scholarly journals Proteostasis is adaptive: Balancing chaperone holdases against foldases

2020 ◽  
Vol 16 (12) ◽  
pp. e1008460
Author(s):  
Adam MR de Graff ◽  
David E. Mosedale ◽  
Tilly Sharp ◽  
Ken A. Dill ◽  
David J. Grainger

Because a cell must adapt to different stresses and growth rates, its proteostasis system must too. How do cells detect and adjust proteome folding to different conditions? Here, we explore a biophysical cost-benefit principle, namely that the cell should keep its proteome as folded as possible at the minimum possible energy cost. This can be achieved by differential expression of chaperones–balancing foldases (which accelerate folding) against holdases (which act as parking spots). The model captures changes in the foldase-holdase ratio observed both within organisms during aging and across organisms of varying metabolic rates. This work describes a simple biophysical mechanism by which cellular proteostasis adapts to meet the needs of a changing growth environment.

2014 ◽  
pp. 281-292
Author(s):  
Einat Shalev-Goldman ◽  
Trevor O’Neill ◽  
Robert Ross
Keyword(s):  

Author(s):  
Martin Peterson

The focus of this chapter is on the application of the Cost-Benefit Principle to technological issues. Cost-benefit analysis is not a single, well-defined methodology but rather a set of slightly different, formalized techniques for weighing costs against benefits in a systematic manner. Four criteria for mainstream cost-benefit analysis are stated, and a paradigm case to which all those techniques are applicable is identified. How the Cost-Benefit Principle can take rights and other deontological constraints into account in a systematic manner is also explained. The conclusion is that the Cost-Benefit Principle can be accepted by consequentialists as well as many nonconsequentialists.


2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  

Abstract Background Lactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data. Results A genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden–Meyerhof–Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden–Meyerhof–Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies. Conclusion We have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.


2001 ◽  
Vol 58 (3) ◽  
pp. 585-593 ◽  
Author(s):  
Jordan S Rosenfeld ◽  
Shelly Boss

To assess freshwater habitat requirements of juvenile anadromous cutthroat trout, Oncorhynchus clarki, we measured habitat preference and growth rates of young-of-the-year (YOY) and 1- to 2-year-old fish confined to either pools or riffles in Husdon Creek, British Columbia, during 1999. YOY preferred pools to riffles in habitat-preference experiments, despite normally occurring at lower densities in pools. YOY grew in both pools and riffles when experimentally confined to either habitat, but growth rates were higher in pools. Larger juvenile cutthroat trout, on average, grew in pools, but consistently lost weight in riffles, indicating that pools are a habitat preference for YOY but a requirement for larger fish. A bioenergetic cost–benefit analysis (based on swimming costs and energy intake from invertebrate drift) indicates that energetics alone are sufficient to account for avoidance of riffles by larger cutthroat trout, without having to invoke greater predation risk in shallow habitats. Energetics modeling demonstrates that the smaller size and energetic needs of YOY allow exploitation of habitats (e.g., pocket pools in riffles) that are unavailable to larger fish.


2017 ◽  
Author(s):  
Henning Onsbring Gustafson ◽  
Mahwash Jamy ◽  
Thijs J. G. Ettema

SummaryWhile ciliates of the genus Stentor are known for their ability to regenerate when their cells are damaged or even fragmented, the physical and molecular mechanisms underlying this process are poorly understood. To identify genes involved in the regenerative capability of Stentor cells, RNA sequencing of individual Stentor polymorphus cell fragments was performed. After splitting a cell over the anterior-posterior axis, the posterior fragment has to regenerate the oral apparatus, while the anterior part needs to regenerate the hold fast. Altogether, differential expression analysis of both posterior and anterior S. polymorphus cell fragments for four different post-split time points revealed over 10,000 up-regulated genes throughout the regeneration process. Among these, genes involved in cell signaling, microtubule-based movement and cell cycle regulation seemed to be particularly important during cellular regeneration. We identified roughly nine times as many up-regulated genes in regenerating S. polymorphus posterior fragments as compared to anterior fragments, indicating that regeneration of the anterior oral apparatus is a complex process that involves many genes. Our analyses identified several expanded groups of genes such as dual-specific tyrosine-(Y)-phosphorylation regulated kinases and MORN domain containing proteins that seemingly act as key-regulators of cellular regeneration. In agreement with earlier morphological and cell biological studies, our differential expression analyses indicate that cellular regeneration and vegetative division share many similarities.


2019 ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  

AbstractBackgroundLactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data.ResultsA genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden-Meyerhof-Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden-Meyerhof-Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies.ConclusionWe have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4283-4283
Author(s):  
Chieh Lee Wong ◽  
Andrew Innes ◽  
Baoshan Ma ◽  
Gareth Gerrard ◽  
Zainul Abidin Norziha ◽  
...  

Abstract Introduction Despite significant progress in the understanding of the molecular pathogenesis of myeloproliferative neoplasms (MPN) and the identification of high molecular risk (HMR) genes (i.e. ASXL1, EZH2, IDH1 and IDH2 genes), the mechanisms by which different cell types predominate in the different disease subtypes and their implications for prognosis remain uncertain. Given the recently described association of senescence and fibrosis in a number of pathologies by Menoz-Espin et al, we hypothesized that genes implicated in oncogene-induced senescence (OIS) and senescence associated secretory phenotype (SASP) may contribute to the pathogenesis of these neoplastic bone marrow disorders that frequently show evidence of fibrosis. Specifically, we were interested in the gene expression levels in different disease subtypes, at a cell-type level, and whether these patterns of differential expression were distinct from the transforming JAK-STAT pathway and the HMR genes. Aim To elucidate the role of OIS and SASP genes in the pathogenesis of MPN subtypes by determining the differential expression of the genes in specific cell types in patients with MPN. Methods We performed gene expression profiling on normal controls (NC) and patients with MPN who were diagnosed with essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) according to the 2008 WHO diagnostic criteria. Two cohorts of patients, the patient and validation cohorts, from 3 tertiary-level hospitals were recruited prospectively over 3 years. Peripheral blood samples were taken and sorted into polymorphonuclear cells (PMN), mononuclear cells (MNC) and T cells. RNA was extracted from each cell population. Gene expression profiling of the human transcriptome was performed using microarray and RNA sequencing on the patient and validation cohorts respectively. Gene expression analyses (GEA) were performed on 4 sets of genes derived from publicly available or custom derived gene set enrichment analysis: 92 OIS genes, 88 SASP genes (Gil et al), 4 HMR genes, and 126 genes associated with JAK-STAT pathway. Gene expression levels for each cell type in each disease were compared with NC to obtain the differential expression of the genes. RNA-seq analysis of samples from the validation cohort was used to validate the microarray results from the patient cohort. Results Twenty-eight patients (10 ET, 11 PV and 7 PMF) and 11 NC were recruited into the patient cohort. Twelve patients (4 ET, 4 PV and 4 PMF) and 4 NC were recruited into the validation cohort. After combination of the microarray and RNA-seq datasets, GEA of the OIS genes revealed the differential expressions of MCTP1 and SULT1B1 genes by PMN in PV but of none in PMF. In contrast, the BEX1 gene was identified as differentially expressed by MNC in PMF but none in PV. GEA of the SASP genes revealed differential expression of THBS1 gene by MNC in PMF but of none in PV. None of the SASP genes were differentially expressed by PMN in either PV or PMF. No differentially expressed genes were identified by PMN or MNC in ET, or by T cells in any of the diseases. Notably, GEA of the HMR genes and genes associated with the JAK-STAT pathways did not show any differential expression in any disease subtype by any cell type. Conclusions We have found strikingly distinct patterns of differential expression of senescence associated genes by PMN (in PV) and MNC (in PMF). These results provide a novel insight into the mechanisms underlying the different phenotype of the MPN subtypes and also to the cells responsible for mediating the differences. The lack of differential expression of OIS and SASP genes in ET may reflect the milder clinical phenotype of the disease. Although mutations in the HMR genes are associated with poor prognosis in PMF, the lack of differential expression in these genes and genes associated with the JAK-STAT pathway is in keeping with their mutated status and suggests that they give rise to the disease phenotypes via altering downstream expression of genes associated in other pathways such as the senescence pathways studied here. Further studies are warranted to investigate the role of these genes and the pathways involved in senescence at a cell-type specific level in order to gain further insight into how they can potentially give rise to the various disease phenotypes in MPN and unmask potential therapeutic targets. Disclosures Aitman: Illumina: Honoraria.


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