it is a cause of evolution.
How is this cause of evolution?

could you quote what the book says and tell us what book that is?

Reproductive isolation isn't exactly a cause of evolution, but rather a cause of speciation. Reproductive isolation allows for two cohorts of one species to be reproductively separated. In this case, evolution via random mutation or mechanisms like genetic drift allows for the differentiation of the two groups, up to the point that the two cohorts and their respective gene pools have evolved to be completely different species.
Truly defining a species is still debatable (via the Biological species definition, Morphological, etc) but reproductive isolation is definitely a mechanism involved in speciation.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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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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Manipulation of gene expression using VP16 fusion and engrailed fusion to a transcription factor?
Today, a presenter briefly mentioned that gene expression in sea urchins during development might be manipulated using VP16 and engrailed fusions.
On a slide, it said that expression might be increased by mRNA injection or "VP16 fusion to binding domain of TF" and decreased by antisense morpholinos or "engrailed fusion to binding domain of TF".
I understand mRNA injection and antisense morpholinos, but I am unclear about the roles of VP16 and engrailed in this context. Can anyone clarify?

VP16-activation domain fusion to a DBD can make the  hybrid protein get strongly and easily activatable. Check this paper out.. quite an old one

@WYSIWYG: thanks, that addressed the first part of the question.  Apparently, genetic manipulation in sea urchin embryos is quite tricky, so I'm not surprised to see a rather old paper as a reference for a technique.

And I found the answer to the second part: http://nar.oxfordjournals.org/content/30/21/4709.abstract. @WYSIWG, if you want to write your part as an answer, I can add this part and mark the whole question as answered.

sure..no problem..

VP16 is a herpesvirus derived protein transcription factor, which activates the early genes of the viral infection cycle. The activation domain (AD) which is formed by the 78-amino acids from the C-terminal, can be fused to DNA binding domain of other protein transcription factors, such as GAL4, to make a hybrid protein that constitutively and strongly activates transcription, without the requirement of any ligands. VP16-AD interacts with TBP, TFIID, SAGA histone acetyltransferase complex, and PC4 (transcriptional coactivator positive cofactor 4) to drive transcription.
The engrailed gene, from Drosophila, is a transcriptional repressor.  When the repressor domain is fused to transcription factors, the fusion results in trans-dominant negative functions of the transcription factor (phenocopying loss of function mutations in the target genes).


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Deterministic model of lambda-phage lysis/lysogeny [MATLAB]

Project 1 Base:

Can someone please help me understand what I need from Project 1 Base code to do questions 1 and 2 from the first image? I'm new to MATLAB so a thorough explanation would be great.

This can be done using loop method or Forward Eular's. I don't know which one is easier for this question nor would I know how to do it myself since I have never taken a programming course before and am somehow expected to know how to do all this.

For homework questions, the policy is to see some work from the poster.  Since you don't know programming, I've outlined what the code is doing, beyond the simple operations (+, -, /, *, ^), to get you started.  I think you should be able to implement the models with this information, and I'd be happy to confirm your own answers.

So the best way to figure out what any line of code means, in any language, is to type it and see what happens. To help you get started with programming in MATLAB:
Any text following a % (on the same line) is a comment: it does nothing in the program, and is only there for you to write notes to yourself.
The first two sections, Time-Related Constants and Simulation Constants, are just setting variables. It's like saying x = 3, so that later on you can do other operations with x.
The semicolon at the end of a line (in MATLAB) suppresses the output of the line. See what happens if you type x = 3; versus x = 3 at the command prompt.
In iteration constants, length is just a function that tells you the length of the vector.  X_rna_0 was previously initialized to go from 0 to 1.4 in steps of 0.2: the syntax is vector_name = start:step:end.
The simulation variables section is creating xyz-matrices, with all values initialized to zero.  The length in x is xr_max, and so on.  The idea is that, later on, at each step in Euler's method and each value of xr_max and xp_max, you'll save the value of X_rna.
The initial conditions are being set using meshgrid, which is best explained here.  The : means all of the rows/columns, corresponding to position: say you had a 3 x 3 matrix called apple.  apple[:,1]  gives you all the first column (1) of all three rows.  apple[1,:] gives you the first row (1) of all three columns. The .' means that the matrix is being transposed: again, the best way to see what's going on is to create a matrix of your own, perform the operation, and see if what you get is what you thought it would be.
For loops, you can read about here, for a start.  I do not think understanding this loop requires more information than that page.
Dot before ^2 means that each element of the matrix is being squared; you are not multiplying the matrix by itself.
That should decipher most of the code for you.  If you have further questions, feel free to comment here.
EDIT: Question 2 asks you to make a plot.  A plot of y vs. x would be made by typing plot(x,y)
Also, help on a particular MATLAB function can be accessed by typing help name_of_function.

This is a set of ordinary differential equations. Proceed like this

Make a matlab function for the ODEs that define the system (equations 1,2,3,4). The function should return a 4 dimensional vector which is basically the dy/dt (the rate equation)
in the main program declare the initial values of different components. There is no absolute rule for what it should be and it is based on your prior knowledge of the system
in the main program write a module to integrate the rate function over a time interval. there are several numerical algorithms to do it such as Euler, implicit euler, runge-kutta, polynomial interpolation- predictor corrector methods (Adam Bashworth) etc. If you want to improve your knowledge on the numerical methods then write your own code for any algorithm. A good book on basics of numerical methods can be referred. Otherwise, you can use inbuilt ODE solvers in Matlab.

A note on numerical methods for solving ODEs: what you precisely do is add-up and update the rate function in small intervals of time. The very basic method is euler in which you just implement this:
y = y + h*f(x,t)....... explicit/forward euler
y = y + h*f(x,t+h)...... implicit/backward euler

where dy/dx =f(x,t) and h is a small time interval
So what you have to do, exactly, is to run a loop which goes from t=t_initial to t=t_final with small increments of h. You can use any basic loop such as for loop or while loop. for loops are quite easy to implement. (the basic syntax is - for(initial;final condition; increment function) which in Matlab is as easy as for t=t_initial:h:t_final
Within the loop you apply the integration operation.
More advanced techniques use variable step size to improve the performance. You can use the inbuilt ODE solvers if you require better performance and accuracy.
As for your homework.. You already have the code; just need to put the parameters.


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What does conditional analysis of a SNP in a GWA study entail?
I am familiar with the use of tag-SNPs in genome-wide association studies to identify gene loci involved in complex traits, but I keep seeing the term "conditional analysis" used without any explanation. Is it some sort of mathematical manipulation in which the significance of a tag-SNP is reduced to zero, to see if other SNPs are directly associated to the phenotype in question?

In GWA studies you tend to analyze your "lead" SNPs in regions where genotypes are correlated (known as linkage disequilibrium).
If you find an association between another SNP with the outcome, and this SNP is correlated with the original variant, you can perform a conditional analysis where you adjust for the original SNP in the model. This is to test if the association between the 2nd SNP is independent of the first, or whether it is just because they are correlated (in LD).
So performing a conditional analysis is just seeing if the association observed is an independent signal.
At least, this is how I have interpreted it perviously!

E.g. SNP-A is found to be associated with increased risk of type-2 diabetes (T2D).
SNP-B is later found to be associated with risk of T2D as well.
SNP-A and SNP-B are correlated.
To see if the association between SNP-B and T2D is independent of the first association, you would adjust for SNP-B in the model (a conditional analysis).
First model: lm( T2D  ~  SNP-A + confounders)
Second model: lm( T2D  ~  SNP-A + confounders + SNP-B)

If the association between SNP-A (and/or SNP-B) and T2D is still significant then they have some independent effect on risk of T2D. If the association disappears then they are only both associated because they are correlated in the individuals.

What if SNP-B isn't significant in the second model.
Does that mean SNP-A is the causal (or lead variant) or SNP-B is?


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The oldest common ancesstor of all human beings
Do all human beings have a single oldest ancestor (a man and a woman), or were there were many ancestors at the same time at different places on earth?
This article sheds some light. Is there another authoritative report released more recently?

http://biology.stackexchange.com/questions/7184/what-is-a-mitochondrial-eve-and-y-chromosomal-adam covers much of the same material.

Isn't that Adam? ;)

Possible duplicate of What is a Mitochondrial Eve and Y-chromosomal Adam

This is not a duplicate. The MRCA is different from mtEve and YcAdam.

You are talking about the mitochondrial eve and the chromosome Y adam.  At some point there must be just one pair, though historically the evidence can be lost if there is a near complete extinction event.  Current evidence for eve points to SE Africa.


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What is the energy balance of cooking?
If I cook some food, I get apparently several energetic advantages:

thermal : the temperature of the food is closer or superior to the temperature of my body or internal organs, so I do not have to produce energy to warm it.
chemical : the transformations of the organic compounds during cooking operations may store energy in a potential form: more energy will be released by the digestive process from these compounds than from the raw ones.
mechanical : the food may become easier to chew, absorb, conduct in the digestive tract, leading to less muscular force used.
The cooking procedure may involve water immersion, and the water may penetrate the food and improve all three energetic aspects outline above.

(I may have forgotten a few things)
But what are the respective scale of these advantages, compared to the Joule intake of the raw food ?
Focusing on meat, for instance, is there an optimal cooking duration/temperature and eating temperature for human eaters, independently of personal tastes, for say, beef or chicken meat ?

If I cook some food, I get apparently several energetic advantages...

Let's make things a little more explicit. If you are talking of energy within the body, you are talking proteins, alcohols, fats, and sugars. You are not talking Vitamins or Minerals or any of the unique compounds (like specific antioxidants) that are available in the food.

thermal : the temperature of the food is closer or superior to the temperature of my body or internal organs, so I do not have to produce energy to warm it.

You cannot eat enough to significantly alter the temperature of your body. The average American will eat roughly 5.4lbs of food per day - or roughly 2lbs of food per meal. Given that even raw food is at room temperature, the metabolic requirements to warm food you've eaten is negligible.
What's important is acidity and exposure. Food is generally broken apart and utilized by catalysts and proteins which have specific operating boundaries - which is why your stomach contents is acidic. However, your normal meals will not significantly alter your digestive capabilities either via pKa values or thermoregulation requirements.
What cooking can do is denature the raw food's proteins or compounds so as to make the usable energy sources more readily available. However, it can also just as easily destroy them (the 'char' on barbequed steaks is the meat exposed to high heat long enough to destroy almost everything but the carbon in the tissue). Whether a food gains or loses macronutrients depends upon the specific food and its preparation. A good example is potatoes, which are full of starch (sugars) in their natural state. However, french fries / frites / chips are often blanched before they're fried. The blanching dissolves much of the starch into water, leaving fewer sugars in the end product. However, the process of frying essentially adds fat to the food, and fats have a higher energy density than sugars so you have a net gain in caloric content.

mechanical : the food may become easier to chew, absorb, conduct in the digestive tract, leading to less muscular force used.

For some foods, this is true. Steaming vegetables often makes them easier to chew/eat. The broth of stews and soups often contains micelles of fat and dissolved sugars, affording them greater and faster exposure to the digestive system. Keep in mind, you are not getting a net gain of caloric content from food by doing so, but merely reducing the time to utilization.
The calories saved by chewing less is going to be pathetically small, so to amend the previous paragraph: Yes, for some foods it's true that cooking will allow easier mastication and thus save energy. However, an extra chocolate chip or sip of spoon of rice could easily cover the energy spared.

The cooking procedure may involve water immersion, and the water may penetrate the food and improve all three energetic aspects outline above.

If the energy source is water-soluble (that is: alcohols, ketones, and sugars) then water immersion - assuming you are also digesting the water solution after - will offer faster utilization, not necessarily more.

But what are the respective scale of these advantages, compared to the Joule intake of the raw food?

Negligible in almost all cases. What cooking does is make things more palatable, has the potential to make micronutrients/vitamins more available (not macronutrients), and make the food edible in the first place as is the case with Taro plants, whose roots must be cooked in order to eat.

Focusing on meat, for instance, is there an optimal cooking duration/temperature and eating temperature for human eaters, independently of personal tastes, for say, beef or chicken meat?

No. Cooking meat makes it safer to eat (unless you end up overcooking the meat and end up with a bunch of charred bone) and more palatable. Properly cooked meat has a very low chance of passing on parasites or other harmful organisms. Beyond that, there aren't compelling reasons to expose meat to heat - although as someone who's picked up stomach flus in his travels, it is a very compelling reason to do so.
*The above is based mostly on sporadically gained knowledge. If there are studies indicating otherwise, please alert me to them and I will rectify my errors.


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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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Contracting muscles in humans
I study biology at school, and unfortunately for me, my program skips the muscles in humans chapter.
I know (and mainly, feel) that the movement in one direction isn't created by the same muscle as the movement in the opposite direction, e.g the Triceps ("front") and Biceps ("back").
I know that the triceps straightens the elbow, while the biceps contracts the elbow.
I also know that, instead of actually moving the arm, I can contract these two muscles (when I show off, for example...) without actually moving the arm. That area becomes hard. Both muscles, as I feel, are contracting. I cannot statically contract only one of them.
My question is whether this action is something "special", or simply both muscles working against each other, resulting in zero movement?

The situation you are describing where muscles are situated on opposites sides of a joint and produce opposing movements is called "antagonism." Most joints are set up where one or more muscles on either sides will produce such movements (e.g., flexors vs. extensors). Here's a question about muscles without antagonists.
When you contract all the muscles crossing a joint (i.e., when you are "showing off"), the muscles balance each other. If not, the bones would move and the joint angles would change. So taking the elbow as an example, in the image below, Arnold is contracting the elbow flexors (biceps brachii, brachialis) as well as the elbow extensors (triceps brachii). In order for the bones to remain static, the forces must be equal and opposite.

Arnold is a good model for studying muscle anatomy in schools.. the exaggerated sizes will help kids find each and every muscle..  :-P


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How is the exogenous DNA protected from degradation during bacterial transformation?
During transformation, a bacterium can take up DNA from its environment. A small fraction of bacterial species are known to be naturally competent, meaning that they can engage in this sort of horizontal gene transfer in their natural environments.
As I understand it, naturally competent bacteria carry genes that encode the machinery necessary to facilitate the transport of this DNA across the membrane and into the cell. The exogenous DNA binds to a receptor located on the surface of competent cells, gets fragmented into small pieces, and then one strand is degraded while the other strand is transported across the membrane into the cytoplasm with the aid of a DNA translocase enzyme. Ultimately, assuming a sufficient degree of homology, it incorporates into the host genome via recombination.
During this process, however, the DNA has to be protected from degradative nucleases. I remember reading something about a transformation-specific DNA binding protein that coats the entire length of the DNA strand and prevents degradation. Is it the same translocase enzyme that facilitates movement across the membrane that is responsible for this? Or is there another protein involved?
And then, regardless of which protein is responsible in the case of natural competence, how does that protein get expressed and activated in the case of artificial competence? When we induce competence in the laboratory through one of various methods (e.g., electroporation), the DNA is essentially forced into the cell through openings in the membrane, so no transferase protein is needed. What signals the bacterium, then, to express the protective binding protein? What keeps the exogenous DNA from being readily degraded by endogenous nucleases? Whatever signals induced the expression of this protein in the case of natural competence would seem to be absent when competence is induced artificially, and it doesn't make any sense that the bacterium would constitutively express such a protein.

As an aside, one of the reasons that plasmids are circular no doubt is to prevent natural degradation of the sort you are talking about.

Different bacteria have different modes of transformation and as I understand it is Haemophilus influenzae that takes up the single strand whereas ?Streptococcus [i am not sure which bacteria it is] takes up dsDNA.
I intuitively think that DNAses are not that common like RNAses. Moreover, natural competence is associated with stress and is even triggered by DNA damage. Therefore we can speculate that DNA repair proteins will be prevalent and DNAses will be low in the cell, under these conditions. The chance of foreign DNA being damaged goes down.
In the case of artificial transformation, I guess the entire concept of heat shock is a way of providing stress. Moreover, the lab strains such as DH5alpha have certain mutations which disable them from recognizing a plasmid as "foreign".


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Would muscle fatigue still occur if aerobic conditions for a working muscle is maintained?
Put another way if the muscle is given everything it needs to contract and do work will it ever get tired or have a reduction in energy efficiency?
As far as I understand muscles depend upon a blood supply delivering oxygen and nutrients (e.g. glucose and calcium) to effectively contract at its best level of performance. With the ability to work under anaerobic conditions if need be but producing lactic acid as a by-product which reduces the muscles ability to contract and therefore producing fatigue.
I also know that muscles are dependent upon temperature to work efficiently like the rest of the body. So, if the muscles temperature was able to be regulated well enough to maintain efficiency and aerobic conditions are met could fatigue be negated?

I think you need to clarify something. I was going to answer, but then I realized there's a difference between constantly working and operating under stress. Your heart is an example of a muscle that never quits, so it is one example of an answer to your question. However, if you mean when muscles are stressed beyond their normal operating parameters, as the heart rarely is for extended periods of time, then that's a different answer.

ATP is also needed..

thanks for the input. Yeah I was meaning constantly working and/ or under stress in terms of endurance training or activity, I was curious about the limits to how long and far the skeletal muscles can be exposed to. I should have specified the skeletal muscles in regards to the muscles that allow us to run and walk.

It seems that you are asking about activity significantly above basal metabolic rate. If aerobic conditions are maintained (and with appropriate training), muscles can operate more or less continuously for very long durations, days to weeks. In non-humans:

Godwits have been recorded flying over 7000 miles (>11000 km) without stopping for 9 days
Arctic terms migrate 44000 miles (>70000 km), albeit with stopovers
Humpback whales migrate 5000 miles (8000 km). Their muscles are probably operating close to continuously.
Many (most?) species of sharks swim continuously.

There are probably other examples as well (feel free to add). For humans, usually the limit to endurance is sleep. Two forms of racing push human endurance, but the longer races almost always require at least minimal sleep:

Ultramarathons, foot races of 50 mi (80 km), 100 mi (160 km) or more (e.g., 24 hours, multi-day).
Race Across America, Paris-Brest-Paris, and similar endurance bicycle races. The RAAM has a record time of 3107 mi (4971 km) in 8 days, 9 hours for a mean velocity of 15.4 mi/hr (24.6 km/hr).

thanks, I never thought about it from this point of view with examples of animal performance. In regards to the performance of muscles over such long endurance events do you know if they reduce in their energy efficiency, of converting glucose (ATP) muscular contraction, as time passes. I have read in multiple sources the energy efficiency is around 25% for muscles but could find no stats on their performance over time and increase in operating temperature.

If the muscle is provided with adequate food and oxygen, the muscle can theoretically work indefinitely. However, microtearing when a muscle is stressed more than usual can over time damage the muscle. This is the mechanism by which you get larger, stronger muscles. Without rest, it's theoretically possible to simply destroy the muscle faster than it can be repaired.


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How to classify equilibrium points
I have the two differential equations:
$$\frac{dN_1}{dt} = N_1(2 - N_1 - 2N_2)$$
$$\frac{dN_2}{dt} = N_2(3 - N_2 - 3N_1).$$
I worked out the equilibrium points to be at $N_1 = 0, \frac{4}{5}$ and $N_2 = 0, \frac{3}{5}$. I then calculated all the Jacobi matrices and worked out the eigenvalues (and eigenvectors). I now have to classify these equilibria. How do I do that? Is there a set of rules I follow to classify them?
Also, the next part says:

Sketch the phase portrait of this system in the biologically sensible region: draw the the null- clines of the system and determine the crude directions of trajectories in parts of the phase plane cut by the null clines, designate the equilibria in the phase plane, and sketch a few typical trajectories.

I can do the null - clines and I think once I have found out the stability of the equilibria, I can determine the directions of trajectories of the bits cut by the null -cline, but how would I sketch the trajectories of the equilibria?

The fundamental question here is math, not biology, even though it may have been presented as a biological system. You may have better luck on math SE.

Classification of equilibrium points is done on the basis of the eigenvalues.

If the two eigenvalues have no real parts, it is a hyperbolic fixed point and represents undamped oscillation.
If both have a negative real part, it is a stable fixed point. If any of the eigenvalues has an imaginary part then it represents damped oscillations (in that case the equilibrium point is called a focus).
If one or both eigenvalue have a positive real part, it is an unstable fixed point.
If one eigenvalue has a positive real part and the other a negative real part, it is a saddle point.*

You sketch the trajectories of the equilibria by starting a tiny distance away from the point (where it is not in equilibrium) and trace the quiver plot. Drawing trajectories around unstable points is tricky and you have to plot the function in negative time i.e. instead of plotting f(x1,x2,t), you plot -f(x1,x2,t).  This page has representative trajectories for the different types of equilibrium points.  This page has a more thorough explanation, generalized to multiple dimensions.
*This classification appears to be slightly variable (more or less categories), on the basis of the two links I found.  I think the one I list is the simplest version, but any classification should suffice.  They are all based on the same principles. You can refer to some books on non-linear dynamics:

Nonlinear Systems by Hassan Khalil
Nonlinear Dynamics and Chaos by Steven Strogatz

@WYSIWYG added the references and some additional information -  I would like to second the recommendation for Strogatz's book.

yeah.. its such an easy and comfortable read..


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Were any brain fusion experiments ever conducted?
Did anybody ever conduct experiments on fusing living brains?

You mean this? http://www.huffingtonpost.co.uk/2013/02/28/inter-continental-mind-meld-rats_n_2781469.html

@dd3 no. this seems not to be fusion, but rather a crude transmission of some signals. I am interested in attempts to grow the brains together.

The odds of that are really very slim. "Growing brains" in vitro is rather difficult, and it appears that no one has created the brain of a real organism, but they have created "brains" from cultured dissociated neurons.
Fusing brains is complicated by the fact that you need to make the appropriate synaptic connections between neurons, and what exactly are the appropriate connections is still being worked out.  As a side note, this is one of the goals of the BRAIN Initiative.
The closest I believe people have come to anything approaching fusion are brain transplants in non-human animals.  This might be the closest thing to an in vivo fusion, especially if it is only a partial brain transplant.  This is discussed a bit here.

I did not find anything about brain fusion following your link to the brain initiative...

No, the point is they are working out the behavioral circuits in the brain. Any sort of fusion is dependent on making the right connections. We don't know what most of them are, so that makes it hard to make successful fusions.


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Is local equilibrium a reasonable assumption for evolutionary processes?
Whenever I look at discussions of fitness landscapes (in particular, Kauffman's NK model) the questions tend to resemble:

The population is at a local equilibrium, but another equilibrium of higher fitness exists, how will the population cross the fitness valley between these equilibria?

These sort of statements assume that the population has reached a local equilibrium. Although, the local equilibria must exist, why do the people working in this field believe that they can be found before environmental (or other external events) change the fitness function? Are the timescales required to go from a random initial population to one that is at a local equilibrium compatible with the typical time-scales on which a fixed fitness landscape is an appropriate approximation?
If we switch to the polar opposite model of complete frequency-dependent selection (say replicator dynamics in evolutionary game theory) then limit-cycles (think rock-paper scissors game) and chaotic-attractors are common and it is possible for the population genetics to be constantly changing and never at equilibrium.
In an experimental setting, it also seems like although beneficial point-mutations are much more rare than deleterious, they do exist. This would suggest that experimentally, organisms are not at a local equilibrium. Do model organisms tend to be at local fitness equilibria?
In general, is the local equilibrium assumption in fitness landscapes research a reasonable assumption?

Nothing is at a genome-wide local equilibrium. Graham Bell wrote fairly extensively on this (IIRC).
Some loci

will be at what are likely global optimums (e.g. Cytochrome oxidase)
will be at local but not global optimums (e.g. low-fitness malaria resistance vs. high fitness malaria resistance: for the extremely cool story check out this page)
will not be at any optima because the environment shifts too quickly (e.g. loci clearly under frequency-dependent selection, such as MHC).

So, in general, it depends what you are trying to model. If you want to model a specific kind of evolutionary change, then model that kind of evolutionary change. If you want to model a different kind of change, then model that kind of evolutionary change. Natural populations will likely follow any model some of the time, but will probably never follow any model all of the time.

You mean Graham Bell?

Yup. That's the one. You'd think I could look six inches above my screen to the binding of a book to check the spelling of his name, wouldn't you?

I looked through Bell's publications, and I can't see a paper that suggests that he has been looking at this. Can you give an example?

In his book "Selection: the mechanism of evolution" he talks extensively on the dynamics of selection : i.e. how selection is changing over time, in different environments, etc. In particular I am recall some claims that evolution cannot be modelled as a markov-process because the state space is too large and impossible to characterize. My memory of this is quite vague, so I could be remembering a different author, and I can't find the relevant passage in this book right now.

You are right - overall the environment, which is always subject to change puts individuals in dynamic equilibrium. See the Red Queen hypothesis.  The genome itself is never completely at equilibrium either.

I think the jury is out on this one, there are examples of evidence both for and against reachability of local equilibrium and even these examples can be interpreted in many ways. I present three pieces of evidence and some interpretations. In general, my feeling after reading about this is that the assumption of equilibrium is ingrained in mathematical models for convenience and historic reasons not because there is solid evidence for it. (I expand more on this in this blog post).
Evidence against: vestigial features and macroevolutionary change
From a genome-wide perspective, it seems that equilibrium is at odds with the intuition of naturalists. Consider for example vestigial features of your own body like your appendix, goose bumps, tonsils, wisdom teeth, third eyelid, or the second joint in the middle of your foot made immobile by a tightened ligament (see video below). Wouldn't it be more efficient (and thus produce marginally higher fitness) if you didn't spend the energy to construct these features? Of course, this naturalist argument is not convincing since we don’t know if there are any small mutations that could remove these vestigial features from our development, I could just be describing a different local optimum that lays on the other side of a fitness valley from my current vertex.
The other tempting naturalist example of macroevolutionary changes like speciation is also not convincing for static fitness landscapes. The usual retort is that on these timescales the environment is not constant and depends on the organisms through mechanisms like niche-construction or frequency-dependence. This defense of local equilibria is actually a central part of the punctuated equilibrium theory of evolution; the environment changes (either through an external effect like meteor or internal effect like migration or niche-construction) and the wild-type becomes not locally optimal, but adaptation quickly carries the species to a new nearby local optimum where it remains for a long period of time until the next environmental change. Naturalistic observations are insufficient to settle this question, so we need to turn to experiments.
Evidence for: affinity maturation
The length of evolutionary process leading to affinity maturation is very short, typically a local equilibrium is found after only 6-8 nucleotide changes in CDR (Crews et al., 1981; Tonegawa, 1983; Clark et al., 1985), so you need only a few point mutations to quickly develop a drastically better tuned antibody -- an adaptive process that happens on the order of days. There are two reservations to keep in mind:
First, the adapted B-cells were not experimentally isolated and all of their point-mutations were not checked to guarantee that a fitness peak was reached. In both theoretical and experimental treatments of evolution, it is known that fitness increases tend to show a pattern of geometrically diminishing returns (Lenski & Travisano 1994; Orr, 1998; Cooper & Lenski, 2000) which means that after a few generations the fitness change will be so small that the fixation time in the large population of B-cells will be longer than the presence of the pathogen causing the immune response. We might not be seeing more steps because the next steps might have a fitness increase too small to fixate before the environment (and thus, fitness landscape) changes again.
Second, as can be seen from the AID protein (and other mechanisms) increasing the rate of mutation by a factor of $10^6$ along the gene encoding antibody proteins, this is a fitness landscape that has been shaped by previous evolution of the human immune system to find fit mutants as quickly as possible. This biases the phenomenon towards landscapes where local maxima would be easier to find than usual, and thus makes it not a good candidate for considering evolution under more typical conditions.
Evidence against: long-term evolution experiment
A more typical setting might be the evolution of E. coli in a static fitness landscape. Here, biologists have run long-term experiments tracking a population for over 50,000 generations (Lenski & Travisano 1994; Cooper & Lenski, 2000; Blount et al. 2012) and continue to still find adaptations and marginal increases in fitness. This suggests that a local optimum is not quickly found, even though the environment is static. However, it is difficult to estimate the number of adaptive mutations that fixed in this population, and Lenski (2003) estimated that as few as 100 adaptive point-mutations fixated in the first 20,000 generations. It is also hard to argue that the population doesn't traverse small fitness valleys between measurements, which could be used to suggest that the colony is hopping from one easy-to-find local equilibrium to the next.
References
Blount, Z. D., J. E. Barrick, C. J. Davidson, and R. E. Lenski. (2012). Genomic analysis of a key innovation in an experimental Escherichia coli population. Nature 489: 513-518.
Clark, S.H., Huppi, K., Ruezinsky, D., Staudt, L., Gerhard, W., & Weigert, M. (1985). Inter- and intraclonal diversity in the antibody response to influenza hemagglutin. J. Exp. Med. 161: 687.
Cooper, V.S., & Lenski, R.E. (2000). The population genetics of ecological specialization in evolving Escherichia coli populations. Nature 407: 736-739.
Crews, S., Griffin, J., Huang, H., Calame, K., & Hood, L. (1981). A single V gene segment encodes the immune response to phosphorylcholine: somatic mutation is correlated with the class of the antibody. Cell 25: 59.
Kauffman, S.A., & Weinberger E.D. (1989). The NK model of rugged fitness landscapes and its application to maturation of the immune response. Journal of Theoretical Biology, 141(2): 211-245.
Lenski, Richard E. (2003). "Phenotypic and Genomic Evolution during a 20,000-Generation Experiment with the Bacterium Escherichia coli". In Janick, Jules. Plant Breeding Reviews (New York: Wiley) 24(2): 225–65.
Orr, H.A. (1998). The population genetics of adaptation: the distribution of factors fixed during adaptive evolution. Evolution 52: 935-949.
Tonegawa, S. (1983). Somatic generation of antibody diversity. Nature 302: 575.

authors: Дмитрий Шитиков


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Are there natural selection experiments that quantitatively agree with theoretical modeling?
Has anyone ever conducted an evolution experiment and quantitatively compared it to theory?  For example, has anyone ever put bacteria in a million petri dishes filled with antibiotics and calculated the number of petri dishes that should develop drug-resistant bacteria, and then compared that calculation with the experiment?
I imagine that both the experiment and theoretical modeling would be very difficult, but maybe someone has been ambitious enough to try it.

If this is possible, I'd be particularly interested in finding out what variables they took into account in their calculations.

I'm not really sure what the theoretical model would be. But really, I just wanted to say that you might enjoy reading about the Luria-Delbruck fluctuation experiment, which is tangentially relevant - see http://en.wikipedia.org/wiki/Luria%E2%80%93Delbr%C3%BCck_

The question is definitely unclear. There are tons of theoretical predictions. The vast majority of them have been tested (sometimes through experimental evolution ans sometimes through observation) but not all.

I think the closest example to this is Greg Lang's work at Princeton. His work will take a population of yeast and let it grow for 1000 generations. At each generation a sample will be kept allowing sequencing of the population at each generation.
His website is available here: http://www.genomics.princeton.edu/glang/
And some of his work has already been published here: http://www.genomics.princeton.edu/glang/papers.htm

Unless I am not getting the example you give, it seems to me that there is a classic experiment that does just what you said:  the fluctuation test or the luria-delbruck experiment
Also, this recent paper from R. Lenski's lab is a good example too.
but I am sure there must be others.


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What molecular processes are involved in pseudopodial extension?
I am curious as to the processes and mechanisms involved in the extension of pseudopodia in amoeba. How does the cell know and control the direction and extent of pseudopodia formation at a molecular level? I am not particularly interested in the taxes that amoeba recognize, but rather the mechanism of response to these taxes.

The extracellular cue signal must be relayed to the cell by Rho family of GTPases, like in the case of filopodia and lammelipodia. This causes local actin polymerization leading to extension of pseudopodium.
For a casual reference you can check the wikipedia page on Rho family of GTPases. Cell biology books like MBOTC also have information on mechanism of cytoskeletal dynamics.


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What is the smallest molecule that can present as an antigen to the immune system in the context of allergies?
People often claim, in a colloquial sense, that they are "allergic to everything".
Is it possible to have a full-fledged IgE mediated allergic response to very small molecules?  I was always under the impression that the smallest antigen was a oligopeptide, but is it possible for someone to be allergic to something like isopropanol, glucose, or another small organic molecule?
How about allergies to metals, as I know those are fairly common, would they be mediated through a similar mechanism?

At one of my previous companies that raised antibodies to proteins and post-translational modifications, we found that 6-8 amino acids was generally the smallest peptide length required for an epitope. Anything much smaller than that won't induce the cross-linking or conformational changes required for signal transduction and an allergic response. As WYSIWYG notes, allergies to small molecules/atoms are formed via hapten-carrier interactions. These can be covalent, as in the nickel-transferrin example, or as a result of denaturation/chemical modification, as likely happens with people who are allergic to things like isopropanol or bleach.
I very much doubt that there can be such a thing as a glucose allergy, as it is so ubiquitous in the body that such antibodies/T-cells would be negatively selected long before they could do any damage.

Yes, the glucose example was a figment of my imagination, I just wondered if it was theoretically possible, but your point about negative selection is surely true.

@jonsca you are correct. However, plasma glucose can spontaneously react with the amine side chains of proteins and form pro-inflammatory advanced glycation endproducts.  Certain immune cells have receptors for AGEs.  So although AGE-drive inflammtion is not an adaptive (antigen driven) immune response, it is immune mediated.

Small molecules do not have antigenic properties but they can elicit immune response by binding to a "carrier" protein. The small molecule is called a Hapten. An epitope forms at the protein-hapten binding interface.
Nickel  acts like a hapten and elicits immune response by binding to proteins like transferrin, albumin etc.
Other metals also cause allergy in a similar way.


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How does your body know when it is infected so it can invoke a fever?
How does your body know when it is infected with a virus or bacteria so it can invoke a fever or ramp up the immune system?

During infection certain macromolecules present in the pathogens (pathogen associated molecular patterns) such as lipopolysaccharide launch the innate immune response, through toll like receptors. This leads to production of pro-inflammatory cytokines and also other inflammatory mediators like prostaglandins, thereby causing inflammation and fever.

So it's the toll like receptors that detect the infection?

An opinion by non-technical observer.
If you know the function of a hive, you know that bees communicate with each other, touching and rubbing chemical information. In a few minutes the information reaches the center of the hive and returns to individuals which are caring of it. It is widely accepted that a hive is a unique individual, composed of thousands of insects each with its own function.
I believe that we can make the observation reverse.
The man (and animals) are agglomerations of cells that pass chemically information to each other. Information reaches the central system, which responds by activating the necessary functions.
In case of infection, viral or bacterial, blood flow to the affected place very quickly, scrolling faster and thus raising the temperature. Similarly in the blood activates the necessary antibodies, which communicate with each other chemically referring where necessary. Pile up in the affected areas, resulting in swelling.
Other functions, such as sweating, vomiting or pus, are ways to excrete toxins (such should not be blocked). If we imagine the human body as a great hive where each cell is a member that transmits information and responds to stimulation of central system, acting in cooperation, the operation according to me is very clear.
How do the bees know that they are dying, if not passing to collecting companions honey too thick?
Sorry for non-technical opinion, if not useful delete it.

Very interesting!

Thinking of a body of cells as a hive of bees (i.e. many small organisms communicating on a low level) is a nice analogy, but the details are a little sketchy - the signals that are passed around aren't antibodies, it's not just blood flow activating things, and things don't have to pass through a central system. (I don't think bee communication really has a central system either - all the communication theories I've seen have them just communicating to whatever others are near enough to notice.)

Yes Jefromi. But how a cell, that is locked in its own tissue location, and become infected, can communicate to the others, untill, cell by cell, the information reachs the antibodies? It's just an analogy, not an equality.


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How long does Lentivirus take to express in vivo mouse neurons?
Does anyone know how long it takes for a standard Lentivirus vector to express its genes (under a strong promoter such as CAG, CB7, etc.), after injection into the brain of a mouse?
By hearsay I think it's 2 weeks for full expression, is that true?

i also heard that it takes a week. but you should frame your question better. this looks like a survey

This depends a lot on what you are expressing (such as how stable it is), and where you need it (soma vs dendrites vs axons, and whether it is trafficked actively in the cell).
For optogenetic constructs, our lab has typically seen near-peak expression around 3 weeks, though expression may be suitable earlier, and toxic later.


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Carrying or packaging capacity of SAD B19 dG rabies virus
I'm wondering about the carrying capacity also referred to packaging capacity or loading capacity (how many base pairs can be packed efficiently into virions) of the pseudotyped rabies virus SAD-dG as described in the Wickersham, Callaway publications.

Wickersham, I. R., Finke, S., Conzelmann, K.-K., & Callaway, E. M.
(2006). Retrograde neuronal tracing with a deletion-mutant rabies
virus. Nature methods, 4(1), 47–49. doi:10.1038/nmeth999
Wickersham, I. R., Lyon, D. C., Barnard, R. J. O., Mori, T., Finke,
S., Conzelmann, K.-K., et al. (2007). Monosynaptic Restriction of
Transsynaptic Tracing from Single, Genetically Targeted Neurons.
Neuron, 53(5), 639–647. doi:10.1016/j.neuron.2007.01.033

I have gone through quite a number of papers using this virus, but I haven't found any definite answer on the maximum insert length. There is an indirect answer, though. The two articles cited below both report possible insert length of up to 3.7kb without any experimental problems. This insert length results in a viral genome which is about 1.9kb longer than naturally occurring. So at least 3.7kb insert length are possible, if longer inserts can also be used, needs to be tested.
References:

Design and generation of recombinant rabies virus vectors.
New rabies virus variants for monitoring and manipulating activity
and gene expression in defined neural circuits.


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Whence fecal E. coli (et al.) if swallowing it is dangerous?
I don't know much about medicine, and I know even less about microbiology, but I understand that there are organisms in the lower gastrointestinal tract (and in feces) of a human, like Escherichia coli, that can cause dangerous disease if swallowed (or injected intravenously) by a human. So how did they get to the lower gastrointestinal tract in the first place? I assume either (or some combination of)

its prevalence in feces is less than I'm led to believe, so my question as to how it got there doesn't arise;
the percentage among cases of swallowed E. coli of those that lead to disease is low; or
E. coli-caused disease is more common than I'm lead to believe.

Does anyone know which of these is true? Or is it something else? (Perhaps they enter the gastrointestinal tract from below and not via swallowing?)

normal ecoli wont cause any disease.. certain pathogenic enterobacteria use the fecoral route for transmission.
blood infection (septicaemia) is a different thing altogether.

E. coli is mostly harmless; only a few strains are harmful.
I don't believe the route by which gut biota is established has been entirely established for any species but, for example, koala feed their faeces to their offspring to help them establish biota capable of digesting eucalyptus. It seems that a small proportion of ingested bacteria somehow survive passage through the stomach to the gut and then begin multiplying and colonising the intestines.
It's also important to realise that just because an organism is sometimes harmful doesn't mean it always is. There are many microorganisms that are pretty much ubiquitously found on or in your body which are capable of causing disease but only do so very rarely; usually when the body's defences have already been compromised (e.g. Pseudomonas aeruginosa, Candida albicans aka thrush, and so on).

There are many varieties of E. coli, with differences in their chromosomal DNA, different plasmids (independent loops of DNA that replicate autonomously inside the host cell and can be transferred between bacteria), or both.  Some are harmless, some beneficial, and some deadly.  E. coli of various kinds are found in the feces of cows, dogs, people, and more; but are also found in the environment.  Of course, even normally harmless bacteria can be harmful if they are in the wrong place in the body (e.g., in the blood) or if the body's microbial balance is out of whack.
Your second thought is correct:

the percentage among cases of swallowed E. coli of those that lead to
  disease is low

E. coli is found practically everywhere in homes, in concentrations ranging from very sparse to very dense. A good eye-opener is [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3709336/], which makes it very clear that children (and adults) are exposed to E. coli constantly. We hardly notice until a strain comes along that happens to make us seriously ill.


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How is the appropriately-stratified gut microbiome acquired in organisms performing horizontal transmission?
I am studying horizontal transmission of primary symbionts in insect reproduction. This reminded me of an earlier question I had asked, in which I learned that humans analogously acquired their particular microbiomes. It is also known how the human gut can be stratified in microbial content along the digestive tract. My question is what mechanisms are employed in ensuring that organisms acquiring their microbiomes from outside sources via horizontal transmission acquire the correct microorganisms in the correct parts of the gut? As the human gut metagenome does show "homology" between individuals, it can be safely assumed that the process can't be due to random chance.

Relevent: http://www.ncbi.nlm.nih.gov/pubmed/15831718 and http://www.sciencemag.org/content/312/5778/1355.short

Initial gut microbiota development is influenced to an unknown degree by the fact that human milk contains oligosaccharides that promote the growth of certain strains of Bifidobacteria (see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2596198/).

tl;dr it really might be due mostly to random chance, in terms of intentional mechanisms at least.
One thing that is important to remember about the gut tube is that conditions of life for microflora vary dramatically from one end to the other. This is true of nutrient availability, pH, and antimicrobial load. For example, the bacterial load of the lower intestinal tract is approximately seven orders of magnitude higher than the upper GI tract (stomach). They're just completely different places.
In some cases you can try to impute the bacterial assemblage in some part of the gut to a specific biological cause furnished by the host, for example the role of bile salts in controlling which organisms are able to colonize certain locations.
But a more parsimonious explanation is that the bacteria are growing in the places where they are good at growing. This brings up the old ecological saying: "Everything is everywhere, but the environment selects." We aren't necessarily trying explicitly to reinforce a certain assemblage, that's just the assemblage that works in niches with very low pH, very high nutrient load, bile salts, etc. And most of those features are unavoidable consequences of the gut's main function, digestion/excretion.
It certainly doesn't seem that e.g. behavioral strategies for exposing yourself to the "right" microbes gets you the right microbes in the right places. Recall that fecal microbiome transplant is one of the most successful strategies- just take some healthy poop and put it into a sick person's GI tract, they get better! That's not a very controlled horizontal transmission strategy.
You could propose that there is some second-order selection going on in which we have constructed GI niches in such a way that they encourage certain assemblages. Certainly, dysbiosis occurs and is bad in such cases as e.g. C. difficile infection, we would like to avoid those. Probably some coevolution has occurred between host and microbe, for example immune responses and butyrate production. That Foster paper has some more examples of possible mechanisms for a couple of specific cases, for example mucus. But they are probably not sufficient to explain the full compartmentalization of the microbiome in the way that you seem to be asking.

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


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Do the antlers re-grow in the same pattern every year?
I am a software engineer and I am trying to develop a system to identify a deer by its photograph.
Most deers lose their antlers every year. I would like to know if they re-grow in the same pattern next year and if yes, then what are the measurements that are of interest here?
Any pointers for me? Any software that can help me in recognizing a deer?

This has effectively been superseded by your subsequent question - in future you might want to consider using the [edit] function :)


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What would it take to recognize a deer by its photo?
I am trying to recognize a deer by its antlers or any other means.
Elaborating:
I was hoping to use their antlers to recognize them but I have heard that most deers shed their antlers every year so it would be difficult to recognize it from the last year's photo unless these antlers retain the same pattern every year.
If not the antlers, what other characteristics should I be looking for?
Is there any software that can help me in recognizing a deer?

I'm not so sure about software... but it would help to know what particular trait you are examining, exactly. You can quantify fur color by spectrometry, for example.

i m not sure on what basis you want to identify a deer.. but you can use machine learning algorithms to find your deer (you have to train your classifier first)

I think the main question you have written does not quite fall within the scope of biology SE.  However, your final question, "What would it take to recognize a deer by its photo?" could be answered in biological terms.  Perhaps that might be the better title.

Changed the title, provided more explanation and even though I am a software engineer, my question is now completely biological. Please up vote me now. If zoology experts cannot not help me then who can?

It seems as though one of your only options is deer-adapted facial recognition software (as silly as it might sound) which is definitely not within the scope of biology.

One part of this question remains unanswered- does the shape of a deer's antlers act as some kind of identifier & are they consistent between years? I guess to answer this one would have to collect antlers from a group of individuals with knowledge of who owns each set, and examine how they vary within individual across years... But, if you had access to the antlers could a genetic identity test be a more reliable way to identify?

@rg255 - It is not a way of identify a living animal. Or you have to cut antlers directly from it. Someone would prefer to use their own eyes (see Dian Fossey) and a direct contact, though visual only. I'd prefer recognize my deer broder (or gorilla, or whatever) while he is living, than after the death. The problem is how to recognize deers, not to compare antiers among theirselves. In my opinion.

@violadaprile collecting dna as a form of ID can be done from living animals thus I am not advocating killing or physically interfering with a living animal. DNA can be collected from, amongst other things, faecal matter or antlers which have been shed. And I know the problem is how to recognize a deer, I raised the point of "do antlers vary between years within an individual?" and to answer this, and thus show whether deer can be identified reliably by antlers, would require comparing antlers produced within individuals. The choice of recognition method would depend on the observers needs.

@rg255 - yes, i'v seen you profile. You have right from your point of view. You are microbiologists and informatics, I am just a nature lover, my eyes are my point of contact with the world. Try to drawing two cats, they are never similar, But to me, I dont need to examine their blood to distinguish. And I prefer to leave them alone =)

There is a lot of variation in how and when deer shed their antlers. In most arctic and temperate-zone species, antler growth and shedding is annual, and is controlled by the length of daylight. In tropical species, antlers may be shed at any time of year, and in some species such as the sambar, antlers last several years. Some equatorial deer never shed their antlers.
The horns change every year and, especially, increase the number of branches (and consequently, change their shape). You can't recognize them by antlers, but by other features, such as color of the hair or the lineaments. Like us, animals have individual morphological differences that are recognizable and listable.
Biologists specializing in studies of particular animal species not only take photos, but also make drawings and write descriptions of behavior, to identify individuals within herds.
An optical examination, however, of the subject through drawings and photos (and if possible, direct observation), is more useful than a PC program. This involves identifying particular similarities and equalities that are not "identical". This is possible to do visually on a large (but limited) number of specimens. The human eye is the best computer.

I wouldn't say that automated computer image analysis should not be used to study animals. Its hard to believe that at some point it will be more common than direct observation.

it was just what i meant - you are biologists and microbiologists and informatics, i am only lover of nature and studied a lot about it. So we talk from 2 true different points of view

The Open Source Computer Vision library OpenCV is pretty popular. I'm a Python guy, but it also has C, C++, and Java interfaces. The O'Reilly book Programming Computer Vision with Python was pretty good, and their C-oriented Learning OpenCV from 2008 is coming out with a new C++ edition in July, supposedly. There are also the OpenCV online docs, linking to the reference manual, user guide, tutorial, and Java API for each release.

MATLAB also has a computer vision toolbox

Sure but... this implies that you can distinguish a deer by its photo, which is what we are trying to determine.

We have programs which use a tecnic knew as biometria. that presume an archive of thousands (millions?) of possible variants. I do not think that such an archive exists also for deer.


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

This query sequence uses several degenerate symbols, defined as:

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

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

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

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

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

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

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

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

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

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


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Structure of fitness landscapes in the NK model
The NK model of rugged fitness landscapes consists of $N$ sites where fitness contribution of each site depends on its state $\{0,1\}$ and is epistatically affected by $K$ other sites. When defining the model, Kauffman & Weinberger (1989) stressed that:

The actual structure of [fitness] landscapes, although knowable is currently unknown

They then go on to assume either epistatic interactions are with adjacent sites in a linear ordering or at random, and that fitnesses are assigned to each of the $2^{K + 1}$ epistatic combinations at each site uniformly at random in $[0,1]$. Although it is definitely possible to justify this random generation, it tends to produce a very structured fitness landscapes, that although rugged (for high $K$), has a very regular distribution of local fitness optima. As a computer scientist, this assumption of an arbitrary random distribution over possible NK landscapes seems very misguided. I would be more comfortable with a worst-case analysis on a "reasonable" (hopefully as determined by experiment) subset of possible NK landscapes.
What is known about the typical structure of NK landscapes in biological domains? Also, are there examples of biological papers that do a worst case instead of an arbitrary random analysis on some non-trivial subset of landscapes? The only example I am familiar with is the gadgets used by Weinberger (1996) to show that the unconstrained model is NP-hard, but that is a trivial subset (all possible landscapes) and not of biological interest.

References
Kauffman, S. and Weinberger, E. (1989) The NK Model of rugged fitness landscapes and its application to the maturation of the immune response. Journal of Theoretical Biology, 141(2): 211-245
Weinberger, E. (1996). NP-completeness of Kauffman's N-k model, a Tuneable Rugged Fitness Landscape. Santa Fe Institute Working Paper, 96-02-003.

Artem. I have read several of your posts and found them quite interesting. I am quite unaware of the concept of evolutionary game theory (game theory in general). Can you suggest me a good read so that i can understand your problem better?
I know this is a not a valid comment . please forgive :P

@WYSIWYG Thanks! Coincidently I just wrote an answer where the second part talks about some basic references on EGT. Alternatively, take a look around my blog or just email me at lastnamefirstnamegmailcom

Very little is known about the structure of fitness landscapes.
H.A. Orr (2005; also Whitlock et al., 1995; Kryazhimskiy et al., 2009) explains that most experimental results do not actually attempt to measure the fitness landscape, but instead report just the average fitness versus time and average number of acquired adaptations versus time. This can't be used to discern epistatic interactions, or any combinatorial structure of the landscape. In general, the theory of adaptive walks has developed without reference to real data and even the most refined theories can only correspond in vague qualitative ways (see Kryazhimskiy et al., 2009 for the best example I know).
Szendro et al. (2013) surveyed the few recent experiments that conducted a methodical examination of all mutations in a subset of loci of model organisms, but most studies (6 out of 12) were able to empirically realize only small fitness landscapes of just 4 to 5 loci (so 16 to 32 vertexes), with the largest full fitness landscape having length 6 with all 64 vertexes examined (Hall et al., 2010), and the largest number of vertexes in a single study being 418 out of the possible 512 in a length 9 landscape (O’Maille et al., 2008). These are extremely small landscapes, and thus don't have much power in distinguishing proposed theoretical models.
After extensive searching, I have not been able to find examples of theorists doing worst case analysis of fitness landscapes. The closest to worst-case analysis is Orr-Gillespie theory (Gillespie, 1991; Orr, 2002; 2006; Kryazhimskiy et al., 2009) that assumes that the wild-type is still very fit after an environmental change, and so beneficial mutations are extremely rate. This allows the authors to introduce extreme value theory and consider just the asymptotic properties of distribution tails thus allowing a more general treatment with fewer parameters; in some cases leading to a full classification of adaptive trajectories (Kryazhimskiy et al., 2009). This approach is easier to relate to experiment, but unfortunately completely ignores the combinatorial structure (beyond first-order) of the fitness landscape and always just samples the next potential mutant from the tail of a distribution without taking into account how it is progressing in the landscape. Although Orr (2006) introduced the basics of fitness landscape structure, the structure was much simpler than the NK model; he used Perelson & Macken's (1995) block model with each block as completely unstructured beyond first-order.

References
Gillespie, J.H. (1991). The causes of molecular evolution. Oxford University Press.
Hall, D. W., Agan, M., & Pope, S. C. (2010). Fitness epistasis among 6 biosynthetic loci in the budding yeast Saccharomyces cerevisiae. Journal of Heredity, 101: S75-S84.
Kryazhimskiy, S., Tkacik, G., & Plotkin, J.B. (2009). The dynamics of adaptation on correlated fitness landscapes. Proc. Natl. Acad. Sci. USA 106(44): 18638-18643.
O’Maille, P. E., Malone, A., Dellas, N., Hess, B. A., Smentek, L., Sheehan, I., Greenhagen, B.T., Chappell, J., Manning, G., & Noel, J.P. (2008). Quantitative exploration of the catalytic landscape separating divergent plant sesquiterpene synthases. Nature Chemical Biology, 4(10): 617-623.
Orr, H.A. (2002). The population genetics of adaptation: the adaptation of DNA sequences. Evilution 56: 1317-1330.
Orr, H.A. (2005). The genetic theory of adaptation: a brief history. Nature Reviews Genetics 6(2): 119-127.
Orr, H.A. (2006). The population genetics of adaptation on correlated fitness landscapes: the block model. Evolution 60(6): 1113-1124.
Perelson, A.S., & Macken, C.A. (1995). Protein evolution of partially correlated landscapes. Proc. Natl. Acad. Sci. USA 92:9657-9661.
Szendro, I. G., Schenk, M. F., Franke, J., Krug, J., & de Visser, J. A. G. (2013). Quantitative analyses of empirical fitness landscapes. Journal of Statistical Mechanics: Theory and Experiment 2013(01): P01005.
Whitlock, M.C., Phillips, P.C., Moore, F.B.-G., & Tonsor, S.J. (1995). Multiple fitness peaks and epistasis. Annu. Rev. Ecol. Syst. 26: 601-629.


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What type of photosynthesis is performed by phytoplankton?
I am not a biologist, but I know there exist three variants of photosynthesis, namely C3, C4 and CAM.
I would like to know what type is used by the ocean's phytoplankton? It might also be that different photosynthetic mechanisms are used by the bacteria vs. algae. I have searched the web, but the information I find is too broad.

I'm not sure that all phytoplankton perform the same type of photosynthesis.
Originally, people thought that they all performed C4, on the basis of genome sequencing, which revealed the presence of genes important for C4 photosynthesis.  However, experiments on individual species seemed to indicate that the phytoplankton were performing multiple types of photosynthesis (source).
EDIT: CAM is unlikely, as that is an adaptation for dry environments.
EDIT 2: and of course, some phytoplankton appear to have both C3 and C4 pathways. In short, you can't generalize.

Some wires crossed here.  Most algae are C3, in other words they use the Calvin cycle to fix CO₂. Another way of saying it is that RUBISCO (Ribulose bisphosphate carboxylase) is dorectly responsible for CO₂ fixation.  There is some evidence (disputed) that some diatoms use a form of the C4 pathway in which CO₂ is initially fixed as a 4-carbon compound (CO₂+C3 → C4).  The C4 compound formed is often malic acid.
Trying to establish if the C4 pathway is functional for carbon fixation is not easy.  Genomics can be misleading. Practically all photosynthetic organisms have the genes required for the C4 pathway but whether they are expressed is another matter (look at KEGG).  C4 photosynthesis usually requires complex anatomy because it is essentially a CO₂ supercharger mechanism because the C4 carbon form is then decarboxylated in a special location to provide RUBISCO with a very high CO₂ environment to finally fix CO₂ a 2nd time and pass the two C3 carbon compounds formed from CO₂ plus Ribulose Bisphosphate into the Calvin cycle.


text:
Software for counting fly eggs
Is there any software that could be used to rapidly (quicker than humans) count the eggs laid by Drosophila on a substrate by placing them under a microscope with a camera attached? The eggs are laid on the surface of the food and have a fairly uniform shape - we regularly have to count the number of eggs in >200 vials, which can take a over 4-5 hours per 100 vials.
I wonder if there is some software which could be linked to a microscope with mounted camera connected to a computer, the software could then count from the live feed or a quickly taken photograph. It wouldn't have to be perfect but as long as it could be as accurate as humans (which is surprisingly low from our experience - we count up to a set amount then remove the rest, e.g. if I was aiming to leave 180 eggs I would be quite happy to get anywhere between 150-200 eggs). It would be using a stereo-microscope (aka dissection microscope) with a mounted camera.
The surface of the food with eggs looks something like this ->

purely for illustration, taken with iPhone - real images on microscope would be able to get closer (food surface could fill screen) and have more uniform lighting to give better contrast (this was taken to show in a talk so I wanted pretty rather than practical). The bottom two quarters of the food in this picture would be similar to the real result, just much closer...

Matlab allows image analysis like this. Check the matlab image analysis toolbox.

@WYSIWYG I'll give it a look, do you know if it would be able to do this live? (i.e. put the vial under the scope, focus it, click a button & get a count, then I remove some eggs & put it back under for a recount?)

I am sure it can be configured for a direct data acquisition and counting. I remember someone telling me about counting fluorescent puncta in cells, under confocal microscope, using matlab.
That is, however, beyond the scope of my existent skills and you can talk to any instrumentation engineer in your university

another software called LabView by national instruments can also do such a job. It's not that difficult to use.

here's another image analysis package that may do what you want http://fiji.sc/Fiji

ImageJ is a multi platform piece of software that has a cell counter module that might be of some use, and hey its free! Its easy to use and so ludicrously crude that it is very  versatile. I remember using it in undergrad to count cells under the microscope automatically after a few image contrast tweaks. I don't see why this couldn't be reapplied to count eggs.
Download: http://rsb.info.nih.gov/ij/download.html
Cell Counter documentation: http://imagej.nih.gov/ij/plugins/cell-counter.html

excellent, I'll try to find time to try it out in the new year and let you know how I get on!

Mathematica, if your institution has it as a bulk license option that you can get for free, is also a decent competitor to ImageJ for image analysis, assuming you do not know either program. A bonus is that you can hop over to Mathematica SE if you run into problems. I have used it for fluorescent microscopy counting and imaging as seen in http://mathematica.stackexchange.com/questions/29844/counting-elements-which-are-inside-another-element-on-a-different-colour-channel


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Lineage selection in plasmid evolution
I've been reading through Paulsson (2002) and I am not sure what he means by "lineage selection" in the second to last section. The paper deals with plasmid replication, and mostly concentrates on the contrasting pressures from two levels of selection:

intracell selection - competition between plasmids in a single cell. A plasmid can undergo a cis-mutation and over-replicate, resulting in a higher intracell fitness than the focal plasmid. The plasmids reproduce.
intercell selection - competition between cells. Cells with a heavier load of plasmids will take longer to reproduce, and plasmids that produce a heavy load will have lower intercell fitness. The cells containing plasmids reproduce.

In this context, what does the third level of selection -- lineage selection -- mean? What reproduces? How do the lineages split or interact?
My guess
Does lineage selection simply mean group-selection on separate colonies of cells? In that case, how are new lineages formed? I would expect this group level to select for zero levels of plasmids (since they place no loads on the cells and thus these groups of cells will grow the fastest), but Paulsson (2002) suggests the opposite:

lineage selection could favor plasmid traits that help the population of plasmid-containing cells to fight plasmid-free cells.

Is there a more detailed discussions of this available than the one section in Paulsson (2002)? Neither the unit of selection nor either the evolutionary or genetic lineage Wikipedia articles address my question. The first only mentions lineage in passing, and the second two don't discuss models of selection.

References
Paulsson, J. (2002). Multileveled selection on plasmid replication. Genetics, 161(4): 1373-1384.

i read the paper casually. The lineage selection part is not very clear. I observe that the system has multiple optimum points (atleast for the intracellular selection. Fig 1). This might be the case when intra- and inter- cellular components are coupled and the lineage selection must be related to the selection of one of these optimal points.

i am not sure about it.. i'll read the paper in detail and see if it is the case.

He defines lineage selection as selection for traits which increase the fitness of a group of plasmids, rather than an individual plasmid with in a cell or a particular cell containing plasmids. He says that the unit of selection are "plasmid-host clades" : in other words the unit of selection is the group of closely related plasmids in separate cells. It is an example of a kin-selection though I haven't seen the specific terminology in widespread use. He likely doesn't use kin selection because the plasmids don't have well defined offspring, so he uses a broader term for kin--lineage. I might have preferred clade selection, but this term has its own baggage. I'm not sure (and neither is Paulsson) that kin selection is need to explain 'spitefully low loss' rates, since intra-cellular and inter-cellular selection both favor lower loss rates.

Thanks! So he is using lineage in the genetic sense as described by Wikipedia?

The terms lineage selection, clade selection and  species selection are sometimes used quite interchangeably, and are fairly often found in paleobiology and macroevolution, i.e. when discussing species diversity between lineages/clades/taxa.