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Adam P Arkin

Publications and source records attributed to Adam P Arkin.

At least 37 records · Page 2Linked to original sources

Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity.

HIV-1 Tat transactivation is vital for completion of the viral life cycle and has been implicated in determining proviral latency. We present an extensive experimental/computational study of an HIV-1 model vector (LTR-GFP-IRES-Tat) and show that stochastic fluctuations in Tat influence the viral latency decision. Low GFP/Tat expression was found to generate bifurcating phenotypes with clonal populations derived from single proviral integrations simultaneously exhibiting very high and near zero GFP expression. Although phenotypic bifurcation (PheB) was correlated with distinct genomic integration patterns, neither these patterns nor other extrinsic cellular factors (cell cycle/size, aneuploidy, chromatin silencing, etc.) explained PheB. Stochastic computational modeling successfully accounted for PheB and correctly predicted the dynamics of a Tat mutant that were subsequently confirmed by experiment. Thus, Tat stochastics appear sufficient to generate PheB (and potentially proviral latency), illustrating the importance of stochastic fluctuations in gene expression in a mammalian system.

Biodiversity↗

Phosphatase localization in bacterial chemotaxis: divergent mechanisms, convergent principles.

Chemotaxis is the process by which cells sense changes in their chemical environment and move towards more favorable conditions. In divergent species of bacteria, the chemotaxis proteins localize to the poles of the cell and information is transferred to the flagellar motors through the phosphorylation of a soluble protein CheY. Using mathematical models and computer simulation, we demonstrate that phosphatase localization controls the spatial distribution of CheY-P in the cytosol at steady state. Remarkably, the location of the phosphatase is not conserved in different species of bacteria. The sole phosphatase in Escherichia coli is localized with the signaling complex and the primary phosphatase in Bacillus subtilis is localized at the flagellar motors. Despite these alternate pathway structures, both designs minimize differences in the concentration of phosphorylated CheY proximal to each motor unlike a design where the phosphatase is freely diffusing in the cytoplasm. These results suggest that motile bacteria have evolved alternate mechanisms to ensure that each motor receives roughly the same signal at steady state. The hypothesis is that complex networks have evolved to satisfy certain design principles in order to function robustly. While specific mechanisms are different, the underlying principles of phosphatase localization in E. coli and B. subtilis appear to be the same.

Bacillus subtilis↗

Interruptions in gene expression drive highly expressed operons to the leading strand of DNA replication.

In bacteria, most genes are on the leading strand of replication, a phenomenon attributed to collisions between the DNA and RNA polymerases. In Escherichia coli, these collisions slow the movement of the replication fork through actively transcribed genes only if they are coded on the lagging strand. For genes on both strands, however, these collisions sever nascent transcripts and interrupt gene expression. Based on these observations, we propose a new theory to explain strand bias: genes whose expression is important for fitness are selected to the leading strand because this reduces the duration of these interruptions. Our theory predicts that multi-gene operons, which are subject to longer interruptions, should be more strongly selected to the leading strand than singleton transcripts. We show that this is true even after controlling for the tendency for essential genes, which are strongly biased to the leading strand, to occur in operons. Our theory also predicts that other factors that are associated with strand bias should have stronger effects for genes that are in operons. We find that expression level and phylogenetic ubiquity are correlated with strand bias for both essential and non-essential genes, but only for genes in operons.

DNA Replication↗

A latent variable model for chemogenomic profiling.

MOTIVATION: In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure. RESULTS: We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that requires genes to belong to a single cluster. Drugs such as miconazole and fenpropimorph that have different targets but similar off-target genes are clustered more accurately by the model-based framework. We show that this model is useful for summarizing the relationship among treatments and genes affected by those treatments in a compendium of microarray profiles. AVAILABILITY: Supplementary information and computer code at http://genomics.lbl.gov/llda.

Computer Simulation↗

A microbial modified prisoner's dilemma game: how frequency-dependent selection can lead to random phase variation.

Random phase variation (RPV) is a control strategy in which the expression of a cell state or phenotype randomly alternates between discrete 'on' and 'off' states. Though this mode of control is common for bacterial virulence factors like pili and toxins, precise conditions under which RPV confers an advantage have not been well defined. In Part I of this study, we predicted that fluctuating environments select for RPV if transitions between different selective environments cannot be reliably sensed (J. Theor. Biol. (2005)). However, selective forces both inside and outside of human hosts are also likely to be frequency dependent in the sense that the fitnesses of some bacterial states are greatest when rare. Here we show that RPV at slow rates can provide a survival advantage in such a frequency-dependent environment by generating population heterogeneity, essentially mimicking a polymorphism. More surprisingly, RPV at a faster 'optimal' rate can shift the population composition toward an optimal growth rate that exceeds that possible for polymorphic populations, but this optimal strategy is not evolutionarily stable. The population would be most fit if all cells randomly phase varied at the optimal rate, but individual cells have a growth-rate incentive to defect (mutate) to other switching rates or non-phase variable phenotype expression, leading to an overall loss of fitness of the individual and the population. This scenario describes a modified Prisoner's Dilemma game (Evolution and the Theory of Games, Cambridge University Press, Cambridge, New York, 1982, viii, 224pp.; Nature 398 (6726) (1999) 367), with random phase variation at optimal switching rates serving as the cooperation strategy.

Bacteria↗

Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations.

Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics.

Enzyme Stability↗

A novel method for accurate operon predictions in all sequenced prokaryotes.

We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacter pylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from six phylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC 6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

Base Sequence↗

Diversity in times of adversity: probabilistic strategies in microbial survival games.

Population diversification strategies are ubiquitous among microbes, encompassing random phase-variation (RPV) of pathogenic bacteria, viral latency as observed in some bacteriophage and HIV, and the non-genetic diversity of bacterial stress responses. Precise conditions under which these diversification strategies confer an advantage have not been well defined. We develop a model of population growth conditioned on dynamical environmental and cellular states. Transitions among cellular states, in turn, may be biased by possibly noisy readings of the environment from cellular sensors. For various types of environmental dynamics and cellular sensor capability, we apply game-theoretic analysis to derive the evolutionarily stable strategy (ESS) for an organism and determine when that strategy is diversification. We find that: (1) RPV, effecting a sort of Parrondo paradox wherein random alternations between losing strategies produce a winning strategy, is selected when transitions between different selective environments cannot be sensed, (2) optimal RPV cell switching rates are a function of environmental lifecycle asymmetries and environmental autocorrelation, (3) probabilistic diversification upon entering a new environment is selected when sensors can detect environmental transitions but have poor precision in identifying new environments, and (4) in the presence of excess additive noise, low-pass filtering is required for evolutionary stability. We show that even when RPV is not the ESS, it may minimize growth rate variance and the risk of extinction due to 'unlucky' environmental dynamics.

Bacteria↗

Operon formation is driven by co-regulation and not by horizontal gene transfer.

The organization of bacterial genes into operons was originally ascribed to the benefits of co-regulation. More recently, the "selfish operon" model, in which operons are formed by repeated gain and loss of genes, was proposed. Indeed, operons are often subject to horizontal gene transfer (HGT). On the other hand, non-HGT genes are particularly likely to be in operons. To clarify whether HGT is involved in operon formation, we identified recently formed operons in Escherichia coli K12. We show that genes that have homologs in distantly related bacteria but not in close relatives of E. coli--indicating HGT--form new operons at about the same rates as native genes. Furthermore, genes in new operons are no more likely than other genes to have phylogenetic trees that are inconsistent with the species tree. In contrast, essential genes and ubiquitous genes without paralogs--genes believed to undergo HGT rarely--often form new operons. We conclude that HGT is not a cause of operon formation but instead promotes the prevalence of pre-existing operons. To explain operon formation, we propose that new operons reduce the amount of regulatory information required to specify optimal expression patterns and infer that operons should be more likely to evolve than independent promoters when regulation is complex. Consistent with this hypothesis, operons have greater amounts of conserved regulatory sequences than do individually transcribed genes.

Escherichia coli K12↗

The MicrobesOnline Web site for comparative genomics.

At present, hundreds of microbial genomes have been sequenced, and hundreds more are currently in the pipeline. The Virtual Institute for Microbial Stress and Survival has developed a publicly available suite of Web-based comparative genomic tools (http://www.microbesonline.org) designed to facilitate multispecies comparison among prokaryotes. Highlights of the MicrobesOnline Web site include operon and regulon predictions, a multispecies genome browser, a multispecies Gene Ontology browser, a comparative KEGG metabolic pathway viewer, a Bioinformatics Workbench for in-depth sequence analysis, and Gene Carts that allow users to save genes of interest for further study while they browse. In addition, we provide an interface for genome annotation, which like all of the tools reported here, is freely available to the scientific community.

Animals↗

An allosteric model for transmembrane signaling in bacterial chemotaxis.

Bacteria are able to sense chemical gradients over a wide range of concentrations. However, calculations based on the known number of receptors do not predict such a range unless receptors interact with one another in a cooperative manner. A number of recent experiments support the notion that this remarkable sensitivity in chemotaxis is mediated by localized interactions or crosstalk between neighboring receptors. A number of simple, elegant models have proposed mechanisms for signal integration within receptor clusters. What is a lacking is a model, based on known molecular mechanisms and our accumulated knowledge of chemotaxis, that integrates data from multiple, heterogeneous sources. To address this question, we propose an allosteric mechanism for transmembrane signaling in bacterial chemotaxis based on the "trimer of dimers" model, where three receptor dimers form a stable complex with CheW and CheA. The mechanism is used to integrate a diverse set of experimental data in a consistent framework. The main predictions are: (1) trimers of receptor dimers form the building blocks for the signaling complexes; (2) receptor methylation increases the stability of the active state and retards the inhibition arising from ligand-bound receptors within the signaling complex; (3) trimer of dimer receptor complexes aggregate into clusters through their mutual interactions with CheA and CheW; (4) cooperativity arises from neighboring interaction within these clusters; and (5) cluster size is determined by the concentration of receptors, CheA, and CheW. The model is able to explain a number of seemingly contradictory experiments in a consistent manner and, in the process, explain how bacteria are able to sense chemical gradients over a wide range of concentrations by demonstrating how signals are integrated within the signaling complex.

Allosteric Regulation↗

The Bacillus subtilis sin operon: an evolvable network motif.

The strategy of combining genes from a regulatory protein and its antagonist within the same operon, but controlling their activities differentially, can lead to diverse regulatory functions. This protein-antagonist motif is ubiquitous and present in evolutionarily unrelated regulatory pathways. Using the sin operon from the Bacillus subtilis sporulation pathway as a model system, we built a theoretical model, parameterized it using data from the literature, and used bifurcation analyses to determine the circuit functions it could encode. The model demonstrated that this motif can generate a bistable switch with tunable control over the switching threshold and the degree of population heterogeneity. Further, the model predicted that a small perturbation of a single critical parameter can bias this architecture into functioning like a graded response, a bistable switch, an oscillator, or a pulse generator. By mapping the parameters of the model to specific DNA regions and comparing the genomic sequences of Bacillus species, we showed that phylogenetic variation tends to occur in those regions that tune the switch threshold without disturbing the circuit function. The dynamical plasticity of the protein-antagonist operon motif suggests that it is an evolutionarily convergent design selected not only for particular immediate function but also for its evolvability.

Bacillus subtilis↗

Design and diversity in bacterial chemotaxis: a comparative study in Escherichia coli and Bacillus subtilis.

Comparable processes in different species often involve homologous genes. One question is whether the network structure, in particular the feedback control structure, is also conserved. The bacterial chemotaxis pathways in E. coli and B. subtilis both regulate the same task, namely, excitation and adaptation to environmental signals. Both pathways employ many orthologous genes. Yet how these orthologs contribute to network function in each organism is different. To investigate this problem, we propose what is to our knowledge the first computational model for B. subtilis chemotaxis and compare it to previously published models for chemotaxis in E. coli. The models reveal that the core control strategy for signal processing is the same in both organisms, though in B. subtilis there are two additional feedback loops that provide an additional layer of regulation and robustness. Furthermore, the network structures are different despite the similarity of the proteins in each organism. These results demonstrate the limitations of pathway inferences based solely on homology and suggest that the control strategy is an evolutionarily conserved property.

Acclimatization↗

Chemogenomic profiling: identifying the functional interactions of small molecules in yeast.

We demonstrate the efficacy of a genome-wide protocol in yeast that allows the identification of those gene products that functionally interact with small molecules and result in the inhibition of cellular proliferation. Here we present results from screening 10 diverse compounds in 80 genome-wide experiments against the complete collection of heterozygous yeast deletion strains. These compounds include anticancer and antifungal agents, statins, alverine citrate, and dyclonine. In several cases, we identified previously known interactions; furthermore, in each case, our analysis revealed novel cellular interactions, even when the relationship between a compound and its cellular target had been well established. In addition, we identified a chemical core structure shared among three therapeutically distinct compounds that inhibit the ERG24 heterozygous deletion strain, demonstrating that cells may respond similarly to compounds of related structure. The ability to identify on-and-off target effects in vivo is fundamental to understanding the cellular response to small-molecule perturbants.

Antifungal Agents↗

Biological networks.

Recent advances in high-throughput methods have provided us with a first glimpse of the overall structure of molecular interaction networks in biological systems. Ultimately, we expect that such information will change how we think about biological systems in a fundamental way. Instead of viewing the genetic parts list of an organism as a loose collection of biochemical activities, in the best case, we anticipate discrete networks of function to bridge the gap between genotype and phenotype, and to do so in a more profound way than the current qualitative classification of linked reactions into familiar pathways, such as glycolysis and the MAPK signal transduction cascades. At the present time, however, we are still far from a complete answer to the most basic question: what can we learn about biology by studying networks? Promising steps in this direction have come from such diverse approaches as mathematical analysis of global network structure, partitioning networks into functionally related modules and motifs, and even de novo design of networks. A complete picture will probably require integrating the data obtained from all of these approaches with modeling efforts at many different levels of detail.

Amino Acid Motifs↗

Motifs, modules and games in bacteria.

Global explorations of regulatory network dynamics, organization and evolution have become tractable thanks to high-throughput sequencing and molecular measurement of bacterial physiology. From these, a nascent conceptual framework is developing, that views the principles of regulation in term of motifs, modules and games. Motifs are small, repeated, and conserved biological units ranging from molecular domains to small reaction networks. They are arranged into functional modules, genetically dissectible cellular functions such as the cell cycle, or different stress responses. The dynamical functioning of modules defines the organism's strategy to survive in a game, pitting cell against cell, and cell against environment. Placing pathway structure and dynamics into an evolutionary context begins to allow discrimination between those physical and molecular features that particularize a species to its surroundings, and those that provide core physiological function. This approach promises to generate a higher level understanding of cellular design, pathway evolution and cellular bioengineering.

Animals↗

Theoretical design of a gene therapy to prevent AIDS but not human immunodeficiency virus type 1 infection.

Recent reports confirm that, due to the presence of long-lived, latently infected cell populations, eradication of human immunodeficiency virus type 1 (HIV-1) from infected patients by using antiretroviral drugs will be exceedingly difficult. An alternative to virus eradication may be to use gene therapy to induce a pseudo-latent state in virus-producing cells, thus transforming HIV-1 into a lifelong, but manageable, virus. Conditionally replicating HIV-1 (crHIV-1) gene therapy vectors provide an avenue for subduing HIV-1 expression in infected cells (by creating a parasite, crHIV-1, of the parasite HIV-1), potentially reducing the HIV-1 set point and delaying AIDS onset. Development of crHIV-1 vectors has proceeded in vitro, but the requirements for a crHIV-1 vector to proliferate and persist in vivo have not been explored. We expand a widely accepted mathematical model of HIV-1 in vivo dynamics to include a crHIV-1 gene therapy virus and derive a simple criterion for designing crHIV-1 viruses that will persist in vivo. The model introduces only two new parameters-HIV-1 inhibition and crHIV-1 production-and both can be experimentally engineered and controlled. Analysis demonstrates that crHIV-1 gene therapy can indefinitely reduce HIV-1 set point to levels comparable to those achieved with highly active antiretroviral therapy, provided crHIV-1 production is more efficient than HIV-1. Paradoxically, highly efficient therapeutic inhibition of HIV-1 was found to be disadvantageous. Thus, the field may benefit by shifting the search for more potent antiviral genes toward engineering optimized therapy viruses that package ultra-efficiently while downregulating viral production moderately.

Acquired Immunodeficiency Syndrome↗