Will bacteria become the next thumb drives?

by Reed Stubbendieck (@bactereedia)

The text from the Dispilio tablet [Source]
In 1994, a wooden tablet was unearthed from the swamps near Dispilio, a neolithic settlement in modern-day Greece. The Dispilio tablet was carbon-dated to ~5200 BC and is considered to be among the world’s oldest examples of recorded information, having lasted for >7000 years (see image above). For comparison, without intervention the lifespan of most modern digital storage media ranges from 5 to 20 years (side note: have you backed up your data recently?). However, while the longevity of the Dispilio tablet is impressive, living cells have been storing information in DNA for 3.8 billion years. In my previous post, I discussed the potential for cells to store large amounts of information. Today, I want to cover some recent examples of how scientists and engineers are tapping into this immense storage potential.

My favorite example of using cells to store information comes from a paper published last year (2017) in Nature. In this paper, the authors used CRISPR-Cas technology to introduce DNA into cells and store images. Recently, CRISPR-Cas technology has gained fame for its applications in genome engineering, including a dubiously alleged ability to hide genetically modified criminals from law enforcement. However, in its natural context, the CRISPR-Cas system functions as an adaptive immune system for archaea and bacteria. It’s this feature that the authors co-opted for information storage, which I will discuss below.

Though we often think of viruses as disease-causing agents of humans and other Eukaryotes, bacteria suffer from a far greater number of viral infections. In fact, viruses of bacteria, also known as bacteriophages (or simply phages), are the most abundant biological entities on Earth. Estimates place the global number of phages at 1030, which collectively cause 1023 infections of bacteria each second. For comparison, Avogadro’s number is 6.022×1023, meaning that there nearly one mole of phage infections globally per six seconds (or one round of combat in D&D)!

Bacteria are not powerless to stop phage infections. One mechanism that bacteria use to prevent infections is the CRISPR-Cas system. Though the specific molecular details are beyond the scope of this article (see here, if interested), I would like to take a brief moment to explain how the CRISPR-Cas system functions in bacterial cells. During infection, a bacterial cell may capture small pieces of the phage genome and insert them into a region of the chromosome called the CRISPR array. Subsequently, if the bacterium survives, it uses these captured DNA sequences to generate an immune response against future infections from the same phage. Importantly, the cell inserts new DNA sequences into the CRISPR array in a predetermined position. Thus, the CRISPR array stores a history of infection in linear order, which is passed to both daughter cells when the bacterium divides.

By taking advantage of the ability of the CRISPR array to store new DNA sequences, one research group stored the information to reconstruct images inside of Escherichia coli cells. Instead of infecting E. coli cells with phages, the researchers generated large numbers of synthetic DNAs called oligonucleotide protospacers and tricked the cells into incorporating the custom DNAs into the CRISPR arrays. At the beginning of each of the protospacers was a 4 base pair sequence the authors called a “pixet”. The pixet defined the set of pixels described by the following 28 base pairs of the protospacer, where each of the nucleotides (A, T, G, and C) corresponded to a different shade of gray. By introducing 112 protospacers into the population of E. coli cells, the authors were able to store a 56 × 56 pixel 784 byte grayscale image of a human hand in the bacteria. To access the data, the researchers used high throughput DNA sequencing technology and determined the DNA sequences of many different CRISPR arrays from the population of bacteria. By using a custom algorithm, the researchers were able to decode the information from the CRISPR arrays and they digitally reassembled the original image (see image below).

Retrieval of an image of a hand stored in bacterial DNA [Source]
This research group was not satisfied by encoding a single image. Instead, they wanted to store a movie. Specifically, the researchers encoded five frames of Plate 626 from Animal locomotion. An electro-photographic investigation of consecutive phases of animal movements by Eadweard Muybridge from between 1872-1875. To store this animation, the researchers split each frame into protospacer sequences as above, but instead of introducing all of the information at once, the DNA encoding each individual movie frame was successively introduced into the population of E. coli cells. Recall that the CRISPR array stores a history of infection in linear order. Using this approach, each cell stored a piece of each of the five frames. By sequencing the entire CRISPR array from the population of bacteria and splitting the spacer sequences by order of appearance, the authors were able to reconstruct each frame from the movie (see .gif below).

Movie of a galloping horse stored in bacterial DNA [Source].
One caveat of the above examples is that the images decoded from the E. coli genomes were not perfect reproductions, which is evident from several spurious pixels in the reconstructed movie. The authors found that the differences between the encoded and reproduced frames was most often due to changes in the protospacer sequence by DNA synthesis errors, DNA sequencing errors, or mutation. This latter finding highlights a limitation of storing information inside of cells. In the opening, I mentioned that cells have been using DNA to store information for 3.8 billion years. But, unlike the information encoded in the inscriptions on the Dispilio tablet, this information storage is imperfect. DNA mutates and cells evolve. This process is essential for continuing life but is inconvenient for perfect information archival.

Engineers at Microsoft have recently developed their own form of DNA storage technology. Instead of using cells, the engineers store information in isolated DNA molecules and, under special conditions, these molecules are predicted to last for >2000 years. Though etchings on preserved wood have still exceeded the current longevity estimations of DNA storage, I think we’ll find a more effective solution for perfect information archival before those DNA molecules degrade in the year 4000!

Fish Also Dig the Dad Bod

by Andrew Anderson (@AndersonEvolve)

Imagine you’re on a dating site looking for a potential partner.  You browse through a couple of individuals and find a few that merit a further look.  This particular site allows feedback from individuals who have contacted or dated a person to be viewed on that person’s page.  Would you read the comments? Would you weigh the comments in your decision to engage in further conversations/dates with the person?  If so, you have employed a mate choice strategy called mate copying.

Clunky hypotheticals aside (AOL Instant Messenger was the social media of choice when I last dated), mate copying has been observed in mammals (yes, possibly humans), birds, fishes, and even insects. Most often, these are confirmed by testing if a female’s interest in a male is altered if she observes him with another female.  Personally, I would love to see if this occurs in role-reversed systems, but the research that have studied this pattern generally find females to be the choosier sex. So why would a female rely on another female’s choice? There are some hypotheses that have been proposed, such as: searching for a mate is costly (i.e. lose energy/time or become a target to predators inspecting each potential mate), a female may not have enough experience to determine male quality, or distinguishing between quality males is  challenging. Females do not have to directly observe males being successful with other females; they can use other, more subtle signals to indicate the desirableness of a male. In rats, there is some evidence that the smell of a male who has recently copulated is a potential driver of female choice.

Mate copying is something that occurs across taxa; but, in my opinion, fishes have the most interesting behaviors associated with it.  As a reminder, the dads are more likely to take care of the young in fishes that engage in brood care. Even though dads care for the young,males are still more likely to engage in competition for mates rather than have females compete for them (although I study a few awesome exceptions).  One possible reason for this is that some species of males can tend nests larger than one female can fill with eggs. Some males will have eggs from many females and others have no eggs to care for (unequal mating success is an impetus for sexual selection). As you might be piecing together, females can use the amount of eggs already present in a male’s nest as an indicator of how “sexy” other females have found him.  In fact, in some species of fishes females prefer males who have eggs already in the nest. This has been tested in several species by adding or removing eggs from males’ nests and observing the resulting female choice.

Now the evolutionary mayhem begins.

Egg stealing males.  Left: Three-spined stickleback.  Right: River Bullhead. Bottom: Striped Darter

In three-spined sticklebacks, the males engage in a hurly-burly of activity centered around mating.  Before deciding to mate with a male the female will inspect the male’s nest, his bright colors, his swimming behaviors, and if his nest has eggs in it.  If she is satisfied he has met her criteria, she will lay eggs in his nest. While she’s doing so, other males will try to “sneak” a mating in by releasing sperm next to her.  Such sneak behavior is fairly common among fishes, but some males will also steal eggs from the nest and bring them back to their own. These eggs are not their own and therefore that male has no paternity, but he will care for them and raise them as if he did.  Since females use the presence of eggs in a nest to judge a potential mate’s quality, such behavior may end up actually increasing the total number of offspring they father.

Other species,such as the river bullhead, don’t even bother stealing eggs.  Males nest in close proximity to each other, and females choose which nest to lay eggs in –again with consideration for the presence/absence of eggs.  Instead of stealing a few eggs, males who haven’t mated will attempt to evict egged males from their nest and take over the entire clutch. The expectation, again, is that males who engage in that behavior might do better in overall reproduction than those that don’t, even though some of the eggs they invest in aren’t their own.

There is another example that is rather bizarre.  Darters are small fishes found in creeks that sometimes engage in egg-raiding.  One species, the striped darter, has evolved a unique coloration on its fins. This coloration creates a design that could be considered a facsimile of eggs.  During courtship, the male will display these markings, and there is a correlation between mating success and number of egg-spots on their fins. The hypothesis is that these “egg spots” stimulate the female the same way that seeing eggs might, making her more likely to mate.

As you can see, fish have a wide diversity of adaptations to one stimulus:  a preference for eggs in nest. It’s worth pointing out that the explanations of what’s been observed have varying degrees of confirmation through experimentation.  Here I have presented three species as examples; indeed, there are more species that have these behaviors and traits which lends credence to the explanations given here.  That is what’s so awesome about evolutionary biology: when something exists in nature that grabs your attention, you get to work to try to piece together what might have led to those traits.  

Arming Sharks with Lasers

by Scott Mattison (@FoolsPizza)

In the immortal words of Dr. Evil: “Every creature deserves a warm meal.” To meet this call to action, we have devised a method for efficiently providing sharks with laser beams. To accomplish this, we are going to have to design a high energy laser source that is capable of being submerged in water.

Rendering of proposed design (not to scale)

I will preface this blog post with the knowledge that someone has in fact put a laser onto a shark. As the laser used could not even blind a fish, much less cook one, I do not think it meets our demands.

Building a working laser isn’t that hard; however, designing a laser to attach to a shark has some special challenges. I am going to break down some of the design process over a few posts. Ignoring the ethics of the matter (it’s bad) or if we this is even a good thing for the sharks (it’s not), the first thing we need to do is decide what wavelength of light we want the laser to be.

For this decision, and many future ones, the most important variable that we face is that we will be working in the ocean. You may have noticed that the ocean is blue, at least in the deeper parts. Despite a somewhat odd popular opinion, the ocean is not blue because it is reflecting the sky. In fact the ocean and the sky are actually blue for completely different reasons. To understand this we will have to talk a bit about physics of how light interacts with the environment.

There are many ways light can interact with the world, but the two methods that primarily define how we observe the world are scattering and absorption. Scattering of light in the atmosphere due to small particles, known as Rayleigh scattering, preferentially scatters shorter wavelengths of light than longer wavelengths. Rayleigh scattering is what gives the sky its blue coloring. Readers who are familiar with wavelengths of visible light may be thinking that blue isn’t the shortest wavelength, and asking why isn’t the sky violet. This question is an answer for another time, but the short answer is: colors are crazy.

Unlike the sky, the ocean is blue because of absorption. Absorption occurs as an interaction between light and the electrons of molecules. If the energy level of photon of light is equivalent to the energy difference between two electron energy levels then the electrons may absorb that photon. Without delving too much into the quantum mechanics here, the electron configurations of water make it absorb light of longer wavelengths (more red) better than it absorbs light of shorter wavelengths (more blue).

Water does not absorb light so strongly that we see these effects on a small scale, hence a glass of clean water will appear clear instead of blue. However, over a distance of several meters this absorption starts to become very pronounced. When scuba diving, the deeper a diver goes into the water the less color they will be able to see. In fact, during deep water scuba certification you actually take a color chart down with you as you dive and get to observe the loss of color first hand.

Since absorption takes place over such a long distance, in smaller bodies of water and in bodies of water with a lot of sediment and debris, scattering begins to play a larger role in the appearance of the water. Scattering is why a lot of lakes and beaches will appear brown or green in color instead of blue as light is being scattered back from within the water before the absorption process can play a significant enough role to make water appear blue.

So, what does this all mean for our shark and its warm and tasty meal? Well for starters, this means that we will want to select our wavelength of light based on our desired operating distance. I am not a marine biologist; however, it may be reasonable to assume that we want our shark to be able to cook a warm meal from at least 100 feet away. Based on this distance and the absorption levels of light by water, we are going to want to match the wavelength of our light source to the absorption of the ocean and go for a light source that is shorter.

Absorbance of visible light by water. Horizontal axis is wavelength in nanometers and the vertical axis is absorbance in inverse meters. This figure is reproduced from Wikipedia all rights belong to the original authors.

Looking at the graph above, there is a minimum absorbance around 420 nm, but for reasons we will discuss in more detail in my next post, we want to select a wavelength of light that will penetrate more deeply into biological tissues. Despite biological tissues being mostly water, as a general rule, longer wavelengths penetrate more deeply than shorter wavelengths. This is why two-photon microscopy has taken on such a large role in biological imaging as it uses two photons of a longer wavelength to excite a fluorescent molecule in the same way as a single photon of half the wavelength would. This phenomenon allows researchers to probe fluorescent molecules much deeper in biological tissues. For our shark, this means we are going to need to strike a balance between long wavelengths of imaging depth and short wavelengths for effective range.

Assuming we want half of our light from our laser to hit our shark’s target at a range of 100 feet, we can use what is referred to as the Beer-Lambert law to calculate the maximum acceptable absorbance of water.

Beer Lambert 2

The equation above gives the simplified form of the Beer-Lambert law where we assume half of the initial photons hit their target. α in this case is the absorbance and Δx is the distance the light traveled through some absorbing medium (water).


Next, we can determine our Δx in meters from feet with a simple unit conversion. Also we can use two neat properties of the natural logarithm to simplify our equation and make it easily solvable. 

Finally we can solve our equation to determine the maximum value we can have for absorbance.

Our answer (0.0227 inverse meters) comes out to be very close to a wavelength of 500 nm (found using the graph above), meaning we will be arming our shark with a laser that would appear very teal-blue upon observation. Tune in to my next blog post for a rousing discussion of building an actual laser that will operate well underwater.

Don’t Forget About the Plants

by Ace Pugh (@acepugh_)

Hello, dear reader, and welcome to my own personal corner of this blog. By now, I imagine you’ve already read some of my friends’ blog posts and enjoyed them very much. However, I’m sure that you were probably also asking a very important question: where’s the plants? We get to see some cool fish-dad related things, some information storage in cells, even some frickin’ laser beams; however, plants also need to have their time in the sun, both literally and figuratively. I’m here to give them that spotlight. I’m here to speak for the plants (but not for the trees specifically).

Now, it’s important to note that I’m primarily a plant breeder, so I think a good place to start is to give a quick introduction to my discipline. As a plant breeder, I use principles from many different disciplines in order to improve the genetic potential of plants (Thanks, National Association of Plant Breeders, for that definition). To be more specific, I work to improve plants that are prized by humans for their food, fiber, feed, fuel, etc. For example, nobody is going to spend time breeding poison ivy (or at least, nobody has yet) since it’s not of value to humans.  Thus, we focus our efforts on the crops that we care about such as corn, rice, apples, wheat, pecans, etc. By selecting the very best plant parents, we can attempt to produce progeny that are better (that produce more) than anything we had previously. We decide which material to advance based on a large set of factors including pest or disease resistance, drought tolerance, heat tolerance, yield, and many others.


Yours truly, measuring the height of some sorghum plants. Sorghum is a very important food crop in Africa and Asia. It is also the best crop species ever (citation needed).


Interestingly, plant breeding is a process that is as old as recorded history. While today’s plant breeders use more sophisticated techniques, the first plant breeders were actually early farmers. Whenever a person first decided to keep seeds from one plant over another, and get rid of material that wasn’t as desirable, plant breeding was created as a practice. In fact, the crop species as we know them today are quite far removed from what they originally started as (take maize as an example, below). Centuries of selective breeding has created the crops that we now know and love.  It’s similar to how great movies are made; that is, multiple researchers with different perspectives are constantly working to improve these species, and only the very best material makes its fateful trip through the “editing room” that is the modern breeding program.


Modern maize or corn (bottom) pictured alongside teosinte (top) and a hybrid between the two (middle). Teosinte is a wild species of maize that serves as an example of what the crop was like prior to centuries of artificial selection by humans. Notice that the modern corn appears to have a much higher deliciousness quotient than the teosinte. (Photo by John Doebley https://teosinte.wisc.edu/images.html)


Although that all sounds reasonably simple, it’s probably also becoming obvious that there’s quite a bit more complexity to what plant breeder do. While the basics I just outlined are all true, I’d be remiss if I didn’t point out that modern breeding programs are quite a bit more involved. As breeders, we now must possess a working knowledge in many different disciplines including plant pathology, entomology, statistics, soil science, agronomy, computer science, remote sensing, economics, and countless others. Sure, we can and should collaborate with other researchers whose expertise is in those areas, but we still need to know enough to understand which questions need to be asked. This works out very well for yours truly since I have a notably short attention span, and I’ve gotten to dip my toes into many different fields of study during my time as a graduate student. My passion, my raison d’être in fact, is to integrate devices and techniques from other disciplines into a breeding program, and I’ve focused most of my time and energy in pursuit of that goal. To be sure, this is a very exciting time to be in plant breeding, with remote sensing becoming an increasingly popular avenue by which plant breeders can increase the efficiency of their programs. Anyways, let’s not get ahead of ourselves. I could go on about this for quite a while, so trust me when I say that you’ll get to hear quite a bit about remote sensing and high-throughput phenotyping from me in the months and years to come.

In summary, you can clearly see that plant breeding is a very broad discipline and encompasses many different others therein. You may also surmise that plants are the best thing ever, or that I’m very good at holding a measuring stick, or that popped teosinte would make a lousy snack food to eat while watching the latest Avengers movie (all three assumptions are likely correct). I’m honored that I am going to have a platform through which I can share some of my interests and comment on the latest research in my field. Together we’re going to have a lot of fun and, just maybe, learn something at the same time.