Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources

Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity

In their natural environments, microorganisms mainly operate at suboptimal growth conditions with fluctuations in nutrient abundance. The resulting cellular adaptation is subject to conflicting tasks: growth or survival maximisation. Here, we study this adaptation by systematically measuring the impact of a nitrogen downshift to 24 nitrogen sources on cellular metabolism at the single-cell level. Saccharomyces lineages grown in rich media and exposed to a nitrogen downshift gradually differentiate to form two subpopulations of different cell sizes where one favours growth while the other favours viability with an extended chronological lifespan. This differentiation is asymmetrical with daughter cells representing the new differentiated state with increased viability. We characterise the metabolic response of the subpopulations using RNA sequencing, metabolic biosensors and a transcription factor-tagged GFP library coupled to high-throughput microscopy, imaging more than 800,000 cells. We find that the subpopulation with increased viability is associated with a dormant quiescent state displaying differences in MAPK signalling. Depending on the identity of the nitrogen source present, differentiation into the quiescent state can be actively maintained, attenuated, or aborted. These results establish amino acids as important signalling molecules for the formation of genetically identical subpopulations, involved in chronological lifespan and growth rate determination.

From yeast screening for suitability as single cell protein to fed-batch cultures

PURPOSE

Fed-batch cultures have rarely been used in single cell protein (SCP) research. This work evaluated multiple yeast species for suitability as SCP cultivated using glucose- and sucrose-based substrate and performed in-depth studies of fed-batch SCP cultivation kinetics for selected yeasts, including determination of specific crude nitrogen-to-protein conversion factors.

METHODS

SCP was cultivated using fully synthetic media in flask batch or bioreactor fed-batch cultures. Crude nitrogen and nucleic acid content were determined using the Dumas method and fluorescence assay kits, respectively.

RESULTS

C. utilis compared favorably to other yeasts in flask batch cultures in terms of process yield (0.52 ± 0.01 gx gs-1) and crude nitrogen content (10.0 ± 0.5 and 9.9 ± 0.5%CDW for glucose and sucrose, respectively). This is the first time biomass composition data was reported for SCP cultivated in fed-batch mode. C. utilis crude nitrogen content was consistent across the tested conditions (protein content stabilized around 50%CDW in fed-batch), while that of the benchmark yeast S. cerevisiae was higher in batch cultures and at the beginning of fed-batch relative to the end (protein content decreased over time and stabilized around 43%CDW). Total nucleic acid content of the yeasts was similar (6.8%CDW and 6.3%CDW, for C. utilis and S. cerevisiae, respectively), with crude nitrogen-to-protein conversion factors of 4.97 and 5.80.

CONCLUSION

This study demonstrated the suitability of C. utilis as SCP, notably the robustness of its crude nitrogen content (as an indicator of protein content) across batch and fed-batch conditions, compared to that of the benchmark yeast S. cerevisiae.

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. This study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

Native microalgal-bacterial consortia from the Ecuadorian Amazon region: an alternative to domestic wastewater treatment

In low-middle income countries (LMIC), wastewater treatment using native microalgal-bacterial consortia has emerged as a cost-effective and technologically-accessible remediation strategy. This study evaluated the effectiveness of six microalgal-bacterial consortia (MBC) from the Ecuadorian Amazon in removing organic matter and nutrients from non-sterilized domestic wastewater (NSWW) and sterilized domestic wastewater (SWW) samples. Microalgal-bacterial consortia growth, in NSWW was, on average, six times higher than in SWW. Removal rates (RR) for NH4 +- N and PO4 3--P were also higher in NSWW, averaging 8.04 ± 1.07 and 6.27 ± 0.66 mg L-1 d-1, respectively. However, the RR for NO3 - -N did not significantly differ between SWW and NSWW, and the RR for soluble COD slightly decreased under non-sterilized conditions (NSWW). Our results also show that NSWW and SWW samples were statistically different with respect to their nutrient concentration (NH4 +-N and PO4 3--P), organic matter content (total and soluble COD and BOD5), and physical-chemical parameters (pH, T, and EC). The enhanced growth performance of MBC in NSWW can be plausibly attributed to differences in nutrient and organic matter composition between NSWW and SWW. Additionally, a potential synergy between the autochthonous consortia present in NSWW and the native microalgal-bacterial consortia may contribute to this efficiency, contrasting with SWW where no active autochthonous consortia were observed. Finally, we also show that MBC from different localities exhibit clear differences in their ability to remove organic matter and nutrients from NSWW and SWW. Future research should focus on elucidating the taxonomic and functional profiles of microbial communities within the consortia, paving the way for a more comprehensive understanding of their potential applications in sustainable wastewater management.

Addition of Saccharomyces eubayanus to SCOBY fermentations modulates the chemical and volatile compound profiles in kombucha

Kombucha is a fermented beverage derived from a sweetened tea fermentation inoculated with a bacteria-yeast consortium referred to as Symbiotic Culture of Bacteria and Yeast (SCOBY). Different SCOBY cultures can impact the beverage's quality and make the whole process highly variable. Adding Saccharomyces yeast cultures to the fermentation process can avoid stalled fermentations, providing a reproducible beverage. Here, we explored using different Saccharomyces eubayanus strains together with SCOBY in the context of kombucha fermentation. Our results show that yeast x SCOBY co-cultures exhibited a robust fermentation profile, providing ethanol and acetic acid levels ranging from 0,18-1,81 %v/v and 0,35-1,15 g/L, respectively. The kombucha volatile compound profile of co-cultures was unique, where compounds such as Isopentyl acetate where only found in yeast x SCOBY fermentations. Metabarcoding revealed that the SCOBY composition was also dependent on the S. eubayanus genotype, where besides Saccharomyces, amplicon sequence variants belonging to Brettanomyces and Starmerella were detected. These differences concomitated global changes in transcript levels in S. eubayanus related to the metabolism of organic molecules used in kombucha fermentation. This study highlights the potential for exploring different S. eubayanus strains for kombucha fermentation, and the significant yeast genotype effect in the profile differentiation in this process.

Controlling circuitry underlies the growth optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

The impact of metabolism on the adaptation of organisms to environmental change

Since Jacob and Monod's discovery of the lac operon ∼1960, the explanations offered for most metabolic adaptations have been genetic. The focus has been on the adaptive changes in gene expression that occur, which are often referred to as "metabolic reprogramming." The contributions metabolism makes to adaptation have been largely ignored. Here we point out that metabolic adaptations, including the associated changes in gene expression, are highly dependent on the metabolic state of an organism prior to the environmental change to which it is adapting, and on the plasticity of that state. In support of this hypothesis, we examine the paradigmatic example of a genetically driven adaptation, the adaptation of E. coli to growth on lactose, and the paradigmatic example of a metabolic driven adaptation, the Crabtree effect in yeast. Using a framework based on metabolic control analysis, we have reevaluated what is known about both adaptations, and conclude that knowledge of the metabolic properties of these organisms prior to environmental change is critical for understanding not only how they survive long enough to adapt, but also how the ensuing changes in gene expression occur, and their phenotypes post-adaptation. It would be useful if future explanations for metabolic adaptations acknowledged the contributions made to them by metabolism, and described the complex interplay between metabolic systems and genetic systems that make these adaptations possible.

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.

Controlling microbial co-culture based on substrate pulsing can lead to stability through differential fitness advantages

Microbial consortia are an exciting alternative for increasing the performances of bioprocesses for the production of complex metabolic products. However, the functional properties of microbial communities remain challenging to control, considering the complex interaction mechanisms occurring between co-cultured microbial species. Indeed, microbial communities are highly dynamic and can adapt to changing environmental conditions through complex mechanisms, such as phenotypic diversification. We focused on stabilizing a co-culture of Saccharomyces cerevisiae and Escherichia coli in continuous cultures. Our preliminary data pointed out that transient diauxic shifts could lead to stable co-culture by providing periodic fitness advantages to the yeast. Based on a computational toolbox called MONCKS (for MONod-type Co-culture Kinetic Simulation), we were able to predict the dynamics of diauxic shift for both species based on a cybernetic approach. This toolbox was further used to predict the frequency of diauxic shift to be applied to reach co-culture stability. These simulations were successfully reproduced experimentally in continuous bioreactors with glucose pulsing. Finally, based on a bet-hedging reporter, we observed that the yeast population exhibited an increased phenotypic diversification process in co-culture compared with mono-culture, suggesting that this mechanism could be the basis of the metabolic fitness of the yeast.

Being able to manipulate the dynamics of microbial co-cultures is a technical challenge that need to be addressed in order to get a deeper insight about how microbial communities are evolving in their ecological context, as well as for exploiting the potential offered by such communities in an applied context e.g., for setting up more robust bioprocesses relying on the use of several microbial species. In this study, we used continuous cultures of bacteria (E. coli) and yeast (S. cerevisiae) in order to demonstrate that a simple nutrient pulsing strategy can be used for adjusting the composition of the community with time. As expected, during growth on glucose, E. coli quickly outcompeted S. cerevisiae. However, when glucose is pulsed into the culture, increased metabolic fitness of the yeast was observed upon reconsumption of the main side metabolites i.e., acetate and ethanol, leading to a robust oscillating growth profile for both species. The optimal pulsing frequency was predicted based on a cybernetic version of a Monod growth model taking into account the main metabolic routes involved in the process. Considering the limited number of metabolic details needed, this cybernetic approach could be generalized to other communities.

Transcriptional noise adjusted for expression levels reveals genes with high transcriptional noise that are highly expressed, functionally related, and co-regulated in yeast

Understanding the relationship between variability in single-cell and non-single-cell gene expression studies will aid in understanding the role of and mechanisms that lead to variability in biological systems. Studies on the variation of gene expression levels in yeast normally focus on single cells and use the coefficient of variance (CV) as a measure of noise. The CV is typically negatively correlated with gene expression levels, so most of the studies using yeast find that genes with high transcriptional noise are lowly expressed. We find adjusting noise for expression levels using linear/natural log polynomial, and local fits and analyzing many non-single-cell RNA-seq sets identifies genes with high median transcriptional noise that are different than those that have high median CVs. Interestingly, these genes are heavily regulated by transcription factors that are related to variability and stochastic processes based on single-cell studies, including Msn2p, Msn4p, Hsf1p, and Crz1p but are not associated with genes with high median CVs based on non-single-cell gene expression data. In addition, adjusting noise for expression levels in a single-cell RNA-seq data set adds value by finding genes that have noisy gene expression levels and their associated transcription factors that are not found to be associated with genes with high CVs in the single-cell expression data or a comparable non-single-cell gene expression data. Lastly, S. cerevisiae genes with noisy expression tend to have orthologs with noisy gene expression in C. albicans, indicating transcriptional noise is evolutionarily conserved.

Do microbes have a memory? History-dependent behavior in the adaptation to variable environments

Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or “memory,” with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB.

Epigenetic memory contributing to the pathogenesis of AKI-to-CKD transition

Epigenetic memory, which refers to the ability of cells to retain and transmit epigenetic marks to their daughter cells, maintains unique gene expression patterns. Establishing programmed epigenetic memory at each stage of development is required for cell differentiation. Moreover, accumulating evidence shows that epigenetic memory acquired in response to environmental stimuli may be associated with diverse diseases. In the field of kidney diseases, the “memory” of acute kidney injury (AKI) leads to progression to chronic kidney disease (CKD); epidemiological studies show that patients who recover from AKI are at high risk of developing CKD. The underlying pathological processes include nephron loss, maladaptive epithelial repair, inflammation, and endothelial injury with vascular rarefaction. Further, epigenetic alterations may contribute as well to the pathophysiology of this AKI-to-CKD transition. Epigenetic changes induced by AKI, which can be recorded in cells, exert long-term effects as epigenetic memory. Considering the latest findings on the molecular basis of epigenetic memory and the pathophysiology of AKI-to-CKD transition, we propose here that epigenetic memory contributing to AKI-to-CKD transition can be classified according to the presence or absence of persistent changes in the associated regulation of gene expression, which we designate “driving” memory and “priming” memory, respectively. “Driving” memory, which persistently alters the regulation of gene expression, may contribute to disease progression by activating fibrogenic genes or inhibiting renoprotective genes. This process may be involved in generating the proinflammatory and profibrotic phenotypes of maladaptively repaired tubular cells after kidney injury. “Priming” memory is stored in seemingly successfully repaired tubular cells in the absence of detectable persistent phenotypic changes, which may enhance a subsequent transcriptional response to the second stimulus. This type of memory may contribute to AKI-to-CKD transition through the cumulative effects of enhanced expression of profibrotic genes required for wound repair after recurrent AKI. Further understanding of epigenetic memory will identify therapeutic targets of future epigenetic intervention to prevent AKI-to-CKD transition.

Microbial Adaptation to Enhance Stress Tolerance

Microbial cell factories have been widely used in the production of various chemicals. Although synthetic biology is useful in improving the cell factories, adaptation is still widely applied to enhance its complex properties. Adaptation is an important strategy for enhancing stress tolerance in microbial cell factories. Adaptation involves gradual modifications of microorganisms in a stressful environment to enhance their tolerance. During adaptation, microorganisms use different mechanisms to enhance non-preferred substrate utilization and stress tolerance, thereby improving their ability to adapt for growth and survival. In this paper, the progress on the effects of adaptation on microbial substrate utilization capacity and environmental stress tolerance are reviewed, and the mechanisms involved in enhancing microbial adaptive capacity are discussed.

The yapsin family of aspartyl proteases regulate glucose homeostasis in Candida glabrata

Invasive candidiasis poses a major healthcare threat. The human opportunistic fungal pathogen Candida glabrata, which causes mucosal and deep-seated infections, is armed with distinct virulence attributes, including a family of 11 glycosylphosphatidylinositol-linked aspartyl proteases, CgYapsins. Here, we have profiled total membrane proteomes of the C. glabrata wildtype and 11 proteases-deficient strain, Cgyps1-11Δ, by mass spectrometry analysis and uncovered a novel role for fungal yapsins in glucose sensing and homeostasis. Furthermore, through label-free quantitative membrane proteome analysis, we showed differential abundance of 42% of identified membrane proteins, with electron transport chain and glycolysis proteins displaying lower and higher abundance in Cgyps1-11Δ cells, compared with wildtype cells, respectively. We also demonstrated elevated glucose uptake and upregulation of genes that code for the low-glucose sensor CgSnf3, transcriptional regulators CgMig1 and CgRgt1, and hexose transporter CgHxt2/10 in the Cgyps1-11Δ mutant. We further elucidated a potential underlying mechanism through genetic and transcript measurement analysis under low- and high-glucose conditions and found CgSNF3 deletion to rescue high glucose uptake and attenuated growth of the Cgyps1-11Δ mutant in YPD medium, thereby linking CgYapsins with regulation of the CgSnf3-dependent low-glucose sensing pathway. Last, high ethanol production, diminished mitochondrial membrane potential, and elevated susceptibility to oxidative phosphorylation inhibitors point toward increased fermentative and decreased respiratory metabolism in the Cgyps1-11Δ mutant. Altogether, our findings revealed new possible glucose metabolism-regulatory roles for putative cell surface-associated CgYapsins and advanced our understanding of fungal carbohydrate homeostasis mechanisms.

A Tunable and Expandable Transactivation System in Probiotic Yeast Saccharomyces boulardii

Precise transcriptional modulation is a key requirement for developing synthetic probiotics with predictably tunable functionalities. In this study, an expandable and tunable transactivation system was constructed and validated in probiotic yeast Saccharomyces boulardii. The use of nuclease-null Cas9 and scaffold RNA (scRNA) directed regulation enabled transactivation under the control of a synthetic promoter in S. boulardii. A synthetic promoter consisting of the scRNA target sequence and the core GAL7 promoter region restricted interference from the native galactose regulon. The system was readily expanded by introducing new target sequences to the promoter and scRNA. Complementarity between the promoter and scRNA, and binding specificity between scRNA and transcriptional activator, served as two layers of orthogonality of the transactivation. In addition, activator expression under the control of an inducible promoter enabled control of the transactivation via chemical inducer. The described system has the potential to enable engineering of probiotic yeast to more precisely perform therapeutic functions.

Monitoring single-cell dynamics of entry into quiescence during an unperturbed life cycle

The life cycle of microorganisms is associated with dynamic metabolic transitions and complex cellular responses. In yeast, how metabolic signals control the progressive choreography of structural reorganizations observed in quiescent cells during a natural life cycle remains unclear. We have developed an integrated microfluidic device to address this question, enabling continuous single-cell tracking in a batch culture experiencing unperturbed nutrient exhaustion to unravel the coordination between metabolic and structural transitions within cells. Our technique reveals an abrupt fate divergence in the population, whereby a fraction of cells is unable to transition to respiratory metabolism and undergoes a reversible entry into a quiescence-like state leading to premature cell death. Further observations reveal that nonmonotonous internal pH fluctuations in respiration-competent cells orchestrate the successive waves of protein superassemblies formation that accompany the entry into a bona fide quiescent state. This ultimately leads to an abrupt cytosolic glass transition that occurs stochastically long after proliferation cessation. This new experimental framework provides a unique way to track single-cell fate dynamics over a long timescale in a population of cells that continuously modify their ecological niche.

Fungal behaviour: a new frontier in behavioural ecology

As human beings, behaviours make up our everyday lives. What we do from the moment we wake up to the moment we go back to sleep at night can all be classified and studied through the concepts of behavioural ecology. The same applies to all vertebrates and, to some extent, invertebrates. Fungi are, in most people's eyes perhaps, the eukaryotic multicellular organisms with which we humans share the least commonalities. However, they still express behaviours, and we argue that we could obtain a better understanding of their lives - although they are very different from ours - through the lens of behavioural ecology. Moreover, insights from fungal behaviour may drive a better understanding of behavioural ecology in general.

Adaptation of central metabolite pools to variations in growth rate and cultivation conditions in Saccharomyces cerevisiae

Background

Saccharomyces cerevisiae is a well-known popular model system for basic biological studies and serves as a host organism for the heterologous production of commercially interesting small molecules and proteins. The central metabolism is at the core to provide building blocks and energy to support growth and survival in normal situations as well as during exogenous stresses and forced heterologous protein production. Here, we present a comprehensive study of intracellular central metabolite pool profiling when growing S. cerevisiae on different carbon sources in batch cultivations and at different growth rates in nutrient-limited glucose chemostats. The latest versions of absolute quantitative mass spectrometry-based metabolite profiling methodology were applied to cover glycolytic and pentose phosphate pathway metabolites, tricarboxylic acid cycle (TCA), complete amino acid, and deoxy-/nucleoside phosphate pools.

Results

Glutamate, glutamine, alanine, and citrate were the four most abundant metabolites for most conditions tested. The amino acid is the dominant metabolite class even though a marked relative reduction compared to the other metabolite classes was observed for nitrogen and phosphate limited chemostats. Interestingly, glycolytic and pentose phosphate pathway (PPP) metabolites display the largest variation among the cultivation conditions while the nucleoside phosphate pools are more stable and vary within a closer concentration window. The overall trends for glucose and nitrogen-limited chemostats were increased metabolite pools with the increasing growth rate. Next, comparing the chosen chemostat reference growth rate (0.12 h⁻¹, approximate one-fourth of maximal unlimited growth rate) illuminates an interesting pattern: almost all pools are lower in nitrogen and phosphate limited conditions compared to glucose limitation, except for the TCA metabolites citrate, isocitrate and α-ketoglutarate.

Conclusions

This study provides new knowledge-how the central metabolism is adapting to various cultivations conditions and growth rates which is essential for expanding our understanding of cellular metabolism and the development of improved phenotypes in metabolic engineering.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01557-8.

Variation, Variegation and Heritable Gene Repression in S. cerevisiae

Phenotypic heterogeneity provides growth advantages for a population upon changes of the environment. In S. cerevisiae, such heterogeneity has been observed as "on/off" states in the expression of individual genes in individual cells. These variations can persist for a limited or extended number of mitotic divisions. Such traits are known to be mediated by heritable chromatin structures, by the mitotic transmission of transcription factors involved in gene regulatory circuits or by the cytoplasmic partition of prions or other unstructured proteins. The significance of such epigenetic diversity is obvious, however, we have limited insight into the mechanisms that generate it. In this review, we summarize the current knowledge of epigenetically maintained heterogeneity of gene expression and point out similarities and converging points between different mechanisms. We discuss how the sharing of limiting repression or activation factors can contribute to cell-to-cell variations in gene expression and to the coordination between short- and long- term epigenetic strategies. Finally, we discuss the implications of such variations and strategies in adaptation and aging.

Memorizing environmental signals through feedback and feedforward loops

Cells in diverse organisms can store the information of previous environmental conditions for long periods of time. This form of cellular memory adjusts the cell's responses to future challenges, providing fitness advantages in fluctuating environments. Many biological functions, including cellular memory, are mediated by specific recurring patterns of interactions among proteins and genes, known as 'network motifs.' In this review, we focus on three well-characterized network motifs - negative feedback loops, positive feedback loops, and feedforward loops, which underlie different types of cellular memories. We describe the latest studies identifying these motifs in various molecular processes and discuss how the topologies and dynamics of these motifs can enable memory encoding and storage.

Microfluidics for single-cell lineage tracking over time to characterize transmission of phenotypes in Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is an excellent model organism to dissect the maintenance and inheritance of phenotypes due to its asymmetric division. This requires following individual cells over time as they go through divisions to define pedigrees. Here, we provide a detailed protocol for collecting and analyzing time-lapse imaging data of yeast cells. The microfluidics protocol can achieve improved time resolution for single-cell tracking to enable characterization of maintenance and inheritance of phenotypes. For complete details on the use and execution of this protocol, please refer to Bheda et al. (2020a).

History and Domestication of Saccharomyces cerevisiae in Bread Baking

The yeast Saccharomyces cerevisiae has been instrumental in the fermentation of foods and beverages for millennia. In addition to fermentations like wine, beer, cider, sake, and bread, S. cerevisiae has been isolated from environments ranging from soil and trees, to human clinical isolates. Each of these environments has unique selection pressures that S. cerevisiae must adapt to. Bread dough, for example, requires S. cerevisiae to efficiently utilize the complex sugar maltose; tolerate osmotic stress due to the semi-solid state of dough, high salt, and high sugar content of some doughs; withstand various processing conditions, including freezing and drying; and produce desirable aromas and flavors. In this review, we explore the history of bread that gave rise to modern commercial baking yeast, and the genetic and genomic changes that accompanied this. We illustrate the genetic and phenotypic variation that has been documented in baking strains and wild strains, and how this variation might be used for baking strain improvement. While we continue to improve our understanding of how baking strains have adapted to bread dough, we conclude by highlighting some of the remaining open questions in the field.

A Putative Bet-Hedging Strategy Buffers Budding Yeast against Environmental Instability

To grow and divide, cells must extract resources from dynamic and unpredictable environments. Many organisms use different metabolic strategies for distinct contexts. Budding yeast can produce ATP from carbon sources by mechanisms that prioritize either speed (fermentation) or yield (respiration). Withdrawing glucose from exponentially growing cells reveals variability in their ability to switch from fermentation to respiration. We observe two subpopulations of glucose-starved cells: recoverers, which rapidly adapt and resume growth, and arresters, which enter a shock state characterized by deformation of many cellular structures, including mitochondria. These states are heritable, and on high glucose, arresters grow and divide faster than recoverers. Recoverers have a fitness advantage during a carbon source shift but are less fit in a constant, high-glucose environment, and we observe natural variation in the frequency of the two states across wild yeast strains. These experiments suggest that bet hedging has evolved in budding yeast.

Brewing potential of the wild yeast species Saccharomyces paradoxus

Saccharomyces paradoxus is commonly isolated from environmental samples in Northern Europe and North America, but is rarely found associated with fermentation. However, as novelty has become a selling point in beer markets, interest toward non-conventional and local yeasts is increasing. Here, we report the first comprehensive investigation of the brewing potential of the species. Eight wild strains of S. paradoxus were isolated from oak trees growing naturally in Finland, screened in a series of fermentation trials and the most promising strain was selected for lager beer brewing at pilot scale (40 l). Yeasts were evaluated according to their ability to utilize wort sugars, their production of flavour-active aroma volatiles, diacetyl and organic acids, and sensorial quality of beers produced. All strains could assimilate maltose but this occurred after a considerable lag phase. Once adapted, most wild strains reached attenuation rates close to 70%. Adaptation to maltose could be maintained by re-pitching and with appropriate handling of the adapted yeast. Fermentation at 15 °C with the best performing strain was completed in 17 days. Maltose was consumed as efficiently as with a reference lager yeast, but no maltotriose use was observed. Bottled beers were evaluated by a trained sensory panel, and were generally rated as good as, or better than, reference beers. S. paradoxus beers were considered full-bodied and had a relatively clean flavour profile despite the presence of the clove-like 4-vinyl guaiacol. In conclusion, S. paradoxus exhibits a number of traits relevant to brewing, and with appropriate handling could be applied industrially.

The past determines the future: sugar source history and transcriptional memory

Transcriptional reinduction memory is a phenomenon whereby cells “remember” their transcriptional response to a previous stimulus such that subsequent encounters with the same stimulus can result in altered gene expression kinetics. Chromatin structure is thought to play a role in certain transcriptional memory mechanisms, leading to questions as to whether and how memory can be actively maintained and inherited to progeny through cell division. Here we summarize efforts towards dissecting chromatin-based transcriptional memory inheritance of GAL genes in Saccharomyces cerevisiae. We focus on methods and analyses of GAL (as well as MAL and INO) memory in single cells and discuss the challenges in unraveling the underlying mechanisms in yeast and higher eukaryotes.

A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast

Current 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.

Microbial lag phase can be indicative of, or independent from, cellular stress

Measures of microbial growth, used as indicators of cellular stress, are sometimes quantified at a single time-point. In reality, these measurements are compound representations of length of lag, exponential growth-rate, and other factors. Here, we investigate whether length of lag phase can act as a proxy for stress, using  a number of model systems (Aspergillus penicillioides; Bacillus subtilis; Escherichia coli; Eurotium amstelodami, E. echinulatum, E. halophilicum, and E. repens; Mrakia frigida; Saccharomyces cerevisiae; Xerochrysium xerophilum; Xeromyces bisporus) exposed to mechanistically distinct types of cellular stress including low water activity, other solute-induced stresses, and dehydration-rehydration cycles. Lag phase was neither proportional to germination rate for X. bisporus (FRR3443) in glycerol-supplemented media (r2 = 0.012), nor to exponential growth-rates for other microbes. In some cases, growth-rates varied greatly with stressor concentration even when lag remained constant. By contrast, there were strong correlations for B. subtilis in media supplemented with polyethylene-glycol 6000 or 600 (r2 = 0.925 and 0.961), and for other microbial species. We also  analysed data from independent studies of food-spoilage fungi under glycerol stress (Aspergillus aculeatinus and A. sclerotiicarbonarius); mesophilic/psychrotolerant bacteria under diverse, solute-induced stresses (Brochothrix thermosphacta, Enterococcus faecalis, Pseudomonas fluorescens, Salmonella typhimurium, Staphylococcus aureus); and fungal enzymes under acid-stress (Terfezia claveryi lipoxygenase and Agaricus bisporus tyrosinase). These datasets also exhibited diversity, with some strong- and moderate correlations between length of lag and exponential growth-rates; and sometimes none. In conclusion, lag phase is not  a reliable measure of stress because length of lag and growth-rate inhibition are sometimes highly correlated, and sometimes not at all.

Convergence between Regulation of Carbon Utilization and Catabolic Repression in Xanthophyllomyces dendrorhous

Xanthophyllomyces dendrorhous is a carotenogenic yeast with a singular metabolic capacity to produce astaxanthin, a valuable antioxidant pigment. This yeast can assimilate several carbon sources and sustain fermentation even under aerobic conditions. Since astaxanthin biosynthesis is affected by the carbon source, the study of carotenogenesis regulatory mechanisms is key for improving astaxanthin yield in X. dendrorhous This study aimed to elucidate the regulation of the metabolism of different carbon sources and the phenomenon of catabolic repression in this yeast. To this end, protein and transcript levels were quantified by iTRAQ (isobaric tags for relative and absolute quantification) and transcriptomic sequencing (RNA-seq) in the wild-type strain under conditions of glucose, maltose, or succinate treatment and in the mutant strains for genes MIG1, CYC8, and TUP1 under conditions of glucose treatment. Alternative carbon sources such as maltose and succinate affected the relative abundances of 14% of the wild-type proteins, which were mainly grouped into the carbohydrate metabolism category, with the glycolysis/gluconeogenesis and citrate cycle pathways being the most highly represented pathways. Each mutant strain showed significant proteomic profile changes, affecting approximately 2% of the total proteins identified, compared to the wild-type strain under glucose treatment conditions. Similarly to the results seen with the alternative carbon sources, the changes in the mutant strains mainly affected carbohydrate metabolism, with glycolysis/gluconeogenesis and the pentose phosphate and citrate cycle pathways being the most highly represented pathways. Our results showed convergence between carbon assimilation and catabolic repression in the strains studied. Interestingly, indications of cooperative, opposing, and overlapping processes during catabolic regulation were found. We also identified target proteins of the regulatory processes, reinforcing the likelihood of catabolic repression at the posttranscriptional level.IMPORTANCE The conditions affecting catabolic regulation in X. dendrorhous are complex and suggest the presence of an alternative mechanism of regulation. The repressors Mig1, Cyc8, and Tup1 are essential elements for the regulation of the use of glucose and other carbon sources. All play different roles but, depending on the growth conditions, can work in convergent, synergistic, and complementary ways to use carbon sources and to regulate other targets for yeast metabolism. Our results reinforced the belief that further studies in X. dendrorhous are needed to clarify a specific regulatory mechanism at the domain level of the repressors as well as its relationship with those of other metabolic repressors, i.e., the stress response, to elucidate carotenogenic regulation at the transcriptomic and proteomic levels in this yeast.

Metabolic transcriptional memory

Background

Organisms can be primed by metabolic exposures to continue expressing response genes even once the metabolite is no longer available, and can affect the speed and magnitude of responsive gene expression during subsequent exposures. This “metabolic transcriptional memory” can have a profound impact on the survivability of organisms in fluctuating environments.

Scope of review

Here I present several examples of metabolic transcriptional memory in the microbial world and discuss what is known so far regarding the underlying mechanisms, which mainly focus on chromatin modifications, protein inheritance, and broad changes in metabolic network. From these lessons learned in microbes, some insights into the yet understudied human metabolic memory can be gained. I thus discuss the implications of metabolic memory in disease progression in humans – i.e., the memory of high blood sugar exposure and the resulting effects on diabetic complications.

Major conclusions

Carbon source shifts from glucose to other less preferred sugars such as lactose, galactose, and maltose for energy metabolism as well as starvation of a signal transduction precursor sugar inositol are well-studied examples of metabolic transcriptional memory in Escherichia coli and Saccharomyces cerevisiae. Although the specific factors guiding metabolic transcriptional memory are not necessarily conserved from microbes to humans, the same basic mechanisms are in play, as is observed in hyperglycemic memory. Exploration of new metabolic transcriptional memory systems as well as further detailed mechanistic analyses of known memory contexts in microbes is therefore central to understanding metabolic memory in humans, and may be of relevance for the successful treatment of the ever-growing epidemic of diabetes.

•

Metabolic exposures can prime genes to have memory.

•

Memory of carbon source shifts occurs in all kingdoms of life.

•

Memory is maintained through multiple mechanisms including chromatin modifications, proteins, and metabolic network.

•

Metabolic transcriptional memory in unicellular organisms is a part of “bet-hedging” strategies to ensure survival.

•

Hyperglycemic memory in humans contributes to diabetes and aging.

Metabolic activity affects the response of single cells to a nutrient switch in structured populations

Microbes live in ever-changing environments where they need to adapt their metabolism to different nutrient conditions. Many studies have characterized the response of genetically identical cells to nutrient switches in homogeneous cultures; however, in nature, microbes often live in spatially structured groups such as biofilms where cells can create metabolic gradients by consuming and releasing nutrients. Consequently, cells experience different local microenvironments and vary in their phenotype. How does this phenotypic variation affect the ability of cells to cope with nutrient switches? Here, we address this question by growing dense populations of Escherichia coli in microfluidic chambers and studying a switch from glucose to acetate at the single-cell level. Before the switch, cells vary in their metabolic activity: some grow on glucose, while others cross-feed on acetate. After the switch, only few cells can resume growth after a period of lag. The probability to resume growth depends on a cells' phenotype prior to the switch: it is highest for cells cross-feeding on acetate, while it depends in a non-monotonic way on the growth rate for cells growing on glucose. Our results suggest that the strong phenotypic variation in spatially structured populations might enhance their ability to cope with fluctuating environments.

On the duration of the microbial lag phase

When faced with environmental changes, microbes enter a lag phase during which cell growth is arrested, allowing cells to adapt to the new situation. The discovery of the lag phase started the field of gene regulation and led to the unraveling of underlying mechanisms. However, the factors determining the exact duration and dynamics of the lag phase remain largely elusive. Naively, one would expect that cells adapt as quickly as possible, so they can resume growth and compete with other organisms. However, recent studies show that the lag phase can last from several hours up to several days. Moreover, some cells within the same population take much longer than others, despite being genetically identical. In addition, the lag phase duration is also influenced by the past, with recent exposure to a given environment leading to a quicker adaptation when that environment returns. Genome-wide screens in Saccharomyces cerevisiae on carbon source shifts now suggest that the length of the lag phase, the heterogeneity in lag times of individual cells, and the history-dependent behavior are not determined by the time it takes to induce a few specific genes related to uptake and metabolism of a new carbon source. Instead, a major shift in general metabolism, and in particular a switch between fermentation and respiration, is the major bottleneck that determines lag duration. This suggests that there may be a fitness trade-off between complete adaptation of a cell’s metabolism to a given environment, and a short lag phase when the environment changes.

Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources

Cells 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.