Research

Our work, which spans theory, computational and experiment is performed in three interrelated areas whose common thread is understanding and exploiting the evolutionary and synthetic design principles of cells. These areas include comparative functional genomics to discover and understand the key subsystems in cells and their dynamic organization that allow them to survive and transform the environment and to adapt and evolve to new circumstances; systems biology to understand the biophysical, dynamical, and control/information theoretical aspects of cellular network operation in uncertain environments and when modified for applications; and synthetic biology for the efficient and predictable engineering of new function in cells for applications of benefit to society.

The tabs below give some sense of the projects currently ongoing in the laboratory. Many of our efforts to develop core technology cross many of these individual projects.

Projects

(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)

Status: current

According to estimates from the UNAIDS 2009 AIDS Epidemic Update, around 31.3 million adults and 2.1 million children were living with HIV at the end of 2008.During 2008, some 2.7 million people became infected with the human immunodeficiency virus (HIV), which causes AIDS. Deaths from AIDS have decreased only slightly from its peak in 2004 despite amazing advances antiretroviral (ARV) therapy, which reduced AIDS-related deaths among those who received it. The eradication of HIV-1 will likely require novel clinical approaches to purge the reservoir of latently infected cells from a patient. In this project we study the molecular basis for regulation of HIV expression dynamics, the role of gene expression noise in establishment of latency and new therapeutic approaches to treatment directed towards overcoming its problems. Using multiscale modeling informed by quantitative molecular biological manipulation and measurement we aim to understand the systems biology of HIV infection/expression dynamics and the synthetic biology of the design of new therapies. Even if we are not success in the clinical applications this virus presents a fantastic model system for understanding the role of stochastic gene expression in mammalian cells and rapid evolution of regulatory networks.

Publications

  • Burnett, J. C., Lim, K. I., Calafi, A., Rossi, J. J., Schaffer, D. V., Arkin, A. P. (2010) "Combinatorial latency reactivation for HIV-1 subtypes and variants", J Virol pp. 5958-74
  • Burnett, J. C., Miller-Jensen, K., Shah, P. S., Arkin, A. P., Schaffer, D. V. (2009) "Control of stochastic gene expression by host factors at the HIV promoter", PLoS Pathog pg. 1000260
  • Weinberger, L. S., Burnett, J. C., Toettcher, J. E., Arkin, A. P., Schaffer, D. V. (2005) "Stochastic Gene Expression in a Lentiviral Positive-Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity", Cell pp. 169-82
  • Weinberger, L. S., Schaffer, D. V., Arkin, A. P. (2003) "Theoretical design of a gene therapy to prevent AIDS but not human immunodeficiency virus type 1 infection", J Virol pp. 10028-36

 

(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)

Status: current

The sophisticated and sensitive stress response and spore-developmental systems of the model gram-positive soil bacterium B. subtilis provide a route to studying one of the key challenges in the post-genomic age-to map genotype to phenotype and phenotype finally to fitness in a given environment. Systems biology has been largely concerned with the former mapping and population dynamics with the latter. In recent years, there has been a slow convergence of the two fields, particularly in microbiology. In the few cases where models of realistic pathway function have matured to the point that optimality can be explored (e.g. chemotaxis, heat shock, phase variation, and viral decisions), it has been found that both the architecture and particular dynamics of biological networks seem to be evolutionarily selected for top performance: for example, optimal sensing and foraging in chemotaxis or maximal protection against unfolded proteins for minimal energy in heat shock. In at least three of these examples and numerous others, nongenetic diversity has been observed to arise in the behavior of single cells/viruses and the role of such possibly “noisy” processes in conferring fitness (usually defined as a growth advantage) to the clonal population has been an active topic of discussion. In the case of cellular decision-making, a number of theories, including one of our own, have cited so-called “Bet-Hedging” as a key driver for selection of stochastic population dynamics. Bet-hedging is a strategy to maximize long-term growth rate and evade “unlucky” extinction events in the presence of environmental uncertainty by stochastic expression of favoured phenotypes for each environmental condition. This viewpoint has even been applied to explain the possible utility of the diversification of phenotype observed during the stress responses of the model organism we will study here, Bacillus subtilis. However, our studies of the decision-making by Bacillus subtilis to sporulate have begun to suggest another possible explanations. In this work we study the architecture of the B.subtilis stress response networks and relate their stochastic and spatial dynamics to the development of history dependent complex population diversification, communication and growth phenotypes.

Publications

  • Ross, J., Arkin, A. P. (2009) "Complex systems: from chemistry to systems biology", Proc Natl Acad Sci U S A pp. 6433-4
  • Bischofs, I. B., Hug, J. A., Liu, A. W., Wolf, D. M., Arkin, A. P. (2009) "Complexity in bacterial cell-cell communication: quorum signal integration and subpopulation signaling in the Bacillus subtilis phosphorelay", Proc Natl Acad Sci U S A pp. 6459-64
  • Wolf, D. M., Fontaine-Bodin, L., Bischofs, I., Price, G., Keasling, J., Arkin, A. P. (2008) "Memory in microbes: quantifying history-dependent behavior in a bacterium", PLoS ONE pg. 1700
  • Singh, A. H., Wolf, D. M., Wang, P., Arkin, A. P. (2008) "Modularity of stress response evolution", Proc Natl Acad Sci U S A pp. 7500-5
  • Voigt, C. A., Wolf, D. M., Arkin, A. P. (2005) "The Bacillus subtilis sin Operon: An Evolvable Network Motif", Genetics pp. 1187-202
  • Rao, C. V., Kirby, J. R., Arkin, A. P. (2005) "Phosphatase localization in bacterial chemotaxis: divergent mechanisms, convergent principles", Phys Biol pp. 148-58
  • Rao, C. V., Kirby, J. R., Arkin, A. P. (2004) "Design and Diversity in Bacterial Chemotaxis: A Comparative Study in Escherichia coli and Bacillus subtilis", PLoS Biol pg. 49
  • Rao, C. V., Frenklach, M., Arkin, A. P. (2004) "An allosteric model for transmembrane signaling in bacterial chemotaxis", J Mol Biol pp. 291-303

 

(alttext needed)
(description needed)

Status: current

Building on our long expertise in the systems biology of microbes, we are building an experimental and computational comparative microbial systems biology infrastructure that we can apply widely to identify, understand and engineer the central pathways in bacteria and fungi that are important to their specific activities of interest to our projects in synthetic and systems biology generally and our work in bioenergy, bioremediation and human health. The approach combines functional genomics in the form of gene expression and metabolic analysis, high throughput genetics, and quantitative dynamic analysis of pathway function using highly controlled and reproducibly perturbed microbial cultures for elucidating the interactions between individual genes, pathways, and the environment. The core experimental technologies involve extensive use of custom high-density tiling microarrays for genome annotation and inference of regulatory elements, custom oligonucleotide microarrays for gene expression, metabolite analysis, and the parallel, quantitative analysis of thousands of sequence defined mutants using a molecular barcoding strategy. In addition to providing genetic resources for any microorganism, our proposed facility will enable automated sample preparation as well as automated, high-throughput microbial experiments (using liquid handling robotics and microplate readers). These experimental efforts will be supported by the development of a sophisticated computational infrastructure whose beginnings can be found in the MicrobesOnline (http://microbesonline.org) and RegTransBase (http//regtransbase.lbl.gov). For this project, these tools will be deepened with more genomes, better metabolic and stress gene annotation, regulatory network curation and inference, and functional genomic analysis tools, and tools for metabolic inference and engineering. Together, the facility will generate a quantitative, systems-level view of microbial physiology that will serve as the blueprint for the rational engineering of these organisms to meet biotechnological challenges.

Publications

 

(alttext needed)
(description needed)
(alttext needed)
(description needed)

Status: current

Bacteria are an attractive alternative to yeast for industrial level fuel ethanol production and perhaps the production of other types of fuels such as lipids and diesel. While, currently, few bacteria are close to the efficiency of fungi in the production of ethanol, recent findings show that rational engineering can greatly increase output. Bacteria like Zymomonas mobilis, a successful model microbe for ethanol production, have been moderately engineered and selected for industrial output of ethanol. However, there have been no systematic genomic or high-throughput genetic studies to elucidate how other metabolic and stress pathways affect the process in bacteria. Rational engineering of bacteria to optimize ethanol production or any fuel molecule requires a thorough, systems-level understanding of the how bacterial metabolism, gene regulation, and stress response influence this process. Our project will develop a facility for these studies (See the Microbial Characterization Facility Project) and apply them to key biofuel relevant organisms starting with Zymomonas mobilis. The facility will generate a quantitative, systems-level view of microbial physiology that will serve as the blueprint for the rational engineering of these organisms to meet bioenergy challenges. Our first target is to use this framework to improve ethanol production in Zymomonas mobilis. Until very recently, the only commercial fermentations have relied on yeast and other super-fungi that have been identified as excellent producers of ethanol from C5 sugars and other carbon sources. However, for some time it has been recognized that the facultative anaerobe Zymomonas mobilis can have a higher yield and faster specific rate of ethanol production when compared to yeast. In addition, yeast has a higher aeration cost, a high biomass production, and low temperature and ethanol tolerance compared to Zymomonas. Its yield of ethanol from sugar, derived from the Entner-Doudoroff pathway, is around 96%, the same as yeast. Because of its industrial potential, DuPont and others have dedicated themselves to scaling up Zymomonas for commercial fermentation of lignocellulosic residues such as corn stover. Zymomonas has already, for over a decade, been a target of metabolic engineering for utilization of diverse C5 sugars such as xylose and arabinose that are present in lignocellulosic hydrolysates. A number of components in hydrolysates can inhibit the growth and ethanol production of bacteria and yeast. While in Z. mobilis the major inhibitor is usually acetate, other products such as vanillin, syringaldehyde, hydroxymethyl-furfural and furfural all show significant inhibitory effects. These inhibitors, and ethanol itself, have differential effects on growth and on ethanol production and have different behaviors depending on the sugars being utilized. In fact, the osmotic stress of sugars themselves can have a strong affect on the productivity of fermentation and different sugars have different uptake rates and saturation points. Further, the growth mode of Z. mobilis can have a strong effect on its productivity. Immobilized and suspended cultures have very different productivities and the use of flocculent cultures can increase volumetric productivity by as much as ten-fold. Efforts to optimize Z. mobilis for production are limited because a detailed understanding of all the physiological factors affecting metabolism including stress responses and inessential secondary metabolic pathways are not currently available. Identifying the genetic factors that contribute to these effects is a main aim of this proposal. Despite availability of both the genome and a developed genetic toolbox with plasmids, a promoter system, and conjugal shuttle vectors capable of delivering transposons from E. coli, there has not yet been a large-scale genomic analysis of Zymomonas physiology. Consequently, the factors affecting key metabolisms and behaviors for ethanol production and tolerances to inhibitors in the feedstock and in its products are unknown. In doing so, we hope to elucidate engineering principles to improve ethanol production from lignocellulosic sources by Z. mobilis and perhaps other species.

 

Standard Synthetic Biology
(a) Different classes of a biological device. (b) Gaining control over the central dogma with designable/scalable RNA devices.
(alttext needed)
(description needed)

Status: current

Our current ability to engineer biological circuits is hindered by design cycles that are costly in terms of time and money, with constructs failing to operate as desired, or evolving away from the desired function once deployed. Synthetic biologists seek to understand biological design principles and use them to create technologies that increase the efficiency of the genetic engineering design cycle. Central to the approach is the creation of biological parts--encapsulated functions that can be composited together to create new pathways with predictable behaviors. We define six desirable characteristics of biological parts--independence, reliability, tunability, orthogonality, composability, and homogeneity. We propose that the creation of appropriate sets of families of parts with these properties is a prerequisite for efficient, predictable engineering of new function in cells and will enable a large increase in the sophistication of genetic engineering applications. An example of such an effort in our lab is our attempt to gain control over the central dogma with designable/scalable RNA devices. The diversity of known RNA structure–based mechanisms for regulating all aspects of gene expression and the emerging principles for altering their specificities suggest that it may be possible to develop designable, predictable and large families of parts to greatly simplify predictive gene regulatory network design. We are also working on biological computer-aided design tools for allowing rapid functional and sequence-based designs of function circuits based on these and other components.

Publications

  • Anderson, J. C., Dueber, J. E., Leguia, M., Wu, G. C., Goler, J. A., Arkin, A. P., Keasling, J. D. (2010) "BglBricks: A flexible standard for biological part assembly", J Biol Eng pg. 1
  • Lucks, J. B., Qi, L., Whitaker, W. R., Arkin, A. P. (2008) "Toward scalable parts families for predictable design of biological circuits", Curr Opin Microbiol pp. 567-73
  • Ham, T. S., Lee, S. K., Keasling, J. D., Arkin, A. P. (2008) "Design and construction of a double inversion recombination switch for heritable sequential genetic memory", PLoS ONE pg. 2815
  • Arkin, A. (2008) "Setting the standard in synthetic biology", Nat Biotechnol pp. 771-4
  • Anderson, J. C., Voigt, C. A., Arkin, A. P. (2007) "Environmental signal integration by a modular AND gate", Mol Syst Biol pg. 133
  • Ham, T. S., Lee, S. K., Keasling, J. D., Arkin, A. P. (2006) "A tightly regulated inducible expression system utilizing the fim inversion recombination switch", Biotechnol Bioeng pp. 1-4
  • Anderson, J. C., Clarke, E. J., Arkin, A. P., Voigt, C. A. (2006) "Environmentally Controlled Invasion of Cancer Cells by Engineered Bacteria", J Mol Biol pp. 619-627
  • Weinberger, L. S., Schaffer, D. V., Arkin, A. P. (2003) "Theoretical design of a gene therapy to prevent AIDS but not human immunodeficiency virus type 1 infection", J Virol pp. 10028-36
  • McAdams, H. H., Arkin, A. (2000) "Towards a circuit engineering discipline", Curr Biol pp. 318-20
  • Arkin, A. P., Youvan, D. C. (1992) "Optimizing nucleotide mixtures to encode specific subsets of amino acids for semi-random mutagenesis", Biotechnology (N Y) pp. 297-300
  • Arkin, A. P., Youvan, D. C. (1992) "An algorithm for protein engineering: simulations of recursive ensemble mutagenesis", Proc Natl Acad Sci U S A pp. 7811-5
  • J. B. Lucks and L. Qi and V. K. Mutalik and Denise Wang and A. P. Arkin (2011) "Versatile RNA-sensing transcriptional regulators for engineering genetic networks", PNAS pp. 8617-8622

 

(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)

Status: current

Systems biology concerns itself with the architecture and dynamic/biophysical operation of cellular networks as well as the organization and strategies of cellular response.

Publications

  • Novichkov, P. S., Laikova, O. N., Novichkova, E. S., Gelfand, M. S., Arkin, A. P., Dubchak, I., Rodionov, D. A. (2010) "RegPrecise: a database of curated genomic inferences of transcriptional regulatory interactions in prokaryotes", Nucleic Acids Res pp. 111-8
  • Dehal, P. S., Joachimiak, M. P., Price, M. N., Bates, J. T., Baumohl, J. K., Chivian, D., Friedland, G. D., Huang, K. H., Keller, K., Novichkov, P. S., Dubchak, I. L., Alm, E. J., Arkin, A. P. (2010) "MicrobesOnline: an integrated portal for comparative and functional genomics", Nucleic Acids Res pp. 396-400
  • Andrews, S. S., Addy, N. J., Brent, R., Arkin, A. P. (2010) "Detailed simulations of cell biology with Smoldyn 2.1", PLoS Comput Biol pg. 1000705
  • Singh, A. H., Wolf, D. M., Wang, P., Arkin, A. P. (2008) "Modularity of stress response evolution", Proc Natl Acad Sci U S A pp. 7500-5
  • Flaherty, P., Radhakrishnan, M. L., Dinh, T., Rebres, R. A., Roach, T. I., Jordan, M. I., Arkin, A. P. (2008) "A dual receptor crosstalk model of g-protein-coupled signal transduction", PLoS Comput Biol pg. 1000185
  • Kazakov, A. E., Cipriano, M. J., Novichkov, P. S., Minovitsky, S., Vinogradov, D. V., Arkin, A., Mironov, A. A., Gelfand, M. S., Dubchak, I. (2007) "RegTransBase--a database of regulatory sequences and interactions in a wide range of prokaryotic genomes", Nucleic Acids Res pp. 407-12
  • Samoilov, M. S., Price, G., Arkin, A. P. (2006) "From fluctuations to phenotypes: the physiology of noise", Sci STKE pg. 17
  • Samoilov, M. S., Arkin, A. P. (2006) "Deviant effects in molecular reaction pathways", Nat Biotechnol pp. 1235-1240
  • Plyasunov, S., Arkin, A.P. (2006) "Efficient stochastic sensitivity analysis of discrete event systems", Journal of Computational Physics pp. 724-738
  • Plyasunov, S., Arkin, A.P. (2006) "Averaging Methods For Stochastic Dynamics of Complex Reaction Networks: Description of Multi-scale Couplings", Multiscale Modeling and Simulation pp. 497-513
  • Onsum, M. D., Wong, K., Herzmark, P., Bourne, H. R., Arkin, A. P. (2006) "Morphology matters in immune cell chemotaxis: membrane asymmetry affects amplification", Phys Biol pp. 190-9
  • Feeley, R., Frenklach, M., Onsum, M., Russi, T., Arkin, A., Packard, A. (2006) "Model discrimination using data collaboration", J Phys Chem A Mol Spectrosc Kinet Environ Gen Theory pp. 6803-13
  • Andrews, S. S., Arkin, A. P. (2006) "Simulating cell biology", Curr Biol pp. 523-7
  • Wolf, D. M., Vazirani, V. V., Arkin, A. P. (2005) "Diversity in times of adversity: probabilistic strategies in microbial survival games", J Theor Biol pp. 227-53
  • Wolf, D. M., Vazirani, V. V., Arkin, A. P. (2005) "A microbial modified prisoner's dilemma game: how frequency-dependent selection can lead to random phase variation", J Theor Biol pp. 255-62
  • Samoilov, M., Plyasunov, S., Arkin, A. P. (2005) "Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations", Proc Natl Acad Sci U S A pp. 2310-5
  • Flaherty, P., Giaever, G., Kumm, J., Jordan, M. I., Arkin, A. P. (2005) "A latent variable model for chemogenomic profiling", Bioinformatics pp. 3286-93
  • Alm, E. J., Huang, K. H., Price, M. N., Koche, R. P., Keller, K., Dubchak, I. L., Arkin, A. P. (2005) "The MicrobesOnline Web site for comparative genomics", Genome Res pp. 1015-22
  • Wolf, D. M., Arkin, A. P. (2003) "Motifs, modules and games in bacteria", Curr Opin Microbiol pp. 125-34
  • Rao, C. V., Arkin, A. P. (2003) "Stochastic chemical kinetics and the quasi-steady-state assumption: Application to the Gillespie algorithm", Journal of Chemical Physics pp. 4999-5010
  • Hucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., Arkin, A. P., Bornstein, B. J., Bray, D., Cornish-Bowden, A., Cuellar, A. A., Dronov, S., Gilles, E. D., Ginkel, M., Gor, V., Goryanin, II, Hedley, W. J., Hodgman, T. C., Hofmeyr, J. H., Hunter, P. J., Juty, N. S., Kasberger, J. L., Kremling, A., Kummer, U., Le Novere, N., Loew, L. M., Lucio, D., Mendes, P., Minch, E., Mjolsness, E. D., Nakayama, Y., Nelson, M. R., Nielsen, P. F., Sakurada, T., Schaff, J. C., Shapiro, B. E., Shimizu, T. S., Spence, H. D., Stelling, J., Takahashi, K., Tomita, M., Wagner, J., Wang, J. (2003) "The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models", Bioinformatics pp. 524-31
  • Alm, E., Arkin, A. P. (2003) "Biological networks", Curr Opin Struct Biol pp. 193-202
  • Wolf, D. M., Arkin, A. P. (2002) "Fifteen minutes of fim: control of type 1 pili expression in E. coli", Omics pp. 91-114
  • Rao, C. V., Wolf, D. M., Arkin, A. P. (2002) "Control, exploitation and tolerance of intracellular noise", Nature pp. 231-7
  • Gilman, A. G., Simon, M. I., Bourne, H. R., Harris, B. A., Long, R., Ross, E. M., Stull, J. T., Taussig, R., Bourne, H. R., Arkin, A. P., Cobb, M. H., Cyster, J. G., Devreotes, P. N., Ferrell, J. E., Fruman, D., Gold, M., Weiss, A., Stull, J. T., Berridge, M. J., Cantley, L. C., Catterall, W. A., Coughlin, S. R., Olson, E. N., Smith, T. F., Brugge, J. S., Botstein, D., Dixon, J. E., Hunter, T., Lefkowitz, R. J., Pawson, A. J., Sternberg, P. W., Varmus, H., Subramaniam, S., Sinkovits, R. S., Li, J., Mock, D., Ning, Y., Saunders, B., Sternweis, P. C., Hilgemann, D., Scheuermann, R. H., DeCamp, D., Hsueh, R., Lin, K. M., Ni, Y., Seaman, W. E., Simpson, P. C., O'Connell, T. D., Roach, T., Simon, M. I., Choi, S., Eversole-Cire, P., Fraser, I., Mumby, M. C., Zhao, Y., Brekken, D., Shu, H., Meyer, T., Chandy, G., Heo, W. D., Liou, J., O'Rourke, N., Verghese, M., Mumby, S. M., Han, H., Brown, H. A., Forrester, J. S., Ivanova, P., Milne, S. B., Casey, P. J., Harden, T. K., Arkin, A. P., Doyle, J., Gray, M. L., Meyer, T., Michnick, S., Schmidt, M. A., Toner, M., Tsien, R. Y., Natarajan, M., Ranganathan, R., Sambrano, G. R. (2002) "Overview of the Alliance for Cellular Signaling", Nature pp. 703-6
  • Gilman, A., Arkin, A. P. (2002) "GENETIC "CODE": Representations and Dynamical Models of Genetic Components and Networks", Annu Rev Genomics Hum Genet pp. 341-69
  • Rao, C. V., Arkin, A. P. (2001) "Control motifs for intracellular regulatory networks", Annu Rev Biomed Eng pp. 391-419
  • Arkin, A. P. (2001) "Synthetic cell biology", Curr Opin Biotechnol pp. 638-44
  • McAdams, H. H., Arkin, A. (1999) "It's a noisy business! Genetic regulation at the nanomolar scale", Trends Genet pp. 65-9
  • McAdams, H. H., Arkin, A. (1998) "Simulation of prokaryotic genetic circuits", Annu Rev Biophys Biomol Struct pp. 199-224
  • Arkin, A., Ross, J., McAdams, H. H. (1998) "Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells", Genetics pp. 1633-48
  • Swanson, C. A., Arkin, A. P., Ross, J. (1997) "An endogenous calcium oscillator may control early embryonic division", Proc Natl Acad Sci U S A pp. 1194-9
  • McAdams, H. H., Arkin, A. (1997) "Stochastic mechanisms in gene expression", Proc Natl Acad Sci U S A pp. 814-9
  • Arkin, A. P. , Ross, J. (1994) "Computational functions in biochemical reaction networks", Biophys. J. pp. 560-578
  • J. B. Lucks and S. A. Mortimer and C. Trapnell and S. Luof and S. Avirana and G. P. Schroth and L. Pachter and J. A. Doudna and A. P. Arkin (2011) "Multiplexed RNA structure characterization with selective 2?-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq)", PNAS pp. 11063-8
  • S. Aviran and C. Trapnell and J. B. Lucks and S. A. Mortimer and S. Luof and G. P. Schroth and J. A. Doudna and A. P. Arkin and L. Pachter (2011) "Modeling and automation of sequencing-based characterization of RNA structure", PNAS pp. 11069-74
  • Lara Rajeev, Eric G Luning, Paramvir S Dehal, Morgan N Price, Adam P Arkin and Aindrila Mukhopadhyay (2011) "Systematic Mapping of Two component Response Regulators to Gene Targets in a Model Sulfate Reducing Bacterium", Genome Biology pg. to appear

 

(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)

Status: current

One of the central challenges in biology is the mapping of the interactions among all the biochemical/biophysical components of the cell. Here we are concerned with methods for direct measurement or indirect inference of such interactions as a precursor to modeling the cellular networks.

Publications

  • Vlad, M. O., Arkin, A., Ross, J. (2004) "Response experiments for nonlinear systems with application to reaction kinetics and genetics", Proc Natl Acad Sci U S A pp. 7223-8
  • Vance, W., Arkin, A., Ross, J. (2002) "Determination of causal connectivities of species in reaction networks", Proc Natl Acad Sci U S A pp. 5816-21
  • Samoilov, M., Arkin, A., Ross, J. (2001) "On the deduction of chemical reaction pathways from measurements of time series of concentrations", Chaos pp. 108-114
  • Arkin, A.P , .Shen, P.-D., Ross, J. (1997) "A Test Case of Correlation Metric Construction of a Reaction Pathways from Measurements.", Science pg. 1275
  • Jajamovich, G.H., Wang, X., Arkin, A.P., Samoilov, M.S. (2011) "Bayesian multiple-instance motif discovery with BAMBI: inference of recombinase and transcription factor binding sites", Nucleic Acids Res pg. to appear

 

(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)
(alttext needed)
(description needed)

Status: current

Key to discovering the principles of operation of cellular systems is to understand how they operate in their natural environments. Microbes are found anywhere life can exist and thus they represent small programs (less than 10 Mb) that solve the problem of surviving in incredibly diverse environments and there have been 3.5 billion years of evolution with relatively short generation times to optimize their strategies. On top of these these organisms express activities that transform their environments to the benefit and detriment to human purposes and thus they represent an important resource to gain control over. Our goal is to discover the microbial contributions to geochemical processes in key environments and to map the networks of interaction among environmental factors and members of the microbial community that perform the central functions. We seek to define the principles of selection of microbial community function and composition in given environments and the molecular basis of the feedback from the communities to the physics and chemistry of those sites. We aim to uncover the biochemical/biophysical mechanisms of survival and activity in these environments from the individual microbe through to the cooperative and competitive communities to which it belongs. Core to our approach is the postulate that this is best accomplished by a multiscale approach that links carefully designed environmental experiments to more detailed follow-up studies in the laboratory. Currently, we are carrying out a good fraction of this work in collaboration with a Department of Energy project called ENIGMA (Ecosystems and Networks Integrated with Genes and Molecular Assemblies): A multiscale systems approach to microbial bioremediation, carbon sequestration, and energy production; from molecules to cells to communities. As part of this we have built or collaborated on building sophisticated computational resources such as MicrobesOnline, RegTransBase, RegPrecise and RegPredict which aid in the integration and analysis of complex comparative functional genomic data in phylogenetic context for understand gene and network function.

Publications

  • He, Z., Zhou, A., Baidoo, E., He, Q., Joachimiak, M. P., Benke, P., Phan, R., Mukhopadhyay, A., Hemme, C. L., Huang, K., Alm, E. J., Fields, M. W., Wall, J., Stahl, D., Hazen, T. C., Keasling, J. D., Arkin, A. P., Zhou, J. (2010) "Global transcriptional, physiological, and metabolite analyses of the responses of Desulfovibrio vulgaris hildenborough to salt adaptation", Appl Environ Microbiol pp. 1574-86
  • Price, M. N., Dehal, P. S., Arkin, A. P. (2010) "FastTree 2--approximately maximum-likelihood trees for large alignments", PLoS One pg. 9490
  • Novichkov, P. S., Laikova, O. N., Novichkova, E. S., Gelfand, M. S., Arkin, A. P., Dubchak, I., Rodionov, D. A. (2010) "RegPrecise: a database of curated genomic inferences of transcriptional regulatory interactions in prokaryotes", Nucleic Acids Res pp. 111-8
  • Dehal, P. S., Joachimiak, M. P., Price, M. N., Bates, J. T., Baumohl, J. K., Chivian, D., Friedland, G. D., Huang, K. H., Keller, K., Novichkov, P. S., Dubchak, I. L., Alm, E. J., Arkin, A. P. (2010) "MicrobesOnline: an integrated portal for comparative and functional genomics", Nucleic Acids Res pp. 396-400
  • Yang, Y., Harris, D. P., Luo, F., Xiong, W., Joachimiak, M., Wu, L., Dehal, P., Jacobsen, J., Yang, Z., Palumbo, A. V., Arkin, A. P., Zhou, J. (2009) "Snapshot of iron response in Shewanella oneidensis by gene network reconstruction", BMC Genomics pg. 131
  • Walker, C. B., Stolyar, S., Chivian, D., Pinel, N., Gabster, J. A., Dehal, P. S., He, Z., Yang, Z. K., Yen, H. C., Zhou, J., Wall, J. D., Hazen, T. C., Arkin, A. P., Stahl, D. A. (2009) "Contribution of mobile genetic elements to Desulfovibrio vulgaris genome plasticity", Environ Microbiol pp. 2244-52
  • Tang, Y. J., Martin, H. G., Dehal, P. S., Deutschbauer, A., Llora, X., Meadows, A., Arkin, A., Keasling, J. D. (2009) "Metabolic flux analysis of Shewanella spp. reveals evolutionary robustness in central carbon metabolism", Biotechnol Bioeng pp. 1161-9
  • Price, M. N., Dehal, P. S., Arkin, A. P. (2009) "FastTree: computing large minimum evolution trees with profiles instead of a distance matrix", Mol Biol Evol pp. 1641-50
  • Kazakov, A. E., Rodionov, D. A., Alm, E., Arkin, A. P., Dubchak, I., Gelfand, M. S. (2009) "Comparative genomics of regulation of fatty acid and branched-chain amino acid utilization in proteobacteria", J Bacteriol pp. 52-64
  • Jo, W. J., Kim, J. H., Oh, E., Jaramillo, D., Holman, P., Loguinov, A. V., Arkin, A. P., Nislow, C., Giaever, G., Vulpe, C. D. (2009) "Novel insights into iron metabolism by integrating deletome and transcriptome analysis in an iron deficiency model of the yeast Saccharomyces cerevisiae", BMC Genomics pg. 130
  • Elias, D. A., Mukhopadhyay, A., Joachimiak, M. P., Drury, E. C., Redding, A. M., Yen, H. C., Fields, M. W., Hazen, T. C., Arkin, A. P., Keasling, J. D., Wall, J. D. (2009) "Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation", Nucleic Acids Res pp. 2926-39
  • Bischofs, I. B., Hug, J. A., Liu, A. W., Wolf, D. M., Arkin, A. P. (2009) "Complexity in bacterial cell-cell communication: quorum signal integration and subpopulation signaling in the Bacillus subtilis phosphorelay", Proc Natl Acad Sci U S A pp. 6459-64
  • Wolf, D. M., Fontaine-Bodin, L., Bischofs, I., Price, G., Keasling, J., Arkin, A. P. (2008) "Memory in microbes: quantifying history-dependent behavior in a bacterium", PLoS ONE pg. 1700
  • Singh, A. H., Wolf, D. M., Wang, P., Arkin, A. P. (2008) "Modularity of stress response evolution", Proc Natl Acad Sci U S A pp. 7500-5
  • Price, M. N., Dehal, P. S., Arkin, A. P. (2008) "FastBLAST: homology relationships for millions of proteins", PLoS ONE pg. 3589
  • Price, M. N., Dehal, P. S., Arkin, A. P. (2008) "Horizontal gene transfer and the evolution of transcriptional regulation in Escherichia coli", Genome Biol pg. 4
  • Chivian, D., Brodie, E. L., Alm, E. J., Culley, D. E., Dehal, P. S., Desantis, T. Z., Gihring, T. M., Lapidus, A., Lin, L. H., Lowry, S. R., Moser, D. P., Richardson, P. M., Southam, G., Wanger, G., Pratt, L. M., Andersen, G. L., Hazen, T. C., Brockman, F. J., Arkin, A. P., Onstott, T. C. (2008) "Environmental genomics reveals a single-species ecosystem deep within Earth", Science pp. 275-8
  • Stolyar, S., He, Q., Joachimiak, M. P., He, Z., Yang, Z. K., Borglin, S. E., Joyner, D. C., Huang, K., Alm, E., Hazen, T. C., Zhou, J., Wall, J. D., Arkin, A. P., Stahl, D. A. (2007) "Response of Desulfovibrio vulgaris to alkaline stress", J Bacteriol pp. 8944-52
  • Price, M. N., Dehal, P. S., Arkin, A. P. (2007) "Orthologous Transcription Factors in Bacteria Have Different Functions and Regulate Different Genes", PLoS Comput Biol pg. 175
  • Mukhopadhyay, A., Redding, A. M., Joachimiak, M. P., Arkin, A. P., Borglin, S. E., Dehal, P. S., Chakraborty, R., Geller, J. T., Hazen, T. C., He, Q., Joyner, D. C., Martin, V. J., Wall, J. D., Yang, Z. K., Zhou, J., Keasling, J. D. (2007) "Cell-wide responses to low-oxygen exposure in Desulfovibrio vulgaris Hildenborough", J Bacteriol pp. 5996-6010
  • Kazakov, A. E., Cipriano, M. J., Novichkov, P. S., Minovitsky, S., Vinogradov, D. V., Arkin, A., Mironov, A. A., Gelfand, M. S., Dubchak, I. (2007) "RegTransBase--a database of regulatory sequences and interactions in a wide range of prokaryotic genomes", Nucleic Acids Res pp. 407-12
  • Bender, K. S., Yen, H. C., Hemme, C. L., Yang, Z., He, Z., He, Q., Zhou, J., Huang, K. H., Alm, E. J., Hazen, T. C., Arkin, A. P., Wall, J. D. (2007) "Analysis of a ferric uptake regulator (Fur) mutant of Desulfovibrio vulgaris Hildenborough", Appl Environ Microbiol pp. 5389-400
  • Price, M. N., Arkin, A. P., Alm, E. J. (2006) "The life-cycle of operons", PLoS Genet pg. 96
  • Price, M. N., Arkin, A. P., Alm, E. J. (2006) "OpWise: operons aid the identification of differentially expressed genes in bacterial microarray experiments", BMC Bioinformatics pg. 19
  • Mukhopadhyay, A., He, Z., Alm, E. J., Arkin, A. P., Baidoo, E. E., Borglin, S. C., Chen, W., Hazen, T. C., He, Q., Holman, H. Y., Huang, K., Huang, R., Joyner, D. C., Katz, N., Keller, M., Oeller, P., Redding, A., Sun, J., Wall, J., Wei, J., Yang, Z., Yen, H. C., Zhou, J., Keasling, J. D. (2006) "Salt Stress in Desulfovibrio vulgaris Hildenborough: an Integrated Genomics Approach", J Bacteriol pp. 4068-78
  • Leaphart, A. B., Thompson, D. K., Huang, K., Alm, E., Wan, X. F., Arkin, A., Brown, S. D., Wu, L., Yan, T., Liu, X., Wickham, G. S., Zhou, J. (2006) "Transcriptome profiling of Shewanella oneidensis gene expression following exposure to acidic and alkaline pH", J Bacteriol pp. 1633-42
  • He, Q., Huang, K. H., He, Z., Alm, E. J., Fields, M. W., Hazen, T. C., Arkin, A. P., Wall, J. D., Zhou, J. (2006) "Energetic consequences of nitrite stress in Desulfovibrio vulgaris Hildenborough, inferred from global transcriptional analysis", Appl Environ Microbiol pp. 4370-81
  • Clark, M. E., He, Q., He, Z., Huang, K. H., Alm, E. J., Wan, X. F., Hazen, T. C., Arkin, A. P., Wall, J. D., Zhou, J. Z., Fields, M. W. (2006) "Temporal transcriptomic analysis as Desulfovibrio vulgaris Hildenborough transitions into stationary phase during electron donor depletion", Appl Environ Microbiol pp. 5578-88
  • Chhabra, S. R., He, Q., Huang, K. H., Gaucher, S. P., Alm, E. J., He, Z., Hadi, M. Z., Hazen, T. C., Wall, J. D., Zhou, J., Arkin, A. P., Singh, A. K. (2006) "Global analysis of heat shock response in Desulfovibrio vulgaris Hildenborough", J Bacteriol pp. 1817-28
  • Brown, S. D., Martin, M., Deshpande, S., Seal, S., Huang, K., Alm, E., Yang, Y., Wu, L., Yan, T., Liu, X., Arkin, A., Chourey, K., Zhou, J., Thompson, D. K. (2006) "Cellular response of Shewanella oneidensis to strontium stress", Appl Environ Microbiol pp. 890-900
  • Wolf, D. M., Vazirani, V. V., Arkin, A. P. (2005) "Diversity in times of adversity: probabilistic strategies in microbial survival games", J Theor Biol pp. 227-53
  • Wolf, D. M., Vazirani, V. V., Arkin, A. P. (2005) "A microbial modified prisoner's dilemma game: how frequency-dependent selection can lead to random phase variation", J Theor Biol pp. 255-62
  • Rodionov, D. A., Dubchak, I. L., Arkin, A. P., Alm, E. J., Gelfand, M. S. (2005) "Dissimilatory metabolism of nitrogen oxides in bacteria: comparative reconstruction of transcriptional networks", PLoS Comput Biol pg. 55
  • Price, M. N., Huang, K. H., Arkin, A. P., Alm, E. J. (2005) "Operon formation is driven by co-regulation and not by horizontal gene transfer", Genome Res pp. 809-19
  • Price, M. N., Huang, K. H., Alm, E. J., Arkin, A. P. (2005) "A novel method for accurate operon predictions in all sequenced prokaryotes", Nucleic Acids Res pp. 880-92
  • Price, M. N., Alm, E. J., Arkin, A. P. (2005) "Interruptions in gene expression drive highly expressed operons to the leading strand of DNA replication", Nucleic Acids Res pp. 3224-34
  • Liu, Y., Gao, W., Wang, Y., Wu, L., Liu, X., Yan, T., Alm, E., Arkin, A., Thompson, D. K., Fields, M. W., Zhou, J. (2005) "Transcriptome Analysis of Shewanella oneidensis MR-1 in Response to Elevated Salt Conditions", J Bacteriol pp. 2501-7
  • Lee, W., St Onge, R. P., Proctor, M., Flaherty, P., Jordan, M. I., Arkin, A. P., Davis, R. W., Nislow, C., Giaever, G. (2005) "Genome-Wide Requirements for Resistance to Functionally Distinct DNA-Damaging Agents", PLoS Genet pg. 24
  • Rodionov, D. A., Dubchak, I., Arkin, A., Alm, E., Gelfand, M. S. (2004) "Reconstruction of regulatory and metabolic pathways in metal-reducing delta-proteobacteria", Genome Biol pg. 90
  • McAdams, H. H., Srinivasan, B., Arkin, A. P. (2004) "The evolution of genetic regulatory systems in bacteria", Nat Rev Genet pp. 169-78
  • Giaever, G., Flaherty, P., Kumm, J., Proctor, M., Nislow, C., Jaramillo, D. F., Chu, A. M., Jordan, M. I., Arkin, A. P., Davis, R. W. (2004) "Chemogenomic profiling: identifying the functional interactions of small molecules in yeast", Proc Natl Acad Sci U S A pp. 793-8
  • Gao, H., Wang, Y., Liu, X., Yan, T., Wu, L., Alm, E., Arkin, A., Thompson, D. K., Zhou, J. (2004) "Global transcriptome analysis of the heat shock response of Shewanella oneidensis", J Bacteriol pp. 7796-803
  • Wolf, D. M., Arkin, A. P. (2003) "Motifs, modules and games in bacteria", Curr Opin Microbiol pp. 125-34
  • S. Aviran and C. Trapnell and J. B. Lucks and S. A. Mortimer and S. Luof and G. P. Schroth and J. A. Doudna and A. P. Arkin and L. Pachter (2011) "Modeling and automation of sequencing-based characterization of RNA structure", PNAS pp. 11069-74