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Dive into the research topics where Stephen G. Chamberlin is active.

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Featured researches published by Stephen G. Chamberlin.


Research in Microbiology | 2000

Functional inferences from reconstructed evolutionary biology involving rectified databases : an evolutionarily grounded approach to functional genomics

Steven A. Benner; Stephen G. Chamberlin; David A Liberles; Sridhar Govindarajan; Lukas Knecht

If bioinformatics tools are constructed to reproduce the natural, evolutionary history of the biosphere, they offer powerful approaches to some of the most difficult tasks in genomics, including the organization and retrieval of sequence data, the updating of massive genomic databases, the detection of database error, the assignment of introns, the prediction of protein conformation from protein sequences, the detection of distant homologs, the assignment of function to open reading frames, the identification of biochemical pathways from genomic data, and the construction of a comprehensive model correlating the history of biomolecules with the history of planet Earth.


Applied and Environmental Microbiology | 2012

Experimental Evolution of a Facultative Thermophile from a Mesophilic Ancestor

Ian K. Blaby; Benjamin J. Lyons; Ewa Wroclawska-Hughes; Grier C. F. Phillips; Tyler P. Pyle; Stephen G. Chamberlin; Steven A. Benner; Thomas J. Lyons; Valérie de Crécy-Lagard; Eudes de Crécy

ABSTRACT Experimental evolution via continuous culture is a powerful approach to the alteration of complex phenotypes, such as optimal/maximal growth temperatures. The benefit of this approach is that phenotypic selection is tied to growth rate, allowing the production of optimized strains. Herein, we demonstrate the use of a recently described long-term culture apparatus called the Evolugator for the generation of a thermophilic descendant from a mesophilic ancestor (Escherichia coli MG1655). In addition, we used whole-genome sequencing of sequentially isolated strains throughout the thermal adaptation process to characterize the evolutionary history of the resultant genotype, identifying 31 genetic alterations that may contribute to thermotolerance, although some of these mutations may be adaptive for off-target environmental parameters, such as rich medium. We undertook preliminary phenotypic analysis of mutations identified in the glpF and fabA genes. Deletion of glpF in a mesophilic wild-type background conferred significantly improved growth rates in the 43-to-48°C temperature range and altered optimal growth temperature from 37°C to 43°C. In addition, transforming our evolved thermotolerant strain (EVG1064) with a wild-type allele of glpF reduced fitness at high temperatures. On the other hand, the mutation in fabA predictably increased the degree of saturation in membrane lipids, which is a known adaptation to elevated temperature. However, transforming EVG1064 with a wild-type fabA allele had only modest effects on fitness at intermediate temperatures. The Evolugator is fully automated and demonstrates the potential to accelerate the selection for complex traits by experimental evolution and significantly decrease development time for new industrial strains.


Journal of Molecular Evolution | 2011

Phylogenetic and Preliminary Phenotypic Analysis of Yeast PAQR Receptors: Potential Antifungal Targets

Nancy Y. Villa; Patricia Moussatche; Stephen G. Chamberlin; Anuj Kumar; Thomas J. Lyons

Proteins belonging to the Progestin and AdipoQ Receptor (PAQR) superfamily of membrane bound receptors are ubiquitously found in fungi. Nearly, all fungi possess two evolutionarily distinct paralogs of PAQR protein, which we have called the PQRA and PQRB subtypes. In the model fungus Saccharomyces cerevisiae, these subtypes are represented by the Izh2p and Izh3p proteins, respectively. S. cerevisiae also possesses two additional PQRA-type receptors called Izh1p and Izh4p that are restricted to other species within the “Saccharomyces complex”. Izh2p has been the subject of several recent investigations and is of particular interest because it regulates fungal growth in response to proteins produced by plants and, as such, represents a new paradigm for interspecies communication. We demonstrate that IZH2 and IZH3 gene dosage affects resistance to polyene antifungal drugs. Moreover, we provide additional evidence that Izh2p and Izh3p negatively regulate fungal filamentation. These data suggest that agonists of these receptors might make antifungal therapeutics, either by inhibiting fungal development or by sensitizing fungi to the toxic effects of current antifungal therapies. This is particularly relevant for pathogenic fungi such as Candida glabrata that are closely related to S. cerevisiae and contain the same complement of PAQR receptors.


Angewandte Chemie | 2010

Expanded Genetic Alphabets in the Polymerase Chain Reaction

Zunyi Yang; Fei Chen; Stephen G. Chamberlin; Steven A. Benner


Archive | 1999

Graphical user interface for display and analysis of biological sequence data

Stephen G. Chamberlin; Steven A. Benner; Lukas Knecht


Biochemical and Biophysical Research Communications | 1998

Structure Prediction in a Post-genomic Environment: A Secondary and Tertiary Structural Model for the Initiation Factor 5A Family

Dietlind L. Gerloff; Marcin P Joachimiak; Fred E. Cohen; Gina M. Cannarozzi; Stephen G. Chamberlin; Steven A. Benner


BMC Evolutionary Biology | 2006

Analysis of transitions at two-fold redundant sites in mammalian genomes. Transition redundant approach-to-equilibrium (TREx) distance metrics

Tang Li; Stephen G. Chamberlin; M. Daniel Caraco; David A. Liberles; Eric A. Gaucher; Steven A. Benner


Archive | 2014

Thermophile from a Mesophilic Ancestor Experimental Evolution of a Facultative

Steven A. Benner; Thomas J. Lyons; Tyler P. Pyle; Stephen G. Chamberlin; Ian K. Blaby; Benjamin J. Lyons


Archive | 2010

Joining Astrobiology to Medicine, Resurrecting Ancient Alcohol Metabolism

Matthew A. Carrigan; Oleg Uryasev; Ronald W. Davis; Stephen G. Chamberlin; Steven A. Benner


Archive | 2010

Next-Generation Tools for Extracting Function from Genomic Sequence Data. A Working Synthetic Biology

Felicia F. Chen; Eric A. Gaucher; Yang Zhu; Nicole A. Leal; Stephen G. Chamberlin; Steven A. Benner

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Eric A. Gaucher

Georgia Institute of Technology

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Anuj Kumar

University of Michigan

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