Growing cells adopt common basic strategies to achieve optimal resource allocation under limited resource availability. Our current understanding of such "growth laws" neglects degradation, assuming that it occurs slowly compared to the cell cycle duration. Here we argue that this assumption cannot hold at slow growth, leading to important consequences. We propose a simple framework showing that at slow growth protein degradation is balanced by a fraction of "maintenance" ribosomes. Consequently, active ribosomes do not drop to zero at vanishing growth, but as growth rate diminishes, an increasing fraction of active ribosomes performs maintenance. Through a detailed analysis of compiled data, we show that the predictions of this model agree with data from E. coli and S. cerevisiae. Intriguingly, we also find that protein degradation increases at slow growth, which we interpret as a consequence of active waste management and/or recycling. Our results highlight protein turnover as an underrated factor for our understanding of growth laws across kingdoms.

This work studies the effects of the two rounds of Whole Genome Duplication (WGD) at the origin of the vertebrate lineage on the architecture of the human gene regulatory networks. We integrate information on transcriptional regulation, miRNA regulation, and protein-protein interactions to comparatively analyse the role of WGD and Small Scale Duplications (SSD) in the structural properties of the resulting multilayer network. We show that complex network motifs, such as combinations of feed-forward loops and bifan arrays, deriving from WGD events are specifically enriched in the network. Pairs of WGD-derived proteins display a strong tendency to interact both with each other and with common partners and WGD-derived transcription factors play a prominent role in the retention of a strong regulatory redundancy. Combinatorial regulation and synergy between different regulatory layers are in general enhanced by duplication events, but the two types of duplications contribute in different ways. Overall, our findings suggest that the two WGD events played a substantial role in increasing the multi-layer complexity of the vertebrate regulatory network by enhancing its combinatorial organization, with potential consequences on its overall robustness and ability to perform high-level functions like signal integration and noise control. Lastly, we discuss in detail the RAR/RXR pathway as an illustrative example of the evolutionary impact of WGD duplications in human.

UNLABELLED: Different experimental results suggest the presence of an interplay between global transcriptional regulation and chromosome spatial organization in bacteria. The identification and clear visualization of spatial clusters of contiguous genes targeted by specific DNA-binding proteins or sensitive to nucleoid perturbations can elucidate links between nucleoid structure and gene expression patterns. Similarly, statistical analysis to assess correlations between results from independent experiments can provide the integrated analysis needed in this line of research. NuST (Nucleoid Survey tools), based on the Escherichia coli genome, gives the non-expert the possibility to analyze the aggregation of genes or loci sets along the genome coordinate, at different scales of observation. It is useful to discover correlations between different sources of data (e.g. expression, binding or genomic data) and genome organization. A user can use it on datasets in the form of gene lists coming from his/her own experiments or bioinformatic analyses, but also make use of the internal database, which collects data from many published studies. AVAILABILITY AND IMPLEMENTATION: NuST is a web server (available at http://www.lgm.upmc.fr/nust/). The website is implemented in PHP, SQLite and Ajax, with all major browsers supported, while the core algorithms are optimized and implemented in C. NuST has an extensive help page and provides a direct visualization of results as well as different downloadable file formats. A template Perl code for automated access to the web server can be downloaded at http://www.lgm.upmc.fr/nust/downloads/, in order to allow the users to use NuST in systematic bioinformatic analyses.

MicroRNAs are endogenous non-coding RNAs which negatively regulate the expression of protein-coding genes in plants and animals. They are known to play an important role in several biological processes and, together with transcription factors, form a complex and highly interconnected regulatory network. Looking at the structure of this network, it is possible to recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions. Among them, a special role is played by the microRNA-mediated feedforward loop in which a master transcription factor regulates a microRNA and, together with it, a set of target genes. In this paper we show analytically and through simulations that the incoherent version of this motif can couple the fine-tuning of a target protein level with an efficient noise control, thus conferring precision and stability to the overall gene expression program, especially in the presence of fluctuations in upstream regulators. Among the other results, a nontrivial prediction of our model is that the optimal attenuation of fluctuations coincides with a modest repression of the target expression. This feature is coherent with the expected fine-tuning function and in agreement with experimental observations of the actual impact of a wide class of microRNAs on the protein output of their targets. Finally, we describe the impact on noise-buffering efficiency of the cross-talk between microRNA targets that can naturally arise if the microRNA-mediated circuit is not considered as isolated, but embedded in a larger network of regulations.