Determinants of Protein Abundance and Translation Efficiency in S. cerevisiae

The translation efficiency of most Saccharomyces cerevisiae genes remains fairly constant across poor and rich growth media. This observation has led us to revisit the available data and to examine the potential utility of a protein abundance predictor in reinterpreting existing mRNA expression data. Our predictor is based on large-scale data of mRNA levels, the tRNA adaptation index, and the evolutionary rate. It attains a correlation of 0.76 with experimentally determined protein abundance levels on unseen data and successfully cross-predicts protein abundance levels in another yeast species (Schizosaccharomyces pombe). The predicted abundance levels of proteins in known S. cerevisiae complexes, and of interacting proteins, are significantly more coherent than their corresponding mRNA expression levels. Analysis of gene expression measurement experiments using the predicted protein abundance levels yields new insights that are not readily discernable when clustering the corresponding mRNA expression levels. Comparing protein abundance levels across poor and rich media, we find a general trend for homeostatic regulation where transcription and translation change in a reciprocal manner. This phenomenon is more prominent near origins of replications. Our analysis shows that in parallel to the adaptation occurring at the tRNA level via the codon bias, proteins do undergo a complementary adaptation at the amino acid level to further increase their abundance

Application of ceramic coating to improve abrasive wear resistance of die inserts used to press-mould stampings of refractories

The paper presents results of a study on abrasive wear resistance of die inserts for composite moulds used to pressmould stampings from refractory materials, determined based on susceptibility to scratching with a diamond indenter. For the study, two inserts of high-chromium cast iron were prepared, of which one was provided with a ceramic coating (60 % Al2O3 + 40 % TiO2) with a metallic interlayer (NiAlCrSi). Both layers were deposited by means of the Atmospheric Plasma Spraying (APS) method. The obtained scratch test results indicate that with the use of the same load force (20 N), die inserts with ceramic coating are characterized with less indenter penetration depth which should translate to higher resistance to abrasive wear

A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in a Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are repeatedly revisited, and allows associations of more than one state to the same syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network hypothesis of how syntax is controlled within the premotor song nucleus HVC, and suggests that adaptation and many-to-one mapping from neural substrates to syllables are important features of the neural control of complex song syntax

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u

The Origin of Phenotypic Heterogeneity in a Clonal Cell Population In Vitro

BACKGROUND: The spontaneous emergence of phenotypic heterogeneity in clonal populations of mammalian cells in vitro is a rule rather than an exception. We consider two simple, mutually non-exclusive models that explain the generation of diverse cell types in a homogeneous population. In the first model, the phenotypic switch is the consequence of extrinsic factors. Initially identical cells may become different because they encounter different local environments that induce adaptive responses. According to the second model, the phenotypic switch is intrinsic to the cells that may occur even in homogeneous environments. PRINCIPAL FINDINGS: We have investigated the “extrinsic” and the “intrinsic” mechanisms using computer simulations and experimentation. First, we simulated in silico the emergence of two cell types in a clonal cell population using a multiagent model. Both mechanisms produced stable phenotypic heterogeneity, but the distribution of the cell types was different. The “intrinsic” model predicted an even distribution of the rare phenotype cells, while in the “extrinsic” model these cells formed small clusters. The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line. CONCLUSIONS: The observations emphasize the importance of the “ecological” context and suggest that, consistently with the “extrinsic” model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch. Nevertheless, the “intrinsic” model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells

Discovering local patterns of co - evolution: computational aspects and biological examples

<p>Abstract</p> <p>Background</p> <p>Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions and to predict physical interactions. More generally, it can be used for answering fundamental questions about the evolution of biological systems.</p> <p>Orthologs that exhibit a strong signal of co-evolution in a certain part of the evolutionary tree may show a mild signal of co-evolution in other branches of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive selection. Previous publications in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local.</p> <p>Results</p> <p>In this work, we describe a new set of biological problems that are related to finding patterns of <it>local </it>co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above.</p> <p>We use our approach to trace the co-evolution of fungal, eukaryotic, and mammalian genes at high resolution across the different parts of the corresponding phylogenetic trees. Specifically, we discover regions in the fungi tree that are enriched with positive evolution. We show that metabolic genes exhibit a remarkable level of co-evolution and different patterns of co-evolution in various biological datasets.</p> <p>In addition, we find that protein complexes that are related to gene expression exhibit non-homogenous levels of co-evolution across different parts of the <it>fungi </it>evolutionary line. In the case of mammalian evolution, signaling pathways that are related to <it>neurotransmission </it>exhibit a relatively higher level of co-evolution along the <it>primate </it>subtree.</p> <p>Conclusions</p> <p>We show that finding local patterns of co-evolution is a computationally challenging task and we offer novel algorithms that allow us to solve this problem, thus opening a new approach for analyzing the evolution of biological systems.</p

The role of Holliday junction resolvases in the repair of spontaneous and induced DNA damage

DNA double-strand breaks (DSBs) and other lesions occur frequently during cell growth and in meiosis. These are often repaired by homologous recombination (HR). HR may result in the formation of DNA structures called Holliday junctions (HJs), which need to be resolved to allow chromosome segregation. Whereas HJs are present in most HR events in meiosis, it has been proposed that in vegetative cells most HR events occur through intermediates lacking HJs. A recent screen in yeast has shown HJ resolution activity for a protein called Yen1, in addition to the previously known Mus81/Mms4 complex. Yeast strains deleted for both YEN1 and MMS4 show a reduction in growth rate, and are very sensitive to DNA-damaging agents. In addition, we investigate the genetic interaction of yen1 and mms4 with mutants defective in different repair pathways. We find that in the absence of Yen1 and Mms4 deletion of RAD1 or RAD52 have no further effect, whereas additional sensitivity is seen if RAD51 is deleted. Finally, we show that yeast cells are unable to carry out meiosis in the absence of both resolvases. Our results show that both Yen1 and Mms4/Mus81 play important (although not identical) roles during vegetative growth and in meiosis

A Genetic and Structural Study of Genome Rearrangements Mediated by High Copy Repeat Ty1 Elements

Ty elements are high copy number, dispersed repeated sequences in the Saccharomyces cerevisiae genome known to mediate gross chromosomal rearrangements (GCRs). Here we found that introduction of Ty912, a previously identified Ty1 element, onto the non-essential terminal region of the left arm of chromosome V led to a 380-fold increase in the rate of accumulating GCRs in a wild-type strain. A survey of 48 different mutations identified those that either increased or decreased the rate of Ty-mediated GCRs and demonstrated that suppression of Ty-mediated GCRs differs from that of both low copy repeat sequence- and single copy sequence-mediated GCRs. The majority of the Ty912-mediated GCRs observed were monocentric nonreciprocal translocations mediated by RAD52-dependent homologous recombination (HR) between Ty912 and a Ty element on another chromosome arm. The remaining Ty912-mediated GCRs appeared to involve Ty912-mediated formation of unstable dicentric translocation chromosomes that were resolved by one or more Ty-mediated breakage-fusion-bridge cycles. Overall, the results demonstrate that the Ty912-mediated GCR assay is an excellent model for understanding mechanisms and pathways that suppress genome rearrangements mediated by high copy number repeat sequences, as well as the mechanisms by which such rearrangements occur