Interplay between gene expression noise and regulatory network architecture

Complex regulatory networks orchestrate most cellular processes in biological systems. Genes in such networks are subject to expression noise, resulting in isogenic cell populations exhibiting cell-to-cell variation in protein levels. Increasing evidence suggests that cells have evolved regulatory strategies to limit, tolerate or amplify expression noise. In this context, fundamental questions arise: how can the architecture of gene regulatory networks generate, make use of or be constrained by expression noise? Here, we discuss the interplay between expression noise and gene regulatory network at different levels of organization, ranging from a single regulatory interaction to entire regulatory networks. We then consider how this interplay impacts a variety of phenomena, such as pathogenicity, disease, adaptation to changing environments, differential cell-fate outcome and incomplete or partial penetrance effects. Finally, we highlight recent technological developments that permit measurements at the single-cell level, and discuss directions for future research.     

Dynamics of gene silencing by RNA interference

The large number of candidate genes identified by modern high-throughput technologies require efficient methods for generating knockout phenotypes or gene silencing in order to study gene function. RNA interference (RNAi) is an efficient method that can be used for this purpose. Effective gene silencing by RNAi depends on a number of important parameters, including the dynamics of gene expression and the RNA dose. Using mouse hepatoma cells, we detail some of the principal characteristics of RNAi as a tool for gene silencing, such as the RNA dose level, RNA complex exposure time, and the time of transfection relative to gene induction, in the context of silencing a green fluorescent protein reporter gene. Our experiments demonstrate that different levels of silencing can be attained by modulating the dose level of RNA and the time of transfection and illustrate the importance of a dynamic analysis in designing robust silencing protocols. By quantifying the kinetics of RNAi-based gene silencing, we present a model that may be used to help determine key parameters in more complex silencing experiments and explore alternative gene silencing protocols.     

Effect of alpha-lipoic acid supplementation on markers of protein oxidation in post-mitotic tissues of ageing rat

In the present study, we investigated whether DL-alpha-lipoic acid (LA) supplementation could have prooxidant or antioxidant effects on oxidative protein damage parameters such as protein carbonyl (PCO), nitrotyrosine (NT), advanced oxidation protein products (AOPP), and protein thiol (P-SH), as well as oxidative stress parameters such as total thiol (T-SH), non-protein thiol (Np-SH), and lipid hydroperoxide (LHP) in the brain and the skeletal muscle tissue of aged rats. PCO, and NT levels were increased, AOPP and P-SH levels were not changed in the brain tissue of aged rats given LA supplementation. On the other hand, TSH, Np-SH, and LHP levels were decreased in the brain tissue of aged rats given LA supplementation. The levels of the same parameters were not significantly different in the skeletal muscle tissue of aged rats given LA supplementation. The increased levels of protein oxidation markers such as PCO, and NT in the brain tissue of LA-supplemented aged rats compared with non-supplemented aged rats may suggest that oxidative protein damage is increased in LA-supplemented aged rats. We assume that an explanation for our findings regarding LA supplementation on protein oxidation markers in the brain tissue of aged rats may be due to the prooxidant effects of LA. Depending on post-mitotic tissue type and dosage of LA, the prooxidant effects of LA supplementation, should be considered in future studies.     

Not born equal: increased rate asymmetry in relocated and retrotransposed rodent gene duplicates

Duplicated genes frequently evolve at different rates. This asymmetry is evidence of natural selection's ability to discriminate between the 2 copies, subjecting them to different levels of purifying selection or even permitting adaptive evolution of one or both copies. However, if gene duplication creates pairs of protein-coding sequences that are initially identical, this raises the question of how selection tells the 2 copies apart. Here, we investigated asymmetric sequence divergence of recently duplicated genes in rodents and related this to 2 possible sources of such asymmetry: gene relocation as a consequence of duplication and retrotransposition as a mechanism of gene duplication. We found that most young rodent duplicates that have been relocated were created by retrotransposition. The degree of rate asymmetry in gene pairs where one copy has been relocated (either by retrotransposition or DNA-based duplication) is greater than in pairs formed by local DNA-based duplication events. Furthermore, by considering the direction of transposition for distant duplicates, we found a consistent tendency for retrogenes to undergo accelerated protein evolution relative to their static paralogs, whereas DNA-based transpositions showed no such tendency. Finally, we demonstrate that the faster sequence evolution of retrogenes correlates with the profound alteration of their expression pattern that is precipitated by retrotransposition.     

Human hnRNP Q re-localizes to cytoplasmic granules upon PMA, thapsigargin, arsenite and heat-shock treatments

Eukaryotic gene expression is regulated on different levels ranging from pre-mRNA processing to translation. One of the most characterized families of RNA-binding proteins is the group of hnRNPs: heterogenous nuclear ribonucleoproteins. Members of this protein family play important roles in gene expression control and mRNAs metabolism. In the cytoplasm, several hnRNPs proteins are involved in RNA-related processes and they can be frequently found in two specialized structures, known as GW-bodies (GWbs), previously known as processing bodies: PBs, and stress granules, which may be formed in response to specific stimuli. GWbs have been early reported to be involved in the mRNA decay process, acting as a site of mRNA degradation. In a similar way, stress granules (SGs) have been described as cytoplasmic aggregates, which contain accumulated mRNAs in cells under stress conditions and present reduced or inhibited translation. Here, we characterized the hnRNP Q localization after different stress conditions. hnRNP Q is a predominantly nuclear protein that exhibits a modular organization and several RNA-related functions. Our data suggest that the nuclear localization of hnRNP Q might be modified after different treatments, such as: PMA, thapsigargin, arsenite and heat shock. Under different stress conditions, hnRNP Q can fully co-localize with the endoplasmatic reticulum specific chaperone, BiP. However, under stress, this protein only co-localizes partially with the proteins: GW182 — GWbs marker protein and TIA-1 stress granule component.     

Interaction energy based protein structure networks

The three-dimensional structure of a protein is formed and maintained by the noncovalent interactions among the amino-acid residues of the polypeptide chain. These interactions can be represented collectively in the form of a network. So far, such networks have been investigated by considering the connections based on distances between the amino-acid residues. Here we present a method of constructing the structure network based on interaction energies among the amino-acid residues in the protein. We have investigated the properties of such protein energy-based networks (PENs) and have shown correlations to protein structural features such as the clusters of residues involved in stability, formation of secondary and super-secondary structural units. Further we demonstrate that the analysis of PENs in terms of parameters such as hubs and shortest paths can provide a variety of biologically important information, such as the residues crucial for stabilizing the folded units and the paths of communication between distal residues in the protein. Finally, the energy regimes for different levels of stabilization in the protein structure have clearly emerged from the PEN analysis.     

Optimal Feedback Strength for Noise Suppression in Autoregulatory Gene Networks

Autoregulatory feedback loops, where the protein expressed from a gene inhibits or activates its own expression are common gene network motifs within cells. In these networks, stochastic fluctuations in protein levels are attributed to two factors: intrinsic noise (i.e., the randomness associated with mRNA/protein expression and degradation) and extrinsic noise (i.e., the noise caused by fluctuations in cellular components such as enzyme levels and gene-copy numbers). We present results that predict the level of both intrinsic and extrinsic noise in protein numbers as a function of quantities that can be experimentally determined and/or manipulated, such as the response time of the protein and the level of feedback strength. In particular, we show that for a fixed average number of protein molecules, decreasing response times leads to attenuation of both protein intrinsic and extrinsic noise, with the extrinsic noise being more sensitive to changes in the response time. We further show that for autoregulatory networks with negative feedback, the protein noise levels can be minimal at an optimal level of feedback strength. For such cases, we provide an analytical expression for the highest level of noise suppression and the amount of feedback that achieves this minimal noise. These theoretical results are shown to be consistent and explain recent experimental observations. Finally, we illustrate how measuring changes in the protein noise levels as the feedback strength is manipulated can be used to determine the level of extrinsic noise in these gene networks.     

Efficient production of secreted proteins by Aspergillus : progress, limitations and prospects

Filamentous fungi are widely used for the production of homologous and heterologous proteins but, compared to homologous proteins, the levels of production of heterologous proteins are usually low. During the last 5 years, the levels of production of heterologous proteins have been drastically improved by fusing the corresponding gene to the 3' end of a homologous gene, encoding a well-secreted protein such as glucoamylase. Nevertheless, little research has been carried out to determine the limitations that hamper heterologous protein production. Recently we have carried out a detailed analysis of the levels of production of several proteins and glucoamylase fusion proteins in defined recombinant Aspergillus awamori strains. In this review we will focus on the use of filamentous fungi for the production of heterologous, especially non-fungal, proteins. In particular, the effect of gene-fusion strategies will be reviewed. Furthermore, the remaining limitations in heterologous protein production and suggestions for improvement strategies for overproduction of these protein will be discussed. Received: 5 July 1996 / Accepted: 6 September 1996     

Time series proteome profiling to study endoplasmic reticulum stress response

Time series profiling is a powerful approach for obtaining information on protein expression dynamics and prevailing biochemical pathways. To date, such information could only be obtained at the mRNA level using mature and highly parallel technologies such as microarray gene expression profiling. The generation of time series data at the protein level has lagged due to the lack of robust and highly reproducible methodologies. Using a combination of SILAC strategy, SDS-PAGE and LC-MS/MS, we demonstrate successful monitoring of expression levels of the same set of proteins across different time points within the ER compartment of human primary fibroblast cells when exposed to ER stress inducers tunicamycin and thapsigargin. Data visualization was facilitated using GeneSpring GX analysis platform that was designed to process Affymetrix microarray data. This software also facilitated the generation of important parameters such as data normalization, calculation of statistical values to extract significant changes in protein expression, and the cross comparison of data sets.     

Convergence in pigmentation at multiple levels: mutations,genes and function

Convergence—the independent evolution of the same trait by two or more taxa—has long been of interest to evolutionary biologists, but only recently has the molecular basis of phenotypic convergence been identified. Here, we highlight studies of rapid evolution of cryptic coloration in vertebrates to demonstrate that phenotypic convergence can occur at multiple levels: mutations, genes and gene function. We first show that different genes can be responsible for convergent phenotypes even among closely related populations, for example, in the pale beach mice inhabiting Florida''s Gulf and Atlantic coasts. By contrast, the exact same mutation can create similar phenotypes in distantly related species such as mice and mammoths. Next, we show that different mutations in the same gene need not be functionally equivalent to produce similar phenotypes. For example, separate mutations produce divergent protein function but convergent pale coloration in two lizard species. Similarly, mutations that alter the expression of a gene in different ways can, nevertheless, result in similar phenotypes, as demonstrated by sister species of deer mice. Together these studies underscore the importance of identifying not only the genes, but also the precise mutations and their effects on protein function, that contribute to adaptation and highlight how convergence can occur at different genetic levels.