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Emeryville, CA, United States

The Joint BioEnergy Institute is a research institute funded by the Department of Energy of the United States. It is led by the Lawrence Berkeley National Laboratory, and includes participation from the Sandia National Laboratory, Lawrence Livermore National Laboratory, as well as UC Berkeley, UC Davis and the Carnegie Institute. It is located in Emeryville, California.The goal of the Institute is to develop biofuels, bio-synthesized from cellulosic materials as an alternative to fossil fuels. Wikipedia.

Ronald P.C.,University of California at Davis | Ronald P.C.,Joint BioEnergy Institute
PLoS Biology | Year: 2014

Over the last 300 years, plant science research has provided important knowledge and technologies for advancing the sustainability of agriculture. In this Essay, I describe how basic research advances have been translated into crop improvement, explore some lessons learned, and discuss the potential for current and future contribution of plant genetic improvement technologies to continue to enhance food security and agricultural sustainability. © 2014 Pamela C. Source

Ronald P.C.,University of California at Davis | Ronald P.C.,Joint BioEnergy Institute | Ronald P.C.,Kyung Hee University | Beutler B.,Scripps Research Institute
Science | Year: 2010

The last common ancestor of plants and animals may have lived 1 billion years ago. Plants and animals have occasionally exchanged genes but, for the most part, have countered selective pressures independently. Microbes (bacteria, eukaryotes, and viruses) were omnipresent threats, influencing the direction of multicellular evolution. Receptors that detect molecular signatures of infectious organisms mediate awareness of nonself and are integral to host defense in plants and animals alike. The discoveries leading to elucidation of these receptors and their ligands followed a similar logical and methodological pathway in both plant and animal research. Source

Rosengarten R.D.,Joint BioEnergy Institute | Nicotra M.L.,University of Pittsburgh
Current Biology | Year: 2011

Nearly all colonial marine invertebrates are capable of allorecognition - the ability to distinguish between self and genetically distinct members of the same species. When two or more colonies grow into contact, they either reject each other and compete for the contested space or fuse and form a single, chimeric colony. The specificity of this response is conferred by genetic systems that restrict fusion to self and close kin. Two selective pressures, intraspecific spatial competition between whole colonies and competition between stem cells for access to the germline in fused chimeras, are thought to drive the evolution of extensive polymorphism at invertebrate allorecognition loci. After decades of study, genes controlling allorecognition have been identified in two model systems, the protochordate Botryllus schlosseri and the cnidarian Hydractinia symbiolongicarpus. In both species, allorecognition specificity is determined by highly polymorphic cell-surface molecules, encoded by the fuhc and fester genes in Botryllus, and by the alr1 and alr2 genes in Hydractinia. Here we review allorecognition phenomena in both systems, summarizing recent molecular advances, comparing and contrasting the life history traits that shape the evolution of these distinct allorecognition systems, and highlighting questions that remain open in the field. © 2011 Elsevier Ltd All rights reserved. Source

Brunk E.,Ecole Polytechnique Federale de Lausanne | Brunk E.,Joint BioEnergy Institute | Rothlisberger U.,Ecole Polytechnique Federale de Lausanne
Chemical Reviews | Year: 2015

The current state of the art of Quantum Mechanical/molecular mechanical (QM/MM) molecular dynamics approaches in ground and electronically excited states and their applications to biological problems is reviewed. For a complete description of quantum phenomena, the quantum nature of both electrons and nuclei has to be taken into account. Most of the current QM/MM applications are based on adiabatic dynamics in the electronic ground state. However, for dynamics in electronically excited states, the coupling between states, which is mediated via the nuclear motion, can be sizable, and nonadiabatic effects have to be taken into account. Configuration Interaction Singles (CIS) is a popular method in QM/MM applications due to its computational expedience that allows for the treatment of several hundred atoms. Since the 1990s, the Modified Neglect of Differential Overlap (MNDO) method has been further extended to a d orbital basis. This MNDO/d extension allows for the treatment of heavier elements. By using feature selection algorithms348 to identify the most appropriate subset of relevant variables that describe a certain phenomenon, the high-dimensionality of QM/MM data can be reduced and used for further analysis with causal inference algorithms to establish unique cause-effect relationships. Source

Frederix M.,John Innes Center | Downie A.J.,Joint BioEnergy Institute
Advances in Microbial Physiology | Year: 2011

Many bacteria use 'quorum sensing' (QS) as a mechanism to regulate gene induction in a population-dependent manner. In its simplest sense this involves the accumulation of a signaling metabolite during growth; the binding of this metabolite to a regulator or multiple regulators activates induction or repression of gene expression. However QS regulation is seldom this simple, because other inputs are usually involved. In this review we have focussed on how those other inputs influence QS regulation and as implied by the title, this often occurs by environmental or physiological effects regulating the expression or activity of the QS regulators. The rationale of this review is to briefly introduce the main QS signals used in Gram-negative bacteria and then introduce one of the earliest understood mechanisms of regulation of the regulator, namely the plant-mediated control of expression of the TraR QS regulator in Agrobacterium tumefaciens. We then describe how in several species, multiple QS regulatory systems can act as integrated hierarchical regulatory networks and usually this involves the regulation of QS regulators. Such networks can be influenced by many different physiological and environmental inputs and we describe diverse examples of these. In the final section, we describe different examples of how eukaryotes can influence QS regulation in Gram-negative bacteria. © 2011 Elsevier Ltd. Source

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