A major difference between the divergence patterns within the lines-1 families in mice and voles

L1 retroposons are represented in mice by subfamilies of interspersed sequences of varied abundance. Previous analyses have indicated that subfamilies are generated by duplicative transposition of a small number of members of the L1 family, the progeny of which then become a major component of the murine L1 population, and are not due to any active processes generating homology within preexisting groups of elements in a particular species. In mice, more than a third of the L1 elements belong to a clade that became active approximately 5 Mya and whose elements are > or = 95% identical. We have collected sequence information from 13 L1 elements isolated from two species of voles (Rodentia: Microtinae: Microtus and Arvicola) and have found that divergence within the vole L1 population is quite different from that in mice, in that there is no abundant subfamily of homologous elements. Individual L1 elements from voles are very divergent from one another and belong to a clade that began a period of elevated duplicative transposition approximately 13 Mya. Sequence analyses of portions of these divergent L1 elements (approximately 250 bp each) gave no evidence for concerted evolution having acted on the vole L1 elements since the split of the two vole lineages approximately 3.5 Mya; that is, the observed interspecific divergence (6.7%-24.7%) is not larger than the intraspecific divergence (7.9%-27.2%), and phylogenetic analyses showed no clustering into Arvicola and Microtus clades.      

Neuromechanics: an integrative approach for understanding motor control

Neuromechanics seeks to understand how muscles, sense organs,motor pattern generators, and brain interact to produce coordinatedmovement, not only in complex terrain but also when confrontedwith unexpected perturbations. Applications of neuromechanicsinclude ameliorating human health problems (including prosthesisdesign and restoration of movement following brain or spinalcord injury), as well as the design, actuation and control ofmobile robots. In animals, coordinated movement emerges fromthe interplay among descending output from the central nervoussystem, sensory input from body and environment, muscle dynamics,and the emergent dynamics of the whole animal. The inevitablecoupling between neural information processing and the emergentmechanical behavior of animals is a central theme of neuromechanics.Fundamentally, motor control involves a series of transformationsof information, from brain and spinal cord to muscles to body,and back to brain. The control problem revolves around the specifictransfer functions that describe each transformation. The transferfunctions depend on the rules of organization and operationthat determine the dynamic behavior of each subsystem (i.e.,central processing, force generation, emergent dynamics, andsensory processing). In this review, we (1) consider the contributionsof muscles, (2) sensory processing, and (3) central networksto motor control, (4) provide examples to illustrate the interplayamong brain, muscles, sense organs and the environment in thecontrol of movement, and (5) describe advances in both roboticsand neuromechanics that have emerged from application of biologicalprinciples in robotic design. Taken together, these studiesdemonstrate that (1) intrinsic properties of muscle contributeto dynamic stability and control of movement, particularly immediatelyafter perturbations; (2) proprioceptive feedback reinforcesthese intrinsic self-stabilizing properties of muscle; (3) controlsystems must contend with inevitable time delays that can simplifyor complicate control; and (4) like most animals under a varietyof circumstances, some robots use a trial and error processto tune central feedforward control to emergent body dynamics.     

A data management system for structural genomics

Background  

Structural genomics (SG) projects aim to determine thousands of protein structures by the development of high-throughput techniques for all steps of the experimental structure determination pipeline. Crucial to the success of such endeavours is the careful tracking and archiving of experimental and external data on protein targets.     

Battling for Ribosomes: Translational Control at the Forefront of the Antiviral Response

In the early stages of infection, gaining control of the cellular protein synthesis machinery including its ribosomes is the ultimate combat objective for a virus. To successfully replicate, viruses unequivocally need to usurp and redeploy this machinery for translation of their own mRNA. In response, the host triggers global shutdown of translation while paradoxically allowing swift synthesis of antiviral proteins as a strategy to limit collateral damage. This fundamental conflict at the level of translational control defines the outcome of infection. As part of this special issue on molecular mechanisms of early virus–host cell interactions, we review the current state of knowledge regarding translational control during viral infection with specific emphasis on protein kinase RNA-activated and mammalian target of rapamycin-mediated mechanisms. We also describe recent technological advances that will allow unprecedented insight into how viruses and host cells battle for ribosomes.     

Molecular mechanisms creating bistable switches at cell cycle transitions

Progression through the eukaryotic cell cycle is characterized by specific transitions, where cells move irreversibly from stage i−1 of the cycle into stage i. These irreversible cell cycle transitions are regulated by underlying bistable switches, which share some common features. An inhibitory protein stalls progression, and an activatory protein promotes progression. The inhibitor and activator are locked in a double-negative feedback loop, creating a one-way toggle switch that guarantees an irreversible commitment to move forward through the cell cycle, and it opposes regression from stage i to stage i−1. In many cases, the activator is an enzyme that modifies the inhibitor in multiple steps, whereas the hypo-modified inhibitor binds strongly to the activator and resists its enzymatic activity. These interactions are the basis of a reaction motif that provides a simple and generic account of many characteristic properties of cell cycle transitions. To demonstrate this assertion, we apply the motif in detail to the G1/S transition in budding yeast and to the mitotic checkpoint in mammalian cells. Variations of the motif might support irreversible cellular decision-making in other contexts.