Different Levels of Catabolite Repression Optimize Growth in Stable and Variable Environments
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{"title"=>"Different Levels of Catabolite Repression Optimize Growth in Stable and Variable Environments", "type"=>"journal", "authors"=>[{"first_name"=>"Aaron M.", "last_name"=>"New", "scopus_author_id"=>"16302011500"}, {"first_name"=>"Bram", "last_name"=>"Cerulus", "scopus_author_id"=>"56031395700"}, {"first_name"=>"Sander K.", "last_name"=>"Govers", "scopus_author_id"=>"55628154500"}, {"first_name"=>"Gemma", "last_name"=>"Perez-Samper", "scopus_author_id"=>"55177040400"}, {"first_name"=>"Bo", "last_name"=>"Zhu", "scopus_author_id"=>"55938336400"}, {"first_name"=>"Sarah", "last_name"=>"Boogmans", "scopus_author_id"=>"36027882900"}, {"first_name"=>"Joao B.", "last_name"=>"Xavier", "scopus_author_id"=>"55220759500"}, {"first_name"=>"Kevin J.", "last_name"=>"Verstrepen", "scopus_author_id"=>"6602078067"}], "year"=>2014, "source"=>"PLoS Biology", "identifiers"=>{"sgr"=>"84893765873", "scopus"=>"2-s2.0-84893765873", "doi"=>"10.1371/journal.pbio.1001764", "isbn"=>"1545-7885 (Electronic)\\n1544-9173 (Linking)", "pui"=>"372349034", "issn"=>"15449173", "pmid"=>"24453942"}, "id"=>"986b6824-8de0-39d2-be43-4cf0b61d5314", "abstract"=>"Organisms respond to environmental changes by adapting the expression of key genes. However, such transcriptional reprogramming requires time and energy, and may also leave the organism ill-adapted when the original environment returns. Here, we study the dynamics of transcriptional reprogramming and fitness in the model eukaryote Saccharomyces cerevisiae in response to changing carbon environments. Population and single-cell analyses reveal that some wild yeast strains rapidly and uniformly adapt gene expression and growth to changing carbon sources, whereas other strains respond more slowly, resulting in long periods of slow growth (the so-called \"lag phase\") and large differences between individual cells within the population. We exploit this natural heterogeneity to evolve a set of mutants that demonstrate how the frequency and duration of changes in carbon source can favor different carbon catabolite repression strategies. At one end of this spectrum are \"specialist\" strategies that display high rates of growth in stable environments, with more stringent catabolite repression and slower transcriptional reprogramming. The other mutants display less stringent catabolite repression, resulting in leaky expression of genes that are not required for growth in glucose. This \"generalist\" strategy reduces fitness in glucose, but allows faster transcriptional reprogramming and shorter lag phases when the cells need to shift to alternative carbon sources. Whole-genome sequencing of these mutants reveals that mutations in key regulatory genes such as HXK2 and STD1 adjust the regulation and transcriptional noise of metabolic genes, with some mutations leading to alternative gene regulatory strategies that allow \"stochastic sensing\" of the environment. Together, our study unmasks how variable and stable environments favor distinct strategies of transcriptional reprogramming and growth.", "link"=>"http://www.mendeley.com/research/different-levels-catabolite-repression-optimize-growth-stable-variable-environments", "reader_count"=>196, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>7, "Researcher"=>41, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>60, "Student > Postgraduate"=>12, "Student > Master"=>38, "Other"=>4, "Student > Bachelor"=>14, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>7}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>7, "Researcher"=>41, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>60, "Student > Postgraduate"=>12, "Student > Master"=>38, "Other"=>4, "Student > Bachelor"=>14, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>7}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>132, "Chemical Engineering"=>1, "Chemistry"=>4, "Computer Science"=>3, "Earth and Planetary Sciences"=>1, "Engineering"=>5, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>27, "Medicine and Dentistry"=>3, "Physics and Astronomy"=>6, "Social Sciences"=>1, "Immunology and Microbiology"=>4, "Mathematics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>3}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Engineering"=>{"Engineering"=>5}, "Chemistry"=>{"Chemistry"=>4}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>132}, "Computer Science"=>{"Computer Science"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>27}}, "reader_count_by_country"=>{"Colombia"=>1, "Argentina"=>1, "United States"=>6, "Portugal"=>1, "Switzerland"=>2, "Spain"=>1, "Canada"=>1, "Sweden"=>1, "Netherlands"=>2, "Belgium"=>3, "Mexico"=>1, "Israel"=>1, "France"=>3}, "group_count"=>8}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1346638"], "description"=>"<p>(A) Example of a growth curve showing the biphasic growth associated with the switch from one carbon source to another (diauxic shift) of a strain (YS4) growing in the presence of LG supplemented with galactose. The figure shows a marked decrease in growth rate (lag phase) during the switch from glucose to maltose. MaxR is the maximal growth rate (or maximal fitness) attained at the beginning of the experiment when glucose levels are high, and correspond closely with growth rate measurements made of cells growing in very dilute conditions (not shown). GMR is a measure of average fitness throughout the experiment, calculated as the average growth rate between two preset cell densities that represent the beginning of measurable growth and the onset of stationary phase (see <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#s4\" target=\"_blank\">Materials and Methods</a> for details). (B) Same data as panel (A), where the instantaneous growth rates of the culture are plotted as a function of population size. This representation shows more clearly how growth decelerates during the lag phase, leading to the often large difference between MaxR and GMR (black dotted line). (C and D) Growth pattern of a reference strain (S288c) with a pronounced lag phase growing either HG conditions (3% glucose, green) or 0.5% glucose, either alone (red) or supplemented with galactose (blue), maltose (purple). The growth rate in 3% glucose is relatively stable, whereas growth rates in the other media are more variable, with a temporary decrease typical of the lag phase when cells shift their metabolism from glucose to another carbon source. (E and F) Similar to (B) and (C) but with a strain UWOPS83-787.3 that shows almost equal fitness in different media. Note that the lag phase is barely detectable, and that growth only slows down at the end of the experiment, probably because of the depletion of nutrients and the accumulation of ethanol and other toxic metabolites. (G) Live-cell microscopy of yeast populations shifting between glucose and other carbon sources allows measurement of the lag phase of individual cells. Each curve represents the cumulative distribution histogram of single-cell lag phases of 1 of 18 different yeast strains. Each trace represents the fraction of a population of one given strain that has escaped the lag phase after a transfer from glucose to maltose as measured by budding events (<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#s4\" target=\"_blank\">Materials and Methods</a>). The histograms reveal large differences in lag duration between strains, as well as variation in lag duration between individual cells within populations. One strain was omitted from this analysis because fewer than 1 in 150 cells resumed growth after transition to maltose. (H) Correlation between the average single-cell lags from (1 g) and population-level fitness variability (i.e., the variability of the GMR across different growth media). The vertical axis shows the average duration of a strain's lag phase (as measured by single-cell live microscopy), and error bars on this axis correspond to the lower and upper quartiles. The size of each data point is proportional to the fraction of cells that were observed to resume growth after transition to maltose. The horizontal axis represents the ratio of a strain's fitness in media requiring diauxic shift (LG, LG + galactose, and LG + maltose), relative to its fitness in stable HG conditions. Error bars on this axis are the standard deviations of 1,000 repeated calculations of the statistic obtained by random sampling of one biological replicate from each condition (<i>n</i> = 2–6 per strain in each condition). See also main text, <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#pbio.1001764.s001\" target=\"_blank\">Dataset S1</a>, and <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#pbio.1001764.s009\" target=\"_blank\">Figure S1</a>.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "strains", "differences", "duration", "lag"], "article_id"=>900490, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Yeast_strains_show_large_differences_in_the_duration_of_the_lag_phase_/900490", "title"=>"Yeast strains show large differences in the duration of the lag phase.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346639"], "description"=>"<p>A population of glucose-repressed MALS-YeCitrine reference strain (S288c) cells was grown in maltose until 50% of cells had escaped the lag phase and committed to growth on maltose, and then transferred back into glucose-containing media to measure the costs of commitment. Commitment to growth in maltose was measured as the cells' initial expression of the maltase-YeCitrine reporter. These cells were then tracked by time-lapse microscopy to allow growth rate measurements. The blue bars represent cells committed to growth on maltose, which grow at significantly longer doubling times after they were transferred back to glucose compared to sister cells that were still in the lag phase when they were transferred back to glucose (red bars). The results of a Mann–Whitney U test, reported in <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#pbio.1001764.s010\" target=\"_blank\">Figure S2E</a>, show that these differences are robust for MAL “ON” cutoff values greater than background levels (<i>p</i><0.01).</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "adaptation", "carbon"], "article_id"=>900491, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rapid_adaptation_to_a_new_carbon_source_can_come_at_a_fitness_cost_/900491", "title"=>"Rapid adaptation to a new carbon source can come at a fitness cost.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346640"], "description"=>"<p>Parallel cultures of a strain showing long lag phases were evolved in variable nutrient conditions, by transferring the cells back and forth between glucose and maltose medium. After 6–8 cycles, individual cells were isolated from the different cultures and their growth properties were analyzed (see main text for details). (A) Single-cell lag profiles from representative isolates from independently evolving populations, illustrating the diversity of glucose-to-maltose lag phase lengths. Note that a few isolates showed longer lag phases than the ancestral strain (Isolate 6, orange trace and <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#pbio.1001764.s011\" target=\"_blank\">Figure S3C</a>). (B) The isolates are fitter than the ancestor in conditions mimicking the selection. Three of these isolates and the ancestor were directly competed against a reference strain in conditions mimicking the selection protocol (<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#s4\" target=\"_blank\">Materials and Methods</a>). The large circles represent the average fitness relative to the ancestor of six biological replicates, and error bars represent standard deviations.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "environments", "shapes", "lag"], "article_id"=>900492, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experimental_evolution_in_variable_environments_shapes_the_lag_phase_/900492", "title"=>"Experimental evolution in variable environments shapes the lag phase.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346641"], "description"=>"<p>Many evolved strains show reduced lag phases in variable environments (LG; LG + maltose or LG + galactose). (A) Growth pattern of the ancestral strain in either stable glucose conditions (HG or in media that require a shift from glucose to a less preferred carbon source (LG; LG + maltose or LG + galactose). (B) Similar analysis as panel (A) of Isolate 1 from <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#pbio-1001764-g003\" target=\"_blank\">Figure 3A</a>. Note that the reduction in growth speed (lag phase) is much less pronounced than for the ancestral strain shown in panel (A). (C) Dividing the growth rates of the evolved clone by the ancestral reveals that the evolved clone grows more slowly than the ancestral strain, except during the lag phase, where the evolved isolate shows a much higher growth rate. This shorter lag phase is responsible for the increased GMR relative to the ancestral strain. (D) The MaxR and the GMRs are anticorrelated. Each point represents the geometric mean of the GMRs in all different conditions used in this study (LG, LG + galactose, LG + maltose, HG) versus the geometric mean of all MaxRs in the same conditions. Error bars represent standard deviations. The grey square represents the ancestral strain.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "tradeoffs", "adaptation"], "article_id"=>900493, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fitness_tradeoffs_between_rapid_adaptation_and_MaxRs_/900493", "title"=>"Fitness tradeoffs between rapid adaptation and MaxRs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346642"], "description"=>"<p>Sequencing of the genomes of isolates with shorter lag phases isolated after repeated cycling between glucose and maltose medium revealed mutations in two genes, <i>STD1</i> and <i>HXK2</i> (see text for details). (A) Sanger sequencing confirmed the presence of multiple <i>HXK2</i> mutations and one <i>STD1</i> mutation in the evolved short-lagged strains. (B) Single-cell lag profiles of independent transformants of the ancestral strain bearing either WT (red and purple traces) or evolved (blue traces) <i>HXK2</i> alleles. Black traces correspond to the original evolved strains; the finely dotted line is Isolate 1 and the coarsely dotted line is Isolate 2. (C) Same as (B) but for the <i>STD1</i> allele identified in Isolate 3. Shown in blue are two independent transformants bearing Isolate 3's <i>STD1</i> allele.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "carbon", "catabolite", "repression", "genes", "diversified"], "article_id"=>900494, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mutations_in_global_carbon_catabolite_repression_genes_give_rise_to_diversified_growth_behaviors_/900494", "title"=>"Mutations in global carbon catabolite repression genes give rise to diversified growth behaviors.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346643"], "description"=>"<p>(A) Flow cytometric analysis of four characteristic phenotypes that emerged after repeated glucose-to-maltose selection cycles show different degrees of glucose repression of the <i>MAL</i> genes. The different evolved strains with fluorescently tagged <i>MALS</i> genes were pregrown in maltose and then transferred to glucose media with or without maltose for 20 h of exponential growth, after which fluorescence intensities were measured using flow cytometry. (B) <i>MAL</i> expression in the evolved strains depends on the history of the cells. Initial state (black traces) of samples grown in maltose (left) or glucose (right) are shown, and in blue and red are the same cultures' expression levels after 20 h of growth in glucose alone or in a mixture of glucose and maltose. Note that the <i>MAL</i> expression level in the glucose/maltose mixture clearly depends on the history of the cells; the ancestral strain does not display this hysteresis.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "repeated", "cycling", "glucose", "maltose", "altered", "catabolite", "repression"], "article_id"=>900495, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mutants_isolated_after_repeated_cycling_between_glucose_and_maltose_show_altered_catabolite_repression_of_the_MAL_genes_/900495", "title"=>"Mutants isolated after repeated cycling between glucose and maltose show altered catabolite repression of the <i>MAL</i> genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346645"], "description"=>"<p>Shown are modeled growth characteristics and experimental results of a head-to-head competition between Isolate 1, a strain with reduced catabolite repression, short lag phases, and slow rates of growth in glucose, and Isolate 6, a strain with stringent catabolite repression, long and heterogeneous lag phases but high growth rates in glucose, under varying regimes of glucose-to-maltose shifts. (A) Modeled fitness landscape predicting the relative abundance of short-lagged Isolate 1 relative to the long-lagged parental strain. The model uses experimentally determined lag phase distributions and adapted growth rates for each strain in maltose or glucose (see main text and <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001764#s4\" target=\"_blank\">Materials and Methods</a> for details). (B) Heat map (same color scale as in A) of experiments where the two isolates were competed for different lengths of time in maltose and glucose (12 different regimes, with each 5–6 repetitions). The strains were grown for 20 h in glucose before being transferred to maltose for 1 h, and then mixed together to begin the competition experiment. (C) The cultures represented by the points in panel (B) corresponding to 4 h∶20 h, 8 h∶16 h, and 12 h∶12 h maltose-to-glucose cycles were repeatedly subjected to the same regime of maltose-to-glucose changes to track relative abundance of the competing clones over time. Dots represent experimental observations, and lines represent modeled growth characteristics of these strains.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "tradeoffs", "catabolite", "repression", "duration"], "article_id"=>900497, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_tradeoffs_associated_with_different_levels_of_catabolite_repression_depend_upon_the_frequency_and_duration_of_environmental_change_/900497", "title"=>"The tradeoffs associated with different levels of catabolite repression depend upon the frequency and duration of environmental change.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-14 02:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/1346649", "https://ndownloader.figshare.com/files/1346650", "https://ndownloader.figshare.com/files/1346651", "https://ndownloader.figshare.com/files/1346652", "https://ndownloader.figshare.com/files/1346653", "https://ndownloader.figshare.com/files/1346654", "https://ndownloader.figshare.com/files/1346655", "https://ndownloader.figshare.com/files/1346656", "https://ndownloader.figshare.com/files/1346657", "https://ndownloader.figshare.com/files/1346658", "https://ndownloader.figshare.com/files/1346659", "https://ndownloader.figshare.com/files/1346660", "https://ndownloader.figshare.com/files/1346661", "https://ndownloader.figshare.com/files/1346662", "https://ndownloader.figshare.com/files/1346663", "https://ndownloader.figshare.com/files/1346664", "https://ndownloader.figshare.com/files/1346665", "https://ndownloader.figshare.com/files/1346666", "https://ndownloader.figshare.com/files/1346667", "https://ndownloader.figshare.com/files/1346668", "https://ndownloader.figshare.com/files/1346669", "https://ndownloader.figshare.com/files/1346670", "https://ndownloader.figshare.com/files/1346671", "https://ndownloader.figshare.com/files/1346672", "https://ndownloader.figshare.com/files/1346674"], "description"=>"<div><p>Organisms respond to environmental changes by adapting the expression of key genes. However, such transcriptional reprogramming requires time and energy, and may also leave the organism ill-adapted when the original environment returns. Here, we study the dynamics of transcriptional reprogramming and fitness in the model eukaryote <i>Saccharomyces cerevisiae</i> in response to changing carbon environments. Population and single-cell analyses reveal that some wild yeast strains rapidly and uniformly adapt gene expression and growth to changing carbon sources, whereas other strains respond more slowly, resulting in long periods of slow growth (the so-called “lag phase”) and large differences between individual cells within the population. We exploit this natural heterogeneity to evolve a set of mutants that demonstrate how the frequency and duration of changes in carbon source can favor different carbon catabolite repression strategies. At one end of this spectrum are “specialist” strategies that display high rates of growth in stable environments, with more stringent catabolite repression and slower transcriptional reprogramming. The other mutants display less stringent catabolite repression, resulting in leaky expression of genes that are not required for growth in glucose. This “generalist” strategy reduces fitness in glucose, but allows faster transcriptional reprogramming and shorter lag phases when the cells need to shift to alternative carbon sources. Whole-genome sequencing of these mutants reveals that mutations in key regulatory genes such as <i>HXK2</i> and <i>STD1</i> adjust the regulation and transcriptional noise of metabolic genes, with some mutations leading to alternative gene regulatory strategies that allow “stochastic sensing” of the environment. Together, our study unmasks how variable and stable environments favor distinct strategies of transcriptional reprogramming and growth.</p></div>", "links"=>[], "tags"=>["Evolutionary biology", "Evolutionary ecology", "Evolutionary genetics", "genetics", "gene expression", "microbiology", "microbial ecology", "Microbial evolution", "Microbial growth and development", "Microbial mutation", "Model organisms", "Yeast and fungal models", "Saccharomyces cerevisiae", "catabolite", "repression", "optimize"], "article_id"=>900501, "categories"=>["Biological Sciences"], "users"=>["Aaron M. New", "Bram Cerulus", "Sander K. Govers", "Gemma Perez-Samper", "Bo Zhu", "Sarah Boogmans", "Joao B. Xavier", "Kevin J. Verstrepen"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1001764.s001", "https://dx.doi.org/10.1371/journal.pbio.1001764.s002", "https://dx.doi.org/10.1371/journal.pbio.1001764.s003", "https://dx.doi.org/10.1371/journal.pbio.1001764.s004", "https://dx.doi.org/10.1371/journal.pbio.1001764.s005", "https://dx.doi.org/10.1371/journal.pbio.1001764.s006", "https://dx.doi.org/10.1371/journal.pbio.1001764.s007", "https://dx.doi.org/10.1371/journal.pbio.1001764.s008", "https://dx.doi.org/10.1371/journal.pbio.1001764.s009", "https://dx.doi.org/10.1371/journal.pbio.1001764.s010", "https://dx.doi.org/10.1371/journal.pbio.1001764.s011", "https://dx.doi.org/10.1371/journal.pbio.1001764.s012", "https://dx.doi.org/10.1371/journal.pbio.1001764.s013", "https://dx.doi.org/10.1371/journal.pbio.1001764.s014", "https://dx.doi.org/10.1371/journal.pbio.1001764.s015", "https://dx.doi.org/10.1371/journal.pbio.1001764.s016", "https://dx.doi.org/10.1371/journal.pbio.1001764.s017", "https://dx.doi.org/10.1371/journal.pbio.1001764.s018", "https://dx.doi.org/10.1371/journal.pbio.1001764.s019", "https://dx.doi.org/10.1371/journal.pbio.1001764.s020", "https://dx.doi.org/10.1371/journal.pbio.1001764.s021", "https://dx.doi.org/10.1371/journal.pbio.1001764.s022", "https://dx.doi.org/10.1371/journal.pbio.1001764.s023", "https://dx.doi.org/10.1371/journal.pbio.1001764.s024", "https://dx.doi.org/10.1371/journal.pbio.1001764.s025"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Different_Levels_of_Catabolite_Repression_Optimize_Growth_in_Stable_and_Variable_Environments_/900501", "title"=>"Different Levels of Catabolite Repression Optimize Growth in Stable and Variable Environments", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-01-14 02:49:06"}

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