Metazoan Operons Accelerate Recovery from Growth-Arrested States

Existing theories explain why operons are advantageous in prokaryotes, but their occurrence in metazoans is an enigma. Nematode operon genes, typically consisting of growth genes, are significantly upregulated during recovery from growth-arrested states. This expression pattern is anticorrelated to nonoperon genes, consistent with a competition for transcriptional resources. We find that transcriptional resources are initially limiting during recovery and that recovering animals are highly sensitive to any additional decrease in transcriptional resources. We provide evidence that operons become advantageous because, by clustering growth genes into operons, fewer promoters compete for the limited transcriptional machinery, effectively increasing the concentration of transcriptional resources and accelerating recovery. Mathematical modeling reveals how a moderate increase in transcriptional resources can substantially enhance transcription rate and recovery. This design principle occurs in different nematodes and the chordate C. intestinalis. As transition from arrest to rapid growth is shared by many metazoans, operons could have evolved to facilitate these processes

Invariant Distribution of Promoter Activities in Escherichia coli

Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources

Plasticity of the cis-Regulatory Input Function of a Gene

The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs

Bag6 complex contains a minimal tail-anchor–targeting module and a mock BAG domain

BCL2-associated athanogene cochaperone 6 (Bag6) plays a central role in cellular homeostasis in a diverse array of processes and is part of the heterotrimeric Bag6 complex, which also includes ubiquitin-like 4A (Ubl4A) and transmembrane domain recognition complex 35 (TRC35). This complex recently has been shown to be important in the TRC pathway, the mislocalized protein degradation pathway, and the endoplasmic reticulum-associated degradation pathway. Here we define the architecture of the Bag6 complex, demonstrating that both TRC35 and Ubl4A have distinct C-terminal binding sites on Bag6 defining a minimal Bag6 complex. A crystal structure of the Bag6–Ubl4A dimer demonstrates that Bag6–BAG is not a canonical BAG domain, and this finding is substantiated biochemically. Remarkably, the minimal Bag6 complex defined here facilitates tail-anchored substrate transfer from small glutamine-rich tetratricopeptide repeat-containing protein α to TRC40. These findings provide structural insight into the complex network of proteins coordinated by Bag6

Stochastic approach to molecular interactions and computational theory of metabolic and genetic regulations

Binding and unbinding of ligands to specific sites of a macromolecule are one of the most elementary molecular interactions inside the cell that embody the computational processes of biological regulations. The interaction between transcription factors and the operators of genes and that between ligands and binding sites of allosteric enzymes are typical examples of such molecular interactions. In order to obtain the general mathematical framework of biological regulations, we formulate these interactions as finite Markov processes and establish a computational theory of regulatory activities of macromolecules based mainly on graphical analysis of their state transition diagrams. The contribution is summarized as follows: (1) Stochastic interpretation of Michaelis-Menten equation is given. (2) Notion of \textit{probability flow} is introduced in relation to detailed balance. (3) A stochastic analogy of \textit{Wegscheider condition} is given in relation to loops in the state transition diagram. (4) A simple graphical method of computing the regulatory activity in terms of ligands' concentrations is obtained for Wegscheider cases.Comment: 20 pages, 13 figure

Large-scale inference and graph theoretical analysis of gene-regulatory networks in B. stubtilis

We present the methods and results of a two-stage modeling process that generates candidate gene-regulatory networks of the bacterium B. subtilis from experimentally obtained, yet mathematically underdetermined microchip array data. By employing a computational, linear correlative procedure to generate these networks, and by analyzing the networks from a graph theoretical perspective, we are able to verify the biological viability of our inferred networks, and we demonstrate that our networks' graph theoretical properties are remarkably similar to those of other biological systems. In addition, by comparing our inferred networks to those of a previous, noisier implementation of the linear inference process [17], we are able to identify trends in graph theoretical behavior that occur both in our networks as well as in their perturbed counterparts. These commonalities in behavior at multiple levels of complexity allow us to ascertain the level of complexity to which our process is robust to noise.Comment: 22 pages, 4 figures, accepted for publication in Physica A (2006

Model for eukaryotic tail-anchored protein binding based on the structure of Get3

The Get3 ATPase directs the delivery of tail-anchored (TA) proteins to the endoplasmic reticulum (ER). TA-proteins are characterized by having a single transmembrane helix (TM) at their extreme C terminus and include many essential proteins, such as SNAREs, apoptosis factors, and protein translocation components. These proteins cannot follow the SRP-dependent co-translational pathway that typifies most integral membrane proteins; instead, post-translationally, these proteins are recognized and bound by Get3 then delivered to the ER in the ATP dependent Get pathway. To elucidate a molecular mechanism for TA protein binding by Get3 we have determined three crystal structures in apo and ADP forms from Saccharomyces cerevisae (ScGet3-apo) and Aspergillus fumigatus (AfGet3-apo and AfGet3-ADP). Using structural information, we generated mutants to confirm important interfaces and essential residues. These results point to a model of how Get3 couples ATP hydrolysis to the binding and release of TA-proteins

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Hierarchical sparse coding in the sensory system of Caenorhabditis elegans

Animals with compact sensory systems face an encoding problem where a small number of sensory neurons are required to encode information about its surrounding complex environment. Using Caenorhabditis elegans worms as a model, we ask how chemical stimuli are encoded by a small and highly connected sensory system. We first generated a comprehensive library of transgenic worms where each animal expresses a genetically encoded calcium indicator in individual sensory neurons. This library includes the vast majority of the sensory system in C. elegans. Imaging from individual sensory neurons while subjecting the worms to various stimuli allowed us to compile a comprehensive functional map of the sensory system at single neuron resolution. The functional map reveals that despite the dense wiring, chemosensory neurons represent the environment using sparse codes. Moreover, although anatomically closely connected, chemo- and mechano-sensory neurons are functionally segregated. In addition, the code is hierarchical, where few neurons participate in encoding multiple cues, whereas other sensory neurons are stimulus specific. This encoding strategy may have evolved to mitigate the constraints of a compact sensory system

Structural characterization of the Get4/Get5 complex and its interaction with Get3

The recently elucidated Get proteins are responsible for the targeted delivery of the majority of tail-anchored (TA) proteins to the endoplasmic reticulum. Get4 and Get5 have been identified in the early steps of the pathway mediating TA substrate delivery to the cytoplasmic targeting factor Get3. Here we report a crystal structure of Get4 and an N-terminal fragment of Get5 from Saccharomyces cerevisae. We show Get4 and Get5 (Get4/5) form an intimate complex that exists as a dimer (two copies of Get4/5) mediated by the C-terminus of Get5. We further demonstrate that Get3 specifically binds to a conserved surface on Get4 in a nucleotide dependent manner. This work provides further evidence for a model in which Get4/5 operates upstream of Get3 and mediates the specific delivery of a TA substrate