“…Our recent studies with the use of the so called "longevity mutants" (organisms with increased reproductive potential) showed no significant differences in their time of life (total lifespan). In spite of significant differences in the reproductive potential, the total lifespan of the mutants remained almost identical to that of the wild-type strain (Molon et al, 2015).…”
Section: Introductionmentioning
confidence: 92%
“…On that basis, numerous of "longevity mutants" were proposed. However, when in addition to the number of daughters we also consider the time of life, the only longevity yeast mutant (for longevity expressed in units of time) would be the one that has been recently described as sfp1D (Molon et al, 2015). The product of the SFP1 gene is a protein (split finger-zinc protein) that plays a key role in regulating the biosynthesis of ribosomal proteins.…”
Section: Introductionmentioning
confidence: 99%
“…The product of the SFP1 gene is a protein (split finger-zinc protein) that plays a key role in regulating the biosynthesis of ribosomal proteins. This protein can also have an impact on reproductive potential (Heeren et al, 2009;Molon et al, 2015). An alternative postulate is that the limit of mitotic cycles is not a consequence of accumulation of a "senescence factor" but results from cell achieving its critical volume, which prevents further reproduction (Yang et al, 2011;Zadrag-Tecza et al, 2009).…”
The yeast Saccharomyces cerevisiae has long been used as a model organism for studying the basic mechanisms of aging. However, the main problem with the use of this unicellular fungus is the unit of "longevity". For all organisms, lifespan is expressed in units of time, while in the case of yeast it is defined by the number of daughter cells produced. Additionally, in yeast the phenotypic effects of mutations often show a clear dependence on the genetic background, suggesting the need for an analysis of strains representing different genetic backgrounds. Our results confirm the data presented in earlier papers that the reproductive potential is strongly associated with an increase in cell volume per generation. An excessive cell volume results in the loss of reproductive capacity. These data clearly support the hypertrophy hypothesis. The time of life of all analysed mutants, with the exception of sch9D, is the same as in the case of the wild-type strain. Interestingly, the 121% increase of the fob1D mutant's reproductive potential compared to the sfp1D mutant does not result in prolongation of the mutant's time of life (total lifespan).
“…Our recent studies with the use of the so called "longevity mutants" (organisms with increased reproductive potential) showed no significant differences in their time of life (total lifespan). In spite of significant differences in the reproductive potential, the total lifespan of the mutants remained almost identical to that of the wild-type strain (Molon et al, 2015).…”
Section: Introductionmentioning
confidence: 92%
“…On that basis, numerous of "longevity mutants" were proposed. However, when in addition to the number of daughters we also consider the time of life, the only longevity yeast mutant (for longevity expressed in units of time) would be the one that has been recently described as sfp1D (Molon et al, 2015). The product of the SFP1 gene is a protein (split finger-zinc protein) that plays a key role in regulating the biosynthesis of ribosomal proteins.…”
Section: Introductionmentioning
confidence: 99%
“…The product of the SFP1 gene is a protein (split finger-zinc protein) that plays a key role in regulating the biosynthesis of ribosomal proteins. This protein can also have an impact on reproductive potential (Heeren et al, 2009;Molon et al, 2015). An alternative postulate is that the limit of mitotic cycles is not a consequence of accumulation of a "senescence factor" but results from cell achieving its critical volume, which prevents further reproduction (Yang et al, 2011;Zadrag-Tecza et al, 2009).…”
The yeast Saccharomyces cerevisiae has long been used as a model organism for studying the basic mechanisms of aging. However, the main problem with the use of this unicellular fungus is the unit of "longevity". For all organisms, lifespan is expressed in units of time, while in the case of yeast it is defined by the number of daughter cells produced. Additionally, in yeast the phenotypic effects of mutations often show a clear dependence on the genetic background, suggesting the need for an analysis of strains representing different genetic backgrounds. Our results confirm the data presented in earlier papers that the reproductive potential is strongly associated with an increase in cell volume per generation. An excessive cell volume results in the loss of reproductive capacity. These data clearly support the hypertrophy hypothesis. The time of life of all analysed mutants, with the exception of sch9D, is the same as in the case of the wild-type strain. Interestingly, the 121% increase of the fob1D mutant's reproductive potential compared to the sfp1D mutant does not result in prolongation of the mutant's time of life (total lifespan).
“…The comparison of values of replicative lifespan RLS (expressed in the number of daughters produced) and values of TLS (expressed in units of time) (Fig. 1) clearly demonstrates that the studied “longevity mutants” do not live longer than even the “short lived” mutants, when longevity is expressed in universal units of age, namely the units of time (Molon et al 2015; Zadrag-Tecza et al 2013). Fig.…”
Section: Introductionmentioning
confidence: 86%
“…The deleted genes were mainly ribosomal protein encoding genes or genes related to proteasomal degradation or mitochondria functions (McCormick et al 2015). In turn, the analysis of yeast strains devoid of selected “longevity genes” showed that such strains live no longer than the standard strains of the same background when their length of life is expressed in the most natural units of age and longevity—that is, the units of time (Molon et al 2015; Zadrag-Tecza et al 2013). One can therefore conclude that the methodology used for measuring the lifespan of yeast does not represent the true length of a yeast cell’s life.…”
Experimental gerontology is based on the fundamental assumption that the aging process has a universal character and that the mechanisms of aging are well-conserved among living things. The consequence of this assumption is the use of various organisms, including unicellular yeast Saccharomyces cerevisiae, as models in gerontology, and direct extrapolation of the conclusions drawn from the studies carried on these organisms to human beings. However, numerous arguments suggest that aging is not universal and its mechanisms are not conserved in a wide range of species. Instead, senescence can be treated as a side effect of the evolution of specific features for systematic group, unrelated to the passage of time. Hence, depending on the properties of the group, the senescence and proximal causes of death could have a diverse nature. We postulate that the selection of a model organism to explain the mechanism of human aging and human longevity should be preceded by the analysis of its potential to extrapolate the results to a wide group of organisms. Considering that gerontology is a human-oriented discipline and that aging involves complex, systemic changes affecting the entire organism, the object of experimental studies should be animals which are closest relatives of human beings in evolutionary terms, rather than lower organisms, which do not have sufficient complexity in terms of tissues and organ structures.
Studies of protein phenotypes represent a central challenge of modern genetics in the post-genome era because effective and accurate investigation of protein phenotypes is one of the most critical procedures to identify functional biological processes in microscale, which involves the analysis of multifactorial traits and has greatly contributed to the development of modern biology in the post genome era. Therefore, we have developed a novel computational method that identifies novel proteins associated with certain phenotypes in yeast based on the protein-protein interaction network. Unlike some existing network-based computational methods that identify the phenotype of a query protein based on its direct neighbors in the local network, the proposed method identifies novel candidate proteins for a certain phenotype by considering all annotated proteins with this phenotype on the global network using a shortest path (SP) algorithm. The identified proteins are further filtered using both a permutation test and their interactions and sequence similarities to annotated proteins. We compared our method with another widely used method called random walk with restart (RWR). The biological functions of proteins for each phenotype identified by our SP method and the RWR method were analyzed and compared. The results confirmed a large proportion of our novel protein phenotype annotation, and the RWR method showed a higher false positive rate than the SP method. Our method is equally effective for the prediction of proteins involving in all the eleven clustered yeast phenotypes with a quite low false positive rate. Considering the universality and generalizability of our supporting materials and computing strategies, our method can further be applied to study other organisms and the new functions we predicted can provide pertinent instructions for the further experimental verifications.
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