Diffusion in cells

Diffusion in cells- been teaching the course bio435 - biophysics II or Physical Biology of the Cell or what i really do for a living or...
The fascinating part about diffusion is that it binds both historically and scientifically energy, matter and living-systems. Brown who discovered the motion named after him, was looking at pollen grains. And in order to convince himself it was not 'vital' force, he even went to the extent of grinding pieces of the pyramids of egypt, to see if they.moved (guaranteed to be dead). Einstein who described the relation between macroscopic viscosity and molecular movement is "the physicist". In his Wunderjahr (miracle year) of 1906 papers one of them, less popularly known as compared to the mass energy relations, was the relation between heat (Wärme) and molecular movement (Bewegung).

In the lab, we have been using fluorescence recovery after photobleaching (FRAP), an experimental technique, combined wirh some simple imageJ data extraction and loads of attempts at analyzing the data, to estimate molecular diffusion coefficients inside cells. Currently we find a few odd things.

A FRAP profile of an E. coli cell expressing GFP

1_ GFP diffuses faster in E. coli than we can bleach it out.
2_ Reducing the number of bleach pulses doesn't allow any measurable bleaching, i.e. our scanning system is too slow
3_ The recovery kinetics show heavy amounts of imaging-dependent bleaching. 

Did we not turn down the laser after the bleach?

More on this when i get to it.

The problem(s) with biology and fishy epiphany

Today is a day of epiphany. I bought my first pet fish. And am curious to see how far I get. Hope not to make it into a 10-little indians story (and then there were none). Do we have females and males? Dunno. What species? Orange-Zebrafish.

But the second and more important reason for my feeling of epiphany was facing up to my limited knowledge of biology, and the reasons for which its not my fault.

I enter the aquarium shop knowing well, I know less about fish than the owner. Yet, being a PhD in Biology, I assume I know about general principles of biological life as I have been taught. And when I ask if guppies lay eggs, the man tells me not. So that to me is a contradiction since except for mammalian aquatic organisms like dolphins and whales, fish are "supposed to" lay eggs. So based on smug theoretical knowledge, I wagered a cake. And now after 2 mins of google-research, I find he was right!

Apparently guppy sperm swims up the tubes and fertilizes eggs, which therefore end in live births. Also true of sharks (yes, otherwise the chinese would eat shark egg powder to improve sexual prowess). So apparently Poeciliidae are a genus with high proportion of animals that keep the eggs in their bodies and give live-births [wikipedia].However I was right in one sense that Poeciliidae are oviparous (they produce true eggs). The eggs inside the mother do not get nutrients- package deal, eat what you have inside the egg, no more. However "plitfins and halfbeaks are viviparous [Reference].

So why is it not my fault? The fault lies in the approach to diversity in life. By creating this super structure we have some insights into how animals might be related to each other- habitat (water), egg-layers vs. not, but these are not consistent. And without detailed knowledge of all of the things, we still can't tell what the new animal we come across might be like, without testing in detail. As a theoretical biologist, this is embarassing at the least- if not cause for concern!
More on this.

And the blog is about patterns in living matter. And living matter has patterns and patterns and intersections. And hard to keep apart classifications. So how to we construct laws of living matter, if there is so much "biological variation"?

Writing into the prefrontal cortex or how to avoid a makeup Class in Calculus

I suspect everbody from Sun Tzu, through Susruta the cosmetic surgeon, via Plato all the way to Goebbels, might have racked their brains on how to control what people think.

But more than control, implying constant and involuntary obedience, I wonder how feasible it might be to transfer what one person has learnt to another. Telepathy is clearly old, and relatively discredited. But I wonder with all the progress made in magnetic resonance imaging (MRI), would it be possible indeed not just to read our thoughts, but to write too?

More on this in a bit. There are apparently clear enough indications that the pre-frontal cortex (PFC) of the brain in Rhesus macaques is capable to showing single cell level changes corresponding to numbers [1]. The blogger who posted this [2] appears to also suggest that simple arithmetic is performed in these monkies. The measurements were made using probes inside the brain to monitor firing of single neurons.

So if we can measure firing when an operation of addition is performed, what would it take to "teach" the brain how to do it. Indeed that raises the same old question, how to we learn. But at a neuronal level.

And then how do we modify this. Is this at the single neuron level? For such simple tasks as addition it appears to be controlled in monkies at the single neuron level. So how about higher mathematical functions? Can we "write" calculus into our brains?

References:

1. Bongard, S. & Nieder, A. (2010). Basic mathematical rules are encoded by primate prefrontal cortex neurons Proc. Nat. Acad. Sci. 10.1073/pnas.0909180107
   
2. http://scienceblogs.com/neurophilosophy/2010/01/single_cells_in_the_monkey_brain_encode_abstract_mathematical_concepts.php

Neuronal model contest

I was again reminded of how much is lacking in modelling biological systems. Neuronal modelling has possibly been one of the earliest fields, along with biochemical kinetics for cellular models. The Hodgkin-Huxley model being a case in point. The contest is a call for models of spike timing prediction at the level of a single neuron- Quantitative Single Neuron Modeling.

Besides the prize of getting it right, there are some other incentives too - CHF 10,000 (swiss francs) for the best performance on 2 of the typically 4 challenges.

Alignment of Polarized Cu Sticks

Some recent exciting research from the IISC Bangalore has experimentally demonstrated the breakdown of the central limit theorem that the sample-sample fluctuation of N particle systems grows as N^1/2. They demonstrate that for non-equilibrium systems the fluctuation can vary as N for N particles.

Interestingly their ordering of the Copper rods only occured in the driven system (between two vibrating plates) when the rods were etched at one end, effectively making them arrow-like. Here are some of the comments from Science:

(FIGURE: Swarms and swirls. In the experiments of Narayan et al., agitated sticks form swarming states that exhibit giant number fluctuations. Similar patterns are observed in fish swarms (top left). Swirls are also observed in systems that are close to jamming, for example, in the motion of bubbles in a sheared foam (right).)

Science 6 July 2007: Vol. 317. no. 5834, pp. 49 - 50 DOI: 10.1126/science.1145113

MATERIALS SCIENCE:
Shape Matters

Martin van Hecke
"Swarming and giant number fluctuations are a hallmark of the alignment displayed by driven collections of nonspherical particles. Theoretical models have been developed to describe swarming and alignment observed in schools of fish, flocks of birds, herds of sheep, or bacterial colonies--often borrowing from equilibrium models for magnetization, which consider the alignment of arrowlike objects. A very simple nonequilibrium model that exhibits cooperative motion arises when these arrows are allowed to propagate (2). In similar models, a collective response to predators and decision-making can arise (3). Toner and Tu first pointed out the giant fluctuations in such models (4).

In these systems, the particles have a preferred direction of propagation--just like real fish and birds. In 2003, Ramaswamy et al. (5) wondered what would happen for "active nematics," liquid crystals in which the particles have an orientation but have identical heads and tails (like the sticks in the present experiment). Their theory predicted that nematic systems also should exhibit giant number fluctuations, and these were recently observed in computer simulations (6).

However, when Narayan et al. tried to find such fluctuations in experiments, they encountered a surprising hurdle: cylindrical rods, arguably the simplest nematic particles, do not form nematic states and do not exhibit giant fluctuations (7). The authors achieved their present breakthrough only after etching the rods to obtain sticks with thinner ends (see the figure); for unknown reasons, these sticks exhibit nematic order. To complicate matters further, Aranson et al. recently performed similar experiments and observed that weak coupling between the nematic order and spurious in-plane vibrations of the support plate may strongly influence the swirling motion (8). Clearly, swarming is a subtle problem, and the precise nature of the swarming state and the transition to swarming is not yet fully understood.

The experiments of Narayan et al. are part of a bigger story, where nonequilibrium systems of nonspherical particles exhibit surprising behavior: We do not yet understand the consequence of shape. An earlier striking example of this is the finding that, contrary to expectation, M&M candies can be packed more effectively than spheres (9)."

REFERENCES:

1. V. Narayan, S. Ramaswamy, N. Menon, Science 317, 105 (2007).
2. T. Vicsek, A. Czirok, E. Ben-Jacob, I. Cohen, O. Shochet, Phys. Rev. Lett. 75, 1226 (1995).
3. I. D. Couzin, J. Krause, N. R. Franks, S. A. Levin, Nature 433, 513 (2005).
4. J. Toner, Y. Tu, Phys. Rev. E 58, 4828 (1998).
5. S. Ramaswamy, R. A. Simha, J. Toner, Europhys. Lett. 62, 196 (2003).
6. H. Chaté, F. Ginelli, R. Montagne, Phys. Rev. Lett. 96, 180602 (2006).
7. V. Narayan, N. Menon, S. Ramaswamy, J. Stat. Mech. 2006, P01005 (2006).
8. I. S. Aranson, D. Volfson, L. S. Tsimring, Phys. Rev. E 75, 051301 (2007).
9. A. Donev et al., Science 303, 990 (2004).
10. A. J. Liu, S. R. Nagel, Nature 396, 21 (1998).
11. O. Dauchot, G. Marty, G. Biroli, Phys. Rev. Lett. 95, 265701 (2005).
12. A. S. Keys, A. R. Abate, S. C. Glotzer, D. J. Durian, Nature Phys. 3, 260 (2007).
13. W. G. Ellenbroek, E. Somfai, M. van Hecke, W. van Saarloos, Phys. Rev. Lett. 97, 258001 (2006).
14. F. Lechenault, O. Dauchot, G. Biroli, J.-P. Bouchaud; available online at http://arXiv.org/abs/0706.1531v1.