Multiple mechanisms provide rapid and stringent glucose repression of GAL gene expression in Saccharomyces cerevisiae

Boosting the epoxidation of squalene to produce triterpenoids in Saccharomyces cerevisiae

BACKGROUND

Polycyclic triterpenoids (PTs) are common in plants, and have attracted considerable interest due to their remarkable biological activities. Currently, engineering the ergosterol synthesis pathway in Saccharomyces cerevisiae is a safe and cost-competitive way to produce triterpenoids. However, the strict regulation of ERG1 involved in the epoxidation of squalene limits the triterpenoid production.

RESULTS

In this study, we found that the decrease in ERG7 protein level could dramatically boost the epoxidation of squalene by improving the protein stability of ERG1. We next explored the potential factors that affected the degradation process of ERG1 and confirmed that ERG7 was involved in the degradation process of ERG1. Subsequently, expression of four different triterpene cyclases utilizing either 2,3-oxidosqualene or 2,3:22,23-dioxidosqualene as the substrate in ERG7-degraded strains showed that the degradation of ERG7 to prompt the epoxidation of squalene could significantly increase triterpenoid production. To better display the potential of the strategy, we increased the supply of 2,3-oxidosqualene, optimized flux distribution between ergosterol synthesis pathway and β-amyrin synthesis pathway, and modified the GAL-regulation system to separate the growth stage from the production stage. The best-performing strain ultimately produced 4216.6 ± 68.4 mg/L of β-amyrin in a two-stage fed-fermentation (a 47-fold improvement over the initial strain).

CONCLUSIONS

This study showed that deregulation of the native restriction in ergosterol pathway was an effective strategy to increase triterpenoid production in yeast, which provided a new insight into triterpenoids biosynthesis.

Galectins as pivotal components in oncogenesis and immune exclusion in human malignancies

Galectins are galactoside-binding proteins, exerting numerous functions inside and outside the cell, particularly conferring adaptation to stress factors. For most of them, aberrant expression profiles have been reported in the context of cancer. Albeit not being oncogenic drivers, galectins can be harnessed to exacerbate the malignant phenotype. Their impact on disease establishment and progression is not limited to making cancer cells resistant to apoptosis, but is prominent in the context of the tumor microenvironment, where it fosters angiogenesis, immune escape and exclusion. This review focuses mainly on Gal-1, Gal-3 and Gal-9 for which the involvement in cancer biology is best known. It presents the types of galectin dysregulations, attempts to explain the mechanisms behind them and analyzes the different ways in which they favor tumour growth. In an era where tumour resistance to immunotherapy appears as a major challenge, we highlight the crucial immunosuppressive roles of galectins and the potential therapeutic benefits of combinatorial approaches including galectin inhibition.

Engineering a universal and efficient platform for terpenoid synthesis in yeast

Engineering microbes for the production of valuable natural products is often hindered by the regulation of native competing metabolic networks in host. This is particularly evident in the case of terpenoid synthesis in yeast, where the canonical terpenoid precursors are tightly coupled to the biosynthesis of sterols essential for yeast viability. One way to circumvent this limitation is by engineering product pathways less connected to the host native metabolism. Here, we introduce a two-step isopentenol utilization pathway (IUP) in Saccharomyces cerevisiae to augment the native mevalonate pathway by providing a shortcut to the synthesis of the common terpenoid precursors, isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP). As such, the IUP was capable of elevating the IPP/DMAPP pool by 147-fold compared with the native pathway. We further demonstrate that cofeeding isoprenol and prenol enhances geranyl diphosphate (GPP) content for monoterpene biosynthesis. More importantly, we established a synthetic three-step route for efficient synthesis of di-and tetraterpene precursor geranylgeranyl diphosphate (GGPP), circumventing the competition with farnesyl diphosphate (FPP) for sterol biosynthesis and elevating the GGPP level by 374-fold. We combine these IUP-supported precursor-forming platforms with downstream terpene synthases to harness their potential and improve the production of industrially relevant terpenoids by several fold. Our exploration provides a universal and effective platform for supporting terpenoid synthesis in yeast.

Endosomal cargo recycling mediated by Gpa1 and phosphatidylinositol 3-kinase is inhibited by glucose starvation

Cell surface protein trafficking is regulated in response to nutrient availability, with multiple pathways directing surface membrane proteins to the lysosome for degradation in response to suboptimal extracellular nutrients. Internalized protein and lipid cargoes recycle back to the surface efficiently in glucose-replete conditions, but this trafficking is attenuated following glucose starvation. We find that cells with either reduced or hyperactive phosphatidylinositol 3-kinase (PI3K) activity are defective for endosome to surface recycling. Furthermore, we find that the yeast Gα subunit Gpa1, an endosomal PI3K effector, is required for surface recycling of cargoes. Following glucose starvation, mRNA and protein levels of a distinct Gα subunit Gpa2 are elevated following nuclear translocation of Mig1, which inhibits recycling of various cargoes. As Gpa1 and Gpa2 interact at the surface where Gpa2 concentrates during glucose starvation, we propose that this disrupts PI3K activity required for recycling, potentially diverting Gpa1 to the surface and interfering with its endosomal role in recycling. In support of this model, glucose starvation and overexpression of Gpa2 alter PI3K endosomal phosphoinositide production. Glucose deprivation therefore triggers a survival mechanism to increase retention of surface cargoes in endosomes and promote their lysosomal degradation.

Decoupling transcription factor expression and activity enables dimmer switch gene regulation

Gene-regulatory networks achieve complex mappings of inputs to outputs through mechanisms that are poorly understood. We found that in the galactose-responsive pathway in Saccharomyces cerevisiae, the decision to activate the transcription of genes encoding pathway components is controlled independently from the expression level, resulting in behavior resembling that of a mechanical dimmer switch. This was not a direct result of chromatin regulation or combinatorial control at galactose-responsive promoters; rather, this behavior was achieved by hierarchical regulation of the expression and activity of a single transcription factor. Hierarchical regulation is ubiquitous, and thus dimmer switch regulation is likely a key feature of many biological systems. Dimmer switch gene regulation may allow cells to fine-tune their responses to multi-input environments on both physiological and evolutionary time scales.

Computational study on ratio-sensing in yeast galactose utilization pathway

Metabolic networks undergo gene expression regulation in response to external nutrient signals. In microbes, the synthesis of enzymes that are used to transport and catabolize less preferred carbon sources is repressed in the presence of a preferred carbon source. For most microbes, glucose is a preferred carbon source, and it has long been believed that as long as glucose is present in the environment, the expression of genes related to the metabolism of alternative carbon sources is shut down, due to catabolite repression. However, recent studies have shown that the induction of the galactose (GAL) metabolic network does not solely depend on the exhaustion of glucose. Instead, the GAL genes respond to the external concentration ratio of galactose to glucose, a phenomenon of unknown mechanism that we termed ratio-sensing. Using mathematical modeling, we found that ratio-sensing is a general phenomenon that can arise from competition between two carbon sources for shared transporters, between transcription factors for binding to communal regulatory sequences of the target genes, or a combination of the aforementioned two levels of competition. We analyzed how the parameters describing the competitive interaction influenced ratio-sensing behaviors in each scenario and found that the concatenation of both layers of signal integration could expand the dynamical range of ratio-sensing. Finally, we investigated the influence of circuit topology on ratio-sensing and found that incorporating negative auto-regulation and/or coherent feedforward loop motifs to the basic signal integration unit could tune the sensitivity of the response to the external nutrient signals. Our study not only deepened our understanding of how ratio-sensing is achieved in yeast GAL metabolic regulation, but also elucidated design principles for ratio-sensing signal processing that can be used in other biological settings, such as being introduced into circuit designs for synthetic biology applications.

Microbes make sophisticated choices about the uptake and metabolism of nutrients depending on the variety of nutrient choices available to them in their environment. In the well-studied yeast galactose utilization network, a recent study has shown that galactose metabolic genes respond to the external concentration ratio of galactose to glucose. Using computational models, we showed that this type of phenomenon could arise from a competition between galactose and glucose for transporters, a competition between transcription factors for promoters, or a combination of these two mechanisms. We further revealed the controlling parameters that determined the system sensitivity towards competing input signals and that determined the concentration ratio required to induce the metabolic network in each scenario. Combining competition inhibition at both the transporter level and the transcriptional level can enlarge the ratio-sensing regime, resulting a robust signal integration module. We suspect that modules of this kind may be common in many areas of biology.

Polymerization in the actin ATPase clan regulates hexokinase activity in yeast

The actin fold is found in cytoskeletal polymers, chaperones, and various metabolic enzymes. Many actin-fold proteins, such as the carbohydrate kinases, do not polymerize. We found that Glk1, a Saccharomyces cerevisiae glucokinase, forms two-stranded filaments with ultrastructure that is distinct from that of cytoskeletal polymers. In cells, Glk1 polymerized upon sugar addition and depolymerized upon sugar withdrawal. Polymerization inhibits enzymatic activity; the Glk1 monomer-polymer equilibrium sets a maximum rate of glucose phosphorylation regardless of Glk1 concentration. A mutation that eliminated Glk1 polymerization alleviated concentration-dependent enzyme inhibition. Yeast containing nonpolymerizing Glk1 were less fit when growing on sugars and more likely to die when refed glucose. Glk1 polymerization arose independently from other actin-related filaments and may allow yeast to rapidly modulate glucokinase activity as nutrient availability changes.

Evolutionary repair: Changes in multiple functional modules allow meiotic cohesin to support mitosis

The role of proteins often changes during evolution, but we do not know how cells adapt when a protein is asked to participate in a different biological function. We forced the budding yeast, Saccharomyces cerevisiae, to use the meiosis-specific kleisin, recombination 8 (Rec8), during the mitotic cell cycle, instead of its paralog, Scc1. This perturbation impairs sister chromosome linkage, advances the timing of genome replication, and reduces reproductive fitness by 45%. We evolved 15 parallel populations for 1,750 generations, substantially increasing their fitness, and analyzed the genotypes and phenotypes of the evolved cells. Only one population contained a mutation in Rec8, but many populations had mutations in the transcriptional mediator complex, cohesin-related genes, and cell cycle regulators that induce S phase. These mutations improve sister chromosome cohesion and delay genome replication in Rec8-expressing cells. We conclude that changes in known and novel partners allow cells to use an existing protein to participate in new biological functions.

Epigenetic memory in gene regulation and immune response

Cells must fine-tune their gene expression programs for optimal cellular activities in their natural growth conditions. Transcriptional memory, a unique transcriptional response, plays a pivotal role in faster reactivation of genes upon environmental changes, and is facilitated if genes were previously in an active state. Hyper-activation of gene expression by transcriptional memory is critical for cellular differentiation, development, and adaptation. TREM (Transcriptional REpression Memory), a distinct type of transcriptional memory, promoting hyper-repression of unnecessary genes, upon environmental changes has been recently reported. These two transcriptional responses may optimize specific gene expression patterns, in rapidly changing environments. Emerging evidence suggests that they are also critical for immune responses. In addition to memory B and T cells, innate immune cells are transcriptionally hyperactivated by restimulation, with the same or different pathogens known as trained immunity. In this review, we briefly summarize recent progress in chromatin-based regulation of transcriptional memory, and its potential role in immune responses. [BMB Reports 2019; 52(2): 127-132].

Investigation of Light-Regulated Protein-Protein Interactions Using Yeast Two-Hybrid Assays

Yeast two-hybrid allows for investigation of interactions between two proteins in vivo. Yeast media can be supplemented with phycocyanobilin, allowing the formation of photoactive phytochromes, and the investigation of their light-regulated interactions. Three reporter assays are described; the histidine growth selection assay for the HIS3 reporter, and the filter lift and quantitative ONPG assays for the LacZ reporter. Design considerations for yeast two- and three-hybrid experiments are also covered.

A Single-Component Optogenetic System Allows Stringent Switch of Gene Expression in Yeast Cells

Light is a highly attractive actuator that allows spatiotemporal control of diverse cellular activities. In this study, we developed a single-component light-switchable gene expression system for yeast cells, termed yLightOn system. The yLightOn system is independent of exogenous cofactors, and exhibits more than a 500-fold ON/OFF ratio, extremely low leakage, fast expression kinetics, and high spatial resolution. We demonstrated the usefulness of the yLightOn system in regulating cell growth and cell cycle by stringently controlling the expression of His3 and ΔN Sic1 genes, respectively. Furthermore, we engineered a bidirectional expression module that allows the simultaneous control of the expression of two genes by light. With ClpX and ClpP as the reporters, the fast, quantitative, and spatially specific degradation of ssrA-tagged protein was observed. We suggest that this single-component optogenetic system will be immensely helpful in understanding cellular gene regulatory networks and in the design of robust genetic circuits for synthetic biology.

Pentose Metabolism in Saccharomyces cerevisiae: The Need to Engineer Global Regulatory Systems

Extending the host substrate range of industrially relevant microbes, such as Saccharomyces cerevisiae, has been a highly-active area of research since the conception of metabolic engineering. Yet, rational strategies that enable non-native substrate utilization in this yeast without the need for combinatorial and/or evolutionary techniques are underdeveloped. Herein, this review focuses on pentose metabolism in S. cerevisiae as a case study to highlight the challenges in this field. In the last three decades, work has focused on expressing exogenous pentose metabolizing enzymes as well as endogenous enzymes for effective pentose assimilation, growth, and biofuel production. The engineering strategies that are employed for pentose assimilation in this yeast are reviewed, and compared with metabolism and regulation of native sugar, galactose. In the case of galactose metabolism, multiple signals regulate and aid growth in the presence of the sugar. However, for pentoses that are non-native, it is unclear if similar growth and regulatory signals are activated. Such a comparative analysis aids in identifying missing links in xylose and arabinose utilization. While research on pentose metabolism have mostly concentrated on pathway level optimization, recent transcriptomics analyses highlight the need to consider more global regulatory, structural, and signaling components.

Systematic Engineering for Improved Carbon Economy in the Biosynthesis of Polyhydroxyalkanoates and Isoprenoids

With the rapid development of synthetic biology and metabolic engineering, a broad range of biochemicals can be biosynthesized, which include polyhydroxyalkanoates and isoprenoids. However, some of the bio-approaches in chemical synthesis have just started to be applied outside of laboratory settings, and many require considerable efforts to achieve economies of scale. One of the often-seen barriers is the low yield and productivity, which leads to higher unit cost and unit capital investment for the bioconversion process. In general, higher carbon economy (less carbon wastes during conversion process from biomass to objective bio-based chemicals) will result in higher bioconversion yield, which results in less waste being generated during the process. To achieve this goal, diversified strategies have been applied; matured strategies include pathway engineering to block competitive pathways, enzyme engineering to enhance the activities of enzymes, and process optimization to improve biomass/carbon yield. In this review, we analyze the impact of carbon sources from different types of biomass on the yield of bio-based chemicals (especially for polyhydroxyalkanoates and isoprenoids). Moreover, we summarize the traditional strategies for improving carbon economy during the bioconversion process and introduce the updated techniques in building up non-natural carbon pathways, which demonstrate higher carbon economies than their natural counterparts.

Precise control of SCRaMbLE in synthetic haploid and diploid yeast

Compatibility between host cells and heterologous pathways is a challenge for constructing organisms with high productivity or gain of function. Designer yeast cells incorporating the Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution (SCRaMbLE) system provide a platform for generating genotype diversity. Here we construct a genetic AND gate to enable precise control of the SCRaMbLE method to generate synthetic haploid and diploid yeast with desired phenotypes. The yield of carotenoids is increased to 1.5-fold by SCRaMbLEing haploid strains and we determine that the deletion of YEL013W is responsible for the increase. Based on the SCRaMbLEing in diploid strains, we develop a strategy called Multiplex SCRaMbLE Iterative Cycling (MuSIC) to increase the production of carotenoids up to 38.8-fold through 5 iterative cycles of SCRaMbLE. This strategy is potentially a powerful tool for increasing the production of bio-based chemicals and for mining deep knowledge.

The SCRaMbLE system integrated into Sc2.0’s synthetic yeast chromosome project allows rapid strain evolution. Here the authors use a genetic logic gate to control induction of recombination in a haploid and diploid yeast carrying synthetic chromosomes.

Artificial Mating-Type Conversion and Repetitive Mating for Polyploid Generation

The yeast Saccharomyces cerevisiae is one of the best-understood biological systems and can produce numerous useful compounds. Sexual hybridization (mating) can drive dramatic evolution of yeasts by the inheritance of half of the parental genomic information from each cell. Unfortunately, half of the parental genomic information is lost in individual cells in the next generation. Additionally, recombination of homologous chromosomes during meiosis gives rise to diversity in the next generation; hence, it is commonly employed to identify targets from diverse cell populations, based on the mating machinery. Here, we established a system for generating polyploids that inherit all genetic information from the parental strains via artificial mating-type conversion and repetitive mating. We prepared α-type haploid strains whose chromosomes were tagged with genes encoding fluorescent proteins or transcriptional factors. Only the mating-type locus was successfully converted from α-type to a-type sequence by the endonuclease Ho, and the resultant a-type cells mated with each α-type haploid to yield an a/α-type diploid strain with all genetic information from both parental strains. Importantly, we repeatedly converted the mating-type of polyploid cells to obtain a-type cells capable of mating with α-type cells. This approach can potentially facilitate yeast-strain development with unparalleled versatility, utilizing vast available resources.

The yeast Mig1 transcriptional repressor is dephosphorylated by glucose-dependent and -independent mechanisms

A yeast Saccharomyces cerevisiae Snf1 kinase, an analog of mammalian AMPK, regulates glucose derepression of genes required for utilization of alternative carbon sources through the transcriptional repressor Mig1. It has been suggested that the Glc7-Reg1 phosphatase dephosphorylates Mig1. Here we report that Mig1 is dephosphorylated by Glc7-Reg1 in an apparently glucose-dependent mechanism but also by a mechanism independent of glucose and Glc7-Reg1. In addition to serine/threonine phosphatases another process including tyrosine phosphorylation seems crucial for Mig1 regulation. Taken together, Mig1 dephosphorylation appears to be controlled in a complex manner, in line with the importance for rapid and sensitive regulation upon altered glucose concentrations in the growth medium.

Saccharomyces cerevisiae Mhr1 can bind Xho I-induced mitochondrial DNA double-strand breaks in vivo

Mitochondrial DNA (mtDNA) double-strand break (DSB) repair is essential for maintaining mtDNA integrity, but little is known about the proteins involved in mtDNA DSB repair. Here, we utilize Saccharomyces cerevisiae as a eukaryotic model to identify proteins involved in mtDNA DSB repair. We show that Mhr1, a protein known to possess homologous DNA pairing activity in vitro, binds to mtDNA DSBs in vivo, indicating its involvement in mtDNA DSB repair. Our data also indicate that Yku80, a protein previously implicated in mtDNA DSB repair, does not compete with Mhr1 for binding to mtDNA DSBs. In fact, C-terminally tagged Yku80 could not be detected in yeast mitochondrial extracts. Therefore, we conclude that Mhr1, but not Yku80, is a potential mtDNA DSB repair factor in yeast.

Positive Feedback Genetic Circuit Incorporating a Constitutively Active Mutant Gal3 into Yeast GAL Induction System

The GAL expression system is the most frequently used induction technique in the yeast Saccharomyces cerevisiae. Here we report a simple but powerful genetic circuit for use with the GAL induction system. Briefly, an artificial positive feedback circuit was incorporated into the GAL regulatory network. We selected green fluorescent protein (GFP) as a reporter of GAL1 induction, and designed a strain that expressed a constitutively active Gal3 mutant protein (Gal3^c) under control of the GAL10 promoter. In the resulting strain, GAL1 and GAL10 promoters regulate the expression of GFP and GAL3^c, respectively. Because Gal3^c sequesters the Gal80 repressor away from the Gal4 transcriptional activator in the same manner as the galactose-bound Gal3, the expressed Gal3^c protein provokes further expression of GFP and Gal3^c, yielding further enhancement of GAL induction. Thus, this GAL3^c-mediated positive feedback circuit permits substantially enriched induction of a target gene at extremely low concentrations, or even in the absence, of galactose, while maintaining the strict glucose-mediated repression of the target.

Polymorphisms in the yeast galactose sensor underlie a natural continuum of nutrient-decision phenotypes

In nature, microbes often need to "decide" which of several available nutrients to utilize, a choice that depends on a cell’s inherent preference and external nutrient levels. While natural environments can have mixtures of different nutrients, phenotypic variation in microbes’ decisions of which nutrient to utilize is poorly studied. Here, we quantified differences in the concentration of glucose and galactose required to induce galactose-responsive (GAL) genes across 36 wild S. cerevisiae strains. Using bulk segregant analysis, we found that a locus containing the galactose sensor GAL3 was associated with differences in GAL signaling in eight different crosses. Using allele replacements, we confirmed that GAL3 is the major driver of GAL induction variation, and that GAL3 allelic variation alone can explain as much as 90% of the variation in GAL induction in a cross. The GAL3 variants we found modulate the diauxic lag, a selectable trait. These results suggest that ecological constraints on the galactose pathway may have led to variation in a single protein, allowing cells to quantitatively tune their response to nutrient changes in the environment.

In nature, microbes often need to decide which of many potential nutrients to consume. This decision making process is complex, involving both intracellular constraints and the organism’s perception of the environment. To begin to mimic the complexity of natural environments, we grew cells in mixtures of two sugars, glucose and galactose. We find that in mixed environments, the sugar concentration at which cells decides to induce galactose-utilizing (GAL) genes is highly variable in natural isolates of yeast. By analyzing crosses of phenotypically different strains, we identified a locus containing the galactose sensor, a gene that in theory could allow cells to tune their perception of the environment. We confirmed that the galactose sensor can explain upwards of 90% of the variation in the decision to induce GAL genes. Finally, we show that the variation in the galactose sensor can modulate the time required for cells to switch from utilizing glucose to galactose. Our results suggest that signaling pathways can be highly variable across strains and thereby might allow for rapid adaption in fluctuating environments.

Towards combinatorial transcriptional engineering

The modular nature of the transcriptional unit makes it possible to design robust modules with predictable input-output characteristics using a ‘parts- off a shelf’ approach. Customized regulatory circuits composed of multiple such transcriptional units have immense scope for application in diverse fields of basic and applied research. Synthetic transcriptional engineering seeks to construct such genetic cascades. Here, we discuss the three principle strands of transcriptional engineering: promoter and transcriptional factor engineering, and programming inducibilty into synthetic modules. In this context, we review the scope and limitations of some recent technologies that seek to achieve these ends. Our discussion emphasizes a requirement for rational combinatorial engineering principles and the promise this approach holds for the future development of this field.

A living vector field reveals constraints on galactose network induction in yeast

When a cell encounters a new environment, its transcriptional response can be constrained by its history. For example, yeast cells in galactose induce GAL genes with a speed and unanimity that depends on previous nutrient conditions. Cellular memory of long-term glucose exposure delays GAL induction and makes it highly variable with in a cell population, while other nutrient histories lead to rapid, uniform responses. To investigate how cell-level gene expression dynamics produce population-level phenotypes, we built living vector fields from thousands of single-cell time courses of the proteins Gal3p and Gal1p as cells switched to galactose from various nutrient histories. We show that, after sustained glucose exposure, the lack of these GAL transducers leads to induction delays that are long but also variable; that cellular resources constrain induction; and that bimodally distributed expression levels arise from lineage selection-a subpopulation of cells induces more quickly and outcompetes the rest. Our results illuminate cellular memory in this important model system and illustrate how resources and randomness interact to shape the response of a population to a new environment.

Reverse engineering gene regulatory networks from measurement with missing values

Background

Gene expression time series data are usually in the form of high-dimensional arrays. Unfortunately, the data may sometimes contain missing values: for either the expression values of some genes at some time points or the entire expression values of a single time point or some sets of consecutive time points. This significantly affects the performance of many algorithms for gene expression analysis that take as an input, the complete matrix of gene expression measurement. For instance, previous works have shown that gene regulatory interactions can be estimated from the complete matrix of gene expression measurement. Yet, till date, few algorithms have been proposed for the inference of gene regulatory network from gene expression data with missing values.

Results

We describe a nonlinear dynamic stochastic model for the evolution of gene expression. The model captures the structural, dynamical, and the nonlinear natures of the underlying biomolecular systems. We present point-based Gaussian approximation (PBGA) filters for joint state and parameter estimation of the system with one-step or two-step missing measurements. The PBGA filters use Gaussian approximation and various quadrature rules, such as the unscented transform (UT), the third-degree cubature rule and the central difference rule for computing the related posteriors. The proposed algorithm is evaluated with satisfying results for synthetic networks, in silico networks released as a part of the DREAM project, and the real biological network, the in vivo reverse engineering and modeling assessment (IRMA) network of yeast Saccharomyces cerevisiae.

Conclusion

PBGA filters are proposed to elucidate the underlying gene regulatory network (GRN) from time series gene expression data that contain missing values. In our state-space model, we proposed a measurement model that incorporates the effect of the missing data points into the sequential algorithm. This approach produces a better inference of the model parameters and hence, more accurate prediction of the underlying GRN compared to when using the conventional Gaussian approximation (GA) filters ignoring the missing data points.

Electronic supplementary material

The online version of this article (doi:10.1186/s13637-016-0055-8) contains supplementary material, which is available to authorized users.

LncRNAs: Bridging environmental sensing and gene expression

The survival of all organisms is dependent on complex, coordinated responses to environmental cues. Non-coding RNAs have been identified as major players in regulation of gene expression, with recent evidence supporting roles for long non-coding (lnc)RNAs in both transcriptional and post-transcriptional control. Evidence from our laboratory shows that lncRNAs have the ability to form hybridized structures called R-loops with specific DNA target sequences in S. cerevisiae, thereby modulating gene expression. In this Point of View, we provide an overview of the nature of lncRNA-mediated control of gene expression in the context of our studies using the GAL gene cluster as a model for controlling the timing of transcription.

Ongoing resolution of duplicate gene functions shapes the diversification of a metabolic network

The evolutionary mechanisms leading to duplicate gene retention are well understood, but the long-term impacts of paralog differentiation on the regulation of metabolism remain underappreciated. Here we experimentally dissect the functions of two pairs of ancient paralogs of the GALactose sugar utilization network in two yeast species. We show that the Saccharomyces uvarum network is more active, even as over-induction is prevented by a second co-repressor that the model yeast Saccharomyces cerevisiae lacks. Surprisingly, removal of this repression system leads to a strong growth arrest, likely due to overly rapid galactose catabolism and metabolic overload. Alternative sugars, such as fructose, circumvent metabolic control systems and exacerbate this phenotype. We further show that S. cerevisiae experiences homologous metabolic constraints that are subtler due to how the paralogs have diversified. These results show how the functional differentiation of paralogs continues to shape regulatory network architectures and metabolic strategies long after initial preservation.

Discovery of Enzymatic Targets of Transcriptional Activators via in Vivo Covalent Chemical Capture

The network of activator protein-protein interactions (PPIs) that underpin transcription initiation is poorly defined, particularly in the cellular context. The transient nature of these contacts and the often low abundance of the participants present significant experimental hurdles. Through the coupling of in vivo covalent chemical capture and shotgun LC-MS/MS (MuDPIT) analysis, we can trap the PPIs of transcriptional activators in a cellular setting and identify the binding partners in an unbiased fashion. Using this approach, we discover that the prototypical activators Gal4 and VP16 target the Snf1 (AMPK) kinase complex via direct interactions with both the core enzymatic subunit Snf1 and the exchangeable subunit Gal83. Further, we use a tandem reversible formaldehyde and irreversible covalent chemical capture approach (TRIC) to capture the Gal4-Snf1 interaction at the Gal1 promoter in live yeast. Together, these data support a critical role for activator PPIs in both the recruitment and positioning of important enzymatic complexes at a gene promoter and represent a technical advancement in the discovery of new cellular binding targets of transcriptional activators.

HyCCAPP as a tool to characterize promoter DNA-protein interactions in Saccharomyces cerevisiae

Currently available methods for interrogating DNA-protein interactions at individual genomic loci have significant limitations, and make it difficult to work with unmodified cells or examine single-copy regions without specific antibodies. In this study, we describe a physiological application of the Hybridization Capture of Chromatin-Associated Proteins for Proteomics (HyCCAPP) methodology we have developed. Both novel and known locus-specific DNA-protein interactions were identified at the ENO2 and GAL1 promoter regions of Saccharomyces cerevisiae, and revealed subgroups of proteins present in significantly different levels at the loci in cells grown on glucose versus galactose as the carbon source. Results were validated using chromatin immunoprecipitation. Overall, our analysis demonstrates that HyCCAPP is an effective and flexible technology that does not require specific antibodies nor prior knowledge of locally occurring DNA-protein interactions and can now be used to identify changes in protein interactions at target regions in the genome in response to physiological challenges.

Regulated Formation of lncRNA-DNA Hybrids Enables Faster Transcriptional Induction and Environmental Adaptation

Long non-coding (lnc)RNAs, once thought to merely represent noise from imprecise transcription initiation, have now emerged as major regulatory entities in all eukaryotes. In contrast to the rapidly expanding identification of individual lncRNAs, mechanistic characterization has lagged behind. Here we provide evidence that the GAL lncRNAs in the budding yeast S. cerevisiae promote transcriptional induction in trans by formation of lncRNA-DNA hybrids or R-loops. The evolutionarily conserved RNA helicase Dbp2 regulates formation of these R-loops as genomic deletion or nuclear depletion results in accumulation of these structures across the GAL cluster gene promoters and coding regions. Enhanced transcriptional induction is manifested by lncRNA-dependent displacement of the Cyc8 co-repressor and subsequent gene looping, suggesting that these lncRNAs promote induction by altering chromatin architecture. Moreover, the GAL lncRNAs confer a competitive fitness advantage to yeast cells because expression of these non-coding molecules correlates with faster adaptation in response to an environmental switch.

Evolutionary engineering of Saccharomyces cerevisiae for efficient conversion of red algal biosugars to bioethanol

The aim of this work was to apply the evolutionary engineering to construct a mutant Saccharomyces cerevisiae HJ7-14 resistant on 2-deoxy-D-glucose and with an enhanced ability of bioethanol production from galactose, a mono-sugar in red algae. In batch and repeated-batch fermentations, HJ7-14 metabolized 5-fold more galactose and produced ethanol 2.1-fold faster than the parental D452-2 strain. Transcriptional analysis of genes involved in the galactose metabolism revealed that moderate relief from the glucose-mediated repression of the transcription of the GAL genes might enable HJ7-14 to metabolize galactose rapidly. HJ7-14 produced 7.4 g/L ethanol from hydrolysates of the red alga Gelidium amansii within 12 h, which was 1.5-times faster than that observed with D452-2. We demonstrate conclusively that evolutionary engineering is a promising tool to manipulate the complex galactose metabolism in S. cerevisiae to produce bioethanol from red alga.

The unforeseen challenge: from genotype-to-phenotype in cell populations

Biological cells present a paradox, in that they show simultaneous stability and flexibility, allowing them to adapt to new environments and to evolve over time. The emergence of stable cell states depends on genotype-to-phenotype associations, which essentially reflect the organization of gene regulatory modes. The view taken here is that cell-state organization is a dynamical process in which the molecular disorder manifests itself in a macroscopic order. The genome does not determine the ordered cell state; rather, it participates in this process by providing a set of constraints on the spectrum of regulatory modes, analogous to boundary conditions in physical dynamical systems. We have developed an experimental framework, in which cell populations are exposed to unforeseen challenges; novel perturbations they had not encountered before along their evolutionary history. This approach allows an unbiased view of cell dynamics, uncovering the potential of cells to evolve and develop adapted stable states. In the last decade, our experiments have revealed a coherent set of observations within this framework, painting a picture of the living cell that in many ways is not aligned with the conventional one. Of particular importance here, is our finding that adaptation of cell-state organization is essentially an efficient exploratory dynamical process rather than one founded on random mutations. Based on our framework, a set of concepts underlying cell-state organization-exploration evolving by global, non-specific, dynamics of gene activity-is presented here. These concepts have significant consequences for our understanding of the emergence and stabilization of a cell phenotype in diverse biological contexts. Their implications are discussed for three major areas of biological inquiry: evolution, cell differentiation and cancer. There is currently no unified theoretical framework encompassing the emergence of order, a stable state, in the living cell. Hopefully, the integrated picture described here will provide a modest contribution towards a physics theory of the cell.

Cross-kingdom chemical communication drives a heritable, mutually beneficial prion-based transformation of metabolism

In experimental science, organisms are usually studied in isolation, but in the wild, they compete and cooperate in complex communities. We report a system for cross-kingdom communication by which bacteria heritably transform yeast metabolism. An ancient biological circuit blocks yeast from using other carbon sources in the presence of glucose. [GAR(+)], a protein-based epigenetic element, allows yeast to circumvent this "glucose repression" and use multiple carbon sources in the presence of glucose. Some bacteria secrete a chemical factor that induces [GAR(+)]. [GAR(+)] is advantageous to bacteria because yeast cells make less ethanol and is advantageous to yeast because their growth and long-term viability is improved in complex carbon sources. This cross-kingdom communication is broadly conserved, providing a compelling argument for its adaptive value. By heritably transforming growth and survival strategies in response to the selective pressures of life in a biological community, [GAR(+)] presents a unique example of Lamarckian inheritance.

Population diversification in a yeast metabolic program promotes anticipation of environmental shifts

Detailed study of the dynamic response of yeast to combinations of sugars reveals an anticipatory population diversification strategy that allows rapid adaptation to shifts in environmental carbon source availability.

To survive in resource-limited and dynamic environments, microbial populations implement a diverse repertoire of regulatory strategies. These strategies often rely on anticipating impending environmental shifts, enabling the population to be prepared for a future change in conditions. It has long been known that cells optimize nutritional value from mixtures of carbon sources, for example glucose and galactose, by sequential activation of regulatory programs that allow for metabolizing the preferred carbon source first before metabolizing the secondary carbon source. Using automated flow-cytometry, we mapped the dynamical behavior of populations simultaneously presented with a large panel of different glucose and galactose concentrations. We show that, counter to expectations, in populations presented with glucose and galactose simultaneously, the galactose regulatory pathway is activated in a fraction of the cell population hours before glucose is fully consumed. We demonstrate that the size of this fraction of cells is tuned by the concentration of the two sugars. This population diversification may constitute a tradeoff between the benefit of rapid galactose consumption once glucose is depleted and the cost of expressing the galactose pathway.

Delineating the strategies by which cells contend with combinatorial changing environments is crucial for understanding cellular regulatory organization. When presented with two carbon sources, microorganisms first consume the carbon substrate that supports the highest growth rate (e.g., glucose) and then switch to the secondary carbon source (e.g., galactose), a paradigm known as the Monod model. Sequential sugar utilization has been attributed to transcriptional repression of the secondary metabolic pathway, followed by activation of this pathway upon depletion of the preferred carbon source. In this work, we demonstrate that although Saccharomyces cerevisiae cells consume glucose before galactose, the galactose regulatory pathway is activated in a fraction of the cell population hours before glucose is fully consumed. This early activation reduces the time required for the population to transition between the two metabolic programs and provides a fitness advantage that might be crucial in competitive environments.

Metabolic respiration induces AMPK- and Ire1p-dependent activation of the p38-Type HOG MAPK pathway

Evolutionarily conserved mitogen activated protein kinase (MAPK) pathways regulate the response to stress as well as cell differentiation. In Saccharomyces cerevisiae, growth in non-preferred carbon sources (like galactose) induces differentiation to the filamentous cell type through an extracellular-signal regulated kinase (ERK)-type MAPK pathway. The filamentous growth MAPK pathway shares components with a p38-type High Osmolarity Glycerol response (HOG) pathway, which regulates the response to changes in osmolarity. To determine the extent of functional overlap between the MAPK pathways, comparative RNA sequencing was performed, which uncovered an unexpected role for the HOG pathway in regulating the response to growth in galactose. The HOG pathway was induced during growth in galactose, which required the nutrient regulatory AMP-dependent protein kinase (AMPK) Snf1p, an intact respiratory chain, and a functional tricarboxylic acid (TCA) cycle. The unfolded protein response (UPR) kinase Ire1p was also required for HOG pathway activation in this context. Thus, the filamentous growth and HOG pathways are both active during growth in galactose. The two pathways redundantly promoted growth in galactose, but paradoxically, they also inhibited each other's activities. Such cross-modulation was critical to optimize the differentiation response. The human fungal pathogen Candida albicans showed a similar regulatory circuit. Thus, an evolutionarily conserved regulatory axis links metabolic respiration and AMPK to Ire1p, which regulates a differentiation response involving the modulated activity of ERK and p38 MAPK pathways.

In fungal species, differentiation to the filamentous/hyphal cell type is critical for entry into host cells and virulence. Comparative RNA sequencing was used to explore the pathways that regulate differentiation to the filamentous cell type in yeast. This approach uncovered a role for the stress-response MAPK pathway, HOG, during the increased metabolic respiration that induces filamentous growth. In this context, the AMPK Snf1p and ER stress kinase Ire1p regulated the HOG pathway. Cross-modulation between the HOG and filamentous growth (ERK-type) MAPK pathways optimized the differentiation response. The regulatory circuit described here may extend to behaviors in metazoans.

The yeast galactose network as a quantitative model for cellular memory

Recent experiments have revealed surprising behavior in the yeast galactose (GAL) pathway, one of the preeminent systems for studying gene regulation. Under certain circumstances, yeast cells display memory of their prior nutrient environments. We distinguish two kinds of cellular memory discovered by quantitative investigations of the GAL network and present a conceptual framework for interpreting new experiments and current ideas on GAL memory. Reinduction memory occurs when cells respond transcriptionally to one environment, shut down the response during several generations in a second environment, then respond faster and with less cell-to-cell variation when returned to the first environment. Persistent memory describes a long-term, arguably stable response in which cells adopt a bimodal or unimodal distribution of induction levels depending on their preceding environment. Deep knowledge of how the yeast GAL pathway responds to different sugar environments has enabled rapid progress in uncovering the mechanisms behind GAL memory, which include cytoplasmic inheritance of inducer proteins and positive feedback loops among regulatory genes. This network of genes, long used to study gene regulation, is now emerging as a model system for cellular memory.

Correlations of three-dimensional motion of chromosomal loci in yeast revealed by the double-helix point spread function microscope

Single-particle tracking has been applied to study chromatin motion in live cells, revealing a wealth of dynamical behavior of the genomic material once believed to be relatively static throughout most of the cell cycle. Here we used the dual-color three-dimensional (3D) double-helix point spread function microscope to study the correlations of movement between two fluorescently labeled gene loci on either the same or different budding yeast chromosomes. We performed fast (10 Hz) 3D tracking of the two copies of the GAL locus in diploid cells in both activating and repressive conditions. As controls, we tracked pairs of loci along the same chromosome at various separations, as well as transcriptionally orthogonal genes on different chromosomes. We found that under repressive conditions, the GAL loci exhibited significantly higher velocity cross-correlations than they did under activating conditions. This relative increase has potentially important biological implications, as it might suggest coupling via shared silencing factors or association with decoupled machinery upon activation. We also found that on the time scale studied (∼0.1-30 s), the loci moved with significantly higher subdiffusive mean square displacement exponents than previously reported, which has implications for the application of polymer theory to chromatin motion in eukaryotes.

Blocking endocytotic mechanisms to improve heterologous protein titers in Saccharomyces cerevisiae

Saccharomyces cerevisiae is a useful platform for protein production of biopharmaceuticals and industrial enzymes. To date, substantial effort has focused on alleviating several bottlenecks in expression and the secretory pathway. Recently, it has been shown that highly active endocytosis could decrease the overall protein titer in the supernatant. In this study, we block endocytosis and trafficking to the vacuole using a modified TEV Protease-Mediated Induction of Protein Instability (mTIPI) system to disrupt the endocytotic and vacuolar complexes. We report that conditional knock-down of endocytosis gene Rvs161 improved the concentration of α-amylase in supernatant of S. cerevisiae cultures by 63.7% compared to controls. By adaptive evolution, we obtained knock-down mutants in Rvs161 and End3 genes with 2-fold and 3-fold α-amylase concentrations compared to controls that were not evolved. Our study demonstrates that genetic blocking of endocytotic mechanisms can improve heterologous protein production in S. cerevisiae. This result is likely generalizable to other eukaryotic secretion hosts.

Perturbation of the interaction between Gal4p and Gal80p of the Saccharomyces cerevisiae GAL switch results in altered responses to galactose and glucose

In S. cerevisiae, following the Whole Genome Duplication (WGD), GAL1-encoded galactokinase retained its signal transduction function but lost basal expression. On the other hand, its paralogue GAL3, lost kinase activity but retained its signalling function and basal expression, thus making it indispensable for the rapid induction of the S. cerevisiae GAL switch. However, a gal3Δ strain exhibits delayed growth kinetics due to the redundant signalling function of GAL1. The subfunctionalization between the paralogues GAL1 and GAL3 is due to expression divergence and is proposed to be due to the alteration in the Upstream Activating Sequences (UASG ). We demonstrate that the GAL switch becomes independent of GAL3 by altering the interaction between Gal4p and Gal80p without altering the configuration of UASG . In addition to the above, the altered switch of S. cerevisiae loses ultrasensitivity and stringent glucose repression. These changes caused an increase in fitness in the disaccharide melibiose at the expense of a decrease in fitness in galactose. The above altered features of the ScGAL switch are similar to the features of the GAL switch of K. lactis that diverged from S. cerevisiae before the WGD.

Glucose de-repression by yeast AMP-activated protein kinase SNF1 is controlled via at least two independent steps

The AMP-activated protein kinase, AMPK, controls energy homeostasis in eukaryotic cells but little is known about the mechanisms governing the dynamics of its activation/deactivation. The yeast AMPK, SNF1, is activated in response to glucose depletion and mediates glucose de-repression by inactivating the transcriptional repressor Mig1. Here we show that overexpression of the Snf1-activating kinase Sak1 results, in the presence of glucose, in constitutive Snf1 activation without alleviating glucose repression. Co-overexpression of the regulatory subunit Reg1 of the Glc-Reg1 phosphatase complex partly restores glucose regulation of Snf1. We generated a set of 24 kinetic mathematical models based on dynamic data of Snf1 pathway activation and deactivation. The models that reproduced our experimental observations best featured (a) glucose regulation of both Snf1 phosphorylation and dephosphorylation, (b) determination of the Mig1 phosphorylation status in the absence of glucose by Snf1 activity only and (c) a regulatory step directing active Snf1 to Mig1 under glucose limitation. Hence it appears that glucose de-repression via Snf1-Mig1 is regulated by glucose via at least two independent steps: the control of activation of the Snf1 kinase and directing active Snf1 to inactivating its target Mig1.

Long noncoding RNAs promote transcriptional poising of inducible genes

The GAL cluster-associated long non-coding RNAs (lncRNAs) promote rapid induction of GAL genes in budding yeast, thereby promoting a faster switch in transcriptional programs when needed.

Long noncoding RNAs (lncRNAs) are a class of molecules that impinge on the expression of protein-coding genes. Previous studies have suggested that the GAL cluster-associated lncRNAs of Saccharomyces cerevisiae repress expression of the protein-coding GAL genes. Herein, we demonstrate a previously unrecognized role for the GAL lncRNAs in activating gene expression. In yeast strains lacking the RNA helicase, DBP2, or the RNA decay enzyme, XRN1, we find that the GAL lncRNAs specifically accelerate gene expression from a prior repressive state. Furthermore, we provide evidence that the previously suggested repressive role is a result of specific mutant phenotypes, rather than a reflection of the normal, wild-type function of these noncoding RNAs. To shed light on the mechanism for lncRNA-dependent gene activation, we show that rapid induction of the protein-coding GAL genes is associated with faster recruitment of RNA polymerase II and reduced association of transcriptional repressors with GAL gene promoters. This suggests that the GAL lncRNAs enhance expression by derepressing the GAL genes. Consistently, the GAL lncRNAs enhance the kinetics of transcriptional induction, promoting faster expression of the protein-coding GAL genes upon the switch in carbon source. We suggest that the GAL lncRNAs poise inducible genes for rapid activation, enabling cells to more effectively trigger new transcriptional programs in response to cellular cues.

Long noncoding RNAs (lncRNAs) are a recently identified class of molecules that regulate the expression of protein-coding genes through a number of mechanisms, some of them poorly characterized. The GAL gene cluster of the yeast Saccharomyces cerevisiae encodes a series of three inducible genes that are turned on or off by the presence or absence of specific carbon sources in the environment. Previous studies have documented the presence of two lncRNAs—GAL10 and GAL10s—encoded by genes that overlap the GAL cluster. We have now uncovered a role for both these lncRNAs in promoting the activation of the GAL genes when they are released from repressive conditions. This activation occurs at the kinetic level, through more rapid recruitment of RNA polymerase II and decreased association of the co-repressor, Cyc8. Under normal conditions, but also especially when they are stabilized and their levels are up-regulated, these GAL lncRNAs promote faster GAL gene activation. We suggest that these lncRNA molecules poise inducible genes for quick response to extracellular cues, triggering a faster switch in transcriptional programs.

Gleaning evolutionary insights from the genome sequence of a probiotic yeast Saccharomyces boulardii

Background

The yeast Saccharomyces boulardii is used worldwide as a probiotic to alleviate the effects of several gastrointestinal diseases and control antibiotics-associated diarrhea. While many studies report the probiotic effects of S. boulardii, no genome information for this yeast is currently available in the public domain.

Results

We report the 11.4 Mbp draft genome of this probiotic yeast. The draft genome was obtained by assembling Roche 454 FLX + shotgun data into 194 contigs with an N50 of 251 Kbp. We compare our draft genome with all other Saccharomyces cerevisiae genomes.

Conclusions

Our analysis confirms the close similarity of S. boulardii to S. cerevisiae strains and provides a framework to understand the probiotic effects of this yeast, which exhibits unique physiological and metabolic properties.

Multiple genomic changes associated with reorganization of gene regulation and adaptation in yeast

Frequently during evolution, new phenotypes evolved due to novelty in gene regulation, such as that caused by genome rewiring. This has been demonstrated by comparing common regulatory sequences among species and by identifying single regulatory mutations that are associated with new phenotypes. However, while a single mutation changes a single element, gene regulation is accomplished by a regulatory network involving multiple interactive elements. Therefore, to better understand regulatory evolution, we have studied how mutations contributed to the adaptation of cells to a regulatory challenge. We created a synthetic genome rewiring in yeast cells, challenged their gene regulation, and studied their adaptation. HIS3, an essential enzyme for histidine biosynthesis, was placed exclusively under a GAL promoter, which is induced by galactose and strongly repressed in glucose. Such rewired cells were faced with significant regulatory challenges in a repressive glucose medium. We identified several independent mutations in elements of the GAL system associated with the rapid adaptation of cells, such as the repressor GAL80 and the binding sites of the activator GAL4. Consistent with the extraordinarily high rate of cell adaptation, new regulation emerged during adaptation via multiple trajectories, including those involving mutations in elements of the GAL system. The new regulation of HIS3 tuned its expression according to histidine requirements with or without these significant mutations, indicating that additional factors participated in this regulation and that the regulatory network could reorganize in multiple ways to accommodate different mutations. This study, therefore, stresses network plasticity as an important property for regulatory adaptation and evolution.

Regulations of sugar transporters: insights from yeast

Transport across the plasma membrane is the first step at which nutrient supply is tightly regulated in response to intracellular needs and often also rapidly changing external environment. In this review, I describe primarily our current understanding of multiple interconnected glucose-sensing systems and signal-transduction pathways that ensure fast and optimum expression of genes encoding hexose transporters in three yeast species, Saccharomyces cerevisiae, Kluyveromyces lactis and Candida albicans. In addition, an overview of GAL- and MAL-specific regulatory networks, controlling galactose and maltose utilization, is provided. Finally, pathways generating signals inducing posttranslational degradation of sugar transporters will be highlighted.