Non-Negative Matrix Factorization for Learning Alignment-Specific Models of Protein Evolution

Models of protein evolution currently come in two flavors: generalist and specialist. Generalist models (e.g. PAM, JTT, WAG) adopt a one-size-fits-all approach, where a single model is estimated from a number of different protein alignments. Specialist models (e.g. mtREV, rtREV, HIVbetween) can be estimated when a large quantity of data are available for a single organism or gene, and are intended for use on that organism or gene only. Unsurprisingly, specialist models outperform generalist models, but in most instances there simply are not enough data available to estimate them. We propose a method for estimating alignment-specific models of protein evolution in which the complexity of the model is adapted to suit the richness of the data. Our method uses non-negative matrix factorization (NNMF) to learn a set of basis matrices from a general dataset containing a large number of alignments of different proteins, thus capturing the dimensions of important variation. It then learns a set of weights that are specific to the organism or gene of interest and for which only a smaller dataset is available. Thus the alignment-specific model is obtained as a weighted sum of the basis matrices. Having been constrained to vary along only as many dimensions as the data justify, the model has far fewer parameters than would be required to estimate a specialist model. We show that our NNMF procedure produces models that outperform existing methods on all but one of 50 test alignments. The basis matrices we obtain confirm the expectation that amino acid properties tend to be conserved, and allow us to quantify, on specific alignments, how the strength of conservation varies across different properties. We also apply our new models to phylogeny inference and show that the resulting phylogenies are different from, and have improved likelihood over, those inferred under standard models

HIV-Specific Probabilistic Models of Protein Evolution

Comparative sequence analyses, including such fundamental bioinformatics techniques as similarity searching, sequence alignment and phylogenetic inference, have become a mainstay for researchers studying type 1 Human Immunodeficiency Virus (HIV-1) genome structure and evolution. Implicit in comparative analyses is an underlying model of evolution, and the chosen model can significantly affect the results. In general, evolutionary models describe the probabilities of replacing one amino acid character with another over a period of time. Most widely used evolutionary models for protein sequences have been derived from curated alignments of hundreds of proteins, usually based on mammalian genomes. It is unclear to what extent these empirical models are generalizable to a very different organism, such as HIV-1–the most extensively sequenced organism in existence. We developed a maximum likelihood model fitting procedure to a collection of HIV-1 alignments sampled from different viral genes, and inferred two empirical substitution models, suitable for describing between-and within-host evolution. Our procedure pools the information from multiple sequence alignments, and provided software implementation can be run efficiently in parallel on a computer cluster. We describe how the inferred substitution models can be used to generate scoring matrices suitable for alignment and similarity searches. Our models had a consistently superior fit relative to the best existing models and to parameter-rich data-driven models when benchmarked on independent HIV-1 alignments, demonstrating evolutionary biases in amino-acid substitution that are unique to HIV, and that are not captured by the existing models. The scoring matrices derived from the models showed a marked difference from common amino-acid scoring matrices. The use of an appropriate evolutionary model recovered a known viral transmission history, whereas a poorly chosen model introduced phylogenetic error. We argue that our model derivation procedure is immediately applicable to other organisms with extensive sequence data available, such as Hepatitis C and Influenza A viruses

Hyperactive S6K1 Mediates Oxidative Stress and Endothelial Dysfunction in Aging: Inhibition by Resveratrol

Mammalian target of rapamycin (mTOR)/S6K1 signalling emerges as a critical regulator of aging. Yet, a role of mTOR/S6K1 in aging-associated vascular endothelial dysfunction remains unknown. In this study, we investigated the role of S6K1 in aging-associated endothelial dysfunction and effects of the polyphenol resveratrol on S6K1 in aging endothelial cells. We show here that senescent endothelial cells displayed higher S6K1 activity, increased superoxide production and decreased bioactive nitric oxide (NO) levels than young endothelial cells, which is contributed by eNOS uncoupling. Silencing S6K1 in senescent cells reduced superoxide generation and enhanced NO production. Conversely, over-expression of a constitutively active S6K1 mutant in young endothelial cells mimicked endothelial dysfunction of the senescent cells through eNOS uncoupling and induced premature cellular senescence. Like the mTOR/S6K1 inhibitor rapamycin, resveratrol inhibited S6K1 signalling, resulting in decreased superoxide generation and enhanced NO levels in the senescent cells. Consistent with the data from cultured cells, an enhanced S6K1 activity, increased superoxide generation, and decreased bioactive NO levels associated with eNOS uncoupling were also detected in aortas of old WKY rats (aged 20–24 months) as compared to the young animals (1–3 months). Treatment of aortas of old rats with resveratrol or rapamycin inhibited S6K1 activity, oxidative stress, and improved endothelial NO production. Our data demonstrate a causal role of the hyperactive S6K1 in eNOS uncoupling leading to endothelial dysfunction and vascular aging. Resveratrol improves endothelial function in aging, at least in part, through inhibition of S6K1. Targeting S6K1 may thus represent a novel therapeutic approach for aging-associated vascular disease

A Naturally Occurring Polymorphism at Drosophila melanogaster Lim3 Locus, a Homolog of Human LHX3/4, Affects Lim3 Transcription and Fly Lifespan

Lim3 encodes an RNA polymerase II transcription factor with a key role in neuron specification. It was also identified as a candidate gene that affects lifespan. These pleiotropic effects indicate the fundamental significance of the potential interplay between neural development and lifespan control. The goal of this study was to analyze the causal relationships between Lim3 structural variations, and gene expression and lifespan changes, and to provide insights into regulatory pathways controlling lifespan. Fifty substitution lines containing second chromosomes from a Drosophila natural population were used to analyze the association between lifespan and sequence variation in the 5′-regulatory region, and first exon and intron of Lim3A, in which we discovered multiple transcription start sites (TSS). The core and proximal promoter organization for Lim3A and a previously unknown mRNA named Lim3C were described. A haplotype of two markers in the Lim3A regulatory region was significantly associated with variation in lifespan. We propose that polymorphisms in the regulatory region affect gene transcription, and consequently lifespan. Indeed, five polymorphic markers located within 380 to 680 bp of the Lim3A major TSS, including two markers associated with lifespan variation, were significantly associated with the level of Lim3A transcript, as evaluated by real time RT-PCR in embryos, adult heads, and testes. A naturally occurring polymorphism caused a six-fold change in gene transcription and a 25% change in lifespan. Markers associated with long lifespan and intermediate Lim3A transcription were present in the population at high frequencies. We hypothesize that polymorphic markers associated with Lim3A expression are located within the binding sites for proteins that regulate gene function, and provide general rather than tissue-specific regulation of transcription, and that intermediate levels of Lim3A expression confer a selective advantage and longer lifespan

Pro-autophagic signal induction by bacterial pore-forming toxins

Pore-forming toxins (PFT) comprise a large, structurally heterogeneous group of bacterial protein toxins. Nucleated target cells mount complex responses which allow them to survive moderate membrane damage by PFT. Autophagy has recently been implicated in responses to various PFT, but how this process is triggered is not known, and the significance of the phenomenon is not understood. Here, we show that S. aureus α-toxin, Vibrio cholerae cytolysin, streptolysin O and E. coli haemolysin activate two pathways leading to autophagy. The first pathway is triggered via AMP-activated protein kinase (AMPK). AMPK is a major energy sensor which induces autophagy by inhibiting the target of rapamycin complex 1 (TORC1) in response to a drop of the cellular ATP/AMP-ratio, as is also observed in response to membrane perforation. The second pathway is activated by the conserved eIF2α-kinase GCN2, which causes global translational arrest and promotes autophagy in response to starvation. The latter could be accounted for by impaired amino acid transport into target cells. Notably, PKR, an eIF2α-kinase which has been implicated in autophagy induction during viral infection, was also activated upon membrane perforation, and evidence was obtained that phosphorylation of eIF2α is required for the accumulation of autophagosomes in α-toxin-treated cells. Treatment with 3-methyl-adenine inhibited autophagy and disrupted the ability of cells to recover from sublethal attack by S. aureus α-toxin. We propose that PFT induce pro-autophagic signals through membrane perforation–dependent nutrient and energy depletion, and that an important function of autophagy in this context is to maintain metabolic homoeostasis

The MDT-15 Subunit of Mediator Interacts with Dietary Restriction to Modulate Longevity and Fluoranthene Toxicity in Caenorhabditis elegans

Dietary restriction (DR), the limitation of calorie intake while maintaining proper nutrition, has been found to extend life span and delay the onset of age-associated disease in a wide range of species. Previous studies have suggested that DR can reduce the lethality of environmental toxins. To further examine the role of DR in toxin response, we measured life spans of the nematode Caenorhabditis elegans treated with the mutagenic polyaromatic hydrocarbon, fluoranthene (FLA). FLA is a direct byproduct of combustion, and is one of U.S. Environmental Protection Agency's sixteen priority environmental toxins. Treatment with 5 µg/ml FLA shortened the life spans of ad libitum fed nematodes, and DR resulted in increased sensitivity to FLA. To determine the role of detoxifying enzymes in the toxicity of FLA, we tested nematodes with mutations in the gene encoding the MDT-15 subunit of mediator, a transcriptional coactivator that regulates genes involved in fatty acid metabolism and detoxification. Mutation of mdt-15 increased the life span of FLA treated animals compared to wild-type animals with no difference observed between DR and ad libitum fed mdt-15 animals. We also examined mutants with altered insulin-IGF-1-like signaling (IIS), which is known to modulate life span and stress resistance in C. elegans independently of DR. Mutation of the genes coding for the insulin-like receptor DAF-2 or the FOXO-family transcription factor DAF16 did not alter the animals' susceptibility to FLA compared to wild type. Taken together, our results suggest that certain compounds have increased toxicity when combined with a DR regimen through increased metabolic activation. This increased metabolic activation appears to be mediated through the MDT-15 transcription factor and is independent of the IIS pathway

Elevated Proteasome Capacity Extends Replicative Lifespan in Saccharomyces cerevisiae

Aging is characterized by the accumulation of damaged cellular macromolecules caused by declining repair and elimination pathways. An integral component employed by cells to counter toxic protein aggregates is the conserved ubiquitin/proteasome system (UPS). Previous studies have described an age-dependent decline of proteasomal function and increased longevity correlates with sustained proteasome capacity in centenarians and in naked mole rats, a long-lived rodent. Proof for a direct impact of enhanced proteasome function on longevity, however, is still lacking. To determine the importance of proteasome function in yeast aging, we established a method to modulate UPS capacity by manipulating levels of the UPS–related transcription factor Rpn4. While cells lacking RPN4 exhibit a decreased non-adaptable proteasome pool, loss of UBR2, an ubiquitin ligase that regulates Rpn4 turnover, results in elevated Rpn4 levels, which upregulates UPS components. Increased UPS capacity significantly enhances replicative lifespan (RLS) and resistance to proteotoxic stress, while reduced UPS capacity has opposing consequences. Despite tight transcriptional co-regulation of the UPS and oxidative detoxification systems, the impact of proteasome capacity on lifespan is independent of the latter, since elimination of Yap1, a key regulator of the oxidative stress response, does not affect lifespan extension of cells with higher proteasome capacity. Moreover, since elevated proteasome capacity results in improved clearance of toxic huntingtin fragments in a yeast model for neurodegenerative diseases, we speculate that the observed lifespan extension originates from prolonged elimination of damaged proteins in old mother cells. Epistasis analyses indicate that proteasome-mediated modulation of lifespan is at least partially distinct from dietary restriction, Tor1, and Sir2. These findings demonstrate that UPS capacity determines yeast RLS by a mechanism that is distinct from known longevity pathways and raise the possibility that interventions to promote enhanced proteasome function will have beneficial effects on longevity and age-related disease in humans

CodonTest: Modeling Amino Acid Substitution Preferences in Coding Sequences

Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of rate classes, where is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes

A Genome-Wide Immunodetection Screen in S. cerevisiae Uncovers Novel Genes Involved in Lysosomal Vacuole Function and Morphology

Vacuoles of yeast Saccharomyces cerevisiae are functionally analogous to mammalian lysosomes. Both are cellular organelles responsible for macromolecular degradation, ion/pH homeostasis, and stress survival. We hypothesized that undefined gene functions remain at post-endosomal stage of vacuolar events and performed a genome-wide screen directed at such functions at the late endosome and vacuole interface – ENV genes. The immunodetection screen was designed to identify mutants that internally accumulate precursor form of the vacuolar hydrolase carboxypeptidase Y (CPY). Here, we report the uncovering and initial characterizations of twelve ENV genes. The small size of the collection and the lack of genes previously identified with vacuolar events are suggestive of the intended exclusive functional interface of the screen. Most notably, the collection includes four novel genes ENV7, ENV9, ENV10, and ENV11, and three genes previously linked to mitochondrial processes – MAM3, PCP1, PPE1. In all env mutants, vesicular trafficking stages were undisturbed in live cells as assessed by invertase and active α-factor secretion, as well as by localization of the endocytic fluorescent marker FM4-64 to the vacuole. Several mutants exhibit defects in stress survival functions associated with vacuoles. Confocal fluorescence microscopy revealed the collection to be significantly enriched in vacuolar morphologies suggestive of fusion and fission defects. These include the unique phenotype of lumenal vesicles within vacuoles in the novel env9Δ mutant and severely fragmented vacuoles upon deletion of GET4, a gene recently implicated in tail anchored membrane protein insertion. Thus, our results establish new gene functions in vacuolar function and morphology, and suggest a link between vacuolar and mitochondrial events