Control of Large-Scale Boolean Networks via Network Aggregation.

A major challenge to solve problems in control of Boolean networks is that the computational cost increases exponentially when the number of nodes in the network increases. We consider the problem of controllability and stabilizability of Boolean control networks, address the increasing cost problem by partitioning the network graph into several subnetworks, and analyze the subnetworks separately. Easily verifiable necessary conditions for controllability and stabilizability are proposed for a general aggregation structure. For acyclic aggregation, we develop a sufficient condition for stabilizability. It dramatically reduces the computational complexity if the number of nodes in each block of the acyclic aggregation is small enough compared with the number of nodes in the entire Boolean network.

Identification and modeling of genes with diurnal oscillations from microarray time series data.

Behavior of living organisms is strongly modulated by the day and night cycle giving rise to a cyclic pattern of activities. Such a pattern helps the organisms to coordinate their activities and maintain a balance between what could be performed during the "day" and what could be relegated to the "night." This cyclic pattern, called the "Circadian Rhythm," is a biological phenomenon observed in a large number of organisms. In this paper, our goal is to analyze transcriptome data from Cyanothece for the purpose of discovering genes whose expressions are rhythmic. We cluster these genes into groups that are close in terms of their phases and show that genes from a specific metabolic functional category are tightly clustered, indicating perhaps a "preferred time of the day/night" when the organism performs this function. The proposed analysis is applied to two sets of microarray experiments performed under varying incident light patterns. Subsequently, we propose a model with a network of three phase oscillators together with a central master clock and use it to approximate a set of "circadian-controlled genes" that can be approximated closely.

Global proteomics reveal an atypical strategy for carbon/nitrogen assimilation by a cyanobacterium under diverse environmental perturbations.

Cyanobacteria, the only prokaryotes capable of oxygenic photosynthesis, are present in diverse ecological niches and play crucial roles in global carbon and nitrogen cycles. To proliferate in nature, cyanobacteria utilize a host of stress responses to accommodate periodic changes in environmental conditions. A detailed knowledge of the composition of, as well as the dynamic changes in, the proteome is necessary to gain fundamental insights into such stress responses. Toward this goal, we have performed a large-scale proteomic analysis of the widely studied model cyanobacterium Synechocystis sp. PCC 6803 under 33 different environmental conditions. The resulting high-quality dataset consists of 22,318 unique peptides corresponding to 1955 proteins, a coverage of 53% of the predicted proteome. Quantitative determination of protein abundances has led to the identification of 1198 differentially regulated proteins. Notably, our analysis revealed that a common stress response under various environmental perturbations, irrespective of amplitude and duration, is the activation of atypical pathways for the acquisition of carbon and nitrogen from urea and arginine. In particular, arginine is catabolized via putrescine to produce succinate and glutamate, sources of carbon and nitrogen, respectively. This study provides the most comprehensive functional and quantitative analysis of the Synechocystis proteome to date, and shows that a significant stress response of cyanobacteria involves an uncommon mode of acquisition of carbon and nitrogen.

Integrative analysis of large scale expression profiles reveals core transcriptional response and coordination between multiple cellular processes in a cyanobacterium.

BACKGROUND: Cyanobacteria are the only known prokaryotes capable of oxygenic photosynthesis. They play significant roles in global biogeochemical cycles and carbon sequestration, and have recently been recognized as potential vehicles for production of renewable biofuels. Synechocystis sp. PCC 6803 has been extensively used as a model organism for cyanobacterial studies. DNA microarray studies in Synechocystis have shown varying degrees of transcriptome reprogramming under altered environmental conditions. However, it is not clear from published work how transcriptome reprogramming affects pre-existing networks of fine-tuned cellular processes. RESULTS: We have integrated 163 transcriptome data sets generated in response to numerous environmental and genetic perturbations in Synechocystis. Our analyses show that a large number of genes, defined as the core transcriptional response (CTR), are commonly regulated under most perturbations. The CTR contains nearly 12% of Synechocystis genes found on its chromosome. The majority of genes in the CTR are involved in photosynthesis, translation, energy metabolism and stress protection. Our results indicate that a large number of differentially regulated genes identified in most reported studies in Synechocystis under different perturbations are associated with the general stress response. We also find that a majority of genes in the CTR are coregulated with 25 regulatory genes. Some of these regulatory genes have been implicated in cellular responses to oxidative stress, suggesting that reactive oxygen species are involved in the regulation of the CTR. A Bayesian network, based on the regulation of various KEGG pathways determined from the expression patterns of their associated genes, has revealed new insights into the coordination between different cellular processes. CONCLUSION: We provide here the first integrative analysis of transcriptome data sets generated in a cyanobacterium. This compilation of data sets is a valuable resource to researchers for all cyanobacterial gene expression related queries. Importantly, our analysis provides a global description of transcriptional reprogramming under different perturbations and a basic framework to understand the strategies of cellular adaptations in Synechocystis.

Effect of continuous light on diurnal rhythms in Cyanothece sp. ATCC 51142.

BACKGROUND: Life on earth is strongly affected by alternating day and night cycles. Accordingly, many organisms have evolved an internal timekeeping system with a period of approximately 24 hours. Cyanobacteria are the only known prokaryotes with robust rhythms under control of a central clock. Numerous studies have been conducted to elucidate components of the circadian clock and to identify circadian-controlled genes. However, the complex interactions between endogenous circadian rhythms and external cues are currently not well understood, and a direct and mathematical based comparison between light-mediated and circadian-controlled gene expression is still outstanding. Therefore, we combined and analyzed data from two independent microarray experiments, previously performed under alternating light-dark and continuous light conditions in Cyanothece sp. ATCC 51142, and sought to classify light responsive and circadian controlled genes. RESULTS: Fourier Score-based methods together with random permutations and False Discovery Rates were used to identify genes with oscillatory expression patterns, and an angular distance based criterion was applied to recognize transient behaviors in gene expression under constant light conditions. Compared to previously reported mathematical approaches, the combination of these methods also facilitated the detection of modified amplitudes and phase-shifts of gene expression. Our analysis showed that the majority of diurnally regulated genes, essentially those genes that are maximally expressed during the middle of the light and dark period, are in fact light responsive. In contrast, most of the circadian controlled genes are up-regulated during the beginning of the dark or subjective dark, and are greatly enriched for genes associated with energy metabolism. Many of the circadian controlled and light responsive genes are found in gene clusters within the Cyanothece sp. ATCC 51142 genome. Interestingly, in addition to cyclic expression patterns with a period of 24 hours, we also found several genes that oscillate with an ultradian period of 12 hours, a novel finding among cyanobacteria. CONCLUSION: We demonstrate that a combination of different analytical methods significantly improved the identification of cyclic and transient gene expression in Cyanothece sp. ATCC 51142. Our analyses provide an adaptable and novel analytical tool to study gene expression in a variety of organisms with diurnal, circadian and ultradian behavior.

Synaptic adaptation and sustained generation of waves in a model of turtle visual cortex.

Both single and repeated visual stimuli produce waves of activity in the visual cortex of freshwater turtles. Large-scale, biophysically realistic models of the visual cortex capture the basic features of the waves produced by single stimuli. However, these models do not respond to repetitive stimuli due to the presence of a long-lasting hyperpolarization that follows the initial wave. This paper modifies the large-scale model so that it responds to repetitive stimuli by incorporating Hebbian and anti-Hebbian learning rules in synapses in the model. The resulting adaptive model responds to repetitive stimuli with repetitive waves. However, repeated presentation of a stimulus to a restricted region of visual space produces a habituation in the model in the same way it does in the real cortex.

Using systems biology to simplify complex disease: immune cartography.

What if there was a rapid, inexpensive, and accurate blood diagnostic that could determine which patients were infected, identify the organism(s) responsible, and identify patients who were not responding to therapy? We hypothesized that systems analysis of the transcriptional activity of circulating immune effector cells could be used to identify conserved elements in the host response to systemic inflammation, and furthermore, to discriminate between sterile and infectious etiologies. We review herein a validated, systems biology approach demonstrating that 1) abdominal and pulmonary sepsis diagnoses can be made in mouse models using microarray (RNA) data from circulating blood, 2) blood microarray data can be used to differentiate between the host response to Gram-negative and Gram-positive pneumonia, 3) the endotoxin response of normal human volunteers can be mapped at the level of gene expression, and 4) a similar strategy can be used in the critically ill to follow septic patients and quantitatively determine immune recovery. These findings provide the foundation of immune cartography and demonstrate the potential of this approach for rapidly diagnosing sepsis and identifying pathogens. Further, our data suggest a new approach to determine how specific pathogens perturb the physiology of circulating leukocytes in a cell-specific manner. Large, prospective clinical trails are needed to validate the clinical utility of leukocyte RNA diagnostics (e.g., the riboleukogram).

The genome of Cyanothece 51142, a unicellular diazotrophic cyanobacterium important in the marine nitrogen cycle.

Unicellular cyanobacteria have recently been recognized for their contributions to nitrogen fixation in marine environments, a function previously thought to be filled mainly by filamentous cyanobacteria such as Trichodesmium. To begin a systems level analysis of the physiology of the unicellular N(2)-fixing microbes, we have sequenced to completion the genome of Cyanothece sp. ATCC 51142, the first such organism. Cyanothece 51142 performs oxygenic photosynthesis and nitrogen fixation, separating these two incompatible processes temporally within the same cell, while concomitantly accumulating metabolic products in inclusion bodies that are later mobilized as part of a robust diurnal cycle. The 5,460,377-bp Cyanothece 51142 genome has a unique arrangement of one large circular chromosome, four small plasmids, and one linear chromosome, the first report of a linear element in the genome of a photosynthetic bacterium. On the 429,701-bp linear chromosome is a cluster of genes for enzymes involved in pyruvate metabolism, suggesting an important role for the linear chromosome in fermentative processes. The annotation of the genome was significantly aided by simultaneous global proteomic studies of this organism. Compared with other nitrogen-fixing cyanobacteria, Cyanothece 51142 contains the largest intact contiguous cluster of nitrogen fixation-related genes. We discuss the implications of such an organization on the regulation of nitrogen fixation. The genome sequence provides important information regarding the ability of Cyanothece 51142 to accomplish metabolic compartmentalization and energy storage, as well as how a unicellular bacterium balances multiple, often incompatible, processes in a single cell.

Plasticity of the systemic inflammatory response to acute infection during critical illness: development of the riboleukogram.

BACKGROUND: Diagnosis of acute infection in the critically ill remains a challenge. We hypothesized that circulating leukocyte transcriptional profiles can be used to monitor the host response to and recovery from infection complicating critical illness. METHODOLOGY/PRINCIPAL FINDINGS: A translational research approach was employed. Fifteen mice underwent intratracheal injections of live P. aeruginosa, P. aeruginosa endotoxin, live S. pneumoniae, or normal saline. At 24 hours after injury, GeneChip microarray analysis of circulating buffy coat RNA identified 219 genes that distinguished between the pulmonary insults and differences in 7-day mortality. Similarly, buffy coat microarray expression profiles were generated from 27 mechanically ventilated patients every two days for up to three weeks. Significant heterogeneity of VAP microarray profiles was observed secondary to patient ethnicity, age, and gender, yet 85 genes were identified with consistent changes in abundance during the seven days bracketing the diagnosis of VAP. Principal components analysis of these 85 genes appeared to differentiate between the responses of subjects who did versus those who did not develop VAP, as defined by a general trajectory (riboleukogram) for the onset and resolution of VAP. As patients recovered from critical illness complicated by acute infection, the riboleukograms converged, consistent with an immune attractor. CONCLUSIONS/SIGNIFICANCE: Here we present the culmination of a mouse pneumonia study, demonstrating for the first time that disease trajectories derived from microarray expression profiles can be used to quantitatively track the clinical course of acute disease and identify a state of immune recovery. These data suggest that the onset of an infection-specific transcriptional program may precede the clinical diagnosis of pneumonia in patients. Moreover, riboleukograms may help explain variance in the host response due to differences in ethnic background, gender, and pathogen. Prospective clinical trials are indicated to validate our results and test the clinical utility of riboleukograms.

Encoding of motion targets by waves in turtle visual cortex.

Visual stimuli evoke wave activity in the visual cortex of freshwater turtles. Earlier work from our laboratory showed that information about the positions of stationary visual stimuli is encoded in the spatiotemporal dynamics of the waves and that the waves can be decoded using Bayesian detection theory. This paper extends these results in three ways. First, it shows that flashes of light separated in space and time and stimuli moving with three speeds can be discriminated statistically using the waves generated in a large-scale model of the cortex. Second, it compares the coding capabilities of spike rate and spike time codes. Spike rate codes were obtained by low-pass filtering the activities of individual neurons in the model with filters of different band widths. For the moving targets used in the study, detectability using spike rate codes is immune to the choice of a specific bandwidth, indicating that a coarse filter is able to adequately discriminate targets. Spike timing codes are binary sequences indicating the precise timing of spike activity of individual neurons across the cortex. Spike time codes generally perform better than do spike rate codes. Third, the encoding process is examined in terms of the underlying cellular mechanisms that result in the initiation, propagation and cessation of the wave. The period of peak detectability corresponds to the period in which waves are propagating across the cortex.

Generation of the receptive fields of subpial cells in turtle visual cortex.

The visual cortex of turtles contains cells with at least two different receptive field properties. Superficial units are located immediately below the pial surface. They fire in response to moving bars located anywhere in binocular visual space and to two spots of light presented with different spatiotemporal separations. Their location in the cortex suggests that superficial units correspond to a distinct class of inhibitory interneurons, the subpial cells, that are embedded in geniculocortical axons as they cross the visual cortex of turtles. This study used a detailed compartmental model of a subpial cell and a large-scale model of visual cortex to examine the cellular mechanisms that underlie the formation of superficial units on the assumption that they are subpial cells. Simulations with the detailed model indicated that the biophysical properties of subpial cells allow them to respond strongly to activation by geniculate inputs, but the presence of dendritic beads on the subpial cells decreases their sensitivity and allows them to integrate the inputs from many geniculate afferents. Simulations with the large-scale model indicated that the responses of subpial cells to simulated visual stimuli consist of two phases. A fast phase is mediated by direct geniculate inputs. A slow phase is mediated by recurrent excitation from pyramidal cells. It appears that subpial cells play a major role in controlling the information content of visual responses.

Two cortical circuits control propagating waves in visual cortex.

Visual stimuli produce waves of activity that propagate across the visual cortex of fresh water turtles. This study used a large-scale model of the cortex to examine the roles of specific types of cortical neurons in controlling the formation, speed and duration of these waves. The waves were divided into three components: initial depolarizations, primary propagating waves and secondary waves. The maximal conductances of each receptor type postsynaptic to each population of neurons in the model was systematically varied and the speed of primary waves, durations of primary waves and total wave durations were measured. The analyses indicate that wave formation and speed are controlled principally by feedforward excitation and inhibition, while wave duration is controlled principally by recurrent excitation and feedback inhibition.

Encoding and decoding target locations with waves in the turtle visual cortex.

Visual stimuli elicit waves of activity that propagate across the visual cortex of turtles. An earlier study showed that these waves encode information about the positions of stimuli in visual space. This paper addresses the question of how this information can be decoded from the waves. Windowing techniques were used to temporally localize information contained in the wave. Sliding encoding windows were used to represent waves of activity as low dimensional temporal strands in an appropriate space. Expanding detection window (EDW) or sliding detection window (SDW) techniques were combined with statistical hypothesis testing to discriminate input stimuli. Detection based on an EDW was more reliable than detection based on a SDW. Detection performance improved at a very early stage of the cortical response as the length of the detection window is increased. The property of intrinsic noise was explicitly considered. Assuming that the noise is colored provided a more reliable estimate than did the assumption of a white noise in the cortical output.

Propagating waves in visual cortex: a large-scale model of turtle visual cortex.

This article describes a large-scale model of turtle visual cortex that simulates the propagating waves of activity seen in real turtle cortex. The cortex model contains 744 multicompartment models of pyramidal cells, stellate cells, and horizontal cells. Input is provided by an array of 201 geniculate neurons modeled as single compartments with spike-generating mechanisms and axons modeled as delay lines. Diffuse retinal flashes or presentation of spots of light to the retina are simulated by activating groups of geniculate neurons. The model is limited in that it does not have a retina to provide realistic input to the geniculate, and the cortex and does not incorporate all of the biophysical details of real cortical neurons. However, the model does reproduce the fundamental features of planar propagating waves. Activation of geniculate neurons produces a wave of activity that originates at the rostrolateral pole of the cortex at the point where a high density of geniculate afferents enter the cortex. Waves propagate across the cortex with velocities of 4 microm/ms to 70 microm/ms and occasionally reflect from the caudolateral border of the cortex.

Modeling and estimation problems in the turtle visual cortex.

The goal of this paper is to verify that position and velocity of a spot of light incident on the retina of a turtle are encoded by the spatiotemporal dynamics of the cortical waves they generate. This conjecture is examined using a biophysically realistic large-scale computational model of the visual cortex implemented with the software package, GENESIS. The cortical waves are recorded and analyzed using principal components analysis and the position and velocity information from visual space is mapped onto an abstract B-space, to be described, using the coefficients of the principal components expansion. The likely values of the position/velocity are estimated using standard statistical detection methods.