Genomic Enterprise

Virally Encoded microRNAs

 
by  Peter McErlean, Ph.D.
Division of Allergy-Immunology
Northwestern University
Chicago, IL    USA
e-mail: p-mcerlean@northwestern.edu

 
MicroRNAs (miRs) are a class of small (~20nt) non-coding RNAs that are involved in the post-transcriptional regulation of gene expression. miR-mediated gene regulation is carried out by a collection of proteins known as the RNA-induced silencing complex (RISC) which binds to miR specific target sequences on messenger RNAs (mRNAs) and directs either translational repression or mRNA degradation (1).miRs have been identified within and across many different species of plants and animals indicating that miR-mediated gene regulation appears to be a conserved and evolutionarily favorable process. Given the parasitic nature of viral infections and the potential benefit of viruses to regulate host gene expression to their advantage (i.e. limit the antiviral response during replication), it is of no surprise that miRs have been described in viruses (2-3). Virally encoded miRs (V-miRs) were first identified in Epstein-Bar Virus (EBV), a member of the Herpesvirus family and causative agent of mononucleosis (4). Since this initial discovery bioinformatic-based approaches have predicted the existence of other V-miRs, predominately in viruses with double stranded DNA genomes (5). Experimental validation of predicted V-miRs has so far occurred in additional Herpesviruses; Kaposi sarcoma-associated virus [KSHV], Herpes Simplex-1 and Human Cytomegalovirus; Human Adenoviruses and the simian and murine Polyomaviruses (2). Characterization of V-miRs has revealed that they are employed by viruses primarily to regulate their own viral proteins as opposed to directly targeting host cellular mRNAs that may be involved in the virus life cycle. It has also been shown that the majority of V-miRs share limited sequence homology with not only their host’s endogenous miRs, but also with V-miRs found in other members of the same virus family; a particularly unique aspect when considering miRs found within other plant and animal families remain essentially conserved (3). Interestingly, V-miRs that do share limited sequence homology to host cellular miRs (e.g. KSHV miR-K12-11 and miR-155) may be involved in similar pathways to their endogenous counterparts, although further clarifications of these interactions are needed (2). Finally, given that V-miRs have been characterized from viruses known to cause or be implicated in human diseases (e.g. EBV, KSHV and B-cell lymphomas), targeting of V-miRs during infection may prove to be of therapeutic value. MicroRNA focused studies have provided us with invaluable information about many biological processes across many different organisms. The identification of V-miRs is testament to the diverse nature of miR-mediated gene regulation and although only in its infancy, V-miR focused research has bolstered our understanding of virus biology. Indeed, future studies in this area will reveal more of the immense complexity that exists in virus-host interactions.

 
References:

1. Bartel, D.P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 116 (2): p. 281-297, 2004.

2. Gottwein, E. and B.R. Cullen. Viral and cellular microRNAs as determinants of viral pathogenesis and immunity. Cell Host Microbe. 3 (6): p. 375-387, 2008.

3. Sullivan, C.S. and D. Ganem.  MicroRNAs and viral infection. Mol Cell. 20 (1): p. 3-7, 2005.

4. Pfeffer, S., et al. Identification of virus-encoded microRNAs. Science. 304 (5671): p. 734-736, 2004.

5. Pfeffer, S., et al. Identification of microRNAs of the herpesvirus family. Nat Methods. 2 (4): p. 269-276, 2005.

 
How close are we to resolving the genotype/phenotype map?

by Jerry Rhee, Ph.D.

Developmental Biology, Children’s Memorial Research Center and Northwestern University

Chicago, IL      USA

e-mail: jerryrhee@yahoo.com 

 
    The extent to which we can satisfy the growing optimism for personalized medicine and virtual development of therapeutics is largely dependent on our ability to accurately map correlations between the genotype to the phenotype, an incredibly difficult and unresolved problem (1,2). Historically, this issue has been considered via demonstration of congruence in explaining the Baldwin effect, a population phenomenon scored through individuals that illustrates the potential of the genotype to adapt to its environment over several generations (3). The following is a brief opinion with regards the tractability of this immense problem with consideration of developments in modern techniques and the tendency of biologists to be divided between two groups, viz., “experimentalists who observe things that cannot be explained, and theoreticians who explain things that cannot be observed” - Aharon Katzir-Katchalsky (4).
    Given the wide spatial and temporal range of interactions that constitute evolutionary dynamics, it is not surprising that the study of form has been recognized as a central means by which to dissect the underpinnings of morphogenesis well before the molecular era (5). This is primarily due to the inherent nature of shapes to simplify the complicated complexities operating across different levels of hierarchies through expression as qualities that are shifted to new sets of constrained typicalities and variabilities when perturbed. The impact of this realization is demonstrated by the success of phenotype-based screens that continue to affect the direction of current disease research (6). 
    The central goal for medical virtualization is to visualize and manipulate the dynamics of a comprehensive network on a geometrically transforming manifold (7). The challenges with which we are faced are to do this in a manner that balances accurate information with computability, that is, as more information becomes available, processing speeds are slowed.  As a result, researchers are now starting to move away from trying to generate a singular globalized model to a more manageable approach that takes advantage of local communities (8), but with an eye towards eventual integration.  
From an experimentalist view, resolving phenotype/gentoype correlations is being carried out through complementary high-throughput methods with more targeted means (9) in hopes of mapping networks in the mold of Waddington’s vision of the epigenetic landscape. This is necessitated by the fact that there exists a problem of being unable to assess concentration effects using high throughput methods, which can be exposed through targeted, explicit models (10) as things move towards concurrency. 
    Consideration of the organism as a complex adaptive system (11) naturally allows integration of diverse scientific disciplines onto a singular topic. Therefore, participating in the growth of a genotype/phenotype map offers an opportunity to shuffle and integrate existing programs into new combinations in hopes that it would lead to innovations, a lesson learned from the study of evolutionary novelties. To circumvent potential communication barriers, transparent efforts to develop user-friendly platforms (12,13) that foster exchange are constantly being updated.  Such combined efforts are having an extremely positive effect on modifying education and culture of 21st century biology and engineering (14). Indeed, it is an exciting time to join this multidisciplinary endeavor!

References and links: 

 
1. Webster G, Goodwin BC. Form and transformation: generative and relational principles in biology. Cambridge, U.K. ; New York, N.Y.: Cambridge University Press. xiv p. 287, 1996.

2. Crutchfield JP, Schuster P. Evolutionary dynamics : exploring the interplay of selection, accident, neutrality, and function. Oxford ; New York: Oxford University Press. xxxiv p. 452, 2003.

3. Fontana W. Evolvability of phenotypes.

4. Bower JM, Bolouri H. Computational modeling of genetic and biochemical networks. Cambridge, Mass, 2001.

5. Riedl R. Order in living organisms : a systems analysis of evolution. Chichester ; New York: Wiley. xx, 313, 1978.

6. Garcia-Garcia MJ, Eggenschwiler JT, Caspary T, Alcorn HL, Wyler MR, et al. Analysis of mouse embryonic patterning and morphogenesis by forward genetics. PNAS 102: 5913-5919,
2005.

7. Thom R. Structural stability and morphogenesis; an outline of a general theory of models. Reading, Mass.,: W. A. Benjamin. 348, 1975.

8. Detwiler LT, Suciu D, Franklin JD, Moore EB, Poliakov AV, et al. Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data. Front Neuroinformatics 3: 2, 2009.

9. Hadjantonakis AK, Dickinson ME, Fraser SE, Papaioannou VE. Technicolour transgenics: imaging tools for functional genomics in the mouse. Nat Rev Genet 4: 613-625, 2003.

10. Lee E, Salic A, Kruger R, Heinrich R, Kirschner MW. The roles of APC and Axin derived from experimental and theoretical analysis of the Wnt pathway. PLoS Biol 1: E10, 2003.

11. Gell-Mann M, Baltimore D, Kuhn RL. 
www.pbs.org/kcet/closertotruth/transcripts/306_order.pdf 

12. Cvitanovic P.  http://chaosbook.org/

13. Wilensky U. Netlogo, 1999. http://ccl.northwestern.edu/netlogo/