Do You Have the Guts for Nori?

Source: Precision Nutrition

The paper I will talk about this month is from April of this year and highlights the diversity of our “gut flora” (a pleasant way to describe the many bacteria which live in our digestive tract and help us digest the food we eat). Specifically, this paper highlights how a particular bacteria in the digestive tracts of some Japanese individuals has picked up a unique ability to digest certain certain sugars which are common in marine plants (e.g., Porphyra, the seaweed used to make sushi) but not in terrestrial plants.

Interestingly, the researchers weren’t originally focused on how gut flora function at all, but in understanding how marine bacteria digested marine plants. They started by studying a particular marine bacteria, Zobellia galactanivorans which was known for its ability to digest certain types of algae. Scanning the genome of Zobellia, the researchers were able to identify a few genes which were similar enough to known sugar-digesting enzymes but didn’t seem to have the ability to act on the “usual plant sugars”.

Two of the identified genes, which they called PorA and PorB, were found to be very selective in the type of plant sugar they digested. In the chart below (from Figure 1), 3 different plants are characterized along a spectrum showing if they have more LA (4-linked 3,6-anhydro-a-L-galactopyranose) chemical groups (red) or L6S (4-linked a-L-galactopyranose-6-sulphate) groups (yellow). Panel b on the right shows the H1-NMR spectrum associated with these different sugar mixes and is a chemical technique to verify what sort of sugar groups are present.

Source: Figure 1, Hehemann et al.

These mixes were subjected to PorA and PorB as well as AgaA (a sugar-digesting enzyme which works mainly on LA-type sugars like agarose). The bar charts in the middle show how active the respective enzymes were (as indicated by the amount of plant sugar digested).

As you can see, PorA and PorB are only effective on L6S-type sugar groups, and not LA-type sugar groups. The researchers wondered if they had discovered the key class of enzyme responsible for allowing marine life to digest marine plant sugars and scanned other genomes for other enzymes similar to PorA and PorB. What they found was very interesting

Source: Figure 3, Hehemann et al.

What you see above is an evolutionary family tree for PorA/PorB-like genes. The red and blue boxes represent PorA/PorB-like genes which target “usual plant sugars”, but the yellow show the enzymes which specifically target the sugars found in nori (Porphyra, hence the enzymes are called porhyranases). All the enzymes marked with solid diamonds are actually found in Zgalactanivorans (and were henced dubbed PorC, PorD, and PorE – clearly not the most imaginative naming convention). The other identified genes, however, all belonged to marine bacteria… with the notable exception of Bateroides plebeius, marked with a open circle. And Bacteroides plebeius (at least to the knowledge of the researchers at the time of this publication) has only been found in the guts of certain Japanese people!

The researchers scanned the Bacteroides plebeius genome and found that the bacteria actually had a sizable chunk of genetic material which were a much better match for marine bacteria than other similar Bacteroides strains. The researchers concluded that the best explanation for this is that the Bacteroides plebeius picked up its unique ability to digest marine plants not on its own, but from marine bacteria (in a process called Horizontal Gene Transfer or HGT), most probably from bacteria that were present on dietary seaweed. Or, to put it more simply: your gut bacteria have the ability to “steal” genes/abilities from bacteria on the food we eat!

Cool! While this is a conclusion which we can probably never truly prove (it’s an informed hypothesis based on genetic evidence), this finding does make you wonder if a similar genetic screening process could identify if our gut flora have picked up any other genes from “dietary bacteria.”

Paper: Hehemann et al, “Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota.” Nature464: 908-912 (Apr 2010) – doi:10.1038/nature08937

Check out my other academic paper walkthroughs/summaries

How You Might Cure Asian Glow

The paper I read is something that is very near and dear to my heart. As is commonly known, individuals of Asian ancestry are more likely to experience dizziness and flushed skin after drinking alcohol. This is due to the prevalence of a genetic defect in the Asian population which affects an enzyme called Aldehyde Dehydrogenase 2 (ALDH2). ALDH2 processes one of the by-products of alcohol consumption (acetaldehyde).

In people with the genetic defect, ALDH2 works very poorly. So, people with the ALDH2 defect build up higher levels of acetaldehyde which leads them to get drunker (and thus hung-over/sick/etc) quicker. This is a problem for someone like me, who needs to drink a (comically) large amount of water to be able to properly process wine/beer/liquor. Interestingly, the anti-drinking drug Disulfiram (sold as “Antabuse” and “Antabus”) helps alcoholics keep off of alcohol by basically shutting down a person’s ALDH2, effectively giving them “Asian alcohol-induced flushing syndrome” and making them get drunk and sick very quickly.

Source: Wikipedia

So, what can you do? At this point, nothing really (except, either avoid alcohol or drink a ton of water when you do drink). But, I look forward to the day when there may actually be a solution. A group at Stanford recently identified a small molecule, Alda-1 (chemical structure above), which not only increases the effectiveness of normal ALDH2, but can help “rescue” defective ALDH2!

Have we found the molecule which I have been searching for ever since I started drinking? Jury’s still out, but the same group at Stanford partnered with structural biologists at Indiana University to conduct some experiments on Alda-1 to try to find out how it works.

Source: Figure 4, Perez-Miller et al

To do this, and why this paper was published in Nature Structural and Molecular Biology rather than another journal, they used a technique called X-ray Crystallography to “see” if (and how) Alda-1 interacts with ALDH2. Some of the results of these experiments are shown above. On the left, Panel B (on top) shows a 3D structure of the “defective’ version of ALDH2. If you’re new to structural biology papers, this will take some time getting used to it, but if you look carefully, you can see that ALDH2 is a tetramer: there are 4 identical pieces (in the top-left, top-right, bottom-left, bottom-right) which are attached together in the middle.

It’s not clear from this picture, but the defective version of the enzyme differs from the normal because it is unable to maintain the 3D structure needed to link up with a coenzyme (a chemical needed by enzymes which do this sort of chemical reaction to be able to work properly) called NAD+ or even carry out the reaction (the “active site”, or the part of the enzyme which actually carries out the reaction, is “disrupted” in the mutant).

So what does Alda-1 do, then? In the bottom (Panel C), you can see where the Alda-1 molecules (colored in yellow) are when they interact with ALDH2.  While the yellow molecules have a number of impacts on ALHD2’s 3D structure, the most obvious changes are highlighted in pink (those have no clear counterpart in Panel B). This is the secret of Alda-1: it actually changes the shape of ALDH2, (partially) restoring the enzyme’s ability to bind with NAD+ and carry out the chemical reactions needed to process acetaldehyde, and all without actually directly touching the active site (this is something which you can’t see in the panel I shared above, but you can make out from other X-ray crystallography models in the paper).

The result? If you look at the chart below (Panel A), you’ll see two relationships at play. First, the greater the amount of co-enzyme NAD+ (on the horizontal axis), the faster the reaction speed (on the vertical axis). But, if you increase the amount of Alda-1 from 0 uM (the bottom-most curve) to 30 uM (the highest-most curve), you see a dramatic increase in the enzyme’s reaction speed, for the same amount of NAD+. So, does Alda-1 activate ALDH2? Judging from this chart, it definitely does.

Source: Figure 4, Perez-Miller et al

Alda-1 is particularly interesting because most of the chemicals/drugs which we are able to develop work by breaking, de-activating, or inhibiting something. Have a cold? Break the chemical pathways which lead to runny noses. Suffering from depression? De-activate the process which cleans up serotonin (“happiness” chemicals in the brain) quickly. After all, its much easier to break something than it is to fix/create something. But, instead, Alda-1 is actually an activator (rather than a de-activator), which the authors of the study leave as a tantalizing opportunity for medical science:

This work suggests that it may be possible to rationally design similar molecular chaperones for other mutant enzymes by exploiting the binding of compounds to sites adjacent to the structurally disrupted regions, thus avoiding the possibility of enzymatic inhibition entirely independent of the conditions in which the enzyme operates.

If only it were that easy (it’s not)…

Where should we go from here? Frankly, while the paper tackled a very interesting topic in a pretty rigorous fashion, I felt that a lot of the conclusions being drawn were not clear from the presented experimental results (which is why this post is a bit on the vague side on some of those details).

I certainly understand the difficulty when the study is on phenomena which is molecular in nature (does the enzyme work? are the amino acids in the right location?). But, I personally felt a significant part of the paper was more conjecture than evidence, and while I’m sure the folks making the hypotheses are very experienced, I would like to see more experimental data to back up their theories. A well-designed set of site-directed mutagenesis (mutating specific parts of ALDH2 in the lab to play around with they hypotheses that the group put out) and well-tailored experiments and rounds of X-ray crystallography could help shed a little more light on their fascinating idea.

Paper: Perez-Miller et al. “Alda-1 is an agonist and chemical chaperone for the common human aldehyde dehydrogenase 2 variant.” Nature Structural and Molecular Biology 17:2 (Feb 2010) –doi:10.1038/nsmb.1737

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I Know Enough to Get Myself in Trouble

One of the dangers of a consultant looking at tech is that he can get lost in jargon. A few weeks ago, I did a little research on some of the most cutting-edge software startups in the cloud computing space (the idea that you can use a computer feature/service without actually knowing anything about what sort of technology infrastructure was used to provide you with that feature/service – i.e., Gmail and Yahoo Mail on the consumer side, services like Amazon Web Services and Microsoft Azure on the business side). As a result, I’ve looked at the product offerings from guys like NimbulaClouderaClustrixAppistryElastra, and MaxiScale, to name a few. And, while I know enough about cloud computing to understand, at a high level, what these companies do, the use of unclear terminology sometimes makes it very difficult to pierce the “fog of marketing” and really get a good understanding of the various product strengths and weaknesses.

Is it any wonder that, at times, I feel like this:

Source: Dilbert

Yes, its all about that “integration layer” … My take? A great product should not need to hide behind jargon.

Diet Coke + Mentos = Paper

Unless you just discovered YouTube yesterday, you’ve probably seen countless videos of (and maybe even have tried?) the infamous Diet Coke + Mentos reaction… which brings us to the subject of this month’s paper.

An enterprising physics professor from Appalachian State University decided to have her sophomore physics class take a fairly rigorous look at what drives the Diet Coke + Mentos reaction and what factors might influence its strength and speed. They were not only able to publish their results in the American Journal of Physics, but the students were also given an opportunity to present their findings in a poster session (Professor Coffey reflected on the experience in a presentation she gave). In my humble opinion, this is science education at its finest: instead of having students re-hash boring experiments which they already know the results of, this allowed them to do fairly original research in a field which they probably had more interest in than in the typical science lab course.

So, what did they find?

The first thing they found is that it’s not an acid-base reaction. A lot of people, myself included, believe the diet coke + Mentos reaction is the same as the baking soda + vinegar “volcano” reactions that we all did as kids. Apparently, we were dead wrong, as the paper points out:

The pH of the diet Coke prior to the reaction was 3.0, and the pH of the diet Coke after the mint Mentos reaction was also 3.0. The lack of change in the pH supports the conclusion that the Mint Mentos–Diet Coke reaction is not an acid-base reaction. This conclusion is also supported by the ingredients in the Mentos, none of which are basic: sugar, glucose, syrup, hydrogenated coconut oil, gelatin, dextrin, natural flavor, corn starch, and gum arabic … An impressive acid-base reaction can be generated by adding baking soda to Diet Coke. The pH of the Diet Coke after the baking soda reaction was 6.1, indicating that much of the acid present in the Diet Coke was neutralized by the reaction.

Secondly, the “reaction” is not chemical (no new compounds are created), but a physical response because the Mentos makes bubbles easier to form. The Mentos triggers bubble formation because the surface of the Mentos is itself extremely rough which allows bubbles to aggregate (like how adding string/popsicle stick to an oversaturated mixture of sugar and water is used to make rock candy). But that doesn’t explain why the Mentos + Diet Coke reaction works so well. The logic blew my mind but, in retrospect, is pretty simple. Certain liquids are more “bubbly” by nature – think soapy water vs. regular water. Why? Because the energy that’s needed to form a bubble is lower than the energy available from the environment (e.g., thermal energy). So, the question is, what makes a liquid more “bubbly”? One way is to heat the liquid (heating up Coke makes it more bubbly because heating the carbon dioxide inside the soda gives the gas more thermal energy to draw upon), which the students were able to confirm when they looked at how much mass was lost during a Mentos + Diet coke reaction under three different temperatures (Table 3 below):

What else? It turns out that what other chemicals a liquid has dissolved is capable of changing the ease at which bubbles are made. Physicists/chemists will recognize this “ease” as surface tension (how tightly the surface of a liquid pulls on itself) which you can see visually as a change in the contact angle (the angle that the bubble forms against a flat surface, see below):

The larger the angle, the stronger the surface tension (the more tightly the liquid tries to pull in on itself to become a sphere). So, what happens when we add the artificial sweetener aspartame and potassium benzoate (both ingredients in Diet Coke) to water? As you can see in Figure 4 below, the contact angle in (b) [aspartame] and (c) [potassium benzoate] are smaller than (a) [pure water]. Translation: if you add aspartame and/or potassium benzoate to water, you reduce the amount of work that needs to be done by the solution to create a bubble. Table 4 below that shows the contact angles of a variety of solutions that the students tested as well as the amount of work needed to create a bubble relative to pure water:

Source: Figure 4, Coffey, American Journal of Physics

This table also shows why you use Diet Coke rather than regular Coke (basically sugar-water) to do the Mentos thing – regular coke has a higher contact angle (and ~20% more energy needed to make a bubble).

Another factor which the paper considers is how long it takes the dropped Mentos to sink to the bottom. The faster a Mentos falls to the bottom, the longer the “average distance” that a bubble needs to travel to get to the surface. As bubbles themselves attract more bubbles, this means that the Mentos which fall to the bottom the fastest will have the strongest explosions. As the paper points out:

The speed with which the sample falls through the liquid is also a major factor. We used a video camera to measure the time it took for Mentos, rock salt, Wint-o-Green Lifesavers, and playground sand to fall through water from the top of the water line to the bottom of a clear 2 l bottle. The average times were 0.7 s for the Mentos, 1.0 s for the rock salt and the Lifesavers, and 1.5 s for the sand … If the growth of carbon  dioxide bubbles on the sample takes place at the bottom of the bottle, then the bubbles formed will detach from the sample and rise up the bottle. The bubbles then act as growth sites, where the carbon dioxide still dissolved in the solution moves into the rising bubbles, causing even more liberation of carbon dioxide from the bottle. If the bubbles must travel farther through the liquid, the reaction will be more explosive.

So, in conclusion, what makes a Diet Coke + Mentos reaction stronger?

  • Temperature (hotter = stronger)
  • Adding substances which reduce the surface tension/contact angle
  • Increasing the speed at which the Mentos sink to the bottom (faster = stronger)

I wish I had done something like this when I was in college! The paper itself also goes into a lot of other things, like the use of an atomic force microscope and scanning electron microscopes to measure the “roughness” of the surface of the Mentos, so if you’re interested in additional things which can affect the strength of the reaction (or if you’re a science teacher interested in coming up with a cool project for your students), I’d strongly encourage taking a look at the paper!

Paper: Coffey, T. “Diet Coke and Mentos: What is really behind this physical reaction?”. American Journal of Physics 76:6 (Jun 2008) – doi: 10.1119/1.2888546

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United States of Amoeba

Most people know that viruses are notoriously tricky disease-causing pathogens to tackle. Unlike bacteria which are completely separate organisms, viruses are parasites which use a host cell’s own DNA-and-RNA-and-protein producing mechanisms to reproduce. As a result, most viruses are extremely small, as they need to find a way into a cell to hijack the cell’s  machinery, and, in fact, are oftentimes too small for light microscopes to see as beams of light have wavelengths that are too large to resolve them.

However, just because most viruses are small, doesn’t mean all viruses are. In fact, giant MimivirusesMamaviruses, and Marseillesviruses have been found which are larger than many bacteria. The Mimivirus (pictured below), for instance, was so large it was actually identified incorrectly as a bacteria at first glance!

Source: Wikipedia

Little concrete detail is known about these giant viruses, and there has been some debate about whether or not these viruses constitute a new “kingdom” of life (the way that bacteria and archaebacteria are), but one thing these megaviruses have in common is that they are all found within amoeba!

This month’s paper (HT: Anthony) looks into the genome of the Marseillesvirus to try to get a better understanding of the genetic origins of these giant viruses. The left-hand-side panel of picture below is an electron micrograph of an amoeba phagocytosing Marseillesvirus (amoeba, in the search for food, will engulf almost anything smaller than they are) and the right-hand-side panel shows the virus creating viral factories (“VF”, the very dark dots) within the amoeba’s cytoplasm. If you were to zoom in even further, you’d be able to see viral particles in different stages of viral assembly!

Source: Figure 1, Boyer et al.

Ok, so we can see them. But just what makes them so big? What the heck is inside? Well, because you asked so nicely:

  • ~368000-base pairs of DNA
    • This constitutes an estimated 457 genes
    • This is much larger than the ~5000 base pair genome of SV40, a popular lab virus, the ~10000 base pairs in HIV, the ~49000 in lambda phage (another scientifically famous lab virus), but is comparable to the genome sizes of some of the smaller bacterium
    • This is smaller than the ~1 million-base pair genome of the Mimivirus, the ~4.6 million of E. coli and the ~3.2 billion in humans
  • 49 proteins were identified in the viral particles, including:
    • Structural proteins
    • Transcription factors (helps regulate gene activity)
    • Protein kinases (primarily found in eukaryotic cells because they play a major role in cellular signaling networks)
    • Glutaredoxins and thioredoxins (usually only found in plant and bacterial cells to help fight off chemical stressors)
    • Ubiquitin system proteins (primarily in eukaryotic cells as they control which proteins are sent to a cell’s “garbage collector”)
    • Histone-like proteins (primarily in eukaryotic cells to pack a cell’s DNA into the nucelus)

As you can see, there are a whole lot of proteins which you would only expect to see in a “full-fledged” cell, not a virus. This begs the question, why do these giant viruses have so many extra genes and proteins that you wouldn’t have expected?

To answer this, the researchers ran a genetic analysis on the Marseillesvirus’s DNA, trying to identify not only which proteins were encoded in the DNA but also where those protein-encoding genes seem to come from (by identifying which species has the most similar gene structure). A high-level overview of the results of the analysis is shown in the circular map below:

The outermost orange bands in the circle correspond to the proteins that were identified in the virus itself using mass spectrometry. The second row of red and blue bands represents protein-coding genes that are predicted to exist (but have yet to be detected in the virus; its possible they don’t make up the virus’s “body” and are only made while inside the amoeba, or even that they are not expressed at all). The gray ring with colored bands represents the researchers’ best guess as to what a predicted protein-coding gene codes for (based on seeing if the gene sequence is similar to other known proteins; the legend is below-right) whereas the colored bands just outside of the central pie chart represents a computer’s best determination of what species the gene seems to have come from (based on seeing if the gene sequence is similar to/the same as another species).

Of the 188 genes that a computational database identified as matching a previously characterized gene (~40% of all the predicted protein-coding genes), at least 108 come from sources outside of the giant viruses “evolutionary family”. The sources of these “misplaced” genes include bacteria, bacteria-infecting viruses called bacteriophages, amoeba, and even other eukaryotes! In other words, these giant viruses were genetic chimeras, mixed with DNA from all sorts of creatures in a way that you’d normally only expect in a genetically modified organism.

As many viruses are known to be able to “borrow” DNA from their hosts and from other viruses (a process called horizontal gene transfer), the researchers concluded that, like the immigrant’s conception of the United States of America, amoebas are giant genetic melting pots where genetic “immigrants” like bacteria and viruses comingle and share DNA (pictured below). In the case of the ancestors to the giant viruses, this resulted in viruses which kept gaining more and more genetic material from their amoeboid hosts and the abundance of bacterial and virus parasites living within.

Source: Figure 5, Boyer et al.

his finding is very interesting, as it suggests that amoeba may have played a crucial role in the early evolution of life. In the same way that a cultural “melting pot” like the US allows the combination of ideas from different cultures and walks of life, early amoeba “melting pots” may have helped kickstart evolutionary jumps by letting eukaryotes, bacteria, and viruses to co-exist and share DNA far more rapidly than “regular” natural selection could allow.

Of course, the flip side of this is that amoeba could also very well be allowing super-viruses and super-bacteria to breed…

Paper: Boyer, Mickael et al. “Giant Marseillevirus highlights the role of amoebae as a melting pot in emergence of chimeric microorganisms.” PNAS 106, 21848-21853 (22 Dec 2009) – doi:10.1073/pnas.0911354106

Check out my other academic paper walkthroughs/summaries

Collateral Damage by Mitochondria

This month, I read a paper (HT: my ex-college roommate Eric) by a group from Beth Israel about systemic inflammatory response syndrome (SIRS) following serious injury. SIRS, which is more commonly understood/found as sepsis, happens when the entire body is on high “immune alert.” In the case of sepsis, this is usually due to an infection of some sort. While an immune response may be needed to control an internal infection, SIRS is dangerous because the immune system can cause a great deal of collateral damage, resulting in potentially organ failure and death.

Whereas an infection has a clear link to sepsis, the logic for why injury would cause a similar immune response was less clear. In fact, for years, the best hypothesis from the medical community was that injury would somehow cause the bacteria which naturally live in your gut to appear where they’re not supposed to be. But this explanation was not especially convincing, especially in light of injuries like burns which could still lead to SIRS but which didn’t seem to directly affect gut bacteria.

Zhang et al, instead of assuming that some type of  endogenous bacteria was being released following injury, came up with an interesting hypothesis: it’s not bacteria which is triggering SIRS, but mitochondria. A first year cell biology student will be able to tell you that mitochondria are the parts of eukaryotic cells (sophisticated cells with nuclei) which are responsible for keeping the cell supplied with energy. A long-standing theory in the life science community (pictured above) is that mitochondria, billions of years ago, were originally bacteria which other, larger bacteria swallowed whole. Over countless rounds of evolution, these smaller bacteria became symbiotic with their “neighbor” and eventually adapted to servicing the larger cell’s energy needs. Despite this evolution, mitochondria have not lost all of their (theorized) bacterial ancestry, and in fact still retain bacteria-like DNA and structures. Zhang et al’s guess was that serious injuries could expose a mitochondria’s hidden bacterial nature to the immune system, and cause the body to trigger SIRS as a response.

Interesting idea, but how do you prove it? The researchers were able to show that 15 major trauma patients with no open wounds or injuries to the gut had thousands of times more mitochondrial DNA  in their bloodstream than non-trauma victims. The researchers were then able to show that this mitochondrial DNA was capable of activating polymorphonuclear neutrophils, some of the body’s key “soldier” cells responsible for causing SIRS.

Source: Figure 3, Zhang et al.

The figure above shows the result of an experiments illustrating this effect looking at the levels of a protein called p38 MAPK which gets chemically modified into “p-p38” when neutrophils are activated. As you can see in the p-p38 row, adding more mitochondrial DNA (mtDNA, “-” columns) to a sample of neutrophils increases levels of p-p38 (bigger, darker splotch), but adding special DNA which blocks the neutrophil’s mtDNA “detectors” (ODN, “+” columns) seems to lower it again. Comparing this with the control p38 row right underneath shows that the increase in p-p38 is likely due to neutrophil activation from the cells detecting mitochondrial DNA, and not just because the sample had more neutrophils/more p38 (as the splotches in the second row are all roughly the same).

Cool, but does this mean that mitochondrial DNA actually causes a strong immune response outside of a test tube environment? To test this, the researchers injected mitochondrial DNA into rats and ran a full set of screens on them. While the paper showed numerous charts pointing out how the injected rats had strong immune response across multiple organs, the most striking are the pictures below which show a cross-section of a rat’s lungs comparing rats injected with a buffer solution (panel a, “Sham”) and rats injected with mitochondrial DNA (panel b, MTD). The cross-sections are stained with hematoxylin and eosin which highlight the presence of cells. The darker and “thicker” color on the right shows that there are many more cells in the lungs of rats injected with mitochondrial DNA – most likely from neutrophils and other “soldier cells” which have rushed in looking for bacteria to fight.

Source: Figure 4, Zhang et al.

Amazing isn’t it? Not only did they provide part of the solution to the puzzle of injury-mediated SIRS (what they used to call “sterile SIRS”), but lent some support to the endosymbiont hypothesis!

Paper: Zhang, Qin et al. “Circulating Mitochondrial DAMPs Cause Inflammatory Responses to Injury.” Nature 464, 104-108 (4 March 2010) – doi:10.1038/nature08780

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Slime Takes a Stroll

The paper I read for this month brought up an interesting question I’ve always had but never really dug into: how do individual cells find things they can’t “see”? After all, there are lots of microbes out there who can’t always see where their next meal is coming from. How do they go about looking?

A group of scientists at Princeton University took a stab at the problem by studying the motion of individual slime mold amoeba (from the genus Dictyostelium) and published their findings in the (open access) journal PLoS ONE.

As one would imagine, if you have no idea where something is, your path to finding it will be somewhat random. What this paper sought to discover is what kind of random motion do amoeboid-like cells use? To those of you without the pleasure of training in biophysics or stochastic processes, that may sound like utter nonsense, but suffice to say physicists and mathematicians have created mathematically precise definitions for different kinds of “random motion”.

Now, if the idea of different kinds of randomness makes zero sense to you, then the following figure (from Figure 1 in the paper) might be able to help:

Source: Figure 1, Li et al.

anel A describes a “traditional” random walk, where each “step” that a random walker takes is completely random (unpredictable and independent of the motion before it). As you can see, the path doesn’t really cover a lot of ground. After all, if you were randomly moving in different directions, you’re just as likely to move to the left as you are to move to the right. The result of this chaos is that you’re likely not to move very far at all (but likely to search a small area very thoroughly). As a result, this sort of randomness is probably not very useful for an amoeba hunting for food, unless for some reason it is counting on food to magically rain down on its lazy butt.

Panel B and C describe two other kinds of randomness which are better suited to covering more ground. Although the motion described in panel B (the “Levy walk”) looks very different from the “random walk” in Panel A, it is actually very similar on a mathematical/physical level. In fact, the only difference between the “Levy walk” and the “random walk” is that, in a “normal” random walk, the size of each step is constant, whereas the size of each “step” in a “Levy walk” can be different and, sometimes, extremely long. This lets the path taken cover a whole lot more ground.

A different way of using randomness to cover a lot of ground is shown in Panel C where, instead of taking big steps, the random path actually takes on two different types of motion. In one mode, the steps are exactly like the random walk in Panel A, where the path doesn’t go very far, but “searches” a local area very thoroughly. In another mode, the path bolts in a straight line for a significant distance before settling back into a random walk. This alternation between the different modes defines the “two-state motion” and is another way for randomness to cover more ground than a random walk.

And what do amoeba use? Panel D gives a glimpse of it. Unlike the nice theoretical paths from Panels A-C rooted around random walks and different size steps or different modes of motion, the researchers found that slime mold amoeba like to zig-zag around a general direction which seems to change randomly over the course of ~10 min. Panel A of Figure 2 (shown below) gives a look at three such random paths taken over 10 hours.

Source: Figure 2, Li et al.

The reason for this zig-zagging, or at least the best hypothesis at the time of publication, is that, unlike theoretical particles, amoeba can’t just move in completely random directions with random “step” sizes. They move by “oozing” out pseudopods (picture below), and this physical reality of amoeba motion basically makes the type of motion the researchers discussed more likely and efficient for a cell trying to make its way through uncharted territory.

The majority of the paper actually covers a lot of the mathematical detail involved in understanding the precise nature of the randomness of amoeboid motion, and is, frankly, an overly-intimidating way to explain what I just described above. In all fairness, that extra detail is more useful and precise in terms of understanding how amoeba move and give a better sense of the underlying biochemistry and biophysics of why they move that way. But what I found most impressive was that the paper took a very basic and straightforward experiment (tracking the motion of single cells) and applied a rigorous mathematical and physical analysis of what they saw to understand the underlying properties.

The paper was from May 2008 and, according to the PLoS One website, there have been five papers which have cited it (which I have yet to read). But, I’d like to think that the next steps for the researchers involved would be to:

  1. See how much of this type of zig-zag motion applies to other cell types (i.e., white blood cells from our immune system), and why these differences might have emerged (different cell motion mechanisms? the need to have different types of random search strategies?)
  2. Better understand what controls how quickly these cells change direction (and understand if there are drugs that can be used to modulate how our white blood cells find/identify pathogens or how pathogens find food)

Paper: Li, Liang et al. “Persistent Cell Motion in the Absence of External Signals: a Search Strategy for Eukaryotic Cells.” PLoS ONE3 (5): e2093 (May 2008) – doi:10.1371/journal.pone.0002093

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Why Smartphones are a Big Deal

A cab driver the other day went off on me with a rant about how new smartphone users were all smug, arrogant gadget snobs for using phones that did more than just make phone calls. “Why you gotta need more than just the phone?”, he asked.

While he was probably right on the money with the “smug”, “arrogant”, and “snob” part of the description of smartphone users (at least it accurately describes yours truly), I do think he’s ignoring a lot of the important changes which the smartphone revolution has made in the technology industry and, consequently, why so many of the industry’s venture capitalists and technology companies are investing so heavily in this direction. This post will be the first of two posts looking at what I think are the four big impacts of smartphones like the Blackberry and the iPhone on the broader technology landscape:

  1. It’s the software, stupid
  2. Look ma, no <insert other device here>
  3. Putting the carriers in their place
  4. Contextuality

I. It’s the software, stupid!

You can find possibly the greatest impact of the smartphone revolution in the very definition of smartphone: phones which can run rich operating systems and actual applications. As my belligerent cab-driver pointed out, the cellular phone revolution was originally about being able to talk to other people on the go. People bought phones based on network coverage, call quality, the weight of a phone, and other concerns primarily motivated by call usability.

Smartphones, however, change that. Instead of just making phone calls, they also do plenty of other things. While a lot of consumers focus their attention on how their phones now have touchscreens, built-in cameras, GPS, and motion-sensors, the magic change that I see is the ability to actually run programs.

Why do I say this software thing more significant than the other features which have made their ways on to the phone? There are a number of reasons for this, but the big idea is that the ability to run software makes smartphones look like mobile computers. We have seen this pan out in a number of ways:

  • The potential uses for a mobile phone have exploded overnight. Whereas previously, they were pretty much limited to making phone calls, sending text messages/emails, playing music, and taking pictures, now they can be used to do things like play games, look up information, and even be used by doctors to help treat and diagnose patients. In the same way that a computer’s usefulness extends beyond what a manufacturer like Dell or HP or Apple have built into the hardware because of software, software opens up new possibilities for mobile phones in ways which we are only beginning to see.
  • Phones can now be “updated”. Before, phones were simply replaced when they became outdated. Now, some users expect that a phone that they buy will be maintained even after new models are released. Case in point: Users threw a fit when Samsung decided not to allow users to update their Samsung Galaxy’s operating system to a new version of the Android operating system. Can you imagine 10 years ago users getting up in arms if Samsung didn’t ship a new 2 MP mini-camera to anyone who owned an earlier version of the phone which only had a 1 MP camera?
  • An entire new software industry has emerged with its own standards and idiosyncrasies. About four decades ago, the rise of the computer created a brand new industry almost out of thin air. After all, think of all the wealth and enabled productivity that companies like Oracle, Microsoft, and Adobe have created over the past thirty years. There are early signs that a similar revolution is happening because of the rise of the smartphone. Entire fortunes have been created “out of thin air” as enterprising individuals and companies move to capture the potential software profits from creating software for the legions of iPhones and Android phones out there. What remains to be seen is whether or not the mobile software industry will end up looking more like the PC software industry, or whether or not the new operating systems and screen sizes and technologies will create something that looks more like a distant cousin of the first software revolution.

II. Look ma, no <insert other device here>

One of the most amazing consequences of Moore’s Law is that devices can quickly take on a heckuva lot more functionality then they used to. The smartphone is a perfect example of this Swiss-army knife mentality. The typical high-end smartphone today can:

  • take pictures
  • use GPS
  • play movies
  • play songs
  • read articles/books
  • find what direction its being pointed in
  • sense motion
  • record sounds
  • run software

… not to mention receive and make phone calls and texts like a phone.

But, unlike cameras, GPS devices, portable media players, eReaders, compasses, Wii-motes, tape recorders, and computers, the phone is something you are likely to keep with you all day long. And, if you have a smartphone which can double as a camera, GPS, portable media player, eReaders, compass, Wii-mote, tape recorder, and computer all at once – tell me why you’re going to hold on to those other devices?

That is, of course, a dramatic oversimplification. After all, I have yet to see a phone which can match a dedicated camera’s image quality or a computer’s speed, screen size, and range of software, so there are definitely reasons you’d pick one of these devices over a smartphone. The point, however, isn’t that smartphones will make these other devices irrelevant, it is that they will disrupt these markets in exactly the way that Clayton Christensen described in his book The Innovator’s Dilemma, making business a whole lot harder for companies who are heavily invested in these other device categories. And make no mistake: we’re already seeing this happen as GPS companies are seeing lower prices and demand as smartphones take on more and more sophisticated functionality (heck, GPS makers like Garmin are even trying to get into the mobile phone business!). I wouldn’t be surprised if we soon see similar declines in the market growth rates and profitability for all sorts of other devices.

III. Putting the carriers in their place

Throughout most of the history of the phone industry, the carriers were the dominant power. Sure, enormous phone companies like Nokia, Samsung, and Motorola had some clout, but at the end of the day, especially in the US, everybody felt the crushing influence of the major wireless carriers.

In the US, the carriers regulated access to phones with subsidies. They controlled which functions were allowed. They controlled how many texts and phone calls you were able to make. When they did let you access the internet, they exerted strong influence on which websites you had access to and which ringtones/wallpapers/music you could download. In short, they managed the business to minimize costs and risks, and they did it because their government-granted monopolies (over the right to use wireless spectrum) and already-built networks made it impossible  for a new guy to enter the market.

But this sorry state of affairs has already started to change with the advent of the smartphone. RIM’s Blackberry had started to affect the balance of power, but Apple’s iPhone really shook things up – precisely because users started demanding more than just a wireless service plan – they wanted a particular operating system with a particular internet experience and a particular set of applications – and, oh, it’s on AT&T? That’s not important, tell me more about the Apple part of it!

What’s more, the iPhone’s commercial success accelerated the change in consumer appetites. Smartphone users were now picking a wireless service provider not because of coverage or the cost of service or the special carrier-branded applications  – that was all now secondary to the availability of the phone they wanted and what sort of applications and internet experience they could get over that phone. And much to the carriers’ dismay, the wireless carrier was becoming less like the gatekeeper who got to charge crazy prices because he/she controlled the keys to the walled garden and more like the dumb pipe that people connected to the web on their iPhone with.

Now, it would be an exaggeration to say that the carriers will necessarily turn into the “dumb pipes” that today’s internet service providers are (remember when everyone in the US used AOL?) as these large carriers are still largely immune to competitors. But, there are signs that the carriers are adapting to their new role. The once ultra-closed Verizon now allows Palm WebOS and Google Android devices to roam free on its network as a consequence of AT&T and T-Mobile offering devices from Apple and Google’s partners, respectively, and has even agreed to allow VOIP applications like Skype access to its network, something which jeopardizes their former core voice revenue stream.

As for the carriers, as they begin to see their influence slip over basic phone experience considerations, they will likely shift their focus to finding ways to better monetize all the traffic that is pouring through their networks. Whether this means finding a way to get a cut of the ad/virtual good/eCommerce revenue that’s flowing through or shifting how they charge for network access away from unlimited/“all you can eat” plans is unclear, but it will be interesting to see how this ecosystem evolves.

IV. Contextuality

There is no better price than the amazingly low price of free. And, in my humble opinion, it is that amazingly low price of free which has enabled web services to have such a high rate of adoption. Ask yourself, would services like Facebook and Google have grown nearly as fast without being free to use?

How does one provide compelling value to users for free? Before the age of the internet, the answer to that age-old question was simple: you either got a nice government subsidy, or you just didn’t. Thankfully, the advent of the internet allowed for an entirely new business model: providing services for free and still making a decent profit by using ads. While over-hyping of this business model led to the dot com crash in 2001 as countless websites found it pretty difficult to monetize their sites purely with ads, services like Google survived because they found that they could actually increase the value of the advertising on their pages not only because they had a ton of traffic, but because they could use the content on the page to find ads which visitors had a significantly higher probability of caring about.

The idea that context could be used to increase ad conversion rates (the percent of people who see an ad and actually end up buying) has spawned a whole new world of web startups and technologies which aim to find new ways to mine context to provide better ad targeting. Facebook is one such example of the use of social context (who your friends are, what your interests are, what your friends’ interests are) to serve more targeted ads.

So, where do smartphones fit in? There are two ways in which smartphones completely change the context-to-advertising dynamic:

  • Location-based services: Your phone is a device which not only has a processor which can run software, but is also likely to have GPS built-in, and is something which you carry on your person at all hours of the day. What this means is that the phone not only know what apps/websites you’re using, it also knows where you are and if you’re on a vehicle (based on how fast you are moving) when you’re using them. If that doesn’t let a merchant figure out a way to send you a very relevant ad, I don’t know what will. The Yowza iPhone application is an example of how this might shape out in the future, where you can search for mobile coupons for local stores all on your phone.
  • Augmented reality: In the same way that the GPS lets mobile applications do location-based services, the camera, compass, and GPS in a mobile phone lets mobile applications do something called augmented reality. The concept behind augmented reality (AR) is that, in the real world, you and I are only limited by what our five senses can perceive. If I see an ad for a book, I can only perceive what is on the advertisement. I don’t necessarily know much about how much it costs on Amazon.com or what my friends on Facebook have said about it. Of course, with a mobile phone, I could look up those things on the internet, but AR takes this a step further. Instead of merely looking something up on the internet, AR will actually overlay content and information on top of what you are seeing on your phone screen. One example of this is the ShopSavvy application for Android which allows you to scan product barcodes to find product review information and even information on pricing from online and other local stores! Google has taken this a step further with Google Goggles which can recognize pictures of landmarks, books, and even bottles of wine! For an advertiser or a store, the ability to embed additional content through AR technology is the ultimate in providing context but only to those people who want it. Forget finding the right balance between putting too much or too little information on an ad, use AR so that only the people who are interested will get the extra information.

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How to Properly Define a Company’s Culture

Company culture is a concept which, while incredibly difficult to explain or measure, is very important to a company’s well-being and employee morale. Too often, it comes in the form of vaguely written out “corporate mission statements” or never-ending lists of feel-good, mean-nothing “company values”. Oh joy, you value “teamwork” and “making money” – that was so insightful…

It was thus very refreshing for me to read the Netflix company culture document (sadly no longer embed-able, but you can find it at this Slideshare link).

Slidumentation aside, I think the NetFlix presentation does three things extremely well:

  1. It’s not a list of feel-good words, but  actual values and statements which can actually guide the company in its day-to-day hiring, evaluation. Most company culture statements are nothing but long lists of virtues and things non-sociopaths respect. “Teamwork” and “honesty”, for example, are usually among them. But, as the Netflix presentation points out, even Enron had a list of “values” and that wound up not amounting to much of anything. Instead, Netflix has a clear state of  things they look for in their employees, each with clear explanations for what they actually mean. For “Curiosity”, Netflix has listed four supporting statements:
    • You learn rapidly and eagerly
    • You seek to understand our strategy, markets, subscribers, and suppliers.
    • You are broadly knowledgeable about business, technology, and entertainment.
    • You contribute effectively outside of your specialty
    Admittedly, there is nothing particularly remarkable about these four statements. But what is remarkable is that it is immediately clear to the reader what “curiosity” means, in the context of Netflix’s culture, and how Netflix employees should be judged and evaluated. It’s oftentimes astounding to me how few companies get to this bare minimum in terms of culture documents.
  2. Netflix actually gives clear value judgments.  I’ve already lamented the extent to which company culture statements are nothing more than laundry lists of “feel good” words. Netflix admirably cuts through that by not only explaining what the values mean, but also by what should happen when different “good words” conflict. And, best of all, they do it with brutal honesty. For instance, Netflix on how they won’t play the “benefits race” that other companies play:
    A great work place is stunning colleagues. Great workplace is not day-care, espresso, health benefits, sushi lunches, nice offices, or big compensation, and we only do those that are efficient at attracting stunning colleagues.Netflix on teamwork versus individual performance:Brilliant jerks: some companies tolerate them, [but] for us, the cost to teamwork is too high.Netflix on its annual compensation review policy:Lots of people have the title “Major League Pitcher” but they are not all equally effective. Similarly, all people with the title “Senior Marketing Manager” and “Director of Engineering” are not equally effective … So, essentially, [we are] rehiring each employee each year (and re-evaluating them based on their performance) for the purposes of compensation.Within each of the three examples, Netflix has done two amazing things: they’ve made a bold value judgment, which most companies fail to do, explaining just how the values should be lived, especially when they conflict (“we don’t care how smart you are, if you don’t work well with the team, you have to go”), and they’ve even given a reason(“teamwork is more important to delivering impact for our customers than one smart guy”).
  3. They explain what makes their culture different from other companies and why. Most people who like their jobs will give “culture” as a reason they think their company is unique. yet, if you read the countless mission statements and “our values” documents out there, you’d never be able to see that difference. Granted, the main issue may just be that management has chosen not to live up to the lofty ideals espoused in their list of virtues, but what might help with that and make it clearer to employees about what makes a particular workplace special is explaining how and why the company’s culture is different from another’s. Contrast that with the Netflix presentation, which spends many slides explaining the tradeoffs between too many rules and too few, and why they ultimately sided with having very few rules, whereas a manufacturing company or a medical company would have very many of them. They never go so far as to say that one is better than the other, only that they are different because they are in different industries with different needs and dynamics. And, as a result of that, they have implemented changes, like a simpler expense policy (“Act in Netflix’s best interests”) and a revolutionary vacation policy (“There is no policy or tracking”) [with an awesome explanation: “There is also no clothing policy at Netflix, but no one has come to work naked lately”].

Pay attention, other companies. You would do well to learn from Netflix’s example.

What is with Microsoft’s consumer electronics strategy?

Genius? Source: Softpedia

Regardless of how you feel about Microsoft’s products, you have to appreciate the brilliance of their strategic “playbook”:

  1. Use the fact that Microsoft’s operating system/productivity software is used by almost everyone to identify key customer/partner needs
  2. Build a product which is usually only a second/third-best follower product but make sure it’s tied back to Microsoft’s products
  3. Take advantage of the time and market share that Microsoft’s channel influence, developer community, and product integration buys to invest in the new product with Microsoft’s massive budget until it achieves leadership
  4. If steps 1-3 fail to give Microsoft a dominant position, either exit (because the market is no longer important) or buy out a competitor
  5. Repeat

While the quality of Microsoft’s execution of each step can be called into question, I’d be hard pressed to find a better approach then this one, and I’m sure much of their success can be attributed to finding good ways to repeatedly follow this formula.

It’s for that reason that I’m completely  bewildered by Microsoft’s consumer electronics business strategy. Instead of finding good ways to integrate the Zune, XBox, and Windows Mobile franchises together or with the Microsoft operating system “mothership” the way Microsoft did by integrating its enterprise software with Office or Internet Explorer with Windows, these three businesses largely stand apart from Microsoft’s home field (PC software) and even from each other.

This is problematic for two big reasons. First, because non-PC devices are outside of Microsoft’s usual playground, it’s not a surprise that Microsoft finds it difficult to expand into new territory. For Microsoft to succeed here, it needs to pull out all the stops and it’s shocking to me that a company with a stake in the ground in four key device areas (PCs, mobile phones, game consoles, and portable media players) would choose not to use one of the few advantages it has over its competitors.

The second and most obvious (to consumers at least) is that Apple has not made this mistake. Apple’s iPhone and iPod Touch product lines are clear evolutions of their popular iPod MP3 players which integrate well with Apple’s iTunes computer software and iTunes online store. The entire Apple line-up, although each product is a unique entity, has a similar look and feel. The Safari browser that powers the Apple computer internet experience is, basically, the same that powers the iPhone and iPod Touch. Similarly, the same online store and software (iTunes) which lets iPods load themselves with music lets iPod Touches/iPhones load themselves with applications.

That neat little integrated package not only makes it easier for Apple consumers to use a product, but the coherent experience across the different devices gives customers even more of a reason to use and/or buy other Apple products.

Contrast that approach with Microsoft’s. Not only are the user interfaces and product designs for the Zune, XBox, and Windows Mobile completely different from one another, they don’t play well together at all. Applications that run on one device (be it the Zune HD, on a Windows PC, on an XBox, or on Windows Mobile) are unlikely to be able to run on any other. While one might be able to forgive this if it was just PC applications which had trouble being “ported” to Microsoft’s other devices (after all, apps that run on an Apple computer don’t work on the iPhone and vice versa), the devices that one would expect this to work well with (i.e. the Zune HD and the XBox because they’re both billed as gaming platforms, or the Zune HD and Windows Mobile because they’re both portable products) don’t. Their application development process doesn’t line up well. And, as far as I’m aware, the devices have completely separate application and content stores!

While recreating the Windows PC experience on three other devices is definitely overkill, I think, were I in Ballmer’s shoes, I would recommend a few simple recommendations which I think would dramatically benefit all of Microsoft’s product lines (and I promise they aren’t the standard Apple/Linux fanboy’s “build something prettier” or “go open source”):

  1. Centralize all application/content “marketplaces” – Apple is no internet genius. Yet, they figured out how to do this. I fail to see why Microsoft can’t do the same.
  2. Invest in building a common application runtime across all the devices – Nobody’s expecting a low-end Windows Mobile phone or a Zune HD to run Microsoft Excel, but to expect that little widgets or games should be able to work across all of Microsoft’s devices is not unreasonable, and would go a long way towards encouraging developers to develop for Microsoft’s new device platforms (if a program can run on just the Zune HD, there’s only so much revenue that a developer can take in, but if it can also run on the XBox and all Windows Mobile phones, then the revenue potential becomes much greater) and towards encouraging consumers to buy more Microsoft gear
  3. Find better ways to link Windows to each device – This can be as simple as building something like iTunes to simplify device management and content streaming, but I have yet to meet anyone with a Microsoft device who hasn’t complained about how poorly the devices work with PCs.

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