Xrn1 Exoribonuclease-An Intrinsic Marker of Yeast Population Growth.

BACKGROUND: Xrn1 exoribonuclease is the major mRNA degradation enzyme in Saccharomyces cerevisiae. In exponentially growing cells, Xrn1 is localised in the yeast cells and directs the degradation of mRNA molecules. Xrn1 is gradually deposited and presumably inactivated in the processing bodies (P-bodies) as the yeast population ages. Xrn1 can also localise to the membrane compartment of the arginine permease Can1/eisosome compartment at the yeast plasma membrane. This localisation correlates with the metabolic (diauxic) shift from glucose fermentation to respiration, although the relevance of this Xrn1 localisation remains unknown. METHODS: We monitored the growth rates and morphology of Xrn1-green fluorescent protein (GFP) cells compared to wild-type and Δxrn1 cells and observed the Xrn1-GFP localisation pattern in different media types for up to 72 hours using fluorescence microscopy. RESULTS: We present the dynamic changes in the localisation of Xrn1 as a versatile tool for monitoring the growth of yeast populations at the single-cell level using fluorescence microscopy. CONCLUSIONS: The dynamic changes in the localisation of Xrn1 can be a versatile tool for monitoring the growth of yeast populations at the single-cell level. Simultaneously, Xrn1 localisation outside of P-bodies in post-diauxic cells supports its storage and cytoprotective function, yet the role of P-bodies in cell metabolism has still not yet been entirely elucidated.

H3 Lysine 4 Methylation Is Required for Full Activation of Genes Involved in α-Ketoglutarate Availability in the Nucleus of Yeast Cells after Diauxic Shift.

We show that in S. cerevisiae the metabolic diauxic shift is associated with a H3 lysine 4 tri-methylation (H3K4me3) increase which involves a significant fraction of transcriptionally induced genes which are required for the metabolic changes, suggesting a role for histone methylation in their transcriptional regulation. We show that histone H3K4me3 around the start site correlates with transcriptional induction in some of these genes. Among the methylation-induced genes are IDP2 and ODC1, which regulate the nuclear availability of α-ketoglutarate, which, as a cofactor for Jhd2 demethylase, regulates H3K4 tri-methylation. We propose that this feedback circuit could be used to regulate the nuclear α-ketoglutarate pool concentration. We also show that yeast cells adapt to the absence of Jhd2 by decreasing Set1 methylation activity.

Natural Variation in Diauxic Shift between Patagonian Saccharomyces eubayanus Strains.

The study of natural variation can untap novel alleles with immense value for biotechnological applications. Saccharomyces eubayanus Patagonian isolates exhibit differences in the diauxic shift between glucose and maltose, representing a suitable model to study their natural genetic variation for novel strains for brewing. However, little is known about the genetic variants and chromatin regulators responsible for these differences. Here, we show how genome-wide chromatin accessibility and gene expression differences underlie distinct diauxic shift profiles in S. eubayanus. We identified two strains with a rapid diauxic shift between glucose and maltose (CL467.1 and CBS12357) and one strain with a remarkably low fermentation efficiency and longer lag phase during diauxic shift (QC18). This is associated in the QC18 strain with lower transcriptional activity and chromatin accessibility of specific genes of maltose metabolism and higher expression levels of glucose transporters. These differences are governed by the HAP complex, which differentially regulates gene expression depending on the genetic background. We found in the QC18 strain a contrasting phenotype to those phenotypes described in S. cerevisiae, where hap4Δ, hap5Δ, and cin5Δ knockouts significantly improved the QC18 growth rate in the glucose-maltose shift. The most profound effects were found between CIN5 allelic variants, suggesting that Cin5p could strongly activate a repressor of the diauxic shift in the QC18 strain but not necessarily in the other strains. The differences between strains could originate from the tree host from which the strains were obtained, which might determine the sugar source preference and the brewing potential of the strain. IMPORTANCE The diauxic shift has been studied in budding yeast under laboratory conditions; however, few studies have addressed the diauxic shift between carbon sources under fermentative conditions. Here, we study the transcriptional and chromatin structure differences that explain the natural variation in fermentative capacity and efficiency during diauxic shift of natural isolates of S. eubayanus. Our results show how natural genetic variants in transcription factors impact sugar consumption preferences between strains. These variants have different effects depending on the genetic background, with a contrasting phenotype to those phenotypes previously described in S. cerevisiae. Our study shows how relatively simple genetic/molecular modifications/editing in the lab can facilitate the study of natural variations of microorganisms for the brewing industry.

Rewiring of the protein-protein-metabolite interactome during the diauxic shift in yeast.

In budding yeast Saccharomyces cerevisiae, the switch from aerobic fermentation to respiratory growth is separated by a period of growth arrest, known as the diauxic shift, accompanied by a significant metabolic rewiring, including the derepression of gluconeogenesis and the establishment of mitochondrial respiration. Previous studies reported hundreds of proteins and tens of metabolites accumulating differentially across the diauxic shift transition. To assess the differences in the protein-protein (PPIs) and protein-metabolite interactions (PMIs) yeast samples harvested in the glucose-utilizing, fermentative phase, ethanol-utilizing and early stationary respiratory phases were analysed using isothermal shift assay (iTSA) and a co-fractionation mass spectrometry approach, PROMIS. Whereas iTSA monitors changes in protein stability and is informative towards protein interaction status, PROMIS uses co-elution to delineate putative PPIs and PMIs. The resulting dataset comprises 1627 proteins and 247 metabolites, hundreds of proteins and tens of metabolites characterized by differential thermal stability and/or fractionation profile, constituting a novel resource to be mined for the regulatory PPIs and PMIs. The examples discussed here include (i) dissociation of the core and regulatory particle of the proteasome in the early stationary phase, (ii) the differential binding of a co-factor pyridoxal phosphate to the enzymes of amino acid metabolism and (iii) the putative, phase-specific interactions between proline-containing dipeptides and enzymes of central carbon metabolism.

A Microfluidic Platform for Tracking Individual Cell Dynamics during an Unperturbed Nutrients Exhaustion.

Microorganisms have evolved adaptive strategies to respond to the autonomous degradation of their environment. Indeed, a growing culture progressively exhausts nutrients from its media and modifies its composition. Yet, how single cells react to these modifications remains difficult to study since it requires population-scale growth experiments to allow cell proliferation to have a collective impact on the environment, while monitoring the same individuals exposed to this environment for days. For this purpose, we have previously described an integrated microfluidic pipeline, based on continuous separation of the cells from the media and subsequent perfusion of the filtered media in an observation chamber containing isolated single cells. Here, we provide a detailed protocol to implement this methodology, including the setting up of the microfluidic system and the processing of timelapse images.

Categorization of Phosphorylation Site Behavior during the Diauxic Shift in Saccharomyces cerevisiae.

Protein phosphorylation has long been recognized as an essential regulator of protein activity, structure, complex formation, and subcellular localization among other cellular mechanisms. However, interpretation of the changes in protein phosphorylation is difficult. To address this difficulty, we measured protein and phosphorylation site changes across 11 points of a time course and developed a method for categorizing phosphorylation site behavior relative to protein level changes using the diauxic shift in yeast as a model and TMT11 sample multiplexing. We classified quantified proteins into behavioral categories that reflected differences in kinase activity, protein complex structure, and growth and metabolic pathway regulation across different phases of the diauxic shift. These data also provide a valuable resource for the study of fermentative versus respiratory growth and set a new benchmark for temporal quantitative proteomics and phosphoproteomics for the diauxic shift in Saccharomyces cerevisiae. Data are available via ProteomeXchange with identifier PXD022741.

Fluorescence Detection of Increased Reactive Oxygen Species Levels in Saccharomyces cerevisiae at the Diauxic Shift.

The budding yeast Saccharomyces cerevisiae is a facultative organism that is able to utilize both anaerobic and aerobic metabolism, depending on the composition of carbon source in the growth medium. When glucose is abundant, yeast catabolizes it to ethanol and other by-products by anaerobic fermentation through the glycolysis pathway. Following glucose exhaustion, cells switch to oxygenic respiration (a.k.a. "diauxic shift"), which allows catabolizing ethanol and the other carbon compounds via the TCA cycle and oxidative phosphorylation in the mitochondria. The diauxic shift is accompanied by elevated reactive oxygen species (ROS) levels and is characterized by activation of ROS defense mechanisms. Traditional measurement of the diauxic shift is done through measuring optical density of cultures grown in a batch at intermediate time points and generating a typical growth curve or by estimating the reduction of glucose and accumulation of ethanol in growth media over time. In this manuscript, we describe a method for determining changes in ROS levels upon yeast growth, using carboxy-H(2)-dichloro-dihydrofluorescein diacetate (carboxy-H(2)-DCFDA). H2-DCFDA is a widely used fluorescent dye for measuring intracellular ROS levels. H2-DCFDA enables a direct measurement of ROS in yeast cells at intermediate time points. The outcome of H2-DCFDA fluorescent readout measurements correlates with the growth curve information, hence providing a clear understanding of the diauxic shift.

Absolute yeast mitochondrial proteome quantification reveals trade-off between biosynthesis and energy generation during diauxic shift.

Saccharomyces cerevisiae constitutes a popular eukaryal model for research on mitochondrial physiology. Being Crabtree-positive, this yeast has evolved the ability to ferment glucose to ethanol and respire ethanol once glucose is consumed. Its transition phase from fermentative to respiratory metabolism, known as the diauxic shift, is reflected by dramatic rearrangements of mitochondrial function and structure. To date, the metabolic adaptations that occur during the diauxic shift have not been fully characterized at the organelle level. In this study, the absolute proteome of mitochondria was quantified alongside precise parametrization of biophysical properties associated with the mitochondrial network using state-of-the-art optical-imaging techniques. This allowed the determination of absolute protein abundances at a subcellular level. By tracking the transformation of mitochondrial mass and volume, alongside changes in the absolute mitochondrial proteome allocation, we could quantify how mitochondria balance their dual role as a biosynthetic hub as well as a center for cellular respiration. Furthermore, our findings suggest that in the transition from a fermentative to a respiratory metabolism, the diauxic shift represents the stage where major structural and functional reorganizations in mitochondrial metabolism occur. This metabolic transition, initiated at the mitochondria level, is then extended to the rest of the yeast cell.

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies.

BACKGROUND: Multicellular entities like mammalian tissues or microbial biofilms typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding how this cell-cell and metabolic coupling lead to functionally optimized structures is still limited. RESULTS: Here, we present a data-driven spatial framework to computationally investigate the development of yeast colonies as such a multicellular structure in dependence on metabolic capacity. For this purpose, we first developed and parameterized a dynamic cell state and growth model for yeast based on on experimental data from homogeneous liquid media conditions. The inferred model is subsequently used in a spatially coarse-grained model for colony development to investigate the effect of metabolic coupling by calibrating spatial parameters from experimental time-course data of colony growth using state-of-the-art statistical techniques for model uncertainty and parameter estimations. The model is finally validated by independent experimental data of an alternative yeast strain with distinct metabolic characteristics and illustrates the impact of metabolic coupling for structure formation. CONCLUSIONS: We introduce a novel model for yeast colony formation, present a statistical methodology for model calibration in a data-driven manner, and demonstrate how the established model can be used to generate predictions across scales by validation against independent measurements of genetically distinct yeast strains.

The Proteasome Lid Triggers COP9 Signalosome Activity during the Transition of Saccharomyces cerevisiae Cells into Quiescence.

The class of Cullin-RING E3 ligases (CRLs) selectively ubiquitinate a large portion of proteins targeted for proteolysis by the 26S proteasome. Before degradation, ubiquitin molecules are removed from their conjugated proteins by deubiquitinating enzymes, a handful of which are associated with the proteasome. The CRL activity is triggered by modification of the Cullin subunit with the ubiquitin-like protein, NEDD8 (also known as Rub1 in Saccharomyces cerevisiae). Cullin modification is then reversed by hydrolytic action of the COP9 signalosome (CSN). As the NEDD8-Rub1 catalytic cycle is not essential for the viability of S. cerevisiae, this organism is a useful model system to study the alteration of Rub1-CRL conjugation patterns. In this study, we describe two distinct mutants of Rpn11, a proteasome-associated deubiquitinating enzyme, both of which exhibit a biochemical phenotype characterized by high accumulation of Rub1-modified Cdc53-Cullin1 (yCul1) upon entry into quiescence in S. cerevisiae. Further characterization revealed proteasome 19S-lid-associated deubiquitination activity that authorizes the hydrolysis of Rub1 from yCul1 by the CSN complex. Thus, our results suggest a negative feedback mechanism via proteasome capacity on upstream ubiquitinating enzymes.

Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast.

One of the most challenging tasks in modern science is the development of systems biology models: Existing models are often very complex but generally have low predictive performance. The construction of high-fidelity models will require hundreds/thousands of cycles of model improvement, yet few current systems biology research studies complete even a single cycle. We combined multiple software tools with integrated laboratory robotics to execute three cycles of model improvement of the prototypical eukaryotic cellular transformation, the yeast (Saccharomyces cerevisiae) diauxic shift. In the first cycle, a model outperforming the best previous diauxic shift model was developed using bioinformatic and systems biology tools. In the second cycle, the model was further improved using automatically planned experiments. In the third cycle, hypothesis-led experiments improved the model to a greater extent than achieved using high-throughput experiments. All of the experiments were formalized and communicated to a cloud laboratory automation system (Eve) for automatic execution, and the results stored on the semantic web for reuse. The final model adds a substantial amount of knowledge about the yeast diauxic shift: 92 genes (+45%), and 1,048 interactions (+147%). This knowledge is also relevant to understanding cancer, the immune system, and aging. We conclude that systems biology software tools can be combined and integrated with laboratory robots in closed-loop cycles.

Monitoring ADP/ATP ratio in yeast cells using the fluorescent-protein reporter PercevalHR.

PercevalHR (Perceval High Resolution) is an artificially designed fluorescent protein, which changes its excitation spectrum based on the ADP/ATP ratio of the environment. Here we demonstrated that PercevalHR can be used for monitoring energy status of Saccharomyces cerevisiae cells, which are affected by diauxic shift and mitochondria inhibition, in a non-invasive and non-destructive manner.

Induction and relocalization of telomeric repeat-containing RNAs during diauxic shift in budding yeast.

Telomeres are maintained in a heterochromatic state that represses transcription of subtelomeric genes, a phenomenon known as telomere position effect. Nevertheless, telomeric DNA is actively transcribed, leading to the synthesis of telomeric repeat-containing noncoding RNA or TERRA. This nuclear noncoding RNA has been proposed to play important roles at telomeres, regulating their silencing, capping, repair and elongation by telomerase. In the budding yeast Saccharomyces cerevisiae, TERRA accumulation is repressed by telomeric silencing and the Rat1 exonuclease. On the other hand, telomere shortening promotes expression of TERRA. So far, little is known about the biological processes that induce TERRA expression in yeast. Understanding the dynamics of TERRA expression and localization is essential to define its function in telomere biology. Here, we aim to study the dynamics of TERRA expression during yeast cell growth. Using live-cell imaging, RNA-FISH and quantitative RT-PCR, we show that TERRA expression is induced as yeast cells undergo diauxic shift, a lag phase during which yeast cells switch their metabolism from anaerobic fermentation to oxidative respiration. This induction is transient as TERRA levels decrease during post-diauxic shift. The increased expression of TERRA is not due to the shortening of telomeres or increased stability of this transcript. Surprisingly, this induction is coincident with a cytoplasmic accumulation of TERRA molecules. Our results suggest that TERRA transcripts may play extranuclear functions with important implications in telomere biology and add a novel layer of complexity in the interplay between telomere biology, metabolism and stress response.

Caloric Restriction Extends Yeast Chronological Life Span by Optimizing the Snf1 (AMPK) Signaling Pathway.

AMP-activated protein kinase (AMPK) and the homologous yeast SNF1 complex are key regulators of energy metabolism that counteract nutrient deficiency and ATP depletion by phosphorylating multiple enzymes and transcription factors that maintain energetic homeostasis. AMPK/SNF1 also promotes longevity in several model organisms, including yeast. Here we investigate the role of yeast SNF1 in mediating the extension of chronological life span (CLS) by caloric restriction (CR). We find that SNF1 activity is required throughout the transition of log phase to stationary phase (diauxic shift) for effective CLS extension. CR expands the period of maximal SNF1 activation beyond the diauxic shift, as indicated by Sak1-dependent T210 phosphorylation of the Snf1 catalytic α-subunit. A concomitant increase in ADP is consistent with SNF1 activation by ADP in vivo Downstream of SNF1, the Cat8 and Adr1 transcription factors are required for full CR-induced CLS extension, implicating an alternative carbon source utilization for acetyl coenzyme A (acetyl-CoA) production and gluconeogenesis. Indeed, CR increased acetyl-CoA levels during the diauxic shift, along with expression of both acetyl-CoA synthetase genes ACS1 and ACS2 We conclude that CR maximizes Snf1 activity throughout and beyond the diauxic shift, thus optimizing the coordination of nucleocytosolic acetyl-CoA production with massive reorganization of the transcriptome and respiratory metabolism.

Detecting shifts in gene regulatory networks during time-course experiments at single-time-point temporal resolution.

Comprehensively understanding the dynamics of biological systems is one of the greatest challenges in biology. Vastly improved biological technologies have provided vast amounts of information that must be understood by bioinformatics and systems biology researchers. Gene regulations have been frequently modeled by ordinary differential equations or graphical models based on time-course gene expression profiles. The state-of-the-art computational approaches for analyzing gene regulations assume that their models are same throughout time-course experiments. However, these approaches cannot easily analyze transient changes at a time point, such as diauxic shift. We propose a score that analyzes the gene regulations at each time point. The score is based on the information gains of information criterion values. The method detects the shifts in gene regulatory networks (GRNs) during time-course experiments with single-time-point resolution. The effectiveness of the method is evaluated on the diauxic shift from glucose to lactose in Escherichia coli. Gene regulation shifts were detected at two time points: the first corresponding to the time at which the growth of E. coli ceased and the second corresponding to the end of the experiment, when the nutrient sources (glucose and lactose) had become exhausted. According to these results, the proposed score and method can appropriately detect the time of gene regulation shifts. The method based on the proposed score provides a new tool for analyzing dynamic biological systems. Because the score value indicates the strength of gene regulation at each time point in a gene expression profile, it can potentially infer hidden GRNs from time-course experiments.

Harvesting yeast (Saccharomyces cerevisiae) at different physiological phases significantly affects its functionality in bread dough fermentation.

Fermentation of sugars into CO2, ethanol and secondary metabolites by baker's yeast (Saccharomyces cerevisiae) during bread making leads to leavening of dough and changes in dough rheology. The aim of this study was to increase our understanding of the impact of yeast on dough related aspects by investigating the effect of harvesting yeast at seven different points of the growth profile on its fermentation performance, metabolite production, and the effect on critical dough fermentation parameters, such as gas retention potential. The yeast cells harvested during the diauxic shift and post-diauxic growth phase showed a higher fermentation rate and, consequently, higher maximum dough height than yeast cells harvested in the exponential or stationary growth phase. The results further demonstrate that the onset of CO2 loss from fermenting dough is correlated with the fermentation rate of yeast, but not with the amount of CO2 that accumulated up to the onset point. Analysis of the yeast metabolites produced in dough yielded a possible explanation for this observation, as they are produced in different levels depending on physiological phase and in concentrations that can influence dough matrix properties. Together, our results demonstrate a strong effect of yeast physiology at the time of harvest on subsequent dough fermentation performance, and hint at an important role of yeast metabolites on the subsequent gas holding capacity.