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

A system for inducible mitochondria-specific protein degradation in vivo

Targeted protein degradation systems developed for eukaryotes employ cytoplasmic machineries to perform proteolysis. This has prevented mitochondria-specific analysis of proteins that localize to multiple locations, for example, the mitochondria and the nucleus. Here, we present an inducible mitochondria-specific protein degradation system in Saccharomyces cerevisiae based on the Mesoplasma florum Lon (mf-Lon) protease and its corresponding ssrA tag (called PDT). We show that mitochondrially targeted mf-Lon protease efficiently and selectively degrades a PDT-tagged reporter protein localized to the mitochondrial matrix. The degradation can be induced by depleting adenine from the medium, and tuned by altering the promoter strength of the MF-LON gene. We furthermore demonstrate that mf-Lon specifically degrades endogenous, PDT-tagged mitochondrial proteins. Finally, we show that mf-Lon-dependent PDT degradation can also be achieved in human mitochondria. In summary, this system provides an efficient tool to selectively analyze the mitochondrial function of dually localized proteins.

A fast method to distinguish between fermentative and respiratory metabolisms in single yeast cells

Saccharomyces cerevisiae adjusts its metabolism based on nutrient availability, typically transitioning from glucose fermentation to ethanol respiration as glucose becomes limiting. However, our understanding of the regulation of metabolism is largely based on population averages, whereas nutrient transitions may cause heterogeneous responses. Here we introduce iCRAFT, a method that couples the ATP Förster resonance energy transfer (FRET)-based biosensor yAT1.03 with Antimycin A to differentiate fermentative and respiratory metabolisms in individual yeast cells. Upon Antimycin A addition, respiratory cells experienced a sharp decrease of the normalized FRET ratio, while respiro-fermentative cells showed no response. Next, we tracked changes in metabolism during the diauxic shift of a glucose pre-grown culture. Following glucose exhaustion, the entire cell population experienced a progressive rise in cytosolic ATP produced via respiration, suggesting a gradual increase in respiratory capacity. Overall, iCRAFT is a robust tool to distinguish fermentation from respiration, offering a new single-cell opportunity to study yeast metabolism.

Beyond the (geometric) mean: stochastic models undermine deterministic predictions of bet hedger evolution

Bet hedging is a ubiquitous strategy for risk reduction in the face of unpredictable environmental change where a lineage lowers its variance in fitness across environments at the expense of also lowering its arithmetic mean fitness. Classically, the benefit of bet hedging has been quantified using geometric mean fitness (GMF); bet hedging is expected to evolve if and only if it has a higher GMF than the wild-type. We build upon previous research on the effect of incorporating stochasticity in phenotypic distribution, environment, and reproduction to investigate the extent to which these sources of stochasticity will impact the evolution of real-world bet hedging traits. We utilize both individual-based simulations and Markov chain numerics to demonstrate that modeling stochasticity can alter the sign of selection for the bet hedger compared to deterministic predictions. We find that bet hedging can be deleterious at small population sizes and beneficial at larger population sizes. This non-monotonic dependence of the sign of selection on population size, known as sign inversion, exists across parameter space for both conservative and diversified bet hedgers. We apply our model to published data of bet hedging strategies to show that sign inversion exists for biologically relevant parameters in two study systems: Papaver dubium, an annual poppy with variable germination phenology, and Salmonella typhimurium, a pathogenic bacteria that exhibits antibiotic persistence. Taken together, our results suggest that GMF is not enough to predict when bet hedging is adaptive.

Performance and robustness analysis reveals phenotypic trade-offs in yeast

To design strains that can function efficiently in complex industrial settings, it is crucial to consider their robustness, that is, the stability of their performance when faced with perturbations. In the present study, we cultivated 24 Saccharomyces cerevisiae strains under conditions that simulated perturbations encountered during lignocellulosic bioethanol production, and assessed the performance and robustness of multiple phenotypes simultaneously. The observed negative correlations confirmed a trade-off between performance and robustness of ethanol yield, biomass yield, and cell dry weight. Conversely, the specific growth rate performance positively correlated with the robustness, presumably because of evolutionary selection for robust, fast-growing cells. The Ethanol Red strain exhibited both high performance and robustness, making it a good candidate for bioproduction in the tested perturbation space. Our results experimentally map the robustness-performance trade-offs, previously demonstrated mainly by single-phenotype and computational studies.

Adaptation to sorbic acid in low sugar promotes resistance of yeast to the preservative

The weak acid sorbic acid is a common preservative used in soft drink beverages to control microbial spoilage. Consumers and industry are increasingly transitioning to low-sugar food formulations, but potential impacts of reduced sugar on sorbic acid efficacy are barely characterised. In this study, we report enhanced sorbic acid resistance of yeast in low-glucose conditions. We had anticipated that low glucose would induce respiratory metabolism, which was shown previously to be targeted by sorbic acid. However, a shift from respiratory to fermentative metabolism upon sorbic acid exposure of Saccharomyces cerevisiae was correlated with relative resistance to sorbic acid in low glucose. Fermentation-negative yeast species did not show the low-glucose resistance phenotype. Phenotypes observed for certain yeast deletion strains suggested roles for glucose signalling and repression pathways in the sorbic acid resistance at low glucose. This low-glucose induced sorbic acid resistance was reversed by supplementing yeast cultures with succinic acid, a metabolic intermediate of respiratory metabolism (and a food-safe additive) that promoted respiration. The results indicate that metabolic adaptation of yeast can promote sorbic acid resistance at low glucose, a consideration for the preservation of foodstuffs as both food producers and consumers move towards a reduced sugar landscape.

Advances in automated and reactive flow cytometry for synthetic biotechnology

Automated flow cytometry (FC) has been initially considered for bioprocess monitoring and optimization. More recently, new physical and software interfaces have been made available, facilitating the access to this technology for labs and industries. It also comes with new capabilities, such as being able to act on the cultivation conditions based on population data. This approach, known as reactive FC, extended the range of applications of automated FC to bioprocess control and the stabilization of cocultures, but also to the broad field of synthetic and systems biology for the characterization of gene circuits. However, several issues must be addressed before automated and reactive FC can be considered standard and modular technologies.

Evolving tolerance of Yarrowia lipolytica to hydrothermal liquefaction aqueous phase waste

Hydrothermal liquefaction (HTL) is an emerging method for thermochemical conversion of wet organic waste and biomass into renewable biocrude. HTL also produces an aqueous phase (HTL-AP) side stream containing 2-4% light organic compounds that require treatment. Although anaerobic digestion (AD) of HTL-AP has shown promise, lengthy time periods were required for AD microbial communities to adapt to metabolic inhibitors in HTL-AP. An alternative for HTL-AP valorization was recently demonstrated using two engineered strains of Yarrowia lipolytica, E26 and Diploid TAL, for the overproduction of lipids and the polyketide triacetic acid lactone (TAL) respectively. These strains tolerated up to 10% HTL-AP (v/v) in defined media and up to 25% (v/v) HTL-AP in rich media. In this work, adaptive laboratory evolution (ALE) of these strains increased the bulk population tolerance for HTL-AP to up to 30% (v/v) in defined media and up to 35% (v/v) for individual isolates in rich media. The predominate organic acids within HTL-AP (acetic, butyric, and propionic) were rapidly consumed by the evolved Y. lipolytica strains. A TAL-producing isolate (strain 144-3) achieved a nearly 3-fold increase in TAL titer over the parent strain while simultaneously reducing the chemical oxygen demand (COD) of HTL-AP containing media. Fermentation with HTL-AP as the sole nutrient source demonstrated direct conversion of waste into TAL at 10% theoretical yield. Potential genetic mutations of evolved TAL production strains that could be imparting tolerance were explored. This work advances the potential of Y. lipolytica to biologically treat and simultaneously extract value from HTL wastewater. KEY POINTS: • Adaptive evolution of two Y. lipolytica strains enhanced their tolerance to waste. • Y. lipolytica reduces chemical oxygen demand in media containing waste. • Y. lipolytica can produce triacetic acid lactone directly from wastewater.

Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses

The ability of bacteria to respond to changes in their environment is critical to their survival, allowing them to withstand stress, form complex communities, and induce virulence responses during host infection. A remarkable feature of many of these bacterial responses is that they are often variable across individual cells, despite occurring in an isogenic population exposed to a homogeneous environmental change, a phenomenon known as phenotypic heterogeneity. Phenotypic heterogeneity can enable bet-hedging or division of labor strategies that allow bacteria to survive fluctuating conditions. Investigating the significance of phenotypic heterogeneity in environmental transitions requires dynamic, single-cell data. Technical advances in quantitative single-cell measurements, imaging, and microfluidics have led to a surge of publications on this topic. Here, we review recent discoveries on single-cell bacterial responses to environmental transitions of various origins and complexities, from simple diauxic shifts to community behaviors in biofilm formation to virulence regulation during infection. We describe how these studies firmly establish that this form of heterogeneity is prevalent and a conserved mechanism by which bacteria cope with fluctuating conditions. We end with an outline of current challenges and future directions for the field. While it remains challenging to predict how an individual bacterium will respond to a given environmental input, we anticipate that capturing the dynamics of the process will begin to resolve this and facilitate rational perturbation of environmental responses for therapeutic and bioengineering purposes.

Public good-driven release of heterogeneous resources leads to genotypic diversification of an isogenic yeast population

Understanding the basis of biological diversity remains a central problem in evolutionary biology. Using microbial systems, adaptive diversification has been studied in (a) spatially heterogeneous environments, (b) temporally segregated resources, and (c) resource specialization in a homogeneous environment. However, it is not well understood how adaptive diversification can take place in a homogeneous environment containing a single resource. Starting from an isogenic population of yeast Saccharomyces cerevisiae, we report rapid adaptive diversification, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good enzyme α-galactosidase, which hydrolyzes melibiose into glucose and galactose. The diversification is driven by mutations at a single locus, in the GAL3 gene in the S. cerevisiae GAL/MEL regulon. We show that metabolic co-operation involving public resources could be an important mode of generating biological diversity. Our study demonstrates sympatric diversification of yeast starting from an isogenic population and provides detailed mechanistic insights into the factors and conditions responsible for generating and maintaining the population diversity.

Evolution of yeast hybrids by aborted meiosis

Sterile hybrids are broadly considered evolutionary dead-ends because of their faulty sexual reproduction. While sterility in obligate sexual organisms is a clear constraint in perpetuating the species, some facultative sexual microbes such as yeasts can propagate asexually and maintain genome plasticity. Moreover, incomplete meiotic pathways in yeasts represent alternative routes to the standard meiosis that generates genetic combinations in the population and fuel adaptation. Here, we review how aborting meiosis promotes genome-wide allele shuffling in sterile Saccharomyces hybrids and describe approaches to identify evolved clones in a cell population. We further discuss possible implications of this process in generating phenotypic novelty and report cases of abortive meiosis across yeast species.

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.

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.

DarT-mediated mtDNA damage induces dynamic reorganization and selective segregation of mitochondria

Mitochondria are dynamic organelles that play essential roles in cell growth and survival. Processes of fission and fusion are critical for the distribution, segregation, and maintenance of mitochondria and their genomes (mtDNA). While recent work has revealed the significance of mitochondrial organization for mtDNA maintenance, the impact of mtDNA perturbations on mitochondrial dynamics remains less understood. Here, we develop a tool to induce mitochondria-specific DNA damage using a mitochondrial-targeted base modifying bacterial toxin, DarT. Following damage, we observe dynamic reorganization of mitochondrial networks, likely driven by mitochondrial dysfunction. Changes in the organization are associated with the loss of mtDNA, independent of mitophagy. Unexpectedly, perturbation to exonuclease function of mtDNA replicative polymerase, Mip1, results in rapid loss of mtDNA. Our data suggest that, under damage, partitioning of defective mtDNA and organelle are de-coupled, with emphasis on mitochondrial segregation independent of its DNA. Together, our work underscores the importance of genome maintenance on mitochondrial function, which can act as a modulator of organelle organization and segregation.

pH dependencies of glycolytic enzymes of yeast under in vivo-like assay conditions

Under carbon source transitions, the intracellular pH of Saccharomyces cerevisiae is subject to change. Dynamics in pH modulate the activity of the glycolytic enzymes, resulting in a change in glycolytic flux and ultimately cell growth. To understand how pH affects the global behavior of glycolysis and ethanol fermentation, we measured the activity of the glycolytic and fermentative enzymes in S. cerevisiae under in vivo-like conditions at different pH. We demonstrate that glycolytic enzymes exhibit differential pH dependencies, and optima, in the pH range observed during carbon source transitions. The forward reaction of GAPDH shows the highest decrease in activity, 83%, during a simulated feast/famine regime upon glucose removal (cytosolic pH drop from 7.1 to 6.4). We complement our biochemical characterization of the glycolytic enzymes by fitting the V_max to the progression curves of product formation or decay over time. The fitting analysis shows that the observed changes in enzyme activities require changes in V_max , but changes in K_m cannot be excluded. Our study highlights the relevance of pH as a key player in metabolic regulation and provides a large set of quantitative data that can be explored to improve our understanding of metabolism in dynamic environments.

DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis

Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-cell trajectories have prevented large-scale investigations to assess the dynamics of entry into replicative senescence in yeast. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. We show that DetecDiv can automatically reconstruct cellular replicative lifespans with high accuracy and performs similarly with various imaging platforms and geometries of microfluidic traps. In addition, this methodology provides comprehensive temporal cellular metrics using time-series classification and image semantic segmentation. Last, we show that this method can be further applied to automatically quantify the dynamics of cellular adaptation and real-time cell survival upon exposure to environmental stress. Hence, this methodology provides an all-in-one toolbox for high-throughput phenotyping for cell cycle, stress response, and replicative lifespan assays.

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.

Intron-mediated induction of phenotypic heterogeneity

Intragenic regions that are removed during maturation of the RNA transcript—introns—are universally present in the nuclear genomes of eukaryotes¹. The budding yeast, an otherwise intron-poor species, preserves two sets of ribosomal protein genes that differ primarily in their introns^2,3. Although studies have shed light on the role of ribosomal protein introns under stress and starvation^4–6, understanding the contribution of introns to ribosome regulation remains challenging. Here, by combining isogrowth profiling⁷ with single-cell protein measurements⁸, we show that introns can mediate inducible phenotypic heterogeneity that confers a clear fitness advantage. Osmotic stress leads to bimodal expression of the small ribosomal subunit protein Rps22B, which is mediated by an intron in the 5′ untranslated region of its transcript. The two resulting yeast subpopulations differ in their ability to cope with starvation. Low levels of Rps22B protein result in prolonged survival under sustained starvation, whereas high levels of Rps22B enable cells to grow faster after transient starvation. Furthermore, yeasts growing at high concentrations of sugar, similar to those in ripe grapes, exhibit bimodal expression of Rps22B when approaching the stationary phase. Differential intron-mediated regulation of ribosomal protein genes thus provides a way to diversify the population when starvation threatens in natural environments. Our findings reveal a role for introns in inducing phenotypic heterogeneity in changing environments, and suggest that duplicated ribosomal protein genes in yeast contribute to resolving the evolutionary conflict between precise expression control and environmental responsiveness⁹.

Experiments in yeast show that introns have a role in inducing phenotypic heterogeneity and that intron-mediated regulation of ribosomal proteins confers a fitness advantage by enabling yeast populations to diversify under nutrient-scarce conditions.

Multiple nutrient transporters enable cells to mitigate a rate-affinity tradeoff

Eukaryotic genomes often encode multiple transporters for the same nutrient. For example, budding yeast has 17 hexose transporters (HXTs), all of which potentially transport glucose. Using mathematical modelling, we show that transporters that use either facilitated diffusion or symport can have a rate-affinity tradeoff, where an increase in the maximal rate of transport decreases the transporter’s apparent affinity. These changes affect the import flux non-monotonically, and for a given concentration of extracellular nutrient there is one transporter, characterised by its affinity, that has a higher import flux than any other. Through encoding multiple transporters, cells can therefore mitigate the tradeoff by expressing those transporters with higher affinities in lower concentrations of nutrients. We verify our predictions using fluorescent tagging of seven HXT genes in budding yeast and follow their expression over time in batch culture. Using the known affinities of the corresponding transporters, we show that their regulation in glucose is broadly consistent with a rate-affinity tradeoff: as glucose falls, the levels of the different transporters peak in an order that mostly follows their affinity for glucose. More generally, evolution is constrained by tradeoffs. Our findings indicate that one such tradeoff often occurs in the cellular transport of nutrients.

From yeast to humans, cells often express multiple different types of transporters for the same nutrient, and it is puzzling why a single high-affinity transporter is not expressed instead. Here we initially use mathematical modelling to demonstrate that transporters facilitating diffusion and those powered by the proton motive force can both exhibit a rate-affinity tradeoff, for quite general conditions. A transporter with a higher affinity necessarily has a lower rate, and vice versa. The tradeoff implies that there is a range of nutrient concentrations for which a transporter, characterised by its affinity, has a higher import flux than any other transporter with a different affinity. To mitigate the tradeoff, genomes may therefore encode multiple different transporters, and cells that express each transporter in the concentrations where it imports best will uptake nutrients at higher rates. Consistently, we show that as cells of budding yeast consume glucose, they express five types of hexose transporters in an order that follows the transporters’ affinities.

Robustness: linking strain design to viable bioprocesses

Microbial cell factories are becoming increasingly popular for the sustainable production of various chemicals. Metabolic engineering has led to the design of advanced cell factories; however, their long-term yield, titer, and productivity falter when scaled up and subjected to industrial conditions. This limitation arises from a lack of robustness - the ability to maintain a constant phenotype despite the perturbations of such processes. This review describes predictable and stochastic industrial perturbations as well as state-of-the-art technologies to counter process variability. Moreover, we distinguish robustness from tolerance and discuss the potential of single-cell studies for improving system robustness. Finally, we highlight ways of achieving consistent and comparable quantification of robustness that can guide the selection of strains for industrial bioprocesses.

On the Ecological Significance of Phenotypic Heterogeneity in Microbial Populations Undergoing Starvation

To persist in variable environments, populations of microorganisms have to survive periods of starvation and be able to restart cell division in nutrient-rich conditions. Typically, starvation signals initiate a transition to a quiescent state in a fraction of individual cells, while the rest of the cells remain nonquiescent. It is widely believed that, while quiescent (Q) cells help the population to survive long starvation, the nonquiescent (NQ) cells are a side effect of imperfect transition. We analyzed the regrowth of starved monocultures of Q and NQ cells compared to that of mixed, heterogeneous cultures from simple and complex starvation environments. Our experiments, as well as mathematical modeling, demonstrate that Q monocultures benefit from better survival during long starvation and from a shorter lag phase after resupply of rich medium. However, when the starvation period is very short, the NQ monocultures outperform Q and mixed cultures due to their short lag phase. In addition, only NQ monocultures benefit from complex starvation environments, where nutrient recycling is possible. Our study suggests that phenotypic heterogeneity in starved populations could be a form of bet hedging that is adaptive when environmental determinants, such as the length of the starvation period, the length of the regrowth phase, and the complexity of the starvation environment, vary over time.

IMPORTANCE Nongenetic cell heterogeneity is present in glucose-starved yeast populations in the form of quiescent (Q) and nonquiescent (NQ) phenotypes. There is evidence that Q cells help the population survive long starvation. However, the role of the NQ cell type is not known, and it has been speculated that the NQ phenotype is just a side effect of the imperfect transition to the Q phenotype. Here, we show that, in contrast, there are ecological scenarios in which NQ cells perform better than monocultures of Q cells or naturally occurring mixed populations containing both Q and NQ cells. NQ cells benefit when the starvation period is very short and environmental conditions allow nutrient recycling during starvation. Our experimental and mathematical modeling results suggest a novel hypothesis: the presence of both Q and NQ phenotypes within starved yeast populations may reflect a form of bet hedging where different phenotypes provide fitness advantages depending on the environmental conditions.

Relationship between delayed luminescence emission and mitochondrial status in Saccharomyces cerevisiae

Delayed luminescence (DL) is gradually used in various detection of biological systems as a rapid detection technique, however, its biological mechanism was still not clear. In this study, a new model of DL detection system for liquid biological samples is established to investigate the DL emission of Saccharomyces cerevisiae cells cultured in different glucose concentrations. We analyzed the relationship between the DL emission and cell growth, cell vitality, mitochondrial morphology, mitochondrial DNA (mtDNA) copy number, adenosine triphosphate (ATP), oxygen consumption rate (OCR), as well as mitochondria membrane potential (MMP) in S. cerevisiae cells cultured with 0.01, 0.05, 0.15, 3, 10 and 20 g/L glucose respectively. It was found that the DL emission had strong correlation with mitochondrial morphology, OCR, and MMP. The results suggested that DL is an indicator of mitochondria status under different glucose supply conditions, and may be an effective method to detect mitochondrial metabolism related disorders.

High throughput single-cell genome sequencing gives insights into the generation and evolution of mosaic aneuploidy in Leishmania donovani

Leishmania, a unicellular eukaryotic parasite, is a unique model for aneuploidy and cellular heterogeneity, along with their potential role in adaptation to environmental stresses. Somy variation within clonal populations was previously explored in a small subset of chromosomes using fluorescence hybridization methods. This phenomenon, termed mosaic aneuploidy (MA), might have important evolutionary and functional implications but remains under-explored due to technological limitations. Here, we applied and validated a high throughput single-cell genome sequencing method to study for the first time the extent and dynamics of whole karyotype heterogeneity in two clonal populations of Leishmania promastigotes representing different stages of MA evolution in vitro. We found that drastic changes in karyotypes quickly emerge in a population stemming from an almost euploid founder cell. This possibly involves polyploidization/hybridization at an early stage of population expansion, followed by assorted ploidy reduction. During further stages of expansion, MA increases by moderate and gradual karyotypic alterations, affecting a defined subset of chromosomes. Our data provide the first complete characterization of MA in Leishmania and pave the way for further functional studies.

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.

The Evolutionary Ecology of Dormancy in Nature and in Cancer

Dormancy is an inactive period of an organism’s life cycle that permits it to survive through phases of unfavorable conditions in highly variable environments. Dormancy is not binary. There is a continuum of dormancy phenotypes that represent some degree of reduced metabolic activity (hypometabolism), reduced feeding, and reduced reproduction or proliferation. Similarly, normal cells and cancer cells exhibit a range of states from quiescence to long-term dormancy that permit survival in adverse environmental conditions. In contrast to organismal dormancy, which entails a reduction in metabolism, dormancy in cells (both normal and cancer) is primarily characterized by lack of cell division. “Cancer dormancy” also describes a state characterized by growth stagnation, which could arise from cells that are not necessarily hypometabolic or non-proliferative. This inconsistent terminology leads to confusion and imprecision that impedes progress in interdisciplinary research between ecologists and cancer biologists. In this paper, we draw parallels and contrasts between dormancy in cancer and other ecosystems in nature, and discuss the potential for studies in cancer to provide novel insights into the evolutionary ecology of dormancy.

Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics

Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose-inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose-arabinose co-feeding. For a wide range of glucose-arabinose co-feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.

Starvation induces shrinkage of the bacterial cytoplasm

Environmental fluctuations are a common challenge for single-celled organisms; enteric bacteria such as Escherichia coli experience dramatic changes in nutrient availability, pH, and temperature during their journey into and out of the host. While the effects of altered nutrient availability on gene expression and protein synthesis are well known, their impacts on cytoplasmic dynamics and cell morphology have been largely overlooked. Here, we discover that depletion of utilizable nutrients results in shrinkage of E. coli's inner membrane from the cell wall. Shrinkage was accompanied by an ∼17% reduction in cytoplasmic volume and a concurrent increase in periplasmic volume. Inner membrane retraction after sudden starvation occurred almost exclusively at the new cell pole. This phenomenon was distinct from turgor-mediated plasmolysis and independent of new transcription, translation, or canonical starvation-sensing pathways. Cytoplasmic dry-mass density increased during shrinkage, suggesting that it is driven primarily by loss of water. Shrinkage was reversible: upon a shift to nutrient-rich medium, expansion started almost immediately at a rate dependent on carbon source quality. A robust entry into and recovery from shrinkage required the Tol-Pal system, highlighting the importance of envelope coupling during shrinkage and recovery. Klebsiella pneumoniae also exhibited shrinkage when shifted to carbon-free conditions, suggesting a conserved phenomenon. These findings demonstrate that even when Gram-negative bacterial growth is arrested, cell morphology and physiology are still dynamic.

Nutrient Signaling, Stress Response, and Inter-organelle Communication Are Non-canonical Determinants of Cell Fate

Isogenic cells manifest distinct cellular fates for a single stress; however, the nongenetic mechanisms driving such fates remain poorly understood. Here, we implement a robust multi-channel live-cell imaging approach to uncover noncanonical factors governing cell fate. We show that in response to acute glucose removal (AGR), budding yeast undergoes distinct fates, becoming either quiescent or senescent. Senescent cells fail to resume mitotic cycles following glucose replenishment but remain responsive to nutrient stimuli. Whereas quiescent cells manifest starvation-induced adaptation, senescent cells display perturbed endomembrane trafficking and defective nucleus-vacuole junction (NVJ) expansion. Surprisingly, senescence occurs even in the absence of lipid droplets. Importantly, we identify the nutrient-sensing kinase Rim15 as a key biomarker predicting cell fates before AGR stress. We propose that isogenic yeast challenged with acute nutrient shortage contains determinants influencing post-stress fate and demonstrate that specific nutrient signaling, stress response, trafficking, and inter-organelle biomarkers are early indicators for long-term fate outcomes.