David A. C. Beck
University of Washington
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Featured researches published by David A. C. Beck.
Protein Science | 2009
Ryan Day; David A. C. Beck; Roger S. Armen; Valerie Daggett
We have determined consensus protein‐fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein‐fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web.
Nature Communications | 2013
Marina G. Kalyuzhnaya; Song Yang; Olga N. Rozova; Nicole E. Smalley; J. Clubb; Andrew E. Lamb; G. A. Nagana Gowda; Daniel Raftery; Y. Fu; Françoise Bringel; Stéphane Vuilleumier; David A. C. Beck; Yuri A. Trotsenko; V. N. Khmelenina; Mary E. Lidstrom
Methane is an essential component of the global carbon cycle and one of the most powerful greenhouse gases, yet it is also a promising alternative source of carbon for the biological production of value-added chemicals. Aerobic methane-consuming bacteria (methanotrophs) represent a potential biological platform for methane-based biocatalysis. Here we use a multi-pronged systems-level approach to reassess the metabolic functions for methane utilization in a promising bacterial biocatalyst. We demonstrate that methane assimilation is coupled with a highly efficient pyrophosphate-mediated glycolytic pathway, which under oxygen limitation participates in a novel form of fermentation-based methanotrophy. This surprising discovery suggests a novel mode of methane utilization in oxygen-limited environments, and opens new opportunities for a modular approach towards producing a variety of excreted chemical products using methane as a feedstock.
Structure | 2010
Marc W. van der Kamp; R. Dustin Schaeffer; Amanda L. Jonsson; Alexander D. Scouras; Andrew M. Simms; Rudesh D. Toofanny; Noah C. Benson; Peter C. Anderson; Eric D. Merkley; Steven Rysavy; Dennis Bromley; David A. C. Beck; Valerie Daggett
The dynamic behavior of proteins is important for an understanding of their function and folding. We have performed molecular dynamics simulations of the native state and unfolding pathways of over 2000 protein/peptide systems (approximately 11,000 independent simulations) representing the majority of folds in globular proteins. These data are stored and organized using an innovative database approach, which can be mined to obtain both general and specific information about the dynamics and folding/unfolding of proteins, relevant subsets thereof, and individual proteins. Here we describe the project in general terms and the type of information contained in the database. Then we provide examples of mining the database for information relevant to protein folding, structure building, the effect of single-nucleotide polymorphisms, and drug design. The native state simulation data and corresponding analyses for the 100 most populated metafolds, together with related resources, are publicly accessible through http://www.dynameomics.org.
Proceedings of the National Academy of Sciences of the United States of America | 2008
David A. C. Beck; Darwin O. V. Alonso; Daigo Inoyama; Valerie Daggett
Here, we compare the distributions of main chain (Φ,Ψ) angles (i.e., Ramachandran maps) of the 20 naturally occurring amino acids in three contexts: (i) molecular dynamics (MD) simulations of Gly-Gly-X-Gly-Gly pentapeptides in water at 298 K with exhaustive sampling, where X = the amino acid in question; (ii) 188 independent protein simulations in water at 298 K from our Dynameomics Project; and (iii) static crystal and NMR structures from the Protein Data Bank. The GGXGG peptide series is often used as a model of the unstructured denatured state of proteins. The sampling in the peptide MD simulations is neither random nor uniform. Instead, individual amino acids show preferences for particular conformations, but the peptide is dynamic, and interconversion between conformers is facile. For a given amino acid, the (Φ,Ψ) distributions in the protein simulations and the Protein Data Bank are very similar and often distinct from those in the peptide simulations. Comparison between the peptide and protein simulations shows that packing constraints, solvation, and the tendency for particular amino acids to be used for specific structural motifs can overwhelm the “intrinsic propensities” of amino acids for particular (Φ,Ψ) conformations. We also compare our helical propensities with experimental consensus values using the host–guest method, which appear to be determined largely by context and not necessarily the intrinsic conformational propensities of the guest residues. These simulations represent an improved coil library free from contextual effects to better model intrinsic conformational propensities and provide a detailed view of conformations making up the “random coil” state.
PeerJ | 2013
David A. C. Beck; Marina G. Kalyuzhnaya; Stephanie Malfatti; Susannah G. Tringe; Tijana Glavina del Rio; Natalia Ivanova; Mary E. Lidstrom; Ludmila Chistoserdova
We investigated microbial communities active in methane oxidation in lake sediment at different oxygen tensions and their response to the addition of nitrate, via stable isotope probing combined with deep metagenomic sequencing. Communities from a total of four manipulated microcosms were analyzed, supplied with 13C-methane in, respectively, ambient air, ambient air with the addition of nitrate, nitrogen atmosphere and nitrogen atmosphere with the addition of nitrate, and these were compared to the community from an unamended sediment sample. We found that the major group involved in methane oxidation in both aerobic and microaerobic conditions were members of the family Methylococcaceae, dominated by species of the genus Methylobacter, and these were stimulated by nitrate in aerobic but not microaerobic conditions. In aerobic conditions, we also noted a pronounced response to both methane and nitrate by members of the family Methylophilaceae that are non-methane-oxidizing methylotrophs, and predominantly by the members of the genus Methylotenera. The relevant abundances of the Methylococcaceae and the Methylophilaceae and their coordinated response to methane and nitrate suggest that these species may be engaged in cooperative behavior, the nature of which remains unknown.
Protein Engineering Design & Selection | 2008
David A. C. Beck; Amanda L. Jonsson; R. Dustin Schaeffer; Kathryn A. Scott; Ryan Day; Rudesh D. Toofanny; Darwin O. V. Alonso; Valerie Daggett
The goal of Dynameomics is to perform atomistic molecular dynamics (MD) simulations of representative proteins from all known folds in explicit water in their native state and along their thermal unfolding pathways. Here we present 188-fold representatives and their native state simulations and analyses. These 188 targets represent 67% of all the structures in the Protein Data Bank. The behavior of several specific targets is highlighted to illustrate general properties in the full dataset and to demonstrate the role of MD in understanding protein function and stability. As an example of what can be learned from mining the Dynameomics database, we identified a protein fold with heightened localized dynamics. In one member of this fold family, the motion affects the exposure of its phosphorylation site and acts as an entropy sink to offset another portion of the protein that is relatively immobile in order to present a consistent interface for protein docking. In another member of this family, a polymorphism in the highly mobile region leads to a host of disease phenotypes. We have constructed a web site to provide access to a novel hybrid relational/multidimensional database (described in the succeeding two papers) to view and interrogate simulations of the top 30 targets: http://www.dynameomics.org. The Dynameomics database, currently the largest collection of protein simulations and protein structures in the world, should also be useful for determining the rules governing protein folding and kinetic stability, which should aid in deciphering genomic information and for protein engineering and design.
Applied and Environmental Microbiology | 2015
Aaron W. Puri; Sarah Owen; Frances Chu; Ted Chavkin; David A. C. Beck; Marina G. Kalyuzhnaya; Mary E. Lidstrom
ABSTRACT Aerobic methanotrophs oxidize methane at ambient temperatures and pressures and are therefore attractive systems for methane-based bioconversions. In this work, we developed and validated genetic tools for Methylomicrobium buryatense, a haloalkaliphilic gammaproteobacterial (type I) methanotroph. M. buryatense was isolated directly on natural gas and grows robustly in pure culture with a 3-h doubling time, enabling rapid genetic manipulation compared to many other methanotrophic species. As a proof of concept, we used a sucrose counterselection system to eliminate glycogen production in M. buryatense by constructing unmarked deletions in two redundant glycogen synthase genes. We also selected for a more genetically tractable variant strain that can be conjugated with small incompatibility group P (IncP)-based broad-host-range vectors and determined that this capability is due to loss of the native plasmid. These tools make M. buryatense a promising model system for studying aerobic methanotroph physiology and enable metabolic engineering in this bacterium for industrial biocatalysis of methane.
The ISME Journal | 2015
Igor Y. Oshkin; David A. C. Beck; Andrew E. Lamb; Veronika Tchesnokova; Gabrielle Benuska; Tami L. McTaggart; Marina G. Kalyuzhnaya; Svetlana N. Dedysh; Mary E. Lidstrom; Ludmila Chistoserdova
We report observations on the dynamics of bacterial communities in response to methane stimulus in laboratory microcosm incubations prepared with lake sediment samples. We first measured taxonomic compositions of long-term enrichment cultures and determined that, although dominated by Methylococcaceae types, these cultures also contained accompanying types belonging to a limited number of bacterial taxa, methylotrophs and non-methylotrophs. We then followed the short-term community dynamics, in two oxygen tension regimens (150 μM and 15 μM), observing rapid loss of species diversity. In all microcosms, a single type of Methylobacter represented the major methane-oxidizing partner. The accompanying members of the communities revealed different trajectories in response to different oxygen tensions, with Methylotenera species being the early responders to methane stimulus under both conditions. The communities in both conditions were convergent in terms of their assemblage, suggesting selection for specific taxa. Our results support prior observations from metagenomics on distribution of carbon from methane among diverse bacterial populations and further suggest that communities are likely responsible for methane cycling, rather than a single type of microbe.
Frontiers in Microbiology | 2013
Janet B. Matsen; Song Yang; Lisa Y. Stein; David A. C. Beck; Marina G. Kalyuzhnaya
Methane utilizing bacteria (methanotrophs) are important in both environmental and biotechnological applications, due to their ability to convert methane to multicarbon compounds. However, systems-level studies of methane metabolism have not been carried out in methanotrophs. In this work we have integrated genomic and transcriptomic information to provide an overview of central metabolic pathways for methane utilization in Methylosinus trichosporium OB3b, a model alphaproteobacterial methanotroph. Particulate methane monooxygenase, PQQ-dependent methanol dehydrogenase, the H4MPT-pathway, and NAD-dependent formate dehydrogenase are involved in methane oxidation to CO2. All genes essential for operation of the serine cycle, the ethylmalonyl-CoA (EMC) pathway, and the citric acid (TCA) cycle were expressed. PEP-pyruvate-oxaloacetate interconversions may have a function in regulation and balancing carbon between the serine cycle and the EMC pathway. A set of transaminases may contribute to carbon partitioning between the pathways. Metabolic pathways for acquisition and/or assimilation of nitrogen and iron are discussed.
Biochemistry | 2008
Michelle E. McCully; David A. C. Beck; Valerie Daggett
The principle of microscopic reversibility states that at equilibrium the number of molecules entering a state by a given path must equal those exiting the state via the same path under identical conditions or, in structural terms, that the conformations along the two pathways are the same. There has been some indirect evidence indicating that protein folding is such a process, but there have been few conclusive findings. In this study, we performed molecular dynamics simulations of an ultrafast unfolding and folding protein at its melting temperature to observe, on an atom-by-atom basis, the pathways the protein followed as it unfolded and folded within a continuous trajectory. In a total of 0.67 micros of simulation in water, we found six transient denaturing events near the melting temperature (323 and 330 K) and an additional refolding event following a previously identified unfolding event at a high temperature (373 K). In each case, unfolding and refolding transition state ensembles were identified, and they agreed well with experiment on the basis of a comparison of S and Phi values. On the basis of several structural properties, these 13 transition state ensembles agreed very well with each other and with four previously identified transition states from high-temperature denaturing simulations. Thus, not only were the unfolding and refolding transition states part of the same ensemble, but in five of the seven cases, the pathway the protein took as it unfolded was nearly identical to the subsequent refolding pathway. These events provide compelling evidence that protein folding is a microscopically reversible process. In the other two cases, the folding and unfolding transition states were remarkably similar to each other but the paths deviated.