Why highly expressed proteins evolve slowly

Much recent work has explored molecular and population-genetic constraints on the rate of protein sequence evolution. The best predictor of evolutionary rate is expression level, for reasons which have remained unexplained. Here, we hypothesize that selection to reduce the burden of protein misfolding will favor protein sequences with increased robustness to translational missense errors. Pressure for translational robustness increases with expression level and constrains sequence evolution. Using several sequenced yeast genomes, global expression and protein abundance data, and sets of paralogs traceable to an ancient whole-genome duplication in yeast, we rule out several confounding effects and show that expression level explains roughly half the variation in Saccharomyces cerevisiae protein evolutionary rates. We examine causes for expression's dominant role and find that genome-wide tests favor the translational robustness explanation over existing hypotheses that invoke constraints on function or translational efficiency. Our results suggest that proteins evolve at rates largely unrelated to their functions, and can explain why highly expressed proteins evolve slowly across the tree of life.Comment: 40 pages, 3 figures, with supporting informatio

Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation

© 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Macrophages play a central role in orchestrating immune responses to foreign materials, which are often responsible for the failure of implanted medical devices. Material topography is known to influence macrophage attachment and phenotype, providing opportunities for the rational design of “immune-instructive” topographies to modulate macrophage function and thus foreign body responses to biomaterials. However, no generalizable understanding of the inter-relationship between topography and cell response exists. A high throughput screening approach is therefore utilized to investigate the relationship between topography and human monocyte–derived macrophage attachment and phenotype, using a diverse library of 2176 micropatterns generated by an algorithm. This reveals that micropillars 5–10µm in diameter play a dominant role in driving macrophage attachment compared to the many other topographies screened, an observation that aligns with studies of the interaction of macrophages with particles. Combining the pillar size with the micropillar density is found to be key in modulation of cell phenotype from pro to anti-inflammatory states. Machine learning is used to successfully build a model that correlates cell attachment and phenotype with a selection of descriptors, illustrating that materials can potentially be designed to modulate inflammatory responses for future applications in the fight against foreign body rejection of medical devices

Anti-prion drug mPPIg5 inhibits PrP(C) conversion to PrP(Sc).

Prion diseases, also known as transmissible spongiform encephalopathies, are a group of fatal neurodegenerative diseases that include scrapie in sheep, bovine spongiform encephalopathy (BSE) in cattle and Creutzfeldt-Jakob disease (CJD) in humans. The 'protein only hypothesis' advocates that PrP(Sc), an abnormal isoform of the cellular protein PrP(C), is the main and possibly sole component of prion infectious agents. Currently, no effective therapy exists for these diseases at the symptomatic phase for either humans or animals, though a number of compounds have demonstrated the ability to eliminate PrPSc in cell culture models. Of particular interest are synthetic polymers known as dendrimers which possess the unique ability to eliminate PrP(Sc) in both an intracellular and in vitro setting. The efficacy and mode of action of the novel anti-prion dendrimer mPPIg5 was investigated through the creation of a number of innovative bio-assays based upon the scrapie cell assay. These assays were used to demonstrate that mPPIg5 is a highly effective anti-prion drug which acts, at least in part, through the inhibition of PrP(C) to PrP(Sc) conversion. Understanding how a drug works is a vital component in maximising its performance. By establishing the efficacy and method of action of mPPIg5, this study will help determine which drugs are most likely to enhance this effect and also aid the design of dendrimers with anti-prion capabilities for the future

From START to FINISH : the influence of osmotic stress on the cell cycle

Peer reviewedPublisher PD

Production and Initial Characterization of Dad1p, a Component of the Dam1-DASH Kinetochore Complex

In all dividing eukaryotic cells, the mitotic spindle (composed primarily of microtubules) must interact with chromosomes through a complex protein assembly called the kinetochore. In Saccharomyces cerevisiae, the Dam1-DASH complex plays an important role in promoting attachment between the kinetochore and the mitotic spindle. It also actively participates in the physical separation of sister chromatids in anaphase. Understanding the biochemical mechanisms used by Dam1-DASH has been facilitated by bacterial co-expression of the ten Dam1-DASH genes, which results in the production of a heterodecameric protein complex that can be studied in vitro. However, individual protein subunits are not soluble when expressed in E. coli, thus precluding analysis of the nature of the interaction between subunits and an examination of the assembly of the functional complex. In this paper, we describe the expression, solubilization, purification and refolding of Dad1p, one of the Dam1-DASH complex subunits. In addition, we show that Dad1p, when isolated in this manner forms dimers and/or tetramers, dependent upon protein concentration. This work provides an important tool for studying the Dam1-DASH complex that was previously unavailable, and provides an avenue of investigation for understanding how the individual heterodecamers associate with each other to facilitate chromosome segregation

Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo

© 2020 The Author(s) Implantation of medical devices can result in inflammation. A large library of polymers is screened, and a selection found to promote macrophage differentiation towards pro- or anti-inflammatory phenotypes. The bioinstructive properties of these materials are validated within a rodent model. By identifying novel materials with immune-instructive properties, the relationship between material-immune cell interactions could be investigated, and this offers exciting possibilities to design novel bioinstructive materials that can be used for numerous clinical applications including medical implants

Pharmacokinetics of Quinacrine Efflux from Mouse Brain via the P-glycoprotein Efflux Transporter

The lipophilic cationic compound quinacrine has been used as an antimalarial drug for over 75 years but its pharmacokinetic profile is limited. Here, we report on the pharmacokinetic properties of quinacrine in mice. Following an oral dose of 40 mg/kg/day for 30 days, quinacrine concentration in the brain of wild-type mice was maintained at a concentration of ∼1 µM. As a substrate of the P-glycoprotein (P-gp) efflux transporter, quinacrine is actively exported from the brain, preventing its accumulation to levels that may show efficacy in some disease models. In the brains of P-gp–deficient Mdr10/0 mice, we found quinacrine reached concentrations of ∼80 µM without any signs of acute toxicity. Additionally, we examined the distribution and metabolism of quinacrine in the wild-type and Mdr10/0 brains. In wild-type mice, the co-administration of cyclosporin A, a known P-gp inhibitor, resulted in a 6-fold increase in the accumulation of quinacrine in the brain. Our findings argue that the inhibition of the P-gp efflux transporter should improve the poor pharmacokinetic properties of quinacrine in the CNS

Behavior of a Metabolic Cycling Population at the Single Cell Level as Visualized by Fluorescent Gene Expression Reporters

BACKGROUND: During continuous growth in specific chemostat cultures, budding yeast undergo robust oscillations in oxygen consumption that are accompanied by highly periodic changes in transcript abundance of a majority of genes, in a phenomenon called the Yeast Metabolic Cycle (YMC). This study uses fluorescent reporters of genes specific to different YMC phases in order to visualize this phenomenon and understand the temporal regulation of gene expression at the level of individual cells within the cycling population. METHODOLOGY: Fluorescent gene expression reporters for different phases of the YMC were constructed and stably integrated into the yeast genome. Subsequently, these reporter-expressing yeast were used to visualize YMC dynamics at the individual cell level in cultures grown in a chemostat or in a microfluidics platform under varying glucose concentrations, using fluorescence microscopy and quantitative Western blots. CONCLUSIONS: The behavior of single cells within a metabolic cycling population was visualized using phase-specific fluorescent reporters. The reporters largely recapitulated genome-specified mRNA expression profiles. A significant fraction of the cell population appeared to exhibit basal expression of the reporters, supporting the hypothesis that there are at least two distinct subpopulations of cells within the cycling population. Although approximately half of the cycling population initiated cell division in each permissive window of the YMC, metabolic synchrony of the population was maintained. Using a microfluidics platform we observed that low glucose concentrations appear to be necessary for metabolic cycling. Lastly, we propose that there is a temporal window in the oxidative growth phase of the YMC where the cycling population segregates into at least two subpopulations, one which will enter the cell cycle and one which does not

Identification of RNA recognition elements in the Saccharomyces cerevisiae transcriptome

Post-transcriptional regulation of gene expression, including mRNA localization, translation and decay, is ubiquitous yet still largely unexplored. How is the post-transcriptional regulatory program of each mRNA encoded in its sequence? Hundreds of specific RNA-binding proteins (RBPs) appear to play roles in mediating the post-transcriptional regulatory program, akin to the roles of specific DNA-binding proteins in transcription. As a step toward decoding the regulatory programs encoded in each mRNA, we focused on specific mRNA–protein interactions. We computationally analyzed the sequences of Saccharomyces cerevisiae mRNAs bound in vivo by 29 specific RBPs, identifying eight novel candidate motifs and confirming or extending six earlier reported recognition elements. Biochemical selections for RNA sequences selectively recognized by 12 yeast RBPs yielded novel motifs bound by Pin4, Nsr1, Hrb1, Gbp2, Sgn1 and Mrn1, and recovered the known recognition elements for Puf3, She2, Vts1 and Whi3. Most of the RNA elements we uncovered were associated with coherent mRNA expression changes and were significantly conserved in related yeasts, supporting their functional importance and suggesting that the corresponding RNA–protein interactions are evolutionarily conserved

PROMPT: a protein mapping and comparison tool

BACKGROUND: Comparison of large protein datasets has become a standard task in bioinformatics. Typically researchers wish to know whether one group of proteins is significantly enriched in certain annotation attributes or sequence properties compared to another group, and whether this enrichment is statistically significant. In order to conduct such comparisons it is often required to integrate molecular sequence data and experimental information from disparate incompatible sources. While many specialized programs exist for comparisons of this kind in individual problem domains, such as expression data analysis, no generic software solution capable of addressing a wide spectrum of routine tasks in comparative proteomics is currently available. RESULTS: PROMPT is a comprehensive bioinformatics software environment which enables the user to compare arbitrary protein sequence sets, revealing statistically significant differences in their annotation features. It allows automatic retrieval and integration of data from a multitude of molecular biological databases as well as from a custom XML format. Similarity-based mapping of sequence IDs makes it possible to link experimental information obtained from different sources despite discrepancies in gene identifiers and minor sequence variation. PROMPT provides a full set of statistical procedures to address the following four use cases: i) comparison of the frequencies of categorical annotations between two sets, ii) enrichment of nominal features in one set with respect to another one, iii) comparison of numeric distributions, and iv) correlation of numeric variables. Analysis results can be visualized in the form of plots and spreadsheets and exported in various formats, including Microsoft Excel. CONCLUSION: PROMPT is a versatile, platform-independent, easily expandable, stand-alone application designed to be a practical workhorse in analysing and mining protein sequences and associated annotation. The availability of the Java Application Programming Interface and scripting capabilities on one hand, and the intuitive Graphical User Interface with context-sensitive help system on the other, make it equally accessible to professional bioinformaticians and biologically-oriented users. PROMPT is freely available for academic users from