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Interactions of vortices in viscous, incompressible fluid flows. Working with R. Nagem, G. Sandri both faculty in Aerospace and Mechanical Engineering) and Wayne, grad student David Umansky has been developing new numerical methods for studying the interactions of vortices, using recent theoretical work on the long-time asymptotics of solutions of the Navier-Stokes equations due to Gallay and Wayne. These methods may be thought of as systematic refinements of the Kirchoff vortex method. The method are very "fast" in comparison with ordinary numerical solutions of the Navier-Stokes equation since they reduce the problem to one of solving relatively small systems of ordinary differential equations.
Interactions of solitary waves in non-integrable, infinite dimensional Hamiltonian systems In infinite dimensional integrable Hamiltonian systems (like the Korteweg-de Vries equation for example) solitons possess the remarkable property of passing through each other and retaining the same shape they had after the collision as they did before. This is no longer expected to be the case in non-integrable systems. Postdoc Aaron Hoffman and Wayne are studying the collision of solitary waves in the Fermi-Pasta-Ulam model to understand exactly what sorts of behaviors can be expected. In particular, they are studying the stability (over infinite time intervals) of solutions whose initial conditions are two, counter-propagating solitary waves and they are also investigating whether for special initial conditions there exist solutions that appear asymptotically to consist of two (or more) solitary waves with no radiation, as is the case for the multi-soliton solutions of the integrable equations.
Asymptotics of hyperbolic-parabolic conservation laws. With G. van Baalen and C.E. Wayne, postdoc Nikola Popovic has been investigating the large-time behavior of solutions to systems of conservation laws. Often, one can derive formal asymptotic equations that capture the essential dynamics of the original problem, but are more tractable. In physical systems, these formal equations are typically of parabolic type. They have been studying if the solutions to such systems are approximated well by the corresponding asymptotic states when the original problem is hyperbolic, and in particular studying how the hyperbolic and parabolic natures of these problems interact..
Cellular automata and nonlinear diffusion . A cellular automaton is a uniform array of cells which can each have definite states that change over time according to fixed rules. The dynamics of these automata can often be related to those of certain partial differential equations. With T.J. Kaper, S.M. Marotta, and C.E. Wayne, Popovic used cellular automaton models to study one particular set of rules, called 'Critters,' introduced to mimic quantum mechanical phenomena. They have been studying the relationship of this type of automaton to a class of reaction-diffusion equations with density-dependent diffusivities.
Bioremediation. Former grad student Margaret Beck worked with Kaper on the Oya-Valocchi model of bioremediation, carrying out stability analysis of the travelling waves and determining how the Hopf bifurcation to time-periodic traveling waves and the associated incomplete remediation depend quantitatively on parameter values. This information is useful for the experimentalists, including those after whom the model is named.
Integro-differential equations in neuroscience. Working with Kaper, Marina Bevzushenko carried out a mathematical analysis of Amari type models of integro-differential equations arising in mathematical neuroscience. She showed that Amari's necessary conditions for stability of single bump and two-bump solutions are also sufficient. She also introduced a piece-wise linear coupling function (of Mexican hat type), and showed how to use it to calculate a number of quantities for which no closed-form method exists yet for smooth coupling functions.
Power geometry and matched asymptotics. With Kaper and Wayne, Grad student Oleg Mikitchenko and Popovic are studying whether the power geometry method developed by A. Brjuno to study the behavior of ordinary differential equations near singular points can be used to give an algorithmic, computationally efficient method for approximating the solutions of singularly perturbed ordinary differential equations and partial differential equations.
Mixed-Mode Oscillations and the Canard Phenomenon. Postodc Nicola Popovic, working with Kopell, N.Krupa and former postdoc H. Rotstein, has been investigating the irregular firing patterns that have been observed in the so-called Wilson-Callaway model for the mammalian dopaminergic neuron. They have investigated that model from a geometric point of view by formulating an analytically simpler 'toy' system which, nevertheless, reproduces the essential features of the Wilson-Callaway equations. These features include “mixed mode oscillations”, which are characterized by a combination of small-amplitude oscillations and large-amplitude excursions, and occur frequently in multiple-scale systems of differential equations. They have shown that the observed mixed-mode dynamics is due to a canard phenomenon.
Critical Wave Speeds-Desingularization and Asymptotics . Popovic has also been working with Kaper and F. Dumortier on the so-called critical wave speed in scalar reaction-diffusion equations, which separates traveling wave solutions of different decay rates at a rest state. They have studied a modified family of equations, where the reaction terms are 'cut off' appropriately. This modification is motivated by the fact that such equations often arise in the large-scale limit of discrete many-particle systems. They have shown that the 'cut-off' critical speed is typically smaller than what is expected from the continuum limit; moreover, they have established rigorously the leading-order asymptotics of that speed for a wide array of cut-off functions.
Reduction for Michaelis-Menten Kinetics with Diffusion With L. Kalachev, H.G. Kaper, T.J. Kaper, A. Zagaris (former grad student), Popovic studied the Michaelis-Menten mechanism, which models the kinetics of numerous fundamental reaction processes. In its simplest form, it involves a substrate that reacts reversibly with enzyme, forming a complex which is transformed irreversibly into a product. Dimension reduction has traditionally been achieved by making use of conservation relations and by exploiting the fast-slow structure of the equations. The current work has been investigating how the situation changes if the species are additionally allowed to diffuse, and in what regimes a reduction is still possible.
Analysis of RG methods for differential equations. The RG method has been proposed as a general, algorithmic asymptotic method for solving perturbed differential equations that reproduces the results of many disparate asymptotic methods. In collaboration with Kaper, DeVille (Courant), and Josic (Houston), graduate student Matt Holzer has been studying the RG method with the aim of providing a mathematical understanding for the method. On one hand, they have shown that the method is equivalent to normal form theory, and hence rigorous, for certain classes of systems. On the other hand, they are in the process of extending the method to systems for which normal form theory has not been developed, for example, non-autonomous systems and partial differential equations.
Formation of hippocampal gamma assemblies by O-LM cells. Working with former postdoc Horacio Rotstein and Kopell, postdoc Adriano Tort constructed a biophysical hippocampal network composed of three distinct cell types (pyramidal, basket and O-LM cells) and used it to show that the anatomical and physiological properties of O-LM cells make them suitable to coordinate coherent cell assemblies along the longitudinal axis of the hippocampus associated with entorhinal cortex.. The cells involved in the cell assemblies are synchronous at the fast gamma rhythm period (~ 40 - 90 Hz), even though the O-LM cells themselves fire only at the slower theta rhythm (~ 4-12 Hz). The work was based on experimental evidence provided by T. Gloveli showing distinct axonal projection patterns of O-LM cells in the transverse and longitudinal axis of the hippocampus, with a preference for gamma oscillations in slices cut in the transverse direction and theta oscillations in slices cut in the longitudinal direction.
Analysis of the interaction of gamma and theta rhythms in the hippocampus. Grad student Paola Malerba is working with Kopell on a more detailed understanding of the dynamics of the theta-gamma model in Gloveli et al. Starting from a two-cells network involving one O-LM cell and one I-cell inhibiting each other, they are investigation the 1:n locked patterns (meaning n I-spikes per O-LM-cell cycle), with n increasing as the drive to the I-cell is increased, and elucidating which bifurcations lead to this spike-insertion phenomenon. The series of bifurcations is helping to explain why the frequencies of the gamma and theta oscillations seems to have a fixed ratio as they are changed by increasing excitation.
Altered rhythmogenesis in mesial temporal lobe epilepsy (mTLE): Postdoc Tort and Kopell, have produced a biophysical computational model of in vivo and in vitro physiological evidence for altered rhythmogenesis in the hippocampus in a mouse model of mTLE (particularly at theta and gamma bands). The data were provided by T. Gloveli and T. Dugladze, who collaborated in the study. This study confirmed the chief role of O-LM cells in the generation of the theta rhythm within the hippocampus and also provided indirect evidence for the role of the theta rhythm in cognitive processes.
Hybrid network studies of rhythm switching in hippocampus. Working with White and Kopell, graduate student Tilman Kispersky is using dynamic clamp techniques to study hippocampal gamma and theta rhythms. In brain slices, theta (~8 Hz) and gamma (~40 Hz) rhythms coexist and the relative levels of each are dependent on membrane currents, synaptic strength and network organization. Kispersky is systematically testing which network properties underlie generation of gamma or theta rhythms and what allows coexistence or transitions between the two. He plans to use modeling and dynamic clamp to show that perturbing the membrane currents that underlie theta rhythms in oriens-lacunosum- moleculare (O-LM) interneurons changes the relative amount of theta and gamma. Using these perturbations the network can be biased to preferentially generate theta rhythms, as occurs in models of schizophrenia.
Gamma rhythm switches in entorhinal cortex Working with Kopell, M. Cunningham and M. Whittington, grad student Kispersky and former postdoc Jozsi Jalics modeled different versions of the gamma (30-80 Hz) and theta (4-12 Hz) oscillations of the medial entorhinal cortex. Kainate receptor agonists have been shown to elicit strong persistent gamma activity, which is thought to arise from the reciprocal interactions between pyramidal cells and basket cell interneurons, with a theta modulation of the gamma activity. In the present work, they present evidence for a new type of interneuron that fires at theta frequencies, while the inhibitory basket (I) interneurons fire at gamma frequencies under kainate application. Introduction of NMDA receptor anagonists leads to a large decrease in gamma power, while the theta-producing interneurons switch from theta to gamma frequency firing, and stellate cells increase their firing rate. The model helps explain the mechanisms for the NMDA receptor antagonist induced rhythm switches and leads to predictions about the nature of the synaptic connections in the network.
Rhythm switching in an in vitro model of somatosensory cortex. Working with M Whittington, (University of Newcastle), R. Traub (Downstate Medical School of SUNY) and Kopell, postdoc Mark Kramer developed a mathematical model of rhythm switching observed in rat somatosensory cortex. Observational data reveal a transition from coexistent gamma (30 Hz - 80 Hz) and beta2 (20 Hz - 30 Hz) rhythms in the deep and superficial cortical layers, respectively, to a synchronous beta1 (13 Hz - 20 Hz) rhythm in all cortical layers. To model this system, Kramer and Kopell have constructed a biophysical computational model of cells in rat somatosensory cortex and predicted which synaptic interactions between cells produce the transition to the beta1 rhythm.
Rhythm switching in an in vivo olfactory system. Post doc Jorge Brea is working with Dr. Nancy Kopell and in collaboration with Dr. Leslie Kay's Lab at Chicago University. They model the mechanisms by which different gamma and beta oscillation emerge in the rat olfactory bulb while performing different odor discrimination learning tasks. These experiments where carried out by Jennifer Beshel and Claire Martin working in Dr. Kay's Lab. One of the central questions in this work is how the piriform cortex (PC) and the olfactory bulb (OB) interact in order to switch from a predominant gamma (~30-90 Hz) activity to a predominant beta (~12-30 Hz) activity in the OB as the rat successfully learns the task. The model they are constructing looks at how plasticity between the OB and PC together with the existing delayed feedback from the PC to the OB can generate switching from gamma to beta frequencies of the local field potential in the OB. The work builds on the work of previous postdoc Ehud Siven.
Inhibitory rhythms in the olfactory bulb with periodic inputs. Working with Kopell, in collaboration with the Kay lab, grad student Baldur Hedinnson has constructed a single compartment model of the (inhibitory) granule cells (GC) of the mammalian olfactory bulb, using parameters from detailed biological models. The model is motivated by evidence that the low frequency gamma rhythm, not associated with respiration, is eliminated in a mouse without inhibitory connections to the granule cells. The dynamics of this model displays antiphase solutions in the presence of mild heterogeneity, in contrast to other models of similar inhibitory neurons; the difference has been tracked down to the properties of the activation curve of the standard K+ channel. Exciting the GCs with phasic input (as a signal from the piriform cortex) makes synchrony more robust for certain frequency ranges.
Forced rhythms in the auditory system of normal and schizophrenic subjects. Working with S. Stufflebeam (Mass General Imaging Center_ and Peter Siekmeier (McLean Hospital), grad student Dorea Vieling-Classen has been studing the dynamics of the rhythmic electrical responses of the auditory cortex of normals and persons with schizophrenia when given periodic stimuli. The modeling is used to understand how known deficits at the cellular and synaptic level, in particular, alterations to cortical fast spiking interneurons, might affect responses to auditory stimuli. Mathematical analysis of the models using discrete dynamic maps has provided insight into how inhibitory changes can impact drive response in the gamma/beta range.
Temporal Coding of Time varying Stimuli Postoc Maoz Shamir, with Sen and S. Colburn, studied a model for the noisy dynamic response of a cell to natural stimuli, such as the response of songbird auditory neurons to birdsong stimuli. In contrast to recent claims, they have shown that the information content of the neural dynamic response scales linearly with the overall observation time of the response, thus, enabling accurate sensory representation even in the presence of temporal noise correlations. They found that finite temporal resolution is sufficient for obtaining most of the information from the cell’s dynamic response. This finite time scale is related to the response properties of the cell.
Discrimination of natural sounds by auditory neurons. Graduate student Rajiv Narayan has been extending his previous work on neurons in the songbird auditory cortex analog field L. Narayan previously worked on the analysis of neural discrimination of birdsongs, which has already resulted in three publications (one modeling and two experimental). Recently he has focused on investigating how different forms of background noise affect neural discrimination. To do this he recorded neural responses to songs embedded in different types of background maskers e.g., chorus of other birds and then analyzed the impact of background maskers on discrimination sounds. His results reveal two distinct types of interference due to maskers that can significantly reduce neural discriminability. This reduction may lie at the heart of the difficulty of the so-called “cocktail party problem” i.e., the problem of separating auditory objects from complex noisy backgrounds. These results have led to a conference proceeding and a submitted manuscript. Ultimately, these results can be related to psychophysical results on the perception of sound mixtures by humans (in collaboration with Barbara Shinn-Cunningham’s lab at BU) and birds (in collaboration with Micheal Dent’s lab at SUNY, Buffalo).
Recording neural responses of songbirds. Most of the current data on auditory responses to natural sounds in field L comes from anesthetized songbirds. Graduate student Gilberto Grana is continuing his work with Sen in recording neural responses in field L of awake birds. Previously, Grana obtained data from the awake experiments, which has contributed to two papers. His recent experiments have focused on assessing the stability/variability of spectral temporal receptive fields (STRFs) of field L neurons in awake birds. His results indicate diverse levels of STRF stability with some neurons showing relatively stable STRFs for several hours. His approach will now allow them to identify candidate neurons that would be well suited for plasticity protocols that require longer durations. He also finds that different STRF parameters can show different degrees of stability/variability. This suggests that certain STRF parameters can be more sensitive in revealing changes in the STRF during plasticity.
Variations in auditory stimulus parameters. An important problem for any sensory system is to deal with variations in stimulus parameters. Postdoc Cyrus Billimoria has continued his work with Sen investigating invariance of neural discrimination and recognition in field L by analyzing neural responses to song variations, which mimic natural variations e.g., songs at different intensities and different renditions of the same bird’s song. His results indicate the presence of neurons in field L that are surprisingly robust to variations in intensity and may contribute towards intensity invariant discrimination and recognition of individual songs. Billimoria has also produced results on the effect of timing variations in different renditions of the same song, as well as artificially “warping” the song. This is related to work of postdoc Shamir and collaborators on the processing of time-varying stimuli..
Auditory cortex response to different stimuli, using coding from gamma oscillators. Shamir, working with Kopell, O. Ghitza and S. Epstein, studied how a network that produces gamma oscillators can responds selectively to different time varying stimuli that last several gamma cycles. The research shows that the intrinsic oscillatory behavior of the network enables the system to respond to the stimulus only during specific time intervals, thus, discretizing the neural response. This discretization allows the system to have a robust response to stimuli that are time-stretched by ~20%. They further study the relation between the sensitivity and the robustness of the response to the stimulus.
Single Best Cell (SBC) verses Population Coding Hypotheses. Shamir investigated the dependence of the SBC-accuracy on the population size. The research shows that although SBC accuracy grows with the population size, this improvement is extremely weak and in-line with empirical results showing that the psychophysical accuracy is comparable to information content in a single cell response. He is also working on understanding data suggesting that the same brain region coding for the same stimulus feature may exhibit both kinds of coding paradigms.
Epileptiform activity in hippocampal brain slices. Graduate student, Kyle Lillis, working with White has developed a new technique for two-photon imaging of calcium dynamics in brain tissue. This novel laser-scanning strategy provides a mechanism to sample from many cells distributed across a large area with high temporal and spatial resolution. Lillis is now beginning to apply this technique to study the spread of epileptiform activity in hippocampal brain slices. The object of this study is to better understand the spatiotemporal dynamics of interictal bursting and seizure-like events induced by 4-aminopyridine. In a collaboration with Mark Kramer, social networking analyses will be applied to quantify the correlation structure in the observed neuronal populations. These techniques are being used to understand how the voltage activity of seizure-like events propagates in the hippocampus and exploring new methods for seizure prevention.
Characterizing Emergent Network Topology at Seizure Onset in Humans: Postdoc Mark Kramer, in joint work with Dr. Heidi Kirsch (UCSF) and Kolaczyk, is working on using networks and network summary measures to characterize cortical-level changes in the brain at the onset of epileptic seizures in humans. Network analysis of ECoG data quantifies a marked decrease in connectivity of these networks, as well as an accompanying disruption in apparent `communication patterns'. The focus of the project is on using network analysis methods to summarize structure in network graph representations of coupling among ECoG electrode readings, with an eye towards assessing clinically relevant differences in these networks prior to and during epileptic seizure episodes. The aim is to suggest novel targets for therapeutic interventions.
Mechanisms of action potential initiation . With Kopell and Costa Colbert (Univ. of Houston), postdoc Stefanos Folias has been focused on developing a multicompartmental model of a single pyramidal cell that describes and elucidates some of the mechanisms of action potential initiation, which up until now have not been adequately addressed. With this model, he has investigated the effects of synaptic depolarization on action potential initiation of pyramidal cells by axoaxonic cells. Axoaxonic cells exclusively synapse with the initial segment of the axon, which is a primary location of action potential initiation. He is also working on embedding a simpler version of this compartmental model into a network of pyramidal cells, basket cells and axoaxonic cells to understand the effect of axoaxonic depolarization on the generation of Gamma oscillations.
Modulation of intrinsic theta oscillations by background synaptic conductance fluctuations in entorhinal stellate cells. Previous work has established that stellate cells produce prominent subthreshold oscillations in the membrane voltage response within the theta range (3-8 Hz). It has been speculated that intrinsic stellate oscillations may play an important role in establishing network behavior both in the entorhinal cortex and hippocampus. However, it has not been established how moderate conductance fluctuations, which are likely during in vivo-like conditions, will modulate intrinsic membrane dynamics. Additionally, it has not been established whether subthreshold membrane oscillatory information is carried into the spiking regime of stellate cells. A current study by postdoc Fernando Fernandez and White asks two questions. 1) Does subthreshold oscillatory information in stellate cells come through in the spike train? 2) How do moderate levels of synaptic conductance fluctuations introduced via dynamic-clamp modify intrinsic stellate dynamics?
Stellate cells of the entorhinal cortex. Grad student Michael Economo has been studying the dynamics and development of principle cells in layer II of the entorhinal cortex (EC) under the direction of White. He has collaborated with Brian Burton, now of the University of Marseille, on a study examining the development of ionic currents in layer II stellate cells of the EC and their role in the emergence of subthreshold oscillations in that cell type. He has also studied nonlinearities in the impedance functions and synaptic integration of principle cells in layer II of the EC.
Activity-dependent synaptic plasticity. Grad student Shirley Sanchez is working on a collaborative project in John A. White's Lab and John Eldred's lab investigating the role of gaseous retrograde messengers in the activity dependent synpatic plasticity of CA1. Specifically, nitric oxide and carbon monoxide are preferentially expressed in the CA1 region of the hippocampus and these two gases have been shown to interact in a modulatory manner to affect cGMP levels in the retina.
Rate-dependent efficacy: a new form of plasticity. Postdoc Erwin Idoux, working with White is exploring a new form of plasticity in the hippocampus, which is dependent upon both the pre and post-synaptic activity, and therefore referred to as “Rate Dependent Efficacy” (RDE). They plan to use intracellular patch clamp recording on CA1 neurons of the hippocampus and stimulations of the Schaffer collateral to characterize RDE quantitatively, study the mechanisms underlying RDE, and study the effect of RDE on phase response characteristic.
Electrotherapeutic technique. Grad student Eric Berns, working with Eisenberg and White, has been investigating an electrotherapeutic technique called Interferential Therapy. Berns has conducted experiments to determine if the neuronal thresholds in response to amplitude-modulated and interferential current are similar to the threshold for sinusoidal stimulation at the carrier or modulation frequencies. He has also looked at the longer-term response to such stimulation, noting that high-frequency sinusoidal stimulation results in onset excitation, but no sustained excitation. High frequency current that is amplitude-modulated at a low frequency, however, is capable of inducing sustained excitation.
Hippocampus involvement in spatial position and temporal context. Graduate student Benjamin Kraus, working with White and Howard Eichenbaum (BU, Psychology), is studying the roles of hippocampal subregions in representing spatial position and temporal context while animals perform an alternation task in a T-maze. In these studies, Kraus is using rats with chronically implanted tetrodes to make in vivo single cell recordings of hippocampal cells during task acquisition and performance. These data are analyzed to investigating the emergence of splitter cells—cells whose firing rate depends on both place and temporal context (left-turn vs. right-turn). Kraus is also working on characterizing a modified version of the T-maze that maximizes the percentage of the maze that can be used to study splitter cells. Future work will look at the relationship between splitter cell activity during encoding and retrieval segments of the task and the phase of theta rhythm.
Reverse and forward-engineering metabolic networks. Graduate student David Byrne, working with Gardner and Ionnis Paschalidis, is developing algorithms and methods to facilitate the design of novel biosynthetic pathways, and to predict the outcome of genetic, media and feedstock changes on biosynthesis. This work includes machine learning algorithms for metabolic model validation and refinement, metabolic flux analysis and optimization, and integration of regulatory and metabolic models.
Dynamical analysis of combinatorial regulation. Ilaria Mogno and Gardner are identifying combinatorial regulations in E. coli using time series data. The analysis started with steady state data that have been collected in the M3D compendium. Nonlinear regression analysis has been applied to this data in order to identify the genes that are regulated by two transcription factors. In order to better identify the relationship at the promoter region, Gardner has developed a tool that uses the Extended Kalman Filter to identify the parameters of the regulation (thresholds, cooperativity, etc). This approach uses time series data that will be generated through GFP as a reporter for gene expression. Experimental work has been done to clone the promoters of interest in front of a gfp gene.
Promoter Dynamics. Mogno, Faith and Gardner are exploring the dynamics of promoters. Synthetic promoters with mutations on RNA polymerase binding sites and on Ribosome binding sites are generated. Their expression level is measured using GFP as a reporter for gene expression. These expression measurements are used to associate transcription and translation rate to specific mutations of the regulatory region.
Shotgun mapping of transcriptional regulation from a compendium of expression profiles. Trainees Faith, Boris Hayete, Thaden, and Mogno, with Simon Kasif, Collins, and Gardner, have developed a genome-scale approach for mapping transcriptional regulatory networks in microbes. The approach uses information theoretic analysis of a compendium of 445 Escherichia coli gene expression profiles to identify the gene targets of transcription factors.
Mapping regulatory gene networks. Grad student Mike Driscoll and research staff Frank Juhn, with Gardner are combining network inference tools and high-throughput experimental assays to investigate the metal-reducing bacterium Shewanella oneidensis MR-1. Using a custom microarray platform they designed for Shewanella, they have systematically generated over one hundred genome-wide expression profiles of the organism under a range of environmental conditions. This work of elucidating the regulatory networks governing metal reduction are critical first steps in our goals of optimizing Shewanella for applications in bioremediation and biologically-based fuel cells. In addition, Undergrad Stephen Schneider is investigating the performance of selected single gene knockout strains of Shewanella in microbial fuel cells. These knockout strains are created through transposon mutagenesis and selected based on atypical anaerobic Iron(III) reduction rates. The association of gene to phenotype will aid in the verification of network inference models and help develop an understanding of Shewanella metal reduction.
Paired-end-tag determination of transcriptional units in prokaryotic genomes. Graduate Student Jeremiah Faith and Tim Gardner have developed an experimental method to determine the transcriptional units of multiple prokaryotic genomes using paired-end-tags that allow efficient determination of the 5' and 3' ends of a transcript. By adding an error-correcting barcode to the tags, it is possible to include multiple species and conditions into a single highly parallel sequencing reaction (e.g. pyrosequencing or polony sequencing). This approach provides an alternative to microarrays for gene expression studies, and it is particularly useful for metatranscriptomics studies of mixed cultures where members are not characterized or culturable.
Hierarchical Classification of Protein Function. With Simon Kasif and Martin Steffan, grad student Xiaoyu (Rainey) Jiang is working on the development of a probabilistic classification framework that integrates relational data, in the form of a network, with hierarchical structure among classes. The primary application is the prediction of protein function, using information on the interaction of proteins. Initial results, in the context of yeast, suggest that the methodology can noticeably outperform non-hierarchical methods. Improvements seem to derive particularly from an increased consistency of protein labels predicted across classes near to each other in the underlying hierarchy (here, derived from the gene ontology (GO) network).
Identifying disease mediators using reverse-engineered networks There is a need to identify genetic mediators of solid-tumor cancers, such as prostate cancer, where invasion and distant metastases determine the clinical outcome of the disease. Whole-genome expression profiling offers promise in this regard, but can be complicated by the challenge of identifying the genes affected by a condition from the hundreds to thousands of genes that exhibit changes in expression. Ayla Ergun (grad student), Carrie Lawrence (grad student), Mike Kohanski (grad tudent), Tim Brennan (grad student) and Collins showed that reverse-engineered gene networks can be combined with expression profiles to compute the likelihood that genes and associated pathways are mediators of a disease. They applied their method to non-recurrent primary and metastatic prostate cancer data, and identified the androgen receptor gene (AR) among the top genetic mediators and the AR pathway as a highly enriched pathway for metastatic prostate cancer. These results were not obtained on the basis of expression change alone. They further demonstrated that the AR gene, in the context of the network, can be used as a marker to detect the aggressiveness of primary prostate cancers. This work shows that a network biology approach can be used advantageously to identify the genetic mediators and mediating pathways associated with a disease.
Genetic factors underlying elevated gene expression noise in stationary phase. Previous studies have identified factors associated with transcription and translation, such as promoter sequences and mRNA sequences, that can affect stochasticity in gene expression. Nick Guido (postdoc), Xiao Wang (postdoc), Philina Lee (postdoc), Tim Elston (UNC) and Collins presented evidence for a pathway and associated genetic factors (namely, the ribosome modulation factor RMF and ppGpp) in Escherichia coli that contribute to heightened levels of gene expression noise during stationary phase. Endogenous cellular mechanisms that globally affect gene expression noise, such as those identified in this study, could provide phenotypic diversity under adverse conditions such as stationary phase.
Studying metabolic networks in microfluidic fuel cells. Grad student Kevin Litcofsky is studying the growth and electricity production of Shewanella oneidensis in microfabricated microbial fuel cells. Specifically, effects of multiple electron donors, as well as flow conditions, are studied on growth and electricity production of Shewanella growing on electrodes in the microfabricated fuel cells. Lastly, various methods of promoting the adherence of Shewanella to the electrodes are evaluated.
Dynamics of NO production in endothelial cells. Grad student Chris Garay with Gardner and Loscalzo is building a fully kinetic model of metabolic and gene regulatory circuits governing NO production dynamics in mammalian endothelial cells using time course measurements of metabolite concentrations.
Bacterial cellular death pathways induced by gyrase inhibitors. Modulation of bacterial chromosomal supercoiling is a function of DNA gyrase-catalyzed strand breakage and rejoining. This reaction is exploited by both antibiotic and proteic gyrase inhibitors, which trap the gyrase molecule at the DNA cleavage stage. Due to this interaction, double-stranded DNA breaks are introduced and replication machinery is arrested at blocked replication forks. This immediately results in bacteriostasis and ultimately induces cell death. Dan Dwyer (grad student), Mike Kohanski (grad student), Boris Hayete (grad student) and Collins demonstrated, through a series of phenotypic and gene expression analyses, that superoxide and hydroxyl radical oxidative species are generated following gyrase poisoning and play an important role in cell killing by gyrase inhibitors. They showed that superoxide-mediated oxidation of iron-sulfur clusters promotes a breakdown of iron regulatory dynamics; in turn, iron misregulation drives the generation of highly destructive hydroxyl radicals via the Fenton reaction. Importantly, their data reveal that blockage of hydroxyl radical formation increases the survival of gyrase-poisoned cells. Together, this series of biochemical reactions appears to compose a maladaptive response which serves to amplify the primary effect of gyrase inhibition by oxidatively damaging DNA, proteins and lipids.
A common mechanism of cellular death induced by bactericidal antibiotics . Antibiotic mode-of-action classification is based upon drug-target interaction and whether the resultant inhibition of cellular function is lethal to bacteria. Mike Kohanski (grad student), Dan Dwyer (grad student), Boris Hayete (grad student), Carrie Lawrence (grad student) and Collins showed that the three major classes of bactericidal antibiotics, regardless of drug-target interaction, stimulate the production of highly deleterious hydroxyl radicals in Gram-negative and Gram-positive bacteria, which ultimately contribute to cell death. They also showed, in contrast, that bacteriostatic drugs do not produce hydroxyl radicals. They demonstrated that the mechanism of hydroxyl radical formation, induced by bactericidal antibiotics, is the end-product of an oxidative damage cellular death pathway involving the tricarboxylic acid cycle, a transient depletion of NADH, destabilization of iron-sulfur clusters, and stimulation of the Fenton reaction. These results suggest that all three major classes of bactericidal drugs can be potentiated by targeting bacterial systems that remediate hydroxyl radical damage, including proteins involved in triggering the DNA damage response, e.g., RecA.
Bacterial intercellular communication and cellular senescence Persistence is a phenotypically induced state of cellular senescence which allows a subpopulation of genetically identical bacterial cells to survive diverse environmental stresses, such as antibiotic treatment or heat shock. Mike Koeris (grad student), Mike Kohanski (grad student), Gabor Balazsi (postdoc) and Jim Collins investigated the functions of genes around the high persistence locus, hip, and identify a mechanism for modulation of persistence through cell-to-cell contact. Additionally they found that the AI-2 quorum sensing system of E. coli can alter the ratio of persisters to non-persister cells formed. This work indicates that persister formation is influenced by both short-range and long-range cell-to-cell communication.
Quorum sensing in Pseudomonas aeruginosa. Grad student Josh Thaden and Gardner are uncovering the transcriptional regulatory interactions that occur in response to quorum signals in Pseudomonas aeruginosa..
Patel and Undergrad Justina Tam with Gardner aim to study the transcriptional regulatory networks controlling the stringent response in E. coli. Stringent response is an adaptation to starvation and involves global reprogramming of gene expression. Combining gene expression profiles collected using Affymetrix microarrays and machine-learning algorithms, we are able to predict the transcriptional regulatory networks that are activated during stringent response in E. coli. We are currently provoking this response in multiple ways and characterizing the gene expression changes caused during this adaptation. We also aim to uncover the precise mechanism of regulation for some of the important regulatory genes involved in orchestrating the stringent response.
Grad students Jasmine Zhou and Elissa Cosgrove are working with Kolaczyk and Gardner to develop a statistical framework for drug target prediction from inferred gene regulatory networks, based on microarray measurements. The new framework recasts the MNI framework of Gardner and Collins and colleagues in the context of sparse simultaneous equation models, uses sparse inference methods (e.g., the LASSO) to infer network structure, and implements outlier detection tests with false discovery rate principles to rank candidate genes potentially affected by external compounds. Cosgrove has assembled a new compendium of over 700 yeast Affymetrix microarray experiments. She is using this dataset to test the performance of the LASSO method in comparison to the MNI algorithm and a null approach using compendium-based z-scores.
Combinatorial promoter design for engineering noisy gene expression. Understanding the behavior of basic biomolecular components as parts of larger systems is one of the goals of the developing field of synthetic biology. A multidisciplinary approach, involving mathematical and computational modeling in parallel with experimentation, is often crucial for gaining such insights and improving the efficiency of artificial gene network design. Kevin Murphy (grad student), Gabor Balazsi (postdoc) and Jim Collins utilized such an approach and developed a combinatorial promoter design strategy to characterize how the position and multiplicity of tetO2 operator sites within the GAL1 promoter affect gene expression levels and gene expression noise in Saccharomyces cerevisiae. They observed stronger transcriptional repression and higher gene expression noise as a single operator site was moved closer to the TATA box, while for multiple operator-containing promoters they found that the position and number of operator sites together determined the dose response curve and gene expression noise. They developed a generic computational model that captured the experimentally observed differences for each of the promoters, and more detailed models to successively predict the behavior of multiple operator containing promoters from single operator containing promoters. These results suggest that the independent binding of single repressors is not sufficient to explain the more complex behavior of the multiple operator-containing promoters. Taken together, our findings highlight the importance of joint experimental computational efforts and some of the challenges of using a bottom-up approach based on well-characterized, isolated biomolecular components for predicting the behavior of complex, synthetic gene networks, e.g., the whole can be different from the sum of its parts.
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