User:J. C. Martinez-Garcia/Notebook/HMS Activities/2008/08/14

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The Andreas Wagner book on biological robustness
Yesterday I read the general introduction of the Andreas Wagner book. The following figure shows the table of contes of this book (recovered from Princeton University Press: . I will read again the introduction and I will complete here my summary. Later I will continue with the first chapter of the book (maybe I will also read the second chaper).
 * I was reading my summary concerning the introduction of the Andreas Wagner book and a design a figure with my ideas about the space of solutions for the survival problem. This is the figure: [[Image:Space_of_solution.png]]
 * More about the introduction:
 * 1) * A word on the History: There are two main historic threads of research into mutational robustness. Both go back to the first half of the 20th century. The first of them regards the phenomenon of dominance. Dominancy means that a phenotypic feature of an organism is robust to elimination of one among two copies of a gene product or to a corresponding 50% change in the concentration of the gene product (the first evolutionary explanation of dominance was proposed in the 1930's by Ronald Fisher). A second important phenomenon and early line of investigation is that of canalization. An organismal feature is canalized if its embryonic development is insensitive to variation in the environment or in genes (the term was originated by Conrad Waddington). Wagner also include some comments on the contributions of the concept of homeostasis (the organism's ability to sustain a physiological state in the face of change) to the study of mutational robustness, and he also pointed out that Claude Bernard argued that the constancy of the milieu inside an organism results from regulatory mechanisms inside the body.
 * 2) * Functions and purpose, Problems and Solution: It is convenient to use when speaking about biological systems as serving specific functions or purpose inside an organism, which is to say: such systems solve problems that organisms in reproducing and surviving.
 * 3) * What is the Book for?: For non specialist in the subject, assuming some basic knowledge on biochemistry and genetics, as well as some basic understanding of linear algebra, differential calculus, probability theory, and differential equations.
 * 4) * The Organization of the book: Chapters of parts I and II addresses some examples of genetic robustness (in each case it is discussed what is the robust feature in the concerned organism). The sequence of chapters is a tour through the hierarchy of biological organization, from molecules to the whole organism. Part III uses many of the examples in parts I and II as a raw material to discuss general principles behind robustness and its evolution ( chapter 13 deal with the concept of neutral space, as well as evolvability, and fragility). Part IV relates mutational robustness of the living with robustness in other systems.

The Kafri papers on gene redundancy
I will read the three papers and I will upload them in this system. Well, here I am. I will then read the three following papers: Well I read the Kafri papers. They are very interesting, but not very easy to read. They tourn around the role of genetic redundancy, i.e. the functional significance of redundant paralogs (two or more structures are said to be paralog, homologous, if they are alike because of shared ancestry), that may provide backup for one other in case of mutations.
 * 1) Ran Kafri, Melissa Levy, and Yitzhak Pilpel: The regulatory utilization of genetic redundancy through responsive backup circuits ([[Media:KafriNG2005.pdf]]). PNAS; August 1, 2006; vol. 103; no. 31; pp. 11653-11658.
 * 2) Ran Kafri, Arren Bar-Even, and Yitzhak Pilpel: Transcription control reprogramming in genetic backup circuits. Nature Genetics ([[Media:PNAS-2006-Kafri-11653-8.pdf]]); letters, Published online February 2005.
 * 3) Ran Kafri, Orna Dahan, and Yitzhak Pilpel: Preferencial protection of protein interaction network hubs in yeast: Evolved functionality of genetic redundancy ([[Media:Kafri_PNAS2008.pdf]]). PNAS; January 29, 2008; vol. 105; no. 4; pp. 1243-1248.
 * 1) In the first paper they propose a mechanism to explain why backup is provided (from mRNA infomation of Saccharomyces cerevisae) predominantly by paralogs that are expressed dissimilarly in most growth conditios. This mechanism consist in transcriptional reprogramming that allows the intact paralog to rescue the organism upon mutation of its counterpart (the transcriptional reprogramming is made possible because or partial coregulation across growth conditions). The results for this first paper were obtained from cross analysis of genomic data -paralog classification from the Saccaharomyces Genome Database, growth rates of mutants lacking the concerned paralogs from literature, mRNA expression data from 40 natural and perturbed times series and the Rosetta Compendium data in Express DB-, experiments -seven experiments with Affymetrix chips or PCR product-based microarrays-, detection on motifs -with ChIP-chip, expression data and phylogenetic conservation. They also include in the paper a mathematical model of the transcriptional reprogramming mechanism, based on kinetic analysis.
 * 2) In the second paper a reviews of (transcriptionally) responsive (to the intactness of their redundant partner) backup circuits, based-on genetic redundancy, is given. This paper analyzes the architecture of the circuits. The study is focused in conditional coregulation and maintenance of metabolic fluxes (in particular they review redundancies of developmental regulators). They also argued that responsive backup mechanism are ideal devices for filtering nongenetic noise from transcriptional pathways, which allows then regulatory precision.
 * 3) The third paper tackle evolved functionality of genetic redundancy concerning preferential protection of protein interaction hubs in yeast. Based on genome wide data analysis, expetiments and literature mining in yeast, the authors suggest that compensated duplicates are not randomly distributed within the protein interaction network but are rather strategically allocated to the most highly connected proteins. It means then that redundancy -understood at this level- is fortifies strategic hubs in the  protein network (the more vulnrable hubs are then protected from mutations via redundancy). Their results also suggest that this phenomenon is even more strong whit ancient duplicates, i.e. these functional overlaps have undergone purifying selection.

What is very interesting in the studies concerning the three papers is the extensive application of intuition, bioinformatics, experimentation, and mathematical models, as a way to obtain fundamental information concerning the network structure wich provides mutational robustness to the organism. The methodology allows interpretation of the results in evolutionary terms, and gives some arguments against the position of Andreas Wagner, who does not consider redundancy very important, and argue about a more prominent role for distributed robustness. In fact, the Kafri results would prove that redundancy is also a mechanism of distributed robustness.

I must contact Kafri and ask him about what he is doing now, and also I must try to obtain his PhD thesis.

The Dave Drubin talk
Today I participate in the meeting of the lab (4PM in the fifth floor). Dave Drubin presented his work with Pamela Silver, which deals with the design of a biosynthetic memory device [[Media:bdrubin_paper.pdf]]. The talk was very interesting. Dave is preparing the exposition of his ideas to the company Genstruct. One of the key pint of the project is about the possibility to apply the memory device as a tracer of cellular proliferation (cancer), since the memory -due to a external stimulus which makes the engineered cell to enter in a state, which is interpreted as 'memory'- produce a linneage whose members preserve the memory. I must study the Drubin work to see if I can participate in the memory project. Ah! The mathematical model which supports the function of the memory is a nonlinear system involvinf positive feedback -to avoid sensivity of the system to noise Dave and Pam added a complementary genetic device which only allows activation due to the real stimulus-.


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