Cell Size and Morphological Properties of Yeast Saccharomyces Cerevisiae in Relation to Growth Temperature

Cell volume is an important parameter for modelling cellular processes. Temperature-induced variability of cellular size, volume, intracellular granularity, a fraction of budding cells of yeast Saccharomyces cerevisiae CEN.PK 113–7D (in anaerobic glucose unlimited batch cultures) were measured by flow cytometry and matched with the performance of the biomass growth (maximal specific growth rate (μmax), specific rate of glucose consumption, the rate of maintenance, biomass yield on glucose). The critical diameter of single cells was 7.94 μm and it is invariant at growth temperatures above 18.5◦C. Below 18.5◦C, it exponentially increases up to 10.2 μm. The size of the bud linearly depends on μmax, and it is between 50% at 5◦C and 90% at 31◦C of the averaged single cell. The intracellular granularity (side scatter channel (SSC)-index) negatively depends on μmax. There are two temperature regions (5–31◦C vs. 33–40◦C) where the relationship between SSC-index and various cellular parameters differ significantly. In supraoptimal temperature range (33–40◦C), cells are less granulated perhaps due to a higher rate of the maintenance. There is temperature dependent passage through the checkpoints in the cell cycle which influences the μmax. The results point to the existence of two different morphological states of yeasts in these different temperature regions. © FEMS 2018. All rights reserved.The experimental part of the research has been carried out in Institute of Biochemical Engineering (IBVT, University of Stuttgart, Germany) and has been funded by the transnational research initiative ‘Systems Biology of Microorganisms (SysMO)’ within network MOSES: ‘MicroOrganism Systems Biology: Energy and Saccharomyces cerevisiae’ [http://www.sysmo.net]. Additionally, the author would like to thank Prof.Peter Scheurich (Institute of Cell Biology and Immunology, University of Stuttgart, Germany) for the experimental support, Achim Hauck (IBVT, University of Stuttgart, Germany) and Dr.Xuelian Yang (Beijing Engineering and Technology Research Center of Food Additives, Beijing Technology & Business University, Beijing, China) for the research assistance, Dr.Pavlo Holenya (Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, Germany) for the discussion of the results

Validation of reference genes for quantitative RT-qPCR studies of gene expression in Atlantic cod (Gadus morhua l.) during temperature stress

<p>Abstract</p> <p>Background</p> <p>One important physiological response to environmental stress in animals is change in gene expression. To obtain reliable data from gene expression studies using RT-qPCR it is important to evaluate a set of possible reference genes as normalizers for expression. The expression of these candidate genes should be analyzed in the relevant tissues during normal and stressed situations. To find suitable reference genes it was crucial that the genes were stably expressed also during a situation of physiological stress. For poikilotermic animals like cod, changes in temperature are normal, but if the changes are faster than physiological compensation, the animals respond with typical stress responses. It has previously been shown that Atlantic cod show stress responses when elevation of water temperature is faster than 1 degree/day, for this reason we chose hyperthermia as stress agent for this experiment.</p> <p>Findings</p> <p>We here describe the expression of eight candidate reference genes from Atlantic cod (<it>Gadus morhua l</it>.) and their stability during thermal stress (temperature elevation of one degree C/day for 5 days). The genes investigated were: Eukaryotic elongation factor 1 alpha, <it>ef1a</it>; 18s ribosomal RNA; <it>18s</it>, Ubiquitin conjugate protein; <it>ubiq</it>, cytoskeletal beta-actin; <it>actb</it>, major histcompatibility complex I; MHC-I light chain, beta-2 -microglobulin; <it>b2m</it>, cytoskeletal alpha-tubulin; <it>tba1c</it>, acidic ribosomal phosphoprotein; <it>rplp1</it>, glucose-6-phosphate dehydrogenase; <it>g6pd</it>. Their expression were analyzed in 6 tissues (liver, head kidney, intestine, spleen, heart and gills) from cods exposed to elevated temperature and compared to a control group. Although there were variations between tissues with respect to reference gene stability, four transcripts were more consistent than the others: <it>ubiq</it>, <it>ef1a</it>, <it>18s </it>and <it>rplp1</it>. We therefore used these to analyze the expression of stress related genes (heat shock proteins) induced during hyperthermia. We found that both transcripts were significantly upregulated in several tissues in fish exposed to increased temperature.</p> <p>Conclusion</p> <p>This is the first study comparing reference genes for RT-qPCR analyses of expression during hyperthermia in Atlantic cod. <it>ef1a, 18s, rplp1 </it>and <it>ubiq </it>transcripts were found to be well suited as reference genes during these experimental conditions.</p

MEMOTE for standardized genome-scale metabolic model testing

Supplementary information is available for this paper at https://doi.org/10.1038/s41587-020-0446-yReconstructing metabolic reaction networks enables the development of testable hypotheses of an organisms metabolism under different conditions1. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Geneproteinreaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols2, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking3. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.We acknowledge D. Dannaher and A. Lopez for their supporting work on the Angular parts of MEMOTE; resources and support from the DTU Computing Center; J. Cardoso, S. Gudmundsson, K. Jensen and D. Lappa for their feedback on conceptual details; and P. D. Karp and I. Thiele for critically reviewing the manuscript. We thank J. Daniel, T. Kristjánsdóttir, J. Saez-Saez, S. Sulheim, and P. Tubergen for being early adopters of MEMOTE and for providing written testimonials. J.O.V. received the Research Council of Norway grants 244164 (GenoSysFat), 248792 (DigiSal) and 248810 (Digital Life Norway); M.Z. received the Research Council of Norway grant 244164 (GenoSysFat); C.L. received funding from the Innovation Fund Denmark (project “Environmentally Friendly Protein Production (EFPro2)”); C.L., A.K., N. S., M.B., M.A., D.M., P.M, B.J.S., P.V., K.R.P. and M.H. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 686070 (DD-DeCaF); B.G.O., F.T.B. and A.D. acknowledge funding from the US National Institutes of Health (NIH, grant number 2R01GM070923-13); A.D. was supported by infrastructural funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Cluster of Excellence EXC 2124 Controlling Microbes to Fight Infections; N.E.L. received funding from NIGMS R35 GM119850, Novo Nordisk Foundation NNF10CC1016517 and the Keck Foundation; A.R. received a Lilly Innovation Fellowship Award; B.G.-J. and J. Nogales received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 686585 for the project LIAR, and the Spanish Ministry of Economy and Competitivity through the RobDcode grant (BIO2014-59528-JIN); L.M.B. has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 633962 for project P4SB; R.F. received funding from the US Department of Energy, Offices of Advanced Scientific Computing Research and the Biological and Environmental Research as part of the Scientific Discovery Through Advanced Computing program, grant DE-SC0010429; A.M., C.Z., S.L. and J. Nielsen received funding from The Knut and Alice Wallenberg Foundation, Advanced Computing program, grant #DE-SC0010429; S.K.’s work was in part supported by the German Federal Ministry of Education and Research (de.NBI partner project “ModSim” (FKZ: 031L104B)); E.K. and J.A.H.W. were supported by the German Federal Ministry of Education and Research (project “SysToxChip”, FKZ 031A303A); M.K. is supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054); J.A.P. and G.L.M. acknowledge funding from US National Institutes of Health (T32-LM012416, R01-AT010253, R01-GM108501) and the Wagner Foundation; G.L.M. acknowledges funding from a Grand Challenges Exploration Phase I grant (OPP1211869) from the Bill & Melinda Gates Foundation; H.H. and R.S.M.S. received funding from the Biotechnology and Biological Sciences Research Council MultiMod (BB/N019482/1); H.U.K. and S.Y.L. received funding from the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea; H.U.K. received funding from the Bio & Medical Technology Development Program of the NRF, the Ministry of Science and ICT (NRF-2018M3A9H3020459); P.B., B.J.S., Z.K., B.O.P., C.L., M.B., N.S., M.H. and A.F. received funding through Novo Nordisk Foundation through the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517); D.-Y.L. received funding from the Next-Generation BioGreen 21 Program (SSAC, PJ01334605), Rural Development Administration, Republic of Korea; G.F. was supported by the RobustYeast within ERA net project via SystemsX.ch; V.H. received funding from the ETH Domain and Swiss National Science Foundation; M.P. acknowledges Oxford Brookes University; J.C.X. received support via European Research Council (666053) to W.F. Martin; B.E.E. acknowledges funding through the CSIRO-UQ Synthetic Biology Alliance; C.D. is supported by a Washington Research Foundation Distinguished Investigator Award. I.N. received funding from National Institutes of Health (NIH)/National Institute of General Medical Sciences (NIGMS) (grant P20GM125503).info:eu-repo/semantics/publishedVersio

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing

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Climate induced temperature effects on growth performance, fecundity and recruitment in marine fish: developing a hypothesis for cause and effect relationships in Atlantic cod (Gadus morhua) and common eelpout (Zoarces viviparus).

Effects of global warming on animal distribution and performance become visible in many marine ecosystems. The present study was designed to develop a concept for a cause and effect understanding with respect to temperature changes and to explain ecological findings based on physiological processes. The concept is based on a wide comparison of invertebrate and fish species with a special focus on recent data obtained in two model species of fish. These fish species are both characterized by northern and southern distribution limits in the North Atlantic: eelpout (Zoarces viviparus), as a typical non-migrating inhabitant of the coastal zone and the cod (Gadus morhua), as a typical inhabitant of the continental shelf with a high importance for fisheries. Mathematical modelling demonstrates a clear significant correlation between climate induced temperature fluctuations and the recruitment of cod stocks. Growth performance in cod is optimal at temperatures close to 10 degreesC, regardless of the population investigated in a latitudinal cline. However, temperature specific growth rates decrease at higher latitudes. Also, fecundity is less in White Sea than in North and Baltic Sea cod or eelpout populations. These findings suggest that a cold-induced shift in energy budget occurs which is unfavorable for growth performance and fecundity. Thermal tolerance limits shift depending on latitude and are characterized by oxygen limitation at both low or high temperatures. Oxygen supply to tissues is optimized at low temperature by a shift in hemoglobin isoforms and oxygen binding properties to lower affinities and higher unloading potential. Protective stimulation of heat shock protein synthesis was not observed. According to a recent model of thermal tolerance the downward shift of tolerance limits during cold adaptation is associated with rising mitochondrial densities and, thus, aerobic capacity and performance in the cold. especially in eurythermal species. At the same time the costs of mitochondrial maintenance reflected by mitochondrial proton leakage should rise leaving a lower energy fraction for growth and reproduction. The preliminary conclusion can be drawn that warming will cause a northern shift of distribution limits for both species with a rise in growth performance and fecundity larger than expected from the Q(10) effect in the north and lower growth or even extinction of the species in the south. Such a shift may heavily affect fishing activities in the North Sea