Background: Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes.

Cells use genetic switches to shift between alternate gene expression states, e.g., to adapt to new environments or to follow a developmental pathway. Here, we study the dynamics of switching in a generic-feedback on/off switch. Unlike protein-only models, we explicitly account for stochastic fluctuations of mRNA, which have a dramatic impact on switch dynamics. Employing the WKB theory to treat the underlying chemical master equations, we obtain accurate results for the quasi-stationary distributions of mRNA and protein copy numbers and for the mean switching time, starting from either state. Our analytical results agree well with Monte Carlo simulations. Importantly, one can use the approach to study the effect of varying biological parameters on switch stability.

Analysis of complex gene regulation networks gives rise to a landscape of metastable phenotypic states for cells. Heterogeneity within a population arises due to infrequent noise-driven transitions of individual cells between nearby metastable states. While most previous works have focused on the role of intrinsic fluctuations in driving such transitions, in this Letter we investigate the role of extrinsic fluctuations. First, we develop an analytical framework to study the combined effect of intrinsic and extrinsic noise on a toy model of a Boolean regulated genetic switch. We then extend these ideas to a more biologically relevant model with a Hill-like regulatory function. Employing our theory and Monte Carlo simulations, we show that extrinsic noise can significantly alter the lifetimes of the phenotypic states and may fundamentally change the escape mechanism. Finally, our theory can be readily generalized to more complex decision making networks in biology.

The authors note, "For the 'hybrid' location discrimination task, we report data obtained from 27 electrodes, 16 of which were in area 1; the 11 electrodes in area 3b were divided evenly across the two animals (6 and 5). We had previously tested all of the electrodes, including those in area 3b, in the detection and discrimination tasks (as shown in Fig. 3) and found them all to yield approximately equivalent performance (see Fig 3A). We noticed in the hybrid location discrimination task, however, that one of the animals performed much more poorly based on stimulation of area 3b than it did based on stimulation of area 1 (while the other animal performed better based on stimulation of area 1). Having no reason to question any of the arrays, we attributed this discrepancy to differences across animals and arrived at the conclusion, based on pooled data from both animals, that stimulation of the two areas yields equivalent performance in the 'hybrid location discrimination' task. The overall conclusion, then, was that stimulation of neurons in area 3b and 1 evokes percepts that are equally localized on the skin."Shortly after publication of the paper, we repeated detection experiments across the arrays and found that the animal could no longer detect stimulation through the array in area 3b that had yielded poor performance in the hybrid location discrimination task. It is therefore likely that this array had failed between the time we conducted the initial detection and discrimination experiments and the time we conducted the hybrid location discrimination task (which required 2-3 months of retraining). If this is the case, and we eliminate data from that bad array, then the median performance on hybrid trials is 83% (up from the 80% that was originally reported), which is still statistically poorer than that on the location-matched mechanical trials [median difference between performance on mechanical and hybrid trials was 3.3% rather than 5.6%, t (119) = 6.1, P < 0.001] (see the corrected Fig. 2). Thus, we probably underestimated overall performance on hybrid trials, and thus the degree to which artificial percepts are localized, in the original publication. Importantly, however, performance on hybrid trials based on stimulation of area 3b was significantly better than performance based on stimulation of area 1 [median Δp = 0.028 and 0.054 for areas 3b and 1, respectively; t test: t (76) = 2.8, P < 0.01]. Thus, based on the data obtained from only one animal, it seems as though stimulation of area 3b elicits more localized percepts than does stimulation of area 1, as might be expected given that neurons in area 3b tend to have smaller receptive fields than their counterparts in area 1 (1, 2)."As a result of this error, Fig. 2 and its legend appeared incorrectly. The corrected figure and its corresponding legend appear below. On both mechanical and hybrid trials, the relative locations of stimuli applied to widely spaced digits were more accurately discriminated than were the relative locations of stimuli applie...

Stochastic expression of genes produces heterogeneity in clonal populations of bacteria under identical conditions. We analyze and compare the behavior of the inducible lac genetic switch using well-stirred and spatially resolved simulations for Escherichia coli cells modeled under fast and slow-growth conditions. Our new kinetic model describing the switching of the lac operon from one phenotype to the other incorporates parameters obtained from recently published in vivo single-molecule fluorescence experiments along with in vitro rate constants. For the well-stirred system, investigation of the intrinsic noise in the circuit as a function of the inducer concentration and in the presence/absence of the feedback mechanism reveals that the noise peaks near the switching threshold. Applying maximum likelihood estimation, we show that the analytic two-state model of gene expression can be used to extract stochastic rates from the simulation data. The simulations also provide mRNA–protein probability landscapes, which demonstrate that switching is the result of crossing both mRNA and protein thresholds. Using cryoelectron tomography of an E. coli cell and data from proteomics studies, we construct spatial in vivo models of cells and quantify the noise contributions and effects on repressor rebinding due to cell structure and crowding in the cytoplasm. Compared to systems without spatial heterogeneity, the model for the fast-growth cells predicts a slight decrease in the overall noise and an increase in the repressors rebinding rate due to anomalous subdiffusion. The tomograms for E. coli grown under slow-growth conditions identify the positions of the ribosomes and the condensed nucleoid. The smaller slow-growth cells have increased mRNA localization and a larger internal inducer concentration, leading to a significant decrease in the lifetime of the repressor–operator complex and an increase in the frequency of transcriptional bursts.

Spatial stochastic simulation is a valuable technique for studying reactions in biological systems. With the availability of high-performance computing, the method is poised to allow integration of data from structural, single-molecule, and biochemical studies into coherent computational models of cells. Here we introduce the Lattice Microbes software package for simulating such cell models on high-performance computing systems. The software performs either well-stirred or spatially resolved stochastic simulations with approximated cytoplasmic crowding in a fast and efficient manner. Our new algorithm efficiently samples the reaction-diffusion master equation using NVIDIA GPUs and is shown to be two orders of magnitude faster than exact sampling for large systems while maintaining an accuracy of ∼0.1%. Display of cell models and animation of reaction trajectories involving millions of molecules is facilitated using a plug-in to the popular VMD visualization platform. The Lattice Microbes software is open source and available for download at http://www.scs.illinois.edu/schulten/lm.

Ribosomal signatures, idiosyncrasies in the ribosomal RNA (rRNA) and/or proteins, are characteristic of the individual domains of life. As such, insight into the early evolution of the domains can be gained from a comparative analysis of their respective signatures in the translational apparatus. In this work, we identify signatures in both the sequence and structure of the rRNA and analyze their contributions to the universal phylogenetic tree using both sequence-and structure-based methods. Domain-specific ribosomal proteins can be considered signatures in their own right. Although it is commonly assumed that they developed after the universal ribosomal proteins, we present evidence that at least one may have been present before the divergence of the organismal lineages. We find correlations between the rRNA signatures and signatures in the ribosomal proteins showing that the rRNA signatures coevolved with both domain-specific and universal ribosomal proteins. Finally, we show that the genomic organization of the universal ribosomal components contains these signatures as well. From these studies, we propose the ribosomal signatures are remnants of an evolutionary-phase transition that occurred as the cell lineages began to coalesce and so should be reflected in corresponding signatures throughout the fabric of the cell and its genome.three domains of life ͉ genomic organization ͉ environmental sequences A huge and exponentially increasing dataset regarding the molecular makeup of cells has accumulated over the last several decades. Biologists today routinely ask questions of the data that are far more deeply probing than previously possible. What is not generally appreciated, however, is that large datasets of this type tend to bring into question the conceptual framework within which the questions themselves are posed. An especially informative example is our understanding of the cellular translation mechanism. In the past, the mechanism was conceptualized and probed in a reductionist ''particle'' framework, whereas understanding today comes increasingly from multimodal analyses. The questions and answers bespeak a highly integrated mechanism, whose essence would seem to lie in its delocalized collective properties.This perceptual change not only obviously applies to translation but also embraces all biological organization, all things biological. Ultimate explanations in biology will come largely in terms of processes, a process perspective that unavoidably leads back to the dynamics of evolution, the process that gives rise to all of the subordinate biological processes constituting what we take to be biology today. The process of evolution is a forteriori nonuniform, and whereas its sporadic nature can be glimpsed throughout the fabric of the cell, perhaps its clearest markings are seen in the signatures of the translation apparatus, i.e., the ribosome and its translation factors.Evidence today strongly suggests that a highly developed translation system was a necessary condition for the emergence of cell...

Members of the Id subfamily of helix-loop-helix (HLH) proteins play important roles in promoting cell cycle entry, enhancing apoptosis, stimulating proliferation, and blocking cellular differentiation (reviewed in references 21, 28, and 30). The founding member of this subfamily, Idl, was originally identified as a protein that inhibits the DNA-binding activity of basic HLH (bHLH) proteins (4). Subsequently, three further genes that encode the related proteins Id2 (5, 41), Id3 (8, 11), and Id4 (35) were identified. Like Id1, the other Id proteins (Id2, Id3, and Id4) also inhibit DNA binding by bHLH proteins (reviewed in references 21, 28, and 30). Mechanistically, the Id proteins are thought to inhibit bHLH proteins by sequestering them in inactive heterodimers which are incapable of DNA binding due to the absence of the basic region in the Id proteins (4, 41; reviewed in references 21, 28, and 30). In addition to their association with bHLH transcription factors, Id proteins have also been shown to interact with several non-HLH proteins, including the retinoblastoma protein (pRB) and related pocket proteins (19,22,23), MIDA1 (20,38), and, more recently, members of the TCF subfamily of ETS-domain transcription factors (48). Id proteins inhibit DNA binding by the TCF proteins through interaction with their ETS DNA-binding domains. This interaction also leads to the dissociation of TCFs from ternary TCF-SRF-SRE complexes and hence to the inhibition of c-fos promoter activity (48).A subset of ETS-domain transcription factors, including Elk-1, can also form ternary complexes with the paired-domain transcription factor Pax-5 and the B-cell-specific mb-1 promoter (15). In this case, Pax-5, rather than SRF, serves to recruit the ETS-domain proteins to the promoter. Pax-5 is a member of a subfamily of Pax proteins which also contains Pax-2 and Pax-8 (reviewed in references 25 and 40). This subfamily is characterized by the presence of an octapeptide motif and a partial homeodomain in addition to the N-terminal paired DNA-binding domain. Pax-5 plays an important role in regulating B-cell development (reviewed in references 7 and 27). Several target genes have been identified, which are either up-regulated (mb-1, N-myc, and LEF-1) or down-regulated (PD-1) in keeping with the observation that Pax-5 can function as both a transcriptional activator and repressor. In the case of the mb-1 and LEF-1 genes, the paired domain of Pax-5 is sufficient to up-regulate their expression (31).As Id proteins are also expressed during B-cell development and function as negative regulators of B lymphopoiesis (9,41,42, 44), we tested whether Id proteins could affect the activity of ETS-domain protein complexes that form on the mb-1 promoter. By analogy with the ternary complex that forms on the c-fos SRE, it was expected that Id-mediated dissociation of the ETS-domain protein component might be observed.