16 research outputs found
Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources
No full textCells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells' ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types.sponsorship: Fonds Wetenschappelijk Onderzoek Bram Cerulus Lieselotte Vermeerschr Vlaams Instituut voor Biotechnologie Kevin J Verstrepenr European Research Council CoG682009 Bram Cerulus Abbas Jariani Gemma Perez-Samper Kevin J Verstrepenr AB-InBev-Baillet Latour Fund Kevin J Verstrepenr Human Frontier Science Program 246 RGP0050/2013 Abbas Jariani Peter S Swain Kevin J Verstrepenr SULSA Postdoctoral Exchange Scheme Julian M J Pietschr The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. (Fonds Wetenschappelijk Onderzoek, Vlaams Instituut voor Biotechnologie, European Research Council|CoG682009, AB-InBev-Baillet Latour Fund, SULSA Postdoctoral Exchange Scheme, Human Frontier Science Program|246 RGP0050/2013)status: Publishe
Fenotypische variatie en cellulair geheugen van Saccharomyces cerevisiae in stabiele en veranderende suikeromgevingen
No full textThe field of microbiology has long ignored differences between cells within clonal populations. This is at least partly because technical limitations prevented measuring parameters of individual cells. However, the development of single-cell based techniques has revealed that even within clonal populations in a homogeneous environment, a substantial heterogeneity exists between individual cells. This phenomenon is broadly known as phenotypic heterogeneity, or noise. In addition, it became evident that individual cells have the capacity to remember certain environmental signals, which in some cases can increase the adaptation rate when a similar environment returns. This phenomenon is known as cellular or epigenetic memory.
In general, the observation of phenotypic heterogeneity and cellular memory generates two central questions. First, are these phenomena beneficial or harmful to the organism’s fitness? And second, which molecular mechanisms determine or affect these traits? Here, we try to partially answer these questions, using Saccharomyces cerevisiae during growth in stable and fluctuating sugar environments as a model system.
In the first chapter, we address the former question by studying how noise and cellular memory in single-cell division times affects the organism’s fitness. First, using time-lapse microscopy, we analyze the single-cell growth behavior of a variety of genetically distinct yeast populations. We find large differences in individual division times and substantial epigenetic inheritance of division times within mother-daughter lineages. Next, we develop a stochastic model with single-cell parameters based on these measurements to accurately predict population-level growth. Briefly, we find that, for a given mean division time, increasing heterogeneity and epigenetic inheritance of division times increases the population growth rate. In the second chapter, we address the latter question of how we can mechanistically explain the traits of noise and cellular memory. More specifically, we investigate the molecular mechanism that underlies cellular memory in the switch from glucose to maltose in yeast. Using a combination of single-cell measurements and genome-wide screens, we show that in contrast to what has been reported in other cases, the memory is not linked to cytoplasmic inheritance of Mal proteins during glucose growth. Instead, we propose that, in this case, a gradual transition between respiratory and fermentative metabolism causes cellular memory. Taken together, our results show that noise and epigenetic inheritance of division times have the potential to increase population growth rate during exponential growth, and that unexpectedly, cellular memory during growth in fluctuating sugar environments can be determined by a metabolic re-arrangement taking place in central carbon metabolism.status: Publishe
A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast
No full textCurrent methods for single-cell RNA sequencing (scRNA-seq) of yeast cells do not match the throughput and relative simplicity of the state-of-the-art techniques that are available for mammalian cells. In this study, we report how 10x Genomics' droplet-based single-cell RNA sequencing technology can be modified to allow analysis of yeast cells. The protocol, which is based on in-droplet spheroplasting of the cells, yields an order-of-magnitude higher throughput in comparison to existing methods. After extensive validation of the method, we demonstrate its use by studying the dynamics of the response of isogenic yeast populations to a shift in carbon source, revealing the heterogeneity and underlying molecular processes during this shift. The method we describe opens new avenues for studies focusing on yeast cells, as well as other cells with a degradable cell wall.sponsorship: Fonds Wetenschappelijk Onderzoek Lieselotte Vermeersch Bram Cerulus Karin VoordeckersVlaams Instituut voor Biotechnologie Kevin J VerstrepenEuropean Research Council Council CoG682009 Kevin J VerstrepenAB-InBev-Baillet Latour Fund Kevin J VerstrepenHuman Frontier Science Program 246 RGP0050/2013 Kevin J VerstrepenThe funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. (Fonds Wetenschappelijk Onderzoek, Vlaams Instituut voor Biotechnologie, European Research Council|CoG682009, AB-InBev-Baillet Latour Fund, Human Frontier Science Program|246 RGP0050/2013)status: Publishe
The regulatable MAL32 promoter in S. cerevisiae: characteristics and tools to facilitate its use
No full textHere we describe a set of tools to facilitate the use of maltose and the MAL32 promoter for regulated gene expression in yeast, alone or in combination with the GAL1 promoter. Using fluorescent protein reporters we find that under non-inducing conditions the MAL32 promoter exhibits a low basal level of expression, similar to the GAL1 promoter, and that both promoters can be induced independently of each other using the respective sugars, maltose and galactose. While their repression upon glucose addition is immediate and complete, we found that the MAL32 and GAL1 promoter each exhibit distinct induction kinetics. A set of plasmids is available to facilitate the application of the MAL32 promoter for chromosomal modifications using PCR targeting and for plasmid based gene expression. This article is protected by copyright. All rights reserved.sponsorship: We thank Anton Khmelinskii for discussion and comments on the manuscript. Part of the work was funded through the DFG Grant SFB 1036. (DFG|SFB 1036)status: Publishe
Noise and Epigenetic Inheritance of Single-Cell Division Times Influence Population Fitness
No full textThe fitness effect of biological noise remains unclear. For example, even within clonal microbial populations, individual cells grow at different speeds. Although it is known that the individuals’ mean growth speed can affect population-level fitness, it is unclear how or whether growth speed heterogeneity itself is subject to natural selection. Here, we show that noisy single-cell division times can significantly affect population-level growth rate. Using time-lapse microscopy to measure the division times of thousands of individual S. cerevisiae cells across different genetic and environmental backgrounds, we find that the length of individual cells’ division times can vary substantially between clonal individuals and that sublineages often show epigenetic inheritance of division times. By combining these experimental measurements with mathematical modeling, we find that, for a given mean division time, increasing heterogeneity and epigenetic inheritance of division times increases the population growth rate. Furthermore, we demonstrate that the heterogeneity and epigenetic inheritance of single-cell division times can be linked with variation in the expression of catabolic genes. Taken together, our results reveal how a change in noisy single-cell behaviors can directly influence fitness through dynamics that operate independently of effects caused by changes to the mean. These results not only allow a better understanding of microbial fitness but also help to more accurately predict fitness in other clonal populations, such as tumors.sponsorship: B.C. received a doctoral fellowship grant (Aspirant) from Research Foundation Flanders (FWO-Vlaanderen). A.M.N. acknowledges support from the AB-InBev Baillet-Latour Foundation, Marie Curie Actions, and an EMBO Long-Term Fellowship, ALTF-505-2014. K.P. is a beneficiary of a mobility grant from the Belgian Federal Science Policy Office. K.J.V. acknowledges funding from the European Union Horizon 2020 program (ERC Consolidator Grant CoG682009), HFSP program grant RGP0050/2013, KU Leuven NATAR Program Financing, VIB, the EMBO YIP program, FWO, and IWT. The funders had no role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript. (Research Foundation Flanders (FWO-Vlaanderen), AB-InBev Baillet-Latour Foundation, Marie Curie Actions, EMBO|ALTF-505-2014, Belgian Federal Science Policy Office, European Union (ERC)|CoG682009, HFSP|RGP0050/2013, KU Leuven NATAR Program, VIB, EMBO YIP program, FWO, IWT)status: Publishe
The Crabtree Effect Shapes the Saccharomyces cerevisiae Lag Phase during the Switch between Different Carbon Sources
No full textWhen faced with environmental changes, microbes often enter a temporary growth arrest during which they reprogram the expression of specific genes to adapt to the new conditions. A prime example of such a lag phase occurs when microbes need to switch from glucose to other, less-preferred carbon sources. Despite its industrial relevance, the genetic network that determines the duration of the lag phase has not been studied in much detail. Here, we performed a genome-wide Bar-Seq screen to identify genetic determinants of the Saccharomyces cerevisiae glucose-to-galactose lag phase. The results show that genes involved in respiration, and specifically those encoding complexes III and IV of the electron transport chain, are needed for efficient growth resumption after the lag phase. Anaerobic growth experiments confirmed the importance of respiratory energy conversion in determining the lag phase duration. Moreover, overexpression of the central regulator of respiration, HAP4, leads to significantly shorter lag phases. Together, these results suggest that the glucose-induced repression of respiration, known as the Crabtree effect, is a major determinant of microbial fitness in fluctuating carbon environments.IMPORTANCE The lag phase is arguably one of the prime characteristics of microbial growth. Longer lag phases result in lower competitive fitness in variable environments, and the duration of the lag phase is also important in many industrial processes where long lag phases lead to sluggish, less efficient fermentations. Despite the immense importance of the lag phase, surprisingly little is known about the exact molecular processes that determine its duration. Our study uses the molecular toolbox of S. cerevisiae combined with detailed growth experiments to reveal how the transition from fermentative to respirative metabolism is a key bottleneck for cells to overcome the lag phase. Together, our findings not only yield insight into the key molecular processes and genes that influence lag duration but also open routes to increase the efficiency of industrial fermentations and offer an experimental framework to study other types of lag behavior.BT/Industriele Microbiologi
Different levels of catabolite repression optimize growth in stable and variable environments.
No full textOrganisms 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
Fitness tradeoffs between rapid adaptation and MaxRs.
No full text<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
Yeast strains show large differences in the duration of the lag phase.
No full text<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
