neurotransmitter - Do mammals develop tolerance to anticholinergics?

The tolerance to antihistamines is an ongoing debate in the community. Although there were early studies citing that tolerance to therapeutic effects of antihistamines could occur, more recent data, especially studies involving nonsedating antihistamines, indicate that tolerance to the therapeutic effects of these drugs does not occur.

Overall, it seems like the mechanism driving the sedation vs. the therapeutic effects are two separate down stream effects of regulating the inflammatory response. Neuronal tolerance and synaptic transformation is a fairly fluid and ongoing process, whereas the inflammatory response is much more robust. Meaning, the neuronal response is, theoretically, more able to adapt to chronic use of the anihistmaine while still giving the therapeutic effect. This hypothesis is supported by data, but yet to be confirmed, thus creating polarization on the topic.

Also see, Goodman and Gillman Pharmacological Principles of Therapeutics

human biology - Does mixing alcoholic drinks really make you more drunk?

There is plenty of anecdotal evidence ("beer after wine and you'll feel fine, wine after beer will make you feel queer") that mixing alcoholic drink types leads to a stronger effect, but I can't find any true studies.

In fact the only studies I found are looking at mixing energy drinks and alcohol (mixing with energy drinks increases motivation for more alcohol (in college students) [1]), and discussed mixing caffeinated beverages with alcoholic ones [2].

Are there any studies specifically looking at mixing alcoholic drinks? They would have to compare people drinking the same amount of alcohol, but some people mixing, others drinking the same thing. Maybe even a cross-over study design? Same people do both, one after the other? The only way to get an unclouded answer!

I am also interested in the follow-up why question: Why does mixing some drinks make you more drunk? Presumably it is something in wine (for example) that interacts badly with something in beer at the chemical level (the metabolites maybe)?

1. Marczinski CA, et al, (2012). Mixing an Energy Drink with an Alcoholic Beverage Increases Motivation for More Alcohol in College Students. Alcohol Clin Exp Res, epub. doi: 10.1111/j.1530-0277.2012.01868.x


2. Touyz LZ, (2011). Mixing drinks and concocting troubles. Curr Oncology, 18(6):262-3. PubMed; FullText.

structural biology - RMSD during conformational transition in proteins

When I was investigating the differences between protein structures obtained by X-ray crystallography and NMR spectroscopy, I found the paper [1] compairing structures of several proteins resolved both with X-ray and NMR. The average RMSD between NMR and Xray structures is 1.4Å (max. 3.6Å), and the average RMSD between different NMR structures for same protein is 0.4Å (max. 1.3Å). I've checked some proteins studied in this paper, and they are mostly within 100–200 residues long.

However, there are plenty of papers (e.g. [2], [3], dealing with similarly sized proteins) that base their statements about conformational transitions on structures with RMSD difference 1–2Å.

I wonder what is considered reliable RMSD between two structures to draw any solid conlusions about conformational transitions (e.g. upon ligand binding) as opposed to simple thermal fluctuations or perturbance caused by the method to obtain structure?

Of course, the best way (at least in my opinion) to distinguish actual conformational transition from thermal fluctuations is to measure its lifetime, but it is often not an option.

---

1. Andrec M, Snyder DA, Zhou Z, Young J, Montelione GT, Levy RM. 2007. A large data set comparison of protein structures determined by crystallography and NMR: statistical test for structural differences and the effect of crystal packing. Proteins 69: 449–65.




2. Grant BJ, Gorfe AA, McCammon JA. 2009. Ras conformational switching: simulating nucleotide-dependent conformational transitions with accelerated molecular dynamics. PLoS Computational Biology 5(3): e1000325.




3. Kumaraswami M, Newberry KJ, Brennan RG. 2010. Conformational plasticity of the coiled-coil domain of BmrR is required for bmr operator binding: the structure of unliganded BmrR. Journal of Molecular Biology 398: 264–75.

microbiology - Salvaging a plasmid from a cell culture stored at the incorrect temperature

I would rinse the cells off the agar using a small volume of LB or similar rich medium. Then use a small aliquot (10 μl) to inoculate a 5 ml culture under selection to see if anything will grow. Meanwhile the remainder of the cell suspension from the vial can be used as input for your favourite miniprep procedure.

If necessary, the DNA that you recover should then be used to transform a suitable E. coli strain. Don't bother trying to analyse the rescued DNA first since polysaccharide contaminants from the agar will probably inhibit any restriction enzyme that you might use.

Good luck!

experimental - What does "delineate" mean in this context?

I think this would me more on topic at English.SE, but (from Merriam-Webster):

Delineate:

1 a : to indicate or represent by drawn or painted lines
    b : to mark the outline of

2 : to describe, portray, or set forth with accuracy or in detail — de·lin·ea·tor noun

In this case, it could be either meaning that is used. Either 2, as Richard Smith said in his answer, to define the experiment's parameters in general, or 1b, to mark, limit a specific area of the ocean in which the experiment will be done. Obviously, delimiting an area in a body of liquid is not very easy.

pharmacology - Do drugs always degrade after they have passed their expiration date?

Drugs do not have to degrade after their expiration date and passing the expiration date has more than one possible meaning.

First of all chemical compounds vary in their susceptibility to breakdown over time. If they are kept away from oxygen, high temperatures (or kept in very low temperatures), and they are of a robust chemical nature, they might be stored for much longer than their expiration date and remain just as strong.

Over time, pharma compounds will chemically break down and lose their potency. In many cases, you will find that they simply don't do anything when you take them. This link cites a study that many drugs can retain their potency 15 years after they are made.

There are important exceptions. Two examples are tetracycline and acetaminophen (tylenol) whose breakdown products can increase the tendency for these drugs to induce liver damage.

neuroscience - Do effects of caffeine on human body change with habitual use?

I've been reading about homeostatic nature of a lot of neurobiological processes - the brain is trying to maintain a balance by desensitizing receptors, re-uptaking and breaking down neurotransmitters.

With this in mind, I'm interested in what happens to the receptors in the brain with chronic use of caffeinated beverages. Let's say an occasional caffeine drinker likes the cognitive boost of caffeine and starts to consume it habitually/chronically - every day. Will the caffeine drinker experience the same effects day after day, or will the effect change over time?

If there is a change in how the body responds to caffeine, are there any time frames that can be used to estimate when the change takes place - is it X days/weeks of habitual use?

Thank you for your input!

zoology - When do most mammals mate?

Why would it evolve?

No research (that I can find) is consistent with specific time of day mating across many species. I can't think of any reason why even just a few quite different mammals (e.g. mice, bats, lions, whales, and humans) would all find a fitness benefit of mating at the same specific time of day and therefore it is highly unlikely to evolve. I would suggest that if there are consistent patterns they are no reason other than coincidence (correlation over causality).

For example, dawn and dusk peaks in activity...

I have no references to back this idea up but lets see how this goes. The majority of mammals will be awake around dawn and dusk because there is likely an over lap between nocturnal and diurnal species at these times. Given that mating (normally) requires the participants to be awake then this would be a time when more animals are awake it is therefore a more likely time for mating to occur. But, as I already mentioned it would purely be because of the increased numbers awake.

Simple statistical illustration of the dawn & dusk idea...

Imagine a raffle with 2000 winning tickets. You buy 1000 and put 500 hundred of these in a box called nocturnal and the other 500 go in a box called diurnal. The raffle is drawn 24 times (perhaps every hour). The first 14 times it is drawn you can win if the ticket is from the nocturnal box, the latter 14 times you can instead check the diurnal box. This means during the first 10 draws you have a 25% chance of winning, and likewise in the latter 10 hours, but in the middle 4 hours there is a 50% chance every draw.

This comes down to a simple statistical phenomenon, if you don't buy a ticket you can't win the raffle.

physiology - How much gas is exchanged in one human breath?

According to Wikipedia

"In a healthy, young adult, tidal volume is approximately 500 ml per inspiration..."

(tidal volume is the volume inspired/expired)

Using this figure, together with values for gas composition also taken from Wikipedia, I estimate that in each breath we take in 18 mg O₂ (1.1 mmol) and we release 36 mg of CO₂ (1.2 mmol) plus 20 mg H₂O (1.1 mmol). These are, as you say, ballpark figures.

Sample calculation:

O₂ inspired = 21% by volume; O₂ expired = 16% by volume

O₂ change = 5% by volume = 5*500/100 = 25 mL

1 mole gas = 22.4 L; 1 mmol gas = 22.4 mL

O₂ change = 25/22.4 mmol = 1.1 mmol

MW O₂ = 16

O₂ change = 17.6 mg

The relative values are reassuringly close to what you might predict from the textbook equation for oxidation of carbohydrate: C₆H₁₂O₆ + 6O₂ -> 6CO₂ + 6H₂O

molecular biology - Is there a Reverse Transcription optimization for long, 9kb, transcripts?

Has anyone optimized RT for long transcripts (9kb)? The downstream application will be PCR amplification and Illumina library prep. It will be trivial to make internal primers sets for the PCR that are specific as long as there are no chimeric sequences. If there are, they will probably get primed also. If anyone knows of an optimization and/or other potential pitfalls, I would love to hear them.

bioinformatics - Confusion related to the use of PCA to determine the background network

I am by far not an expert, but I read the paper and maybe I can help clarifing things a bit.

Let's start with the simplest answer to your question:
In the last paragraph of the Introduction paper the authors say

"Throughout this manuscript [...]'background networks' and principle components are used interchangeably." ([1] Torkamani and Schork, Genetic background and drug response, The Pharmacogenomics Journal (2012) 12, 446-452; doi:10.1038/tpj.2011.35)

So they did not "use" PCA to get the background networks, they just call the PCs background models to indicate how they interpret it: As stated earlier in the introduction

"...interacting networks cannot be expected to correlate strongly with drug response, as their influence may only be observed when the major determinant of drug response and the interacting network complement one another or are both at a synergistic state. A major problem with identifying these interaction partners [...] is the extremely large number of possible partners [...] and [...] that individual genes are unlikely to accurately represent the overall state of a biological network." [1]

As far as I understand the article, they suggest PCA as a kind of compromise: Ignoring interactions would miss associations of all networks lacking a single gene representing the network's state accurate enough. Including all interactions is infeasable due to the huge number of gene-pairs. By PCA, the number of interactions can be decreased by orders of magnitude while keeping a maximum on information (as in variation): Instead of using the interaction (as in product) of all probes with all probes, they only consider those of all probes with the first six PCs.

I think, in this context 'background' is not used in the meaning of 'background noise' but of 'cultural background' - instead of assesing individual interactions, genes are assigned a 'background'. Since this corresponds to a) the biological network(s) they belong to and b) the principle components(s) they contribute to, those two ideas are used synonymously by calling PCs 'background networks'.

human biology - Can someone explain the color-changing unit (CCU) to me?

I've been physically carrying out serial tenfold dilutions on samples of Ureaplasma to work out the color-changing units (CCU).

As a definition, the CCU is the highest dilution at which there is a color change.

If the highest dilution is 10^3, apparently that means that there are 10^3 cells per ml in the original sample. But this is what I do not understand. How are we sure of this?

I feel like there is a lot that I am missing.

Any help would be greatly appreciated.

nutrition - Possible to Gain More Weight than the Food You Eat

No it is not possible. Humans are heterotrophic organisms, which means that we use organic molecules (i.e., food) as a source of nutrients and energy. We use the nutrients to add mass to our bodies. These nutrients are the familiar carbohydrates, proteins, lipids (fats), etc... During digestion food is broken down into simpler organic nutrient molecules that are then used to make our body tissues.

So even if we only used food for nutrients we could not gain more weight than the food we consume but note that the food is also used for energy. This means that some of the mass of the food that we eat is not used to add mass to the body but is "burned" as metabolic fuel. The mass of the food used for energy is expelled from the body as waste in the $CO_2$ that we exhale and in the metabolic waste in the urine.

The carbon in the air is mainly $CO_2$, which is an inorganic molecule. Only autotrophic organisms like plants can use inorganic molecules as a source of nutrients. Since inorganic molecules usually contain less potential energy than organic molecules autotrophic organisms need a different source of energy. Plants use sunlight.

Finally, fat contains about 9 Calories per gram whereas a Big Mac has about 2.4 Calories per gram so fat has almost 4 times the energy of a Big Mac.

(Calories are the amount of heat that is released if all of the energy in the organic molecules is released so it is an estimate of how much energy the body can get from food)

human biology - What is the healing process of mouth wounds?

To build on the answers from @Armatus and @S-Sunil

The healing mechanism involves the inflammatory process, which is the same in almost the entire body. In particular in both skin and mucosa (both referred to as "epithelial" tissues), when there is a break, platelets and clotting factors clot off any bleeding vessels, white blood cells (neutrophils and macrophages in particular) collect and destroy any bacteria, dead cells and muck, and then the process of regeneration occurs (with ongoing inflammation), where stem cells in the surrounding tissue regrow cells, new blood vessels may be formed and scar tissue is laid down to give extra strength. Eventually after these stages of healing, there is "remodelling" where the structure basically gets better.

As to why oral wounds heal quickly and don't get infected that much? There are a bunch of reasons. One is that the head and neck has an excellent blood supply- just think of scalp wounds where you bleed like crazy but then they heal very well. Another is that mucous membranes have immune functions that stop invading microbes. Generally speaking we divide this into "innate" immunity which is a general response, and "adaptive" immunity which is tailored towards specific bugs. The mucosa has both. There are neutrophils and macrophages (innate) which live in that area, there are lymphoid patches (like lymph nodes, and adaptive), there are immunoglobulins specific to mucosa (IgA) which is adaptive in nature, and the epithelial lining cells themselves will signal to the rest of the immune system if there is damage or an infection. Plus, saliva itself has chemicals and enzymes which break down oral bugs.

Most of the oral bacteria themselves are not particularly invasive. Just think, every time you brush your teeth, you cause multiple abrasions in your mouth. In fact, measurable amounts of bacteria from the mouth end up in your bloodstream every time you brush your teeth! And yet, we don't end up with bloodstream infections as a result. This is partially because the rest of our immune system (and the structure of our heart and vessels) is intact, and partially because oral bacteria are not very invasive or pathogenic. They kind of have a sweet deal living in your mouth minding their own business and not killing their host, and even causing infection in an oral wound would make their continued survival less likely.

In addition I should probably point out that skin has a great deal of bacteria on it as well, and yet we rarely get infections from them (unless colonised by an invasive species), for the same reasons.

pathology - What are some of the immediate challenges to break through before finding a cure for mad cow disease?

The main problem is that Mad Cow disease is not caused by a "normal" pathogen but by a prion, a protein.

Traditionally, disease causing agents can be classified into viruses, bacteria, fungi, and parasites. Bacteria, fungi and parasites are all living organisms, alive in the traditional sense. It is, therefore, possible to design drugs that kill them.

Viruses are trickier, while not really alive in the traditional sense, they still have to make copies of their genetic material (DNA, or RNA in the case of many viruses) in order to cause infection. Therefore, drugs like ganciclovir that stop the formation of viral DNA can be an effective treatment.

Prion based diseases such as Mad Cow disease, Creutzfeldt–Jakob disease and Kuru, are not caused by a classical infectious agent but by a simple protein, a prion. Prions are misfolded versions of proteins already present in the host's body. When a prion interacts with the host protein, it causes this protein to adopt the same, misfolded, state as the prion. Protein function depends directly on the protein's structure, the way it is folded in three dimensional space. Therefore, the misfolded protein can no longer carry out its physiological role and disease symptoms occur.

Now, since the prion is just a protein, one single molecule, there is no essential life process that we can disrupt. We have to attack them using chemical agents that target the prion while not affecting the healthy, correctly folded, host protein. This is very hard to do.

The blood-brain barrier mentioned by Larry_Parnell is another problem. Briefly, the BBB, is a kind of fence that only allows certain of the various items circulating in the blood stream to enter the organism's brain. This is a wonderful defensive feature but it makes it much harder to design drugs that can enter the brain and target pathogens found there.

genetics - How do PLINK files and HapMap Phased files differ?

According to http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml#ped:

The PED file is a white-space (space or tab) delimited file: the first six columns are mandatory:

 Family ID
 Individual ID
 Paternal ID
 Maternal ID
 Sex (1=male; 2=female; other=unknown)
 Phenotype

[...]

Genotypes (column 7 onwards) should also be white-space delimited; they can be any character (e.g. 1,2,3,4 or A,C,G,T or anything else) except 0 which is, by default, the missing genotype character. All markers should be biallelic. All SNPs (whether haploid or not) must have two alleles specified. Either Both alleles should be missing (i.e. 0) or neither. No header row should be given. For example, here are two individuals typed for 3 SNPs (one row = one person):

 FAM001  1  0 0  1  2  A A  G G  A C 
 FAM001  2  0 0  1  2  A A  A G  0 0 
 ...

And here is what I find in the begining of a HapMap .ped file I got a few years ago (hapmap3_r2_b36_fwd.YRI.qc.poly.ped):

 Y001    NA18488 0       0       2       -9      C C     T T     ...
 Y014    NA18519 0       0       1       -9      C C     T T     ...
 ...

So far, it seems to me than this is plain .ped format: the number of "header" columns is the same, and seems to conform to the specifications given in the above-mentioned web page.

Now let's have a look at the .map files.

By default, each line of the MAP file describes a single marker and must contain exactly 4 columns:

 chromosome (1-22, X, Y or 0 if unplaced)
 rs# or snp identifier
 Genetic distance (morgans)
 Base-pair position (bp units)

[...]

Note: Most analyses do not require a genetic map to be specified in any case; specifying a genetic (cM) map is most crucial for a set of analyses that look for shared segments between individuals. For basic association testing, the genetic distance column can be set at 0.

[...]

The autosomes should be coded 1 through 22. The following other codes can be used to specify other chromosome types:

 X    X chromosome                    -> 23
 Y    Y chromosome                    -> 24
 XY   Pseudo-autosomal region of X    -> 25
 MT   Mitochondrial                   -> 26

The numbers on the right represent PLINK's internal numeric coding of these chromosomes: these will appear in all output rather than the original chromosome codes.

Here we have something that may be different.
The end of the .map file corresponding to the HapMap .ped file looks like this:

 26      rs28357376      0       15825
 26      rs2853510       0       15925
 26      rs2854125       0       16149

The HapMap .map file uses "plink's internal numeric coding" for the chromosome instead of the letter code (MT).

Otherwise, it looks a pretty standard .map file, with no genetic distance indicated.

biochemistry - Can Pfx polymerase add only one 3' A overhang?

I am trying to clone a PCR product that was amplified using Pfx polymerase into pGemT vector. I had to A-tail the PCR product using Taq polymerase since Pfx only generates blunt end products. My ligation reaction was successful, however when I got the sequences, there is an extra T between the 3'end-T of pGem and the start codon of my product. It only happens in the 3' end of pGemT (or 5' end of my product). Can Pfx polymerase generates PCR products with just one 3'end overhang? or Can Taq polymerase add two consecutive dATP during the A-tailing?

Please write me your thoughts ASAP, it has happened twice and it's a pain already :(

GGC CGC GGG A-T-T-T-G ATG GGA AGC ATG AAG

The two Ts in Bold belong to pGemT, the T Italic is the extra T I've got from the sequencing reaction. After the T in Italic you may find the 5'end of my insert. The second T (in bold) from pGemT is the one that ligates with the overhang A added through the A-tailing protocol.

botany - Can Palisade Cells Survive Independently?

I have been intrigued by this question. Can palisade cells survive independently from its parent plant in a chemical environment? For example, if we were to separate a palisade cell from a plant and place it in sucrose solution, how long would it survive?

ecoli - What makes E. coli yellowish?

Bobthejoe's comment is the best answer so far. Despite many other types of bacterial colonies being "more" yellow than E. coli, E. coli is definitely not white.

Flavins, especially riboflavins, are the predominant compound responsible for this coloration.

homework - What range of dose should be used?

In the most basic sense you want to kill the most cancerous cells whilst minimizing the regular somatic cell death. Almost all cancer medications affect regular cells, too - though the better ones do so at a minimum whilst being effective. In reality, it's also nearly impossible to kill all of the cancerous cells. The goal is to bring them below detectable levels, which can allow the body to finish the job. Leaving significant amounts of cancerous cells alive won't do the patient any good - they'll just continue to proliferate and the patient will be back for more operations or treatments soon.

So, with the goal of minimizing benign cell cost and completely eradicating the cancerous line, on your crude chart that falls at about "4".

cancer - What does "tumour budding" mean?

tumour budding, lymphocytic infiltration and resection margins are established factors that influence the outcome of colorectal cancer (1)

In this context what does "tumour budding" mean?

Reference

(1) A. Bolocan, D. Ion, D.N. Ciocan, D.N Paduraru. Chirurgia (2012) 107:555-563. Introduction/0

molecular biology - Question about equilibrium potential formula

That quasi-travesty is the Nernst equation in $\log_{10}$ for a positive monovalent ion at physiological temperatures (37 degrees celsius), but they've hidden all that from you. Shame on them.

The canonical form of the Nernst equation, for an ion $S$ is

$$
E_{S} = \frac{RT}{z_{S}F}\ln{\frac{[S]_{out}}{[S]_{in}}}
$$

where $R$ is the gas constant, $T$ is temperature expressed in Kelvin, $F$ is Faraday's constant, and $z_S$ is the charge of ion $S$. This is the actually useful form of the equation that can be used for any ion for any temperature.

The Nernst equation is a limiting case of the Goldman-Hodgkin-Katz equation for a single ion. The Nernst equation is useful for directly determining the equilibrium potential of a single ionic species. The GHK equation is used for determining the reversal potential of a membrane or channel in multi-ion cases.

Note that the terms "reversal potential" and "equilibrium potential" are not synonymous, except in the case of a single ion system. The reversal potential is where the direction of current switches. An equilibrium is when net ion flux is zero (although, in a living cell, it is more appropriate to call even this situation a steady state). If membrane were only permeable to one ion, the reversal potential will be at the equilibrium potential (given by Nernst) for that single ion. However, when there are several permeant ions, usually none of the ions will be in equilibrium at the reversal potential--that is, all the ions will have a measurable flux across the membrane even though the sum of those fluxes (weighted by permeabilities) is zero at the reversal potential.

---

Converting natural log to log base 10, you can use the identity $\log_b{a} = \frac{\log_{10}{a}}{\log_{10}{b}}$, which gives

$$
E_{S} = \frac{1}{\log_{10}{e}} \cdot \frac{RT}{z_{S}F}\log_{10}{\frac{[S]_{out}}{[S]_{in}}}
$$

In the case of sodium ions (Na+) at 37 degrees (physiological temperature), $T$ is 310 and $z_S$ is +1. Substituting in these values, we have

$$
E_{S} = 2.303 \cdot \frac{(8.3145) (310)}{(+1) (96485) }\log_{10}{\frac{[S]_{out}}{[S]_{in}}} \\
E_{S} = 61.5 \text{ mV} \cdot\log_{10}{\frac{[S]_{out}}{[S]_{in}}}
$$

---

YAK uses a less common form of the Nernst equation in membrane physiology which uses the Boltzmann constant directly and deals with elementary charges instead of moles ($R = N_A k_B$). It is a wonderful exercise to derive the Nernst equation from the Boltzmann equation,

$$
\frac{p_2}{p_1} = \exp{(-\frac{u_2 - u_1}{k_BT})}
$$

where $p_i$ is the probability of a particle being in state $i$, and $u_i$ is the energy of state $i$. All it takes is some rearranging and keeping careful track of the units.

hearing - While someone's ears pops with pressure, can he/she hear other sound at the same time?

Yes, of course they can. What happens when your ears feel 'full' like on an aeroplane is that the air pressure in the middle ear is different from the air pressure outside. When you 'pop' your ears, you push open the Eustachian tubes that connect the middle ear to the throat and make the pressure equal. No matter what the air pressure, the air still conducts sounds. The difference is that your ear drum moves a bit less if the middle ear pressure and outside pressure is different, thus why sound is muffled before you pop your ears.

rna - Are there any strictly chloroplast/mitochondrion-residing ribozymes?

You've already mentioned rRNA. An interesting review (Tanner, 2006), outlines some more:

• Group I Introns - self-splicing; "They are abundant in fungal and plant mitochondria..."


• Group II Introns - some have been shown to self-splice; "...they are found in fungal and plant mitochondria, in chloroplasts of plants ... and especially in the chloroplasts of the protist Euglena gracilis."


• RNase P - involved in tRNA processing, found in mitochondria

None of these are strictly found in mitochondria or chloroplasts. However, the paper goes on to describe VS RNA ribozyme:

The mitochondria of certain strains of Neurospora contain the Varkud plasmid (a retroplasmid), which encodes a reverse transcriptase, and a small, unrelated, RNA (VS RNA). The VS RNA is transcribed from circular or multimeric VS plasmid DNA by a mitochondrial RNA polymerase, and the resulting transcripts are subsequently site-specifically cleaved and ligated to form circular, 881 nucleotides long, RNA monomers. These monomers are then reverse transcribed and made double stranded to form the mature VS plasmid.

In vitro transcribed VS RNA precursors are cleaved and ligated by the RNA itself and this is presumed to occur in vivo as well. Of all the self-cleaving RNAs, the catalytic properties of VS RNA are the most poorly understood.

---

References

Tanner NK. 2006. Ribozymes: the characteristics and properties of catalytic RNAs. FEMS Microbiol Rev. 23(3):257-275.

bioinformatics - How to calculate extent of Sequence similarity

The first thing that comes on my mind is to use cross-correlation (CCF).
Essentially you compare one trace with variously shifted version of the other to see if there is a correlation between them.

For example (I am using R but you should be able to adapt this to your software of choice, I have added comments), say A and B are very similar, but shifted of a certain amount in the x axis (10 units in the example) and C is extremely different

# Set the random seed to get a reproducible example
set.seed(12345)
# Number of points per trace
n <- 1000
# All of the possible sensor values
values <- seq(0, 330, 30)
# Sample with replacement to get 100 random values
A <- sample(values, n, replace=TRUE)
# Let B = A shifted by 10 positions and then change one value every 5
B <- c(A[-1:-10], A[1:10])
B[seq(0, n, 5)] <- sample(values, n/5, replace=TRUE)
# C is a completely different trace
C <- sample(values, n, replace=TRUE)
# Plot the traces (I'm offsetting B and C just for visual clarity)
plot(A, t="l", col="red", lwd=2, ylim=c(0, 1200))
points(B + 360, t="l", col="green", lwd=2)
points(C + 720, t="l", col="blue", lwd=2)

# Now calculate the CCF
c.AB <- ccf(A,B, 100)
c.BC <- ccf(B,C, 100)
c.AC <- ccf(A,C, 100)

# Superimpose the CCF plots
plot(c.AB$lag, c.AB$acf, t="o", col="green", ylim=c(-0.5,1), ylab="CCF", xlab="Lag")
points(c.BC$lag, c.BC$acf, t="o", col="red")
points(c.AC$lag, c.AC$acf, t="o", col="blue")
abline(v=10, col="grey", lty=3)
legend("topleft", c("A-B", "B-C", "A-C"), col=c("green", "red", "blue"), lty=1, lwd=2, pch=20)

The CCF graphs look like this:

This graphs means that there is a strong positive correlation (max correlation = 1, here you have 0.8) between A and B and that they are shifted of 10 units. You can see this because the peak is at lag=10, corresponding to the gray dashed line, so the maximum correlation is when you shift trace B by 10 units.

B and C and A and C are instead uncorrelated.

botany - What is the cause of the spots on this leaf?

This is a "Tar Spot" disease usually found in Europe and North America. It mostly affects the Maple tree leaves. Tar spot is caused by 'Rhytisma acerinum' a plant pathogen fungus. This pathogen does not seem harm to tree but disturbs the leaves as it finds a suitable condition in summer with bit of wetness. It enters the leaves through stoma and then creates yellow lesions of various sizes over the leaf area which later gradually turns into brown-black tar colored spot. It reduces the photosynthesis process of leaves and thus creating more wide dark spots on the leaves. After sometime the leaves will fall.

Entire detail is available in the Wikipedia link with the detail of the pathogen. (Add some more info if you find this detail not enough)

homework - Recent and good quality articles on systems biology

I'll have a go at a short list. This is more of a highlight and primer sort of response to a somewhat subjective question so pardon if this isn't what you wanted. I don't have paper references for all this, but I'll try to come back and add some later - I usually only have half an hour or so to write an answer so bear with me.

Synthetic biology as defined as the use of genes and promoters to engineer cells or even multicellular organisms like devices is a major category. I like browsing the projects from the iGem Competitions. A couple of outstanding efforts in this field are the use of photoreceptors to program E coli gene expression and the general effort to create logic and computational circuits in the cell.

A major application in systems biology is engineering cells to produce new chemical compounds or to overproduce compounds. A classic example (sort of old, but still pretty outstanding) is the engineering of E coli to produce the antimalarial drug artemisinin at levels which would enable world wide release of the drug. This has inspired efforts to produce fuel from algae and bacteria as well.

If you define Systems biology as being often concerned with modeling some or even all the biological processes of the cell, there are probably too many major efforts to cite, but this is just a list of some favorites.

There are lots of papers focused on flux balance analysis which models how the metabolic machinery processes and synthesizes all the scores of chemical compounds that make up a cell.

Another category of synbio tries to take the genes found in a genome and model the actions of all the genes. One of the most exciting papers to come out in this sort of systems biology is the whole cell model of Mycobacterium genetalium. Using data from a massive effort to characterize every gene in this very small genome, the model consists of over 20 specific models which have combined to make a very impressive simulation of the entire cell dividing.

Then there is metagenomics, which looks at the different populations of microorganisms and tries to look at how they vary with different environmental conditions. A recent paper that's exciting is the review of how different bacteria dominate in the gut of obese mice and people (several references in the link). A tour de force in metagenomics was the global sea survey.

bioinformatics - Standard letter for 5-methylcytosine

Well, don't use M or B, those are already taken (C or A, and not A, respectively). You can see the full list here: http://www.dna.affrc.go.jp/misc/MPsrch/InfoIUPAC.html (The enWiki article on Nucleobases lists a few others but I would ignore those as 1. D is present in both and 2. they are rare and inapplicable)

5-methylcytosine isn't on there. If you want to be pedantic about it, 5-methylcytosine is an epigenetic marker and as such is by definition not a genetic sequence; that remains simply a C and, genetically, the sequence is the same, despite the fact that it may indeed make a difference.

Most of the time people use m⁵C, so I'd go with 5 if I were you. That certainly isn't used for anything else and if you must use a single character most anybody will know what you are talking about.

biophysics - How to quantitatively measure work done by a biological system?

Measuring the work done by a biological system seems pretty impossible. Imagine how many different ways one cell of your body uses energy (ATP). You can't really measure all the work done by every cell on a macro scale. Metabolic efficiency has been defined as... "health". That seems just a little ambiguous. That's why we use things like averages to determine if energy use is normal or not, such as in metabolic age.

In short, work is a more tangible term in discrete physics examples, but there is so much complicated energy use in biological systems that total systemic work can't be easily defined.

evolution - What does fitness really mean?

Fitness is certainly the most important concept in the theory of evolution. My question does not have to do with practical measures of fitness but with the theoretical definition of it.

I am a bit lost with the concept of fitness. Below I give some possible definitions of fitness and I EXPECT critizes for these definitions. What is the definition of fitness?

In the following, to make things easier I will consider only one bi-allelic locus. As I said I don't want to talk practical issues but theoretical ones, therefore we will assume to work on a panmictic population of inifinite size evenly distributed into class age.

1) Let the variable $M$ be the mean time of a generation in the species of interest. Measure the allele frequency $p(t)$ and measure the frequency $p(t+M)$. By comparing the two you get the ratio of fitness of the two different genotypes. Obviously it does not work if we have sexual reproduction or diploid selection.

2) Genotype the individuals and wait until they die by counting the number of offspring they had and take the mean per genotype ($W_{AA}$, $W_{Aa}$, $W_{aa}$). This method would not work if they have different lifespan. One individual might make two babies in 8 years and the other would make two babies in 2 years but they would have he same fitness.

3) Do the same that at 2) but don't wait until they die, wait 1 month, Or 2 years?, or $M$?, or $2\cdot M$?, or...? What is the right decision? The more you wait, the closest you will be to the long term effect of natural selection. The less you wait, the more probable you will suffer of genetic drift.

4) Fitness is just a measure of natural selection that is not perfectly accurate because it is measured at short-term. In some circumstances, our measure on this short term is representative (Wright-Fisher equation) enough of what will happen on the long term.

genetics - How does a new species survive without suffering inbreeding?

This is indeed a very good question, that I have spent a long time thinking about myself. My take on this is that there is indeed a very close relationship between inbreeding and speciation, but that inbreeding actually PRECEDES speciation ! The key to this rather counter-intuitive point of view is that inbreeding actually has several advantages, including that of resulting in cleaner genomes in those offspring that survive inbreeding depression.

In populations that have high degrees of inbreeding, because of, for example, small sizes of populations, or high tendencies to self fertilisation, the recessive mutations that cause inbreeding depression will be progressively eliminated, and there will consequently be very little inbreeding depression.

In such a context, there will thus be no barrier to exploiting other advantages of inbreeding such as reducing the cost of sex, or keeping together advantageous gene combinations. Small groups of individuals would thus be better off breeding among one another than with the ancestral stock, leading to speciation.

If you are interested, or just intrigued, by this kind of concept, I invite you to read the rather long essay I wrote on the subject (The existence of species rests on a metastable equilibrium between inbreeding and outbreeding. An essay on the close relationship between speciation, inbreeding and recessive mutations, Etienne Joly, http://www.biologydirect.com/content/6/1/62 ).
And please do not hesitate to get in touch with me directly by email ( atnjoly(at)mac.com ) if you have comments or any further questions after reading this essay.

biochemistry - What happens to dextrorotatory amino acids in humans?

You may also be interested in D-amino-acid oxidase (EC 1.4.3.3), a flavoprotein (FAD) highly specific for the D-form of amino acids, which was discovered by Hans Krebs in 1935 (see here), and which has a wide distribution (including in humans).

The enzyme has been very thoroughly investigated, in particular by Massey & co-workers (see here for example)

D-amino-acid oxidase (EC 1.4.3.3) catalyzes the reaction which results in the following transformation

D-amino acid + H₂O + O₂ = 2-oxo carboxylate + NH₃ + H₂O₂

2-Oxo-carboxylates are what used to be called α-keto acids. For example, pyruvate is produced from D-Ala.

The product of the enzymatic reaction is the imino-acid which is nonenzymatically
hydrolyzed to a-keto acid (see Pollegioni et al., 1994, and references therein)

An excellent review

• D-Amino Acid Oxidase: Physiological Role and Applications

  
  
  

  by S. V. Khoronenkova & V. I. Tishkov,

  
  
  

  Biochemistry (Moscow) is freely available from here

These authors have some intersting things to say about D-Serine, D-Proline and D-Alanine, and much more.

Additional Reference

• Pollegioni L, Fukui K, Massey V. (1994) Studies on the kinetic mechanism of pig kidney D-amino acid oxidase by site-directed mutagenesis of tyrosine 224 and tyrosine 228. J. Biol. Chem. 269, 31666-31673. [pdf]

biochemistry - How to wash the column during protein purification with GST tag?

I have been working with GST tagged proteins for the last 4 years and after loading the cell lysate into the column I was washing it with 20-30 column volumes of PBS and sometimes my proteins were eluted very pure sometimes with a lot of impurities.

A few times I tried washing with NaCl gradient (0-400 mM) but later decided not to do that because it may denature the protein and some of my proteins may not refold.

What do you suggest for washing step?

Note: I don't have any UV detector to see the washouts/flowthroughs/elutions.

homework - Which enzyme catalyzes transcription and which translation?

Sorry, but you started on the right track. What you're looking for is called the central dogma of protein synthesis.

Genomic DNA is transcribed in the nucleus into messenger RNA (mRNA) by RNA polymerase. RNA polymerase is DNA-dependent; it needs a DNA template to make an RNA version of the message.

The messenger RNA moves into the cytoplasm where it gets translated by ribosomes into an a polypeptide (protein). Ribosomes are the enzyme that do the translating, and perhaps your confusion is because ribosomes are made up of both RNA molecules and proteins (a ribonucleotide complex).

Aminoacyl tRNA synthetases are the enzymes that make aminoacyl tRNAs (tRNA for short). These tRNA bring individual amino acids to the ribosome as the ribosome is extending the polypetide product of the mRNA message.

software - Statistical Analysis of Protein Folding Problem

One of the quickest ways to get oriented on what is going in the world of protein folding and modeling is to look at the proceedings of the Critical Assessment of Structure Prediction (CASP). CASP is basically a contest, held every 2 years where anyone can use their algorithm to predict the 3D structure of a protein whose structure is known, but not publicly available.

Its been a few years since I reviewed them results much - it looks like this year was interesting, but a perennial winner has been Rosetta, which has turned into an edifice of many suites of software which each execute different tasks in protein folding and modeling.

Open source software is pretty hard to find in this field. The software is complex. It usually includes components of machine and statistical learning, molecular dynamics, specialized algorithms that build up the protein one residue at a time, others which manipulate blocks of the protein structure around in space, electrostatic calculations, you name it. In addition, the software, once it gives some sort of result is quite valuable. I don't think any of these suites has really been released. I know that Rosetta is available to use as a web service, but you have to apply for access to the source. I don't think its an easy thing to get.

Some of the most complicated components are available open source. Molecular modeling and molecular dynamics open source software is quite sophisticated. I think we need an open source protein folding suite open source. I think David Shortle's algorithms might be a candidate for such a suite as its not so complicated and it works in some cases.

This field is pretty obscure and difficult to get around in. There aren't any easy introductions that I know of. Protein structures are computationally expensive and painful to work with in terms of writing software. On the other hand protein folding that really works is a revolutionary breakthrough, at least equal to the impact of the development of computers as a technology.

molecular genetics - How to calculate virus titre from qPCR

I harvested some lentivirus from 293T cells and want to titre the result. I infected 293T cells on a well plate with 400,000 cells per well which I infected with virus stock, and 1 in 10, 100 and 1000 dilutions (as well as a few uninfected wells). After 72h incubation I trypsinised the cells and used FACS to titre first, but 293T do not express the promoter under which GFP is located in some samples and hence these do not appear on FACS. As an alternative, I extracted the genomic DNA from all samples using a QIAGEN DNeasy kit (also the samples which I was able to titre by FACS already) and then performed qPCR on them.

I used the ABI PRISM 7000 SDS: http://www.cgenetool.com/products/abi_prism_7000.shtml

Included on the PCR plate were:

• Number standards: 1000, 10k, 100k, 1m copies


• Samples in triplicate


• No-template controls as well as untransduced controls

Each of those was doubled, once with primers and probe for WPRE (an element specific for the lentivirus) and once with primers and probe for beta-actin (a housekeeping gene present in all cells).

The results returned by the machine include for each well the cycle at which the threshold fluorescence was crossed - along with the automatically calculated quantity of copies (which the software calculates from the standards I assume).

Since I named the triplicate samples identically, it also automatically calculated the mean quantitiy among each triplicate (practical, eh?). I checked if there were any outliers which should have been excluded from the means but everything was fine.

So now for example I have a result of 700k for the quantity of WPRE in sample A. The quantity of beta-actin in sample A was 6.82 x 10⁶. The transfection was 400,000 cells per well, sample A was transfected with 10uL of viral stock diluted 1:100.

How do I calculate the virus titre per mL from this?

I have been given the formula: WPRE Qty / (b-act Qty*0.5) * cells in well (400k) * dilution factor (100), but am struggling to figure out a) why b-act Qty is divided by 2, b) whether the result would be virus titre per uL or per 10uL (transfection volume) and c) how beta-actin can have almost 10⁷ copy numbers consistently across all samples when there were only supposed to be about 10⁵ cells...

genetics - Can genetically modified genes jump to bacteria in the eater's intestine?

No.

There is nothing special about a piece of GM DNA when compared to any other random piece of DNA. If this phenomenon happened at any detectable level, we'd have found eukaryotic DNA in bacterial genomes/plasmids long before the introduction of genetically modified crops. And that would be front page news in the field of horizontal gene transfer! Which has many talented people in it!

statistics - Is it necessary to conduct a power analysis before beginning an experiment?

Due to my own woeful ignorance on the subject, I have been reading up on statistical methods recently. From what (little) I understand, the real answer to this question is:

Yes, but only if you are doing Neyman-Pearson hypothesis testing

and

Absolutely not, if you are using Fisher p-values

That is, the question isn't formulated correctly, because power analysis is only valid under one statistical framework (Neyman-Pearson). And you are probably not using that framework.

In my experience, most experimental biologists use Fisher's p-value, which gives the probability of the data (or more extreme data) assuming that the null hypothesis is true. Under Fisher's framework, among other drawbacks, there is no quantitative measure of the test's power. However, it has the benefit that it allows scientists to do something close to what we would like to do--that is to draw conclusions from evidence obtained in individual experiments.

The Neyman-Pearson framework does included the idea of a test's power, because you must formulate an alternative hypothesis as well as desired alpha and beta error rates before starting your experiment. However, it mostly denies us the ability to make inferences from individual experiments, and for that reason appears less suited to experimental science. To quote from Goodman (see below), under Neyman-Pearson, "we must abandon our ability to measure evidence, or judge truth, in an individual experiment."

There is no clear right frequentist framework, although what is clear is that you cannot mix Fisher and Neyman-Pearson. Finally, although it doesn't really address your question directly, it seems wrong not to mention Bayesian methods as an alternative to these two frequentist frameworks, which comes with its own baggage.

Further reading from people that understand this much better than me:

Michael Lew's answer to "Setting the threshold p-value as part of hypothesis generation" at Cross Validated

Michael Lew's answer to "What are common statistical sins" at Cross Validated

Hubbard, Raymond, and M. J Bayarri. “Confusion Over Measures of Evidence ( p’S) Versus Errors (α’S) in Classical Statistical Testing.” The American Statistician 57, no. 3 (August 2003): 171–178. (Working Paper PDF)

Arguments for Bayesian statistics:

Goodman, Steven N. “Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy.” Annals of Internal Medicine 130, no. 12 (June 15, 1999): 995–1004.

Jaynes, E. T. Probability Theory: The Logic of Science (Online version of some parts)

lab techniques - Strange behavior of a DNA gel

I ran a PCR product of ~300 bp on a 2% TAE-agarose gel for 30 minutes. I used Sybr-safe as a DNA stain. Voltage was 80V.

When I imaged the gel, the DNA on the bottom half of the gel, including the ladder had disappeared (it showed no bands). The DNA in the top half looked-clear and well-separated, but the bands on the bottom were somehow missing.

What could be the reason? I've never encountered this before.

I know it's not due to gel overheating - I ran the gel in the cold room and when it was done it was cold to the touch.

genetics - Are identical twins exactly the same?

Errors in division occur all the time and can show up in any dividing cell; this is, of course, important for cancer biology. If one of my cells replicates oddly right now it likely won't matter since it's only one out of trillions, but if that happened at a very early age in development it could be present in many if not all of my cells. Identical twins indeed come from the same egg-sperm fusion event but they develop separately from a very early state. It's trivial to imagine a minor replication error in DNA at an early cell stage that results in different genotypes between so-called identical twins. Besides, we've known for years that identical twins can have major epigenetic differences, so this isn't particularly ground-breaking.

If we assume that identical twins are exactly identical, then if we make a clone of a twin, will all three be exactly identical?

Depends on your definition of "clone" but how identical is identical? If you mean exact, then probably not; at the very least they will have different numbers of cells, for example, not to even mention CNV or epigenetics. If you want some SciFi cloning thing then, well, join the club.

bacteriology - Is 1 g/l living biomass for a Biogas fermenter plausible?

A usual number for a healthy biogas fermenter is $10^9 - 10^{10}/mL$ Bacteria, 10-15% of which would be methanogenic archae. Exceptionally healthy fermenters have more total bacteria and up 25% archae.

The mass of E. coli is given with 670 femtograms. If E. coli is representative for fermenting bacteria that would put us on the order of magnitude of 1 g/L living biomass.

This seems like much to me, though this is just a gut feeling.
As additional information, such a fermenter will have a total solids content of about 10%. A typical loading rate will be 4-5 g VS/d l *, two thirds of which get metabolized to gas. To put it another way: The amount of digested biomass per day would be the same order of magnitude as the living biomass. However, as anaerobic digestion is a multistage process, with at least three steps, each population will have a higher rate of digestion to mass.

Are the numbers basically sound? Is E. coli an exceptional bacterium in terms of mass? Are archae generally as massive as bacteria? What are bacteria counts for other fermentation processes?

(*) g volatile solid per day and liter: for each liter fermenter volume, this many g potentially degradable matter are added per day

ecology - Does preservation in ethanol alter leaf litter mass?

I have benthic samples that were collected with an Ekman dredge from some small ponds. The samples contain quite a bit of coarse particulate organic matter (CPOM, basically dead leaves). I would like to quantify the amount of CPOM in the samples but they were preserved with 70% ethanol in the field.

Is there any evidence that ethanol preservation alters benthic CPOM mass?

ecology - In which month should I map maritime vegetation?

One way to approach this problem would be to look at herbarium collections of the taxa that you're interested in. Usually, a flowering or fruiting specimen is easiest to identify; but no matter what character is best for your taxon, if you look at the herbarium collections and see that
-most of the collections identified to species, or
-the especially good-looking collections, or
-flowering/fruiting collections,
were made in a certain month or season, that could help you to narrow down your time window.

As a bonus, in reviewing herbarium collections, you'll have given yourself a step towards being able to identify the species.

Some herbaria have some collections online; here, for instance, are records and images for online Puccinellia collections at a number of UK herbaria.

neuroscience - Are there neuronal firing artifacts produced by head movement?

There are certainly head-orientation cells (e.g. in the hippocampus). But neurons are reasonably immune to the kind of mild physical stresses that come from turning the head around; computing head orientation requires complex analysis of input from e.g. the visual system (optic flow) and vestibular system.

However, the electrical activity of muscles tends to swamp that of (nearby) neurons, so various muscle-related artifacts are often visible in an EEG if not carefully filtered out. And, of course, if the contact is poor you'll get artifacts from that: you're just measuring the variability in resistance between the sensor and your skin, not anything interesting about what faint potential changes are visible at your skin as a result of neuronal activity.

genetics - What accounts for size variation in breeds of dogs?

This is a fascinating bit of genetics.

Dogs are especially variable in size and many appearance, behavioral and temperamental phenotypes. It was long expected that variations in developmental genes were the reason that dog breeds were responsible for the amazing flexibility of dog sizes. One early locus found was IGF1 (insulin like Growth Factor 1).

This 2011 PLOS paper actually review the specific genotypes of dog breeds and identifying loci that are strongly associated with breed phenotype supports this idea.

... (we scanned) the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits.

Emphasis added.

This theory has an intuitive appeal as well - no dog breeds (I think) are larger than the wolf, the stock from which all dog breeds are descended. All such breeds being derived from earlier developmental stages of the wolf makes an intuitive, if imprecise description of the effect here.

Regardless, dogs remain an important model organism for so many traits because relatively few genomic regions can cause so many important phenotypes, including size, but also behavioral and morphological variations.

In the below figure you can see how few genomic regions are responsible for the 46 breeds Vaysee et al. examined.

biochemistry - Why pouring salt in the wounds is painful?

De salt particles are alien bodies and can damage the tissue by mechanical means (This would also happen if you pour sand into an open wound). Also, the exposed tissue is vulnerable to dehydration, wich happens faster if the osmotic pressure is higher. Finally, nerve tissue is particulary sensible to changes in the ion composition of its sorroundings, so the added sodium may affect the action potential of the nociceptors.

genetics - What determines the colors and patterns of a clam shell?

Earlier this week I was looking at some bivalve shells that had ornate patterns which ranged in color from a light orange-pink to a deep orange-red. Here is an image I found online that seems to be of the same type of shell:

The friend who was with me said, "I wonder where the color comes from." We were trying to look for two shells with similar colors, patterns, and approximately equal sizes, and it was hard, even though we were looking through a large collection of similar shells.

What determines this ornate pigmentation? Is it influenced by environmental factors such as the minerals in the water? Does it have anything to do with the age or health of the organism? Or is it purely genetic? Is this determined by the same basic biological principle that determines the color of human hair, or is there something different at work in shells?

evolution - Why aren't antheridia and archegonia touching?

Antheridia and archegonia are the two male and female gametangia, respectively, and they are found in bryophytes. To cause fertilization, usually a thin film of water must be present for the sperm from the antheridia to reach the archegonia. Why hasn't evolution trivialized this process? I have the same question for flowers that primarily undergo self-fertilization. How is this not inefficient?

amino acids - Why are Taurine and Arginine essential components of the feline diet?

From the Taurine Wikipedia article:

The absence of taurine causes a cat's retina to slowly degenerate, causing eye problems and (eventually) irreversible blindness – a condition known as central retinal degeneration (CRD), as well as hair loss and tooth decay. Decreased plasma taurine concentration has been demonstrated to be associated with feline dilated cardiomyopathy.

Arginine is an Essential Amino Acid for cats (and many other mammals - including Humans while we're infants). That is, they cannot synthesize it on their own and must obtain it entirely from their diet. A 10lb. (5kg) cat will require about .86g of Arginine - which is abundant in all meats and can be met with a few ounces of food.

I could not find anything particularly special about Arginine as opposed to other EAA's for cats.

genetics - Origin, or source, of rhesus negative in human blood

This is my first post here, so please be gentle. I recently learned that I have Rh- blood (I'm A-), and was idly looking into blood types on Wikipedia. I was surprised to find that relatively few (~15% of all) humans have it, and most of those seem to be European. Looking just a little further, I found a bunch of crackpot-looking sites that try to explain how people got Rh- blood, and what weird abilities they possess as a result.

I managed to find one site that seemed at least less laughable, which suggested that interbreeding with Homo neanderthalensis (or possibly Homo sapiens neanderthalensis, since the site seemed to indicate that there was some question about how different H. s. sapiens were from H. neanderthalensis) might have accounted for the introduction of the condition.

It seems that from more reputable (medical) sources, the only difference between Rh+ and Rh- is that complications can arise during pregnancy if the mother is Rh- and the fetus is Rh+. Indeed, most sites (e.g., WebMD) seem to explicitly state that there are no other differences of note.

I am not a biologist, or an anthropologist, or a life-science kind of guy at all. However, as a computer scientist, I like to think that I have both an open mind but one which demands scientific and/or logico-mathematical evidence for claims. Lots of the pseudo-scientific, paranormal, etc. theories on the web I basically dismiss out of hand, as explanations which are almost certainly fantasies, but most definitely baseless and untestable.

My question:

What, if any, is the current scientific understanding of the origin, or source, of rhesus negative blood in human beings? Do individuals with Rh- blood have any common (in a statistically significant sense) characteristics or health issues, aside from the issue with pregnancy and tending to be more European than not? Is there anything to continuing to look into this?

For context, I got started down this rabbit hole while looking into different dieting strategies, and found the "blood type diet". Just as an aside, I don't think there's a lot of merit to that diet... sounds like a fad thing. Any sources or information or help on this subject are appreciated.

EDIT:

I have been looking a little more, and I stumbled across a paper entitled, "The influence of RhD phenotype on toxoplasmosis and age-associated changes in personality profile of blood donors" which looks at the effect of the Rh- trait on personality changes caused by toxoplasmosis (if you Google the title, you should be able to download). Using Cloninger's and Cattel's personality factors, they seem to show a variety of things, including (a) personality differences between Rh+ and Rh- individuals not affected by toxoplasmosis, and (b) different reactions to prolonged toxoplasmosis affection in Rh+ and Rh- individuals.

I didn't even know that parasites could affect your behavior; that seems frightening on the one hand, but on the other, it's fascinating if it's for real, especially since the incidence of toxoplasmosis is not insignificant in most people. Anybody who knows anything about this or who reads the paper and can help me understand what it's saying would be doing me a great favor to answer/comment/chat. Thanks!

evolution - Does a fully-resolved phylogenetic tree have to be dichotomous?

In theory, yes, every tree has to be dichotomous. You can understand a trichotomy in a tree as the summatory of two dichotomies that had happened so close in time that you cannot know wich was first.

Given a certain population, assume that some individuals colonize a new environment, got reproductively isolated and form a new specie. This is the typical speciation process. In this case, the two species, share a common ancestor. If you go back in time, all the individuals of the new specie will descend of only one individual. The same goes for the original specie. If you go back further, this individuals will share an ancestor, too. This is the conceptual meaning of the dichotomy, but normally it is impossible to determinate wich was exactly the common ancestor.

Now imagine that the original population formed not one, but two new species. And that this process happened about the same time as the one described before. It is conceptually possible that a set of three brothers were the origin of three different species (wich will be a true trichotomy), but not only it's very unlikely, but it's virtually impossible to prove. Since two close dichotomies are far more probable than a trichotomy, it's assumed that every tree has to be dichotomous, and that a trichotomy is in fact due to lack of resolution.

pathology - What mechanisms do animals living in groups (herds, packs, swarms) have against spreading contagious diseases?

Almberg ES, Mech LD, Smith DW, Sheldon JW, Crabtree RL (2009) A Serological Survey of Infectious Disease in Yellowstone National Park’s Canid Community. PLoS ONE 4(9): e7042. doi:10.1371/journal.pone.0007042

The authors found that the majority of Yellowstone wolves had been exposed to a number of different viruses (evidence from antibodies in blood samples).

They also found evidence for historical outbreaks of canine distemper virus in wolves, coyotes and red foxes in 1999 and 2005. These outbreaks correlated with peaks in wolf pup mortality.

This evidence suggests that wolves have no mechanisms for avoiding the spread of these viral diseases. Perhaps periodic episodes of increased mortality are the price that has to be paid for a longer-term 'herd immunity'?

Edit - in response to OP comment below:

The data indicate very high levels of seropositivity to the viruses. I would say that 'not 100% successful' is an understatement. But I must admit that I am way out of my area of expertise here!

From the abstract:

We found high, constant exposure to canine parvovirus (wolf seroprevalence: 100%; coyote: 94%), canine adenovirus-1 (wolf pups [0.5-0.9 yr]: 91%, adults [>or=1 yr]: 96%; coyote juveniles [0.5-1.5 yrs]: 18%, adults [>or=1.6 yrs]: 83%), and canine herpesvirus (wolf: 87%; coyote juveniles: 23%, young adults [1.6-4.9 yrs]: 51%, old adults [>or=5 yrs]: 87%) suggesting that these pathogens were enzootic within YNP wolves and coyotes.

evolution - How much can you learn about species variation from a skeleton?

It seems as if this article is purely speculative. They didn't mention any DNA testing, but instead discussed physical features.

There are two "types" of archaeologists: clumpers and splitters. Clumpers (like the author of this article) believe that there is wide variety among members of the same species, and so it is often wrong to categorize every new hominid fossil as being a different species. Splitters like to "split" their findings into new species, even though there is no evidence that speciation had ever occurred; they just decide that since the remains look different, they must have speciated.

In the future, I hope that archaeologists will have more sophisticated means of sequencing the DNA of ancient remains, allowing them to construct an accurate phylogeny

microbiology - How can a respiratory infection lead to a skin infection?

Example of a case: 5 children develop a bright red rash on the face and turns violet after a few days and then disappears. Then maculopapular rash appears on the trunk, buttocks and extremities. It soon fades from the trunk but persists on the thights and forearms. Two children have also had a slight fever and a sore throat, but all were not terribly sick. What is the genetic material of the most likely causative agent?

It is a skin infection. Not so severe. Little upper respiratory infection but not necessary caused by the agent. Infects many so spread probably by respiratory droplets. But how a respiratory infection can lead to a skin infection?

human biology - What are the limitations of commercial-grade DNA genotyping compared to full sequencing?

23andme briefly describes the technology they use here. They are testing the genotype of your DNA at roughly 1 million locations. The technology they use to do this is known as a microarray.

The limitations of using a microarray, as compared to sequencing, is that you will only find what you are looking for -- people often describe the disadvantages of microarrays as compared to sequencing with the streetlight effect/metaphor.

Arrays can only measure regions of the genome that they were designed to probe. Technically, if they probe 1,000,000 million locations, and the human genome is roughly 3.4 billion bases ... you can do the math.

In practice, SNPs tell you a bit more about just the nucleotide being interrogated, due to linkage disequilibrium (cf. tag/proxy SNPs), so the array might tell you more than you expect.

Of course, modulo sequencing errors, whole genome sequencing will tell you "everything" as far as recovering the NTs that make up your genome, but how much information that will provide you is another thing altogether (for now, that is).

human anatomy - Why does the sweat of children not smell like adults?

There are two types of sweat glands: (1) eccrine sweat glands and (2) apocrine sweat glands.

1. Eccrine sweat glands are present from birth in humans and secrete sweat that is mostly water and functions in evaporative cooling.


2. Apocrine sweat glands are found in the armpits and groin regions and become active in humans at puberty (although the distribution appears to be broader fetally). These sweat glands secrete an oily substance containing lipids and proteins that through interactions with bacteria on the skin (e.g., bacteria digesting lipids), lead to the "smelliness" of adults (including body odor).

So it's not really the sweat that smells, it's the action of bacteria on apocrine sweat that becomes prevalent after puberty.

genetics - Expression of plasmid genes

It would depend of the plasmid, the genes it contains and the promotors those genes have. Basically, regulation of extrachromosomal genes follow the same patterns of the rest. Bacteria, Archaea and some other organisms that can have plasmids will express the genes if the promotors of those genes are constitutive, or if they trigger by conditions that are present in a given moment. The degree of expression would be a function of the characteristics of the promoter and the number of copies of the plasmid. Finally, the number of copies of the plasmid would depend of its size and the characteristics of its replication origin.

Organisms can loss the plasmids if doing so don't suposse a negative effect (this is a big problem in industrial microbiology, since the recombinant strains may be unstable and reduce its productivity). In laboratory, a plasmid containing resistance genes towards an specific antibiotic would remain stable as long as this antibiotic is present in the media. The characteristics of its replication origin also play a big role determining the stabilty of plasmids. You can even select for the loss of plasmids, take the example of URA3 in Saccaromyces (not a bacteria, but the mechanisms are the same), wich can be used as a negative selection factor if the media contains 5-fluoroorotic acid.

So there's no particular advantage in expressing plasmidic genes all the time. When that happens, actually there exist an evolutionary pressure against the presence of the plasmid, and thus it trends to dissapear. Bacteria can survive without plasmids (with the exception of some that carry megaplasmids that acts more than little chromosomes. In some of this cases, the plasmid may contain genes for important methabolic pathways and other key elements of the cell, thought if the genes they carry are very importants, like polymerases or ribosomal RNAs, the term minichromosome is prefered). However, plasmids may contain genes that confer an important advantage to the population (like in presence of an antibiotic), and if so the plasmid spread. If at some point the ecological pressure cease, the plasmid would turn unstable again. Note that it's not impossible to have horizontal genes transfer between plasmid and chromosomes, and plasmids (alongside viruses and foreign transformed DNA) are important sources of new genetic material.

ethology - are female bonobos "always" pregnant?

In most species, females are pregnant as often as they can be. Since the availability of sex is rarely a limiting factor, it seems likely that female bonobos are as "always" pregnant as other chimps and socially living primates. The actual rate of pregnancy will be hormonally limited by things such as reduced fertility during lactation and so on.

human biology - What causes sinus pain and congestion?

Inflamed sinuses are often associated with some kind of illness or irritant such as flu, the common cold, or hay-fever. As an example the cold causes sinus pain and inflammation because the virus is attacking/located in the nasal passages which causes swelling in the mucus membrane (the mucus membrane lines the sinus cavities). The swelling, along with increased mucus production, combines to create clogging and the pressure associated causes pain. Humidity will help loosen the mucus and anti-inflammatory medication should help reduce pain by reducing the mucus build up and swelling - thus relieving pressure.

The increase in mucus production is because of the role it plays in our bodies - it is produced to trap foreign bodies and help keep our system clean. The more mucus we produce the more our bodies are trying to clean up. This can cause an excess which is difficult to clear such that our sinuses become blocked and dried mucus becomes an irritant.

Sinusitis is the painful condition of swelling in the mucus membrane. Sinus comes from the latin for bent or curved surface, and -itis is from greek meaning swelling or inflammation linked to disease.

In summary: Painful sinuses, aka sinusitis, are painful because of infection in the mucus membrane producing swelling and excessive mucus build-up.

physiology - Why do bats huddle during late fall?

This is basically a trick question and a bit of a cheap shot. All of the reasons cited boil down to "bats huddle to conserve heat", they are basically the same, single, reason.

In order for bats to feed, they need to move, fly out of their cave or wherever they happen to sleep and go forth and look for food. Therefore, they will not be able to huddle while feeding because they will be flying around trying to find fruit or donkeys or whatever each species feeds on. Unless they can figure out a way to huddle while flying, they will not be able to huddle while feeding and so number 5 is wrong.

virology - Why are some viruses not communicable person-to-person?

Below are two quotes from the CDC about Hantavirus:

"Researchers believe that people may be able to get the virus if they
touch something that has been contaminated with rodent urine,
droppings, or saliva, and then touch their nose or mouth."

and:

"You cannot get the virus from touching or kissing a person who has HPS."

This is hard to believe. So, since human saliva is not a problem, can you be contaminated
by human urine or human droppings? The only way for me to interpret this logically is to
say that this virus lives at the end of the digestive tract (for both rodents and humans)
and people can be kissed because they have much better hygiene than rodents. Is there a
better interpretation?

Also, is there a simple reason why Hantavirus leaves the mouth (moving to the end of the
digestive tract) of an infected animal, but influenza does not?

evolution - Why is venom more common in fish and snakes than other vertebrates?

This write up by Carl Zimmer basically covers anything I could have said. He links to a number of resources, in particular this pdf, which at a cursory glance looks utterly fascinating and very well done. Figure 1 in that pdf sums it all up, I guess, or to quote Carl:

"Each lineage of venomous animals became deadly on its own, independent of all the others. And yet, in the end, their venoms echo each other... These results show that there are a limited number of ways to kill your victim quickly. No matter what genes you borrow for the evolution of venom, they will end up very similar to other venoms."

Another Zimmer piece specifically points out research purporting to show that snake venom genes are much older than snakes, maybe 200 million years old. That gets around but doesn't quite answer your question. An older review tried to coalesce things (as best as he could in '92), spending time focusing on insectivora and dealing with mammals. The theory is that while venom is an excellent advantage, it requires a significant investment and is often slow-working. In a world with sharp teeth capable of tearing, venom may not be necessary. Mammals, for example, might evolve to not use venom, as it may not be suitable for their high daily energy demands. The pdf linked above briefly touches on the concept of "reverse recruitment," where venom genes may be usefully re-purposed for other biological processes.

human biology - Do teeth have the capacity to heal?

Yes, it can be done to a certain degree.

Cementum is capable of repairing itself to a limited degree and is not resorbed under normal conditions. Some root resorption of the apical portion of the root may occur, however, if orthodontic pressures are excessive and movement is too fast. Some experts also agree on a third type of cementum, afibrillar cementum, which sometimes extends onto the enamel of the tooth.

Cementum is produced by cells called cementoblasts.

more here:
http://en.wikipedia.org/wiki/Cementum

bioinformatics - Models of quorum sensing for multi-agent systems

Quorum sensing is a system of stimulus and responses correlated to population density that is used by bacteria to coordinate gene-expression. I am looking for a simple computational/mathematical model of quorum sensing that abstracts away from the details of the mechanism implementing it inside the agent, but keeps the key inter-agent properties like diffusion rate, range, and timing.

Is there a standard abstract mathematical model of quorum sensing used by biologists?

I am not interested in the particulars of a specific organism, but would like a general model I could apply to capture the 'gist' for any organism that relies on quorum sensing for part of its behavior.

---

Bernardini et al. (2007) provided an extension to P-systems incorporating the basics of quorum sensing, and Romero-Campero & Pérez-Jiménez (2008) have used their approach to model bioluminosity in vibrio fischeri. This approach is conceptually appealing to me, but that is because I am predominantly a computer scientists. Although P-system can be used for modeling biological systems (Ardelean & Cavaliere, 2003), they still feel fundamentally computer-science-y and are typically not published in orthodox biological venues. This makes me suspect there is a more standard approach among biologists, probably via dynamic systems and diffusion equations.

pharmacology - Why is Paracetamol so great?

Paracetamol is a pain killer, it does not treat the cause of your illness, it only alleviates the symptoms. From its wikipedia page:

Paracetamol [...], chemically named
N-acetyl-p-aminophenol, is a widely used over-the-counter analgesic
(pain reliever) and antipyretic (fever reducer).

So, paracetamol does not make you better. Your immune system makes you better. Paracetamol just makes you feel better while you are waiting for your immune system to get an infection under control.

You should be aware that it is only safe in small doses and a toxic dose is not that much more than the recommended one (source):

Risk of severe liver damage (ie a peak ALT more than 1000 IU/L)

Based on the dose of paracetamol ingested (mg/kg body weight):

Less than 150 mg/kg - unlikely
More than 250 mg/kg - likely
More than 12 g total - potentially fatal

Again from wikipedia:

While generally safe for use at recommended doses (1,000 mg per single
dose and up to 4,000 mg per day for adults),[6] acute overdoses of
paracetamol can cause potentially fatal liver damage and, in rare
individuals, a normal dose can do the same; the risk may be heightened
by chronic alcohol abuse, though it is lessened by contemporary
alcohol consumption. Paracetamol toxicity is the foremost cause of
acute liver failure in the Western world, and accounts for most drug
overdoses in the United States, the United Kingdom, Australia and New
Zealand.

I am sure someone else can explain the pharmacokinetics and details of action of paracetamol. I just wanted to point out that paracetamol can be dangerous and should be treated with respect.

genetics - Difference between mutation and DNA damage

Have you read the DNA repair article on Wikipedia? The DNA damage and mutation section answers exactly what you're asking:

DNA damages and mutation are fundamentally different. Damages are physical abnormalities in the DNA... [and] can be recognized by enzymes, and, thus, they can be correctly repaired if redundant information, such as the undamaged sequence in the complementary DNA strand or in a homologous chromosome, is available for copying.... In contrast to DNA damage, a mutation is a change in the base sequence of the DNA. A mutation cannot be recognized by enzymes once the base change is present in both DNA strands, and, thus, a mutation cannot be repaired.

Here's the entry from the NCBI MeSH Glossary saying the same thing:

Injuries to DNA that introduce deviations from its normal, intact structure and which may, if left unrepaired, result in a MUTATION or a block of DNA REPLICATION... They include the introduction of illegitimate bases during replication or by deamination or other modification of bases; the loss of a base from the DNA backbone leaving an abasic site; single-strand breaks; double strand breaks; and intrastrand (PYRIMIDINE DIMERS) or interstrand crosslinking. Damage can often be repaired (DNA REPAIR).

And for mutation:

Any detectable and heritable change in the genetic material that causes a change in the GENOTYPE and which is transmitted to daughter cells and to succeeding generations.

genetics - How diverse are dogs in their traits other than appearance?

I've asked this question about dogs not so long ago, and the short answer was - dogs are the most diverse looking species of mammals because they got a small number of genes that have a big impact on appearance.

I would like to ask a follow up question- differences in appearance are easy to notice, and I would like to learn about other traits that might be genetically based.

Are there other major differences between dog breeds, like longevity, cognitive performance, friendliness, etc? Or are all dogs more or less the same in traits other than appearance?

Are there plots of traits like these among different dog breeds that identify outliers?

biochemistry - Can the sulphur content of biological material be reliably calculated from fat, fibre and protein contents (Weender Analysis)?

I would say theoretically yes, if you know lots of other information, but practically no, because of all the unknowns.

According to this paper cysteine content and therefore sulfur content of proteins vary depending on what kind of organism your organic material is coming from. Animals have more, bacteria tend to have less.

The sulfur content as a fraction of protein content in a given animal or plant is constant or nearly constant across the entire animal/plant. If a sample's protein content is 50:50 corn protein:sheep protein it's possible to estimate the sulfur content of the protein fraction from the sulfur contents of the sources of the protein.

In addition the sulfur content can be affected by fermentation and sulfur/sulfate-reducing bacteria, many but not all of which are anaerobes. So figures for whatever the source of the feedstock is (as far as cysteine content) can be affected by whatever happens to it afterwards. Chicken waste with a high sulfur content allowed to ferment may give off fairly large amounts of hydrogen sulfide, lowing the sulfur content without necessarily affecting the bulk protein content. The reverse might also happen, where protein is digested and sulfur is released as sulfates but kept in the mixture.

Even if you know for certain the sources of all of the protein(and that no further biological activity has changed them), the unknown amount of organic acids is going to throw off your sulfur estimates if there are sulfur-containing organic acids in the N-free fraction.

genetics - Does DNA contain information beyond protein synthesis?

What a timely question.

Does DNA contain information beyond protein synthesis?

Yes. In fact, protein-coding genes only constitute a tiny part – less than 2% – of the whole DNA. There are of course many other genes which aren’t protein coding: there are genes for ribosomal RNA and we find more and more genes which code for small RNAs, such as tRNA. But even if we count all those genes we won’t come above maybe 10% of the total DNA.

Most of the DNA is instead devoted to the regulation of gene expression, most importantly via the binding of transcription factors (but the picture is much more complex than that). With the conclusion of the ENCODE project, a whole slew of papers were published which show that in fact most of the DNA is actively implicated in the binding of various factors (although it’s not known how much of that actually contributed to the cell’s fitness).

But I’ve hijacked your question a bit here. So let’s come back to what you’re actually interested in:

What about higher levels, such as organelles, cells, tissue, organs?

There is no known mechanism (beyond the already mentioned regulation) which would encode such information in the DNA. Excluding its existence categorically may be hard but given that we haven’t found any machinery which would be necessary to read such information, we can be pretty confident that it doesn’t exist.

If not, what guides those levels of structure?

The higher levels of organisation are to all appearances emergent. That is, they are a consequence of the lower level organisation. For instance, take the cytoskeleton which carries much of the cell’s physical structure. It is composed of different protein complexes which form spontaneously through assembly of globular proteins (such as actin). The are several ways in which the process can be guided but strikingly it’s largely stochastic – i.e. mostly unguided, and it still succeeds in building a stable skeleton, simply by virtue of molecular properties encoded in the proteins.

I think this is a common theme of cell organisation: the elementary building blocks are encoded by the DNA, and their abundance is tightly regulated. Everything else, i.e. higher-level organisation – follows from that: abundance and localisation of the right proteins.

As for differentation into different types of cells, and organization into tissue and organs: the information and control systems for that are currently unknown.

In fact, much is known here, and it goes back to regulation on the level of DNA: we know that genes are differentially expressed depending on the cell type and stage of development (and the stage in the cell cycle). This regulation is highly complex and decoding it is a slow process. Nevertheless, the factors involved here are decoded one by one. This is the domain of developmental biology.