"MICRO"evolution not micro-evolution

Source: Paegel BM, Joyce GF (2008) Darwinian evolution on a chip. PLoS Biol 6(4): e85.

Directed evolution is a process based on darwinian principles which employs artificial selection to achieve optimality in an evolutionary system. This method is widely used both in experimental and industrial labs with the intention of optimizing a given property in a defined context (e.g. thermostability and specificity in case of enzymes). Despite its apparent power, directed evolution is not always tractable and it is usually labor-intensive. Here, the authors have employed a micro-fluidic chamber to construct an autonomous system capable of fast and efficient artificial evolution without any human supervision.

As schematically shown in the figure below, the authors aim to optimize an RNA enzyme capable attaching itself to the 3' end of any DNA fragment. To this end, they make DNA fragments with pre-designed T7 promoters; following incubation with reverse transcriptase and T7 polymerase enzymes the RNAs that have successfully attached themselves to the fragment can be amplified.
This set-up is not new, the novelty of this paper is in how they have implemented it. They have constructed a microfluidic chamber with computer-controlled valves that through automated monitoring can indefinitely repeat the above process. As shown in the figure taken from the original paper, this involves three steps: (1) mixing period for the reaction to happen (C); (2) isolation step in which a small volume of the sample is retained while the rest is washed away (B) and (3) incubation phase where the RT and T7pol are added to amplify RNA and restart the mixing period (A).
While mostly engineering in nature, this study reveals how these systems invented for other purposes can be employed to increase speed and accuracy in biological set-ups.

Re-wiring the transcription networks

Source: Isalan et al (2008). Evolvability and hierarchy in rewired bacterial gene networks. Nature 452:846.

The evolution and adaptation of the living organisms is attributed, in part, to the duplication and divergence of genetic modules. While the fitness effect of single-gene manipulations (either knock-out or over-expression) is studied in many bacterial systems, the effect of specific perturbations to the transcription regulatory network was not addressed before this study.

E. coli, the model organism of choice, has a well studied hierarchical transcription network in which a few master regulators (e.g. CRP, FNR, IHF, Fis...) affect half of the genome (including other transcription factors) either directly or indirectly. The authors set out to randomly modify this network through introducing new regulatory nodes. For example, in the figure below (taken from the original paper), they have artificially put CRP under the control of CsgD. GFP is used as a reporter to measure the expression level of each artificial operon.
Using the same set-up, they have constructed 598 such artificial operons with different transcription and sigma factors. Following the construction of this library, they show that these re-wired operons are generally tolerated and some of them actually do better than the wild-type network in certain conditions.

These observations suggest that the transcription network may be re-wired through evolution for higher adaptation without changes in the underlying genes. In other words, all the functions are already there in the cell, it's just the question of activation/deactivation at the right moment.

Although utterly simple in concept, this paper makes a very vivid point regarding the evolutionary strategies. For example, I'm trying to use this very concept to engineer an E. coli strain with a higher ethanol tolerance compared to wild-type.

On the emergence of punishment

source: Dreber et al (2008). Winners don't punish. nature 452:348-350.

Cooperation in a team ensures higher profit with lower risk in both ecological and sociological contexts. But how do we maintain cooperation? Through two basic concepts: reward and punishment. In biological terms reward is defined as a cost for the donor which translates into a profit for the receiver; however, in case of punishment, this manifests as a larger cost for the other end.

In a game theory set-up based on prisoner dilemma, the authors have tried to model punishment in a repeated setting. In this model, each individual can cooperate, defect or punish in every trial. The results from many rounds of pairwise competitions (i.e. between different behavioral strategies) show that high ranking individuals tend not to punish and individuals with costly punishment behaviors end up in the lowest ranks.

Based on these models, the authors have concluded that costly punishment is not adaptive in cooperation games and the fact that they exist suggests reasons beyond the promotion of cooperation.

"Information is not knowledge"

The title of this post is a quote from Albert Einstein and I truly believe in it based on years of both studying and teaching. However, creativity and innovation comes through knowledge... to know what others have done and to stand on the shoulder of the giants. So far, I have had the privilege and honor of working with truly gifted friends through the years (not that I am that old!), namely the members of Iranian National Biology Olympiad team (1998-2002); and I have learned one thing truly special: "with great knowledge comes great responsibility" (or was it power?!). A forged quote from Spiderman is not the most scholastic way of putting it but I'm sure it is efficient enough. The bottom-line is: let's share what we know to trigger creativity. Let's be the shoulders upon which the future giants can rely.

Mission statement: This blog has one goal (well, other than my probable daily babbeling) and that is to revisit our day to day increase of knowledge... and more importantly share it with others. Simply, imagine 10 years from now every biologist referring to this blog for their questions as we do now in case of wikipedia. In general, I'll post the interesting stuff that I find out about... if you have similar posts just email them to me at "hani.goodarzi AT gmail DOT com" and I'll post them in due course if suitable for the content of this blog. The same holds for questions, if I know the answer I'll post them; if not, everyone can participate in finding it.

"Let the conversation begin." Hillary Clinton