Bet hedging in yeast by heterogeneous, age-correlated expression of a stress protectant

Fungal morphogenesis

Morphogenesis in fungi is often induced by extracellular factors and executed by fungal genetic factors. Cell surface changes and alterations of the microenvironment often accompany morphogenetic changes in fungi. In this review, we will first discuss the general traits of yeast and hyphal morphotypes and how morphogenesis affects development and adaptation by fungi to their native niches, including host niches. Then we will focus on the molecular machinery responsible for the two most fundamental growth forms, yeast and hyphae. Last, we will describe how fungi incorporate exogenous environmental and host signals together with genetic factors to determine their morphotype and how morphogenesis, in turn, shapes the fungal microenvironment.

On the Nature and Evolutionary Impact of Phenotypic Robustness Mechanisms

Biologists have long observed that physiological and developmental processes are insensitive, or robust, to many genetic and environmental perturbations. A complete understanding of the evolutionary causes and consequences of this robustness is lacking. Recent progress has been made in uncovering the regulatory mechanisms that underlie environmental robustness in particular. Less is known about robustness to the effects of mutations, and indeed the evolution of mutational robustness remains a controversial topic. The controversy has spread to related topics, in particular the evolutionary relevance of cryptic genetic variation. This review aims to synthesize current understanding of robustness mechanisms and to cut through the controversy by shedding light on what is and is not known about mutational robustness. Some studies have confused mutational robustness with non-additive interactions between mutations (epistasis). We conclude that a profitable way forward is to focus investigations (and rhetoric) less on mutational robustness and more on epistasis.

How does evolution tune biological noise?

Part of molecular and phenotypic differences between individual cells, between body parts, or between individuals can result from biological noise. This source of variation is becoming more and more apparent thanks to the recent advances in dynamic imaging and single-cell analysis. Some of these studies showed that the link between genotype and phenotype is not strictly deterministic. Mutations can change various statistical properties of a biochemical reaction, and thereby the probability of a trait outcome. The fact that they can modulate phenotypic noise brings up an intriguing question: how may selection act on these mutations? In this review, we approach this question by first covering the evidence that biological noise is under genetic control and therefore a substrate for evolution. We then sequentially inspect the possibilities of negative, neutral, and positive selection for mutations increasing biological noise. Finally, we hypothesize on the specific case of H2A.Z, which was shown to both buffer phenotypic noise and modulate transcriptional efficiency.

Balanced trade-offs between alternative strategies shape the response of C. elegans reproduction to chronic heat stress

To ensure long-term reproductive success organisms have to cope with harsh environmental extremes. A reproductive strategy that simply maximizes offspring production is likely to be disadvantageous because it could lead to a catastrophic loss of fecundity under unfavorable conditions. To understand how an appropriate balance is achieved, we investigated reproductive performance of C. elegans under conditions of chronic heat stress. We found that following even prolonged exposure to temperatures at which none of the offspring survive, worms could recover and resume reproduction. The likelihood of producing viable offspring falls precipitously after exposure to temperatures greater than 28°C primarily due to sperm damage. Surprisingly, we found that worms that experienced higher temperatures can recover considerably better, provided they did not initiate ovulation. Therefore mechanisms controlling this process must play a crucial role in determining the probability of recovery. We show, however, that suppressing ovulation is only beneficial under relatively long stresses, whereas it is a disadvantageous strategy under shorter stresses of the same intensity. This is because the benefit of shutting down egg laying, and thus protecting the reproductive system, is negated by the cost associated with implementing this strategy--it takes considerable time to recover and produce offspring. We interpret these balanced trade-offs as a dynamic response of the C. elegans reproductive system to stress and an adaptation to life in variable and unpredictable conditions.

Whole Cell Modeling: From Single Cells to Colonies

A great deal of research over the last several years has focused on how the inherent randomness in movements and reactivity of biomolecules can give rise to unexpected large-scale differences in the behavior of otherwise identical cells. Our own research has approached this problem from two vantage points - a microscopic kinetic view of the individual molecules (nucleic acids, proteins, etc.) diffusing and interacting in a crowded cellular environment; and a broader systems-level view of how enzyme variability can give rise to well-defined metabolic phenotypes. The former led to the development of the Lattice Microbes software - a GPU-accelerated stochastic simulator for reaction-diffusion processes in models of whole cells; the latter to the development of a method we call population flux balance analysis (FBA). The first part of this article reviews the Lattice Microbes methodology, and two recent technical advances that extend the capabilities of Lattice Microbes to enable simulations of larger organisms and colonies. The second part of this article focuses on our recent population FBA study of Escherichia coli, which predicted variability in the usage of different metabolic pathways resulting from heterogeneity in protein expression. Finally, we discuss exciting early work using a new hybrid methodology that integrates FBA with spatially resolved kinetic simulations to study how cells compete and cooperate within dense colonies and consortia.

Silencing is noisy: population and cell level noise in telomere-adjacent genes is dependent on telomere position and sir2

Cell-to-cell gene expression noise is thought to be an important mechanism for generating phenotypic diversity. Furthermore, telomeric regions are major sites for gene amplification, which is thought to drive genetic diversity. Here we found that individual subtelomeric TLO genes exhibit increased variation in transcript and protein levels at both the cell-to-cell level as well as at the population-level. The cell-to-cell variation, termed Telomere-Adjacent Gene Expression Noise (TAGEN) was largely intrinsic noise and was dependent upon genome position: noise was reduced when a TLO gene was expressed at an ectopic internal locus and noise was elevated when a non-telomeric gene was expressed at a telomere-adjacent locus. This position-dependent TAGEN also was dependent on Sir2p, an NAD+-dependent histone deacetylase. Finally, we found that telomere silencing and TAGEN are tightly linked and regulated in cis: selection for either silencing or activation of a TLO-adjacent URA3 gene resulted in reduced noise at the neighboring TLO but not at other TLO genes. This provides experimental support to computational predictions that the ability to shift between silent and active chromatin states has a major effect on cell-to-cell noise. Furthermore, it demonstrates that these shifts affect the degree of expression variation at each telomere individually.

Epigenetic inheritance, epimutation, and the response to selection

There has been minimal theoretical exploration of the role of epigenetic variation in the response to natural selection. Using a population genetic model, I derive formulae that characterize the response of epigenetic variation to selection over multiple generations. Unlike genetic models in which mutation rates are assumed to be low relative to the strength of selection, the response to selection decays quickly due to a rapid lowering of parent-offspring epiallelic correlation. This effect is separate from the slowing response caused by a reduction in epigenetic variation. These results suggest that epigenetic variation may be less responsive to natural selection than is genetic variation, even in cases where levels of heritability appear similar.

An evolutionarily significant unicellular strategy in response to starvation in Dictyostelium social amoebae

The social amoeba Dictyostelium discoideum is widely studied for its multicellular development program as a response to starvation. Aggregates of up to 10 (6) cells form fruiting bodies containing (i) dormant spores (~80%) that can persist for months in the absence of nutrients, and (ii) dead stalk cells (~20%) that promote the dispersion of the spores towards nutrient-rich areas. It is often overlooked that not all cells aggregate upon starvation. Using a new quantitative approach based on time-lapse fluorescence microscopy and a low ratio of reporting cells, we have quantified this fraction of non-aggregating cells. In realistic starvation conditions, up to 15% of cells do not aggregate, which makes this third cell fate a significant component of the population-level response of social amoebae to starvation. Non-aggregating cells have an advantage over cells in aggregates since they resume growth earlier upon arrival of new nutrients, but have a shorter lifespan under prolonged starvation. We find that phenotypic heterogeneities linked to cell nutritional state bias the representation of cells in the aggregating vs. non-aggregating fractions, and thus affect population partitioning. Next, we report that the fraction of non-aggregating cells depends on genetic factors that regulate the timing of starvation, signal sensing efficiency and aggregation efficiency. In addition, interactions between clones in mixtures of non-isogenic cells affect the partitioning of each clone into both fractions. We further build a numerical model to test the evolutionary significance of the non-aggregating cell fraction. The partitioning of cells into aggregating and non-aggregating fractions is optimal in fluctuating environments with an unpredictable duration of starvation periods. Our study highlights the unicellular component of the response of social amoebae to starvation, and thus extends its evolutionary and ecological framework.

An evolutionarily significant unicellular strategy in response to starvation in Dictyostelium social amoebae

The social amoeba Dictyostelium discoideum is widely studied for its multicellular development program as a response to starvation. Aggregates of up to 10 (6) cells form fruiting bodies containing (i) dormant spores (~80%) that can persist for months in the absence of nutrients, and (ii) dead stalk cells (~20%) that promote the dispersion of the spores towards nutrient-rich areas. It is often overlooked that not all cells aggregate upon starvation. Using a new quantitative approach based on time-lapse fluorescence microscopy and a low ratio of reporting cells, we have quantified this fraction of non-aggregating cells. In realistic starvation conditions, up to 15% of cells do not aggregate, which makes this third cell fate a significant component of the population-level response of social amoebae to starvation. Non-aggregating cells have an advantage over cells in aggregates since they resume growth earlier upon arrival of new nutrients, but have a shorter lifespan under prolonged starvation. We find that phenotypic heterogeneities linked to cell nutritional state bias the representation of cells in the aggregating vs. non-aggregating fractions, and thus affect population partitioning. Next, we report that the fraction of non-aggregating cells depends on genetic factors that regulate the timing of starvation, signal sensing efficiency and aggregation efficiency. In addition, interactions between clones in mixtures of non-isogenic cells affect the partitioning of each clone into both fractions. We further build a numerical model to test the evolutionary significance of the non-aggregating cell fraction. The partitioning of cells into aggregating and non-aggregating fractions is optimal in fluctuating environments with an unpredictable duration of starvation periods. Our study highlights the unicellular component of the response of social amoebae to starvation, and thus extends its evolutionary and ecological framework.

Stochastic galactokinase expression underlies GAL gene induction in a GAL3 mutant of Saccharomyces cerevisiae

GAL1 and GAL3 are paralogous signal transducers that functionally inactivate Gal80p to activate the Gal4p-dependent transcriptional activation of GAL genes in Saccharomyces cerevisiae in response to galactose. Unlike a wild-type strain, the gal3∆ strain shows delayed growth kinetics as a result of the signaling function of GAL1. The mechanism ensuring that GAL1 is eventually expressed to turn on the GAL switch in the gal3∆ strain remains a paradox. Using galactose and histidine growth complementation assays, we demonstrate that 0.3% of the gal3∆ cell population responds to galactose. This is corroborated by flow cytometry and microscopic analysis. The galactose responders and nonresponders isolated from the galactose-adapted population attain the original bimodal state and this phenotype is found to be as hard wired as a genetic trait. Computational analysis suggests that the log-normal distribution in GAL4 synthesis can lead to bimodal expression of GAL80, resulting in the bimodal expression of GAL genes. Heterozygosity at the GAL80 but not at the GAL1, GAL2 or GAL4 locus alters the extent of bimodality of the gal3∆ cell population. We suggest that the asymmetric expression pattern between GAL1 and GAL3 results in the ability of S. cerevisiae to activate the GAL pathway by conferring nongenetic heterogeneity.

Heritability and genetic basis of protein level variation in an outbred population

The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the population’s average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance.

Population heterogeneity and dynamics in starter culture and lag phase adaptation of the spoilage yeast Zygosaccharomyces bailii to weak acid preservatives

The food spoilage yeast Zygosaccharomyces bailii shows great resistance to weak-acid preservatives, including sorbic acid (2, 4-hexadienoic acid). That extreme resistance was shown to be due to population heterogeneity, with a small sub-population of cells resistant to a variety of weak acids, probably caused by a lower internal pH reducing the uptake of all weak acids. In the present paper, it was found that resistant cells were extremely rare in exponential cultures, but increased by up to 8000-fold in stationary phase. Inoculation of media containing sorbic acid with a population of Z. bailii cells gave rise to what appeared to be a prolonged lag phase, suggesting adaptation to the conditions before the cells entered the period of exponential growth. However, the apparent lag phase caused by sorbic acid was largely due to the time required for the resistant sub-population to grow to detectable levels. The slow growth rate of the sub-population was identical to that of the final total population. The non-resistant bulk population remained viable for 3 days but had lost viability by 6 days and, during that time, there was no indication of any development of resistance in the bulk population. The sub-population growing in sorbic acid showed very high population diversity in colony size and internal pH. After removal of sorbic acid, the population rapidly reverted back to the normal, largely non-resistant, population distribution. The data presented suggest that a reevaluation of the lag phase in microbial batch culture is required, at least for the resistance of Z. bailii to sorbic acid. Furthermore, the significance of phenotypic diversity and heterogeneity in microbial populations is discussed more broadly with potential relevance to bacterial “persisters”, natural selection and evolution.

•

Extreme Z. bailii resistance to sorbic acid was due to population heterogeneity.

•

There was a massive rise in resistant cells after exponential growth.

•

Extended lag phase caused by weak acids was not an adaptive response.

•

Prolonged lag phase was due to population replacement.

•

Stress, starvation or weak acid, caused a rise in population diversity.

Collective decision-making in microbes

Microbes are intensely social organisms that routinely cooperate and coordinate their activities to express elaborate population level phenotypes. Such coordination requires a process of collective decision-making, in which individuals detect and collate information not only from their physical environment, but also from their social environment, in order to arrive at an appropriately calibrated response. Here, we present a conceptual overview of collective decision-making as it applies to all group-living organisms; we introduce key concepts and principles developed in the context of animal and human group decisions; and we discuss, with appropriate examples, the applicability of each of these concepts in microbial contexts. In particular, we discuss the roles of information pooling, control skew, speed vs. accuracy trade-offs, local feedbacks, quorum thresholds, conflicts of interest, and the reliability of social information. We conclude that collective decision-making in microbes shares many features with collective decision-making in higher taxa, and we call for greater integration between this fledgling field and other allied areas of research, including in the humanities and the physical sciences.

Budding yeast as a model organism to study the effects of age

Although a budding yeast culture can be propagated eternally, individual yeast cells age and eventually die. The detailed knowledge of this unicellular eukaryotic species as well as the powerful tools developed to study its physiology makes budding yeast an ideal model organism to study the mechanisms involved in aging. Considering both detrimental and positive aspects of age, we review changes occurring during aging both at the whole-cell level and at the intracellular level. The possible mechanisms allowing old cells to produce rejuvenated progeny are described in terms of accumulation and inheritance of aging factors. Based on the dynamic changes associated with age, we distinguish different stages of age: early age, during which changes do not impair cell growth; intermediate age, during which aging factors start to accumulate; and late age, which corresponds to the last divisions before death. For each aging factor, we examine its asymmetric segregation and whether it plays a causal role in aging. Using the example of caloric restriction, we describe how the aging process can be modulated at different levels and how changes in different organelles might interplay with each other. Finally, we discuss the beneficial aspects that might be associated with age.

Age-correlated stress resistance improves fitness of yeast: support from agent-based simulations

BACKGROUND

Resistance to stress is often heterogeneous among individuals within a population, which helps protect against intermittent stress (bet hedging). This is also the case for heat shock resistance in the budding yeast Saccharomyces cerevisiae. Interestingly, the resistance appears to be continuously distributed (vs. binary, switch-like) and correlated with replicative age (vs. random). Older, slower-growing cells are more resistant than younger, faster-growing ones. Is there a fitness benefit to age-correlated stress resistance?

RESULTS

Here this hypothesis is explored using a simple agent-based model, which simulates a population of individual cells that grow and replicate. Cells age by accumulating damage, which lowers their growth rate. They synthesize trehalose at a metabolic cost, which helps protect against heat shock. Proteins Tsl1 and Tps3 (trehalose synthase complex regulatory subunit TSL1 and TPS3) represent the trehalose synthesis complex and they are expressed using constant, age-dependent and stochastic terms. The model was constrained by calibration and comparison to data from the literature, including individual-based observations obtained using high-throughput microscopy and flow cytometry. A heterogeneity network was developed, which highlights the predominant sources and pathways of resistance heterogeneity. To determine the best trehalose synthesis strategy, model strains with different Tsl1/Tps3 expression parameters were placed in competition in an environment with intermittent heat shocks.

CONCLUSIONS

For high severities and low frequencies of heat shock, the winning strain used an age-dependent bet hedging strategy, which shows that there can be a benefit to age-correlated stress resistance. The study also illustrates the utility of combining individual-based observations and modeling to understand mechanisms underlying population heterogeneity, and the effect on fitness.

Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination

Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of “resistant” cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population “hedges” its “bet” on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a bla_CTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger “resistance”). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance—the gradually decreased colony-forming capability in the presence of antibiotic—was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses.

Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of “resistant” cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Lost in transition: start-up of glycolysis yields subpopulations of nongrowing cells

Cells need to adapt to dynamic environments. Yeast that fail to cope with dynamic changes in the abundance of glucose can undergo growth arrest. We show that this failure is caused by imbalanced reactions in glycolysis, the essential pathway in energy metabolism in most organisms. The imbalance arises largely from the fundamental design of glycolysis, making this state of glycolysis a generic risk. Cells with unbalanced glycolysis coexisted with vital cells. Spontaneous, nongenetic metabolic variability among individual cells determines which state is reached and, consequently, which cells survive. Transient ATP (adenosine 5'-triphosphate) hydrolysis through futile cycling reduces the probability of reaching the imbalanced state. Our results reveal dynamic behavior of glycolysis and indicate that cell fate can be determined by heterogeneity purely at the metabolic level.

Different levels of catabolite repression optimize growth in stable and variable environments

This study uses experimentally evolved brewer's yeasts to explore the costs and benefits of different nutrient-switching strategies when energy sources vary or remain constant.

Organisms respond to environmental changes by adapting the expression of key genes. However, such transcriptional reprogramming requires time and energy, and may also leave the organism ill-adapted when the original environment returns. Here, we study the dynamics of transcriptional reprogramming and fitness in the model eukaryote Saccharomyces cerevisiae in response to changing carbon environments. Population and single-cell analyses reveal that some wild yeast strains rapidly and uniformly adapt gene expression and growth to changing carbon sources, whereas other strains respond more slowly, resulting in long periods of slow growth (the so-called “lag phase”) and large differences between individual cells within the population. We exploit this natural heterogeneity to evolve a set of mutants that demonstrate how the frequency and duration of changes in carbon source can favor different carbon catabolite repression strategies. At one end of this spectrum are “specialist” strategies that display high rates of growth in stable environments, with more stringent catabolite repression and slower transcriptional reprogramming. The other mutants display less stringent catabolite repression, resulting in leaky expression of genes that are not required for growth in glucose. This “generalist” strategy reduces fitness in glucose, but allows faster transcriptional reprogramming and shorter lag phases when the cells need to shift to alternative carbon sources. Whole-genome sequencing of these mutants reveals that mutations in key regulatory genes such as HXK2 and STD1 adjust the regulation and transcriptional noise of metabolic genes, with some mutations leading to alternative gene regulatory strategies that allow “stochastic sensing” of the environment. Together, our study unmasks how variable and stable environments favor distinct strategies of transcriptional reprogramming and growth.

When microbes grow in a mixture of different nutrients, they repress the metabolism of nonpreferred nutrients such as complex carbohydrates until preferred nutrients, like glucose, are depleted. While this “catabolite repression” allows cells to use the most efficient nutrients first, it also comes at a cost because the switch to nonpreferred nutrients requires the de-repression of specific genes, and during this transition cells must temporarily stop dividing. Naively, one might expect that cells would activate the genes needed to resume growth in the new environment as quickly as possible. However, we find that the length of the growth lag that occurs when yeast cells are switched from the preferred carbon source glucose to alternative nutrients like maltose, galactose, or ethanol differs between wild yeast strains. By repeatedly alternating a slow-switching strain between glucose and maltose, we obtained mutants that show shortened lag phases. Although these variants can switch rapidly between carbon sources, they show reduced growth rates in environments where glucose is available continuously. Further analysis revealed that mutations in genes like HXK2 cause variations in the degree of catabolite repression, with some mutants showing leaky or stochastic maltose gene expression. Together, these results reveal how different gene regulation strategies can affect fitness in variable or stable environments.

Revisiting Mortimer's Genome Renewal Hypothesis: heterozygosity, homothallism, and the potential for adaptation in yeast

In diploid organisms, the frequency and nature of sexual cycles have a major impact on genome-wide patterns of heterozygosity. Recent population genomic surveys in the budding yeast, Saccharomyces cerevisiae, have revealed surprising levels of genomic heterozygosity in what has been traditionally considered a highly inbred organism. I review evidence and hypotheses regarding the generation, maintenance, and evolutionary consequences of genomic heterozygosity in S. cerevisiae. I propose that high levels of heterozygosity in S. cerevisiae, arising from population admixture due to human domestication, coupled with selfing during rare sexual cycles, can facilitate rapid adaptation to novel environments.

Persisters and beyond: mechanisms of phenotypic drug resistance and drug tolerance in bacteria

One of the challenges in clinical infectious diseases is the problem of chronic infections, which can require long durations of antibiotic treatment and often recur. An emerging explanation for the refractoriness of some infections to treatment is the existence of subpopulations of drug tolerant cells. While typically discussed as "persister" cells, it is becoming increasingly clear that there is significant heterogeneity in drug responses within a bacterial population and that multiple mechanisms underlie the emergence of drug tolerant and drug-resistant subpopulations. Many of these parallel mechanisms have been shown to affect drug susceptibility at the level of a whole population. Here we review mechanisms of phenotypic drug tolerance and resistance in bacteria with the goal of providing a framework for understanding the similarities and differences in these cells.

Epigenetic variation in asexually reproducing organisms

The role that epigenetic inheritance can play in adaptation may differ between sexuals and asexuals because (1) the dynamics of adaptation differ under sexual and asexual reproduction and the opportunities offered by epigenetic inheritance may affect these dynamics differently; and (2) in asexual reproduction epigenetic reprogramming mechanisms that are associated with meiosis can be bypassed, which could promote the buildup of epigenetic variation in asexuals. Here, we evaluate current evidence for an epigenetic contribution to adaptation in asexuals. We argue that two aspects of epigenetic variation should have particular relevance for asexuals, namely epigenetics-mediated phenotypic plasticity within and between generations, and heritable variation via stochastic epimutations. An evaluation of epigenetic reprogramming mechanisms suggests that some, but not all, forms of asexual reproduction enhance the likelihood of stable transmission of epigenetic marks across generations compared to sexual reproduction. However, direct tests of these predicted sexual-asexual differences are virtually lacking. Stable transmission of DNA methylation, transcriptomes, and phenotypes from parent to clonal offspring are demonstrated in various asexual species, and clonal genotypes from natural populations show habitat-specific DNA methylation. We discuss how these initial observations can be extended to demonstrate an epigenetic contribution to adaptation.

Population dynamics of metastable growth-rate phenotypes

Neo-Darwinian evolution has presented a paradigm for population dynamics built on random mutations and selection with a clear separation of time-scales between single-cell mutation rates and the rate of reproduction. Laboratory experiments on evolving populations until now have concentrated on the fixation of beneficial mutations. Following the Darwinian paradigm, these experiments probed populations at low temporal resolution dictated by the rate of rare mutations, ignoring the intermediate evolving phenotypes. Selection however, works on phenotypes rather than genotypes. Research in recent years has uncovered the complexity of genotype-to-phenotype transformation and a wealth of intracellular processes including epigenetic inheritance, which operate on a wide range of time-scales. Here, by studying the adaptation dynamics of genetically rewired yeast cells, we show a novel type of population dynamics in which the intracellular processes intervene in shaping the population structure. Under constant environmental conditions, we measure a wide distribution of growth rates that coexist in the population for very long durations (>100 generations). Remarkably, the fastest growing cells do not take over the population on the time-scale dictated by the width of the growth-rate distributions and simple selection. Additionally, we measure significant fluctuations in the population distribution of various phenotypes: the fraction of exponentially-growing cells, the distributions of single-cell growth-rates and protein content. The observed fluctuations relax on time-scales of many generations and thus do not reflect noisy processes. Rather, our data show that the phenotypic state of the cells, including the growth-rate, for large populations in a constant environment is metastable and varies on time-scales that reflect the importance of long-term intracellular processes in shaping the population structure. This lack of time-scale separation between the intracellular and population processes calls for a new framework for population dynamics which is likely to be significant in a wide range of biological contexts, from evolution to cancer.

Genome-wide consequences of deleting any single gene

Loss or duplication of chromosome segments can lead to further genomic changes associated with cancer. However, it is not known whether only a select subset of genes is responsible for driving further changes. To determine whether perturbation of any given gene in a genome suffices to drive subsequent genetic changes, we analyzed the yeast knockout collection for secondary mutations of functional consequence. Unlike wild-type, most gene knockout strains were found to have one additional mutant gene affecting nutrient responses and/or heat-stress-induced cell death. Moreover, independent knockouts of the same gene often evolved mutations in the same secondary gene. Genome sequencing identified acquired mutations in several human tumor suppressor homologs. Thus, mutation of any single gene may cause a genomic imbalance, with consequences sufficient to drive adaptive genetic changes. This complicates genetic analyses but is a logical consequence of losing a functional unit originally acquired under pressure during evolution.

Yeast metabolic and signaling genes are required for heat-shock survival and have little overlap with the heat-induced genes

Genome-wide gene-expression studies have shown that hundreds of yeast genes are induced or repressed transiently by changes in temperature; many are annotated to stress response on this basis. To obtain a genome-scale assessment of which genes are functionally important for innate and/or acquired thermotolerance, we combined the use of a barcoded pool of ~4,800 nonessential, prototrophic Saccharomyces cerevisiae deletion strains with Illumina-based deep-sequencing technology. As reported in other recent studies that have used deletion mutants to study stress responses, we observed that gene deletions resulting in the highest thermosensitivity generally are not the same as those transcriptionally induced in response to heat stress. Functional analysis of identified genes revealed that metabolism, cellular signaling, and chromatin regulation play roles in regulating thermotolerance and in acquired thermotolerance. However, for most of the genes identified, the molecular mechanism behind this action remains unclear. In fact, a large fraction of identified genes are annotated as having unknown functions, further underscoring our incomplete understanding of the response to heat shock. We suggest that survival after heat shock depends on a small number of genes that function in assessing the metabolic health of the cell and/or regulate its growth in a changing environment.

Ovarian cancer evolution through stochastic genome alterations: defining the genomic role in ovarian cancer

Ovarian cancer is the fifth leading cause of death among women worldwide. Characterized by complex etiology and multi-level heterogeneity, its origins are not well understood. Intense research efforts over the last decade have furthered our knowledge by identifying multiple risk factors that are associated with the disease. However, it is still unclear how genetic heterogeneity contributes to tumor formation, and more specifically, how genome-level heterogeneity acts as the key driving force of cancer evolution. Most current genomic approaches are based on 'average molecular profiling.' While effective for data generation, they often fail to effectively address the issue of high level heterogeneity because they mask variation that exists in a cell population. In this synthesis, we hypothesize that genome-mediated cancer evolution can effectively explain diverse factors that contribute to ovarian cancer. In particular, the key contribution of genome replacement can be observed during major transitions of ovarian cancer evolution including cellular immortalization, transformation, and malignancy. First, we briefly review major updates in the literature, and illustrate how current gene-mediated research will offer limited insight into cellular heterogeneity and ovarian cancer evolution. We next explain a holistic framework for genome-based ovarian cancer evolution and apply it to understand the genomic dynamics of a syngeneic ovarian cancer mouse model. Finally, we employ single cell assays to further test our hypothesis, discuss some predictions, and report some recent findings.

Adaptive evolution of an industrial strain of Saccharomyces cerevisiae for combined tolerance to inhibitors and temperature

INTRODUCTION

Development of industrial yeast strains with high tolerance towards the inhibitors released during biomass pretreatment is critical for bioethanol production. Combining this trait with increased thermotolerance would result in a more efficient production via Simultaneous Saccharification and Fermentation (SSF) as well as reduced cooling costs. The aim of the present work was to develop a yeast strain combining these traits.

RESULTS

Using a long-term adaptation strategy a stable Saccharomyces cerevisiae isolate (ISO12) was evolved from the industrial strain Ethanol Red (ER). ISO12, contrary to the parental strain, is capable of growing and fermenting the liquid fraction of non-detoxified spruce hydrolysate at 39°C with an ethanol yield of 0.38 g ethanol . g hexoses-1. In contrast with previous studies, the superior phenotype of ISO12 does not rely on higher reductase activities for furaldehyde inhibitor conversion, but rather on a higher thermotolerance. ISO12 shows a higher capacity to ferment hydrolysate at 39°C and higher viability during heat-shock at 52°C than ER. In the absence of inhibitors, however, both ER and ISO12 displayed similar growth phenotype at 39°C.

CONCLUSIONS

The evolved isolate ISO12 shows a superior phenotype than the parental strain ER when both stresses, temperature and inhibition by hydrolysate-derived compounds, are applied together. The results suggest that the presence of inhibitors depress the maximum temperature permissible for growth to a value below 39°C. As a result of the adaptation process and acquired improved thermotolerance, ISO12 is able to overcome this synergistic effect. Robust strains, such as ISO12, are interesting candidates for second generation ethanol production by SSF, as well as in tropical countries where fermentations at higher temperature can positively impact the production costs.

The use of chemostats in microbial systems biology

Cells regulate their rate of growth in response to signals from the external world. As the cell grows, diverse cellular processes must be coordinated including macromolecular synthesis, metabolism and ultimately, commitment to the cell division cycle. The chemostat, a method of experimentally controlling cell growth rate, provides a powerful means of systematically studying how growth rate impacts cellular processes - including gene expression and metabolism - and the regulatory networks that control the rate of cell growth. When maintained for hundreds of generations chemostats can be used to study adaptive evolution of microbes in environmental conditions that limit cell growth. We describe the principle of chemostat cultures, demonstrate their operation and provide examples of their various applications. Following a period of disuse after their introduction in the middle of the twentieth century, the convergence of genome-scale methodologies with a renewed interest in the regulation of cell growth and the molecular basis of adaptive evolution is stimulating a renaissance in the use of chemostats in biological research.

Natural sequence variants of yeast environmental sensors confer cell-to-cell expression variability

DNA polymorphisms that change cell-to-cell variability in gene expression are identified in a screen for ‘Probabilistic Trait Loci' in yeast. By modifying transmembrane transporter genes, these natural variants modulate intraclonal phenotypic diversification.

We mapped genetic loci affecting cell–cell variability in gene expression.

One variant enhanced both expression of a transporter and variability in a metabolic pathway.

A sequence change in another transporter also increased pathway variability.

The study invites to apprehend complex traits from a nondeterministic angle.

Living systems may have evolved probabilistic bet hedging strategies that generate cell-to-cell phenotypic diversity in anticipation of environmental catastrophes, as opposed to adaptation via a deterministic response to environmental changes. Evolution of bet hedging assumes that genotypes segregating in natural populations modulate the level of intraclonal diversity, which so far has largely remained hypothetical. Using a fluorescent P_met17-GFP reporter, we mapped four genetic loci conferring to a wild yeast strain an elevated cell-to-cell variability in the expression of MET17, a gene regulated by the methionine pathway. A frameshift mutation in the Erc1p transmembrane transporter, probably resulting from a release of laboratory strains from negative selection, reduced P_met17-GFP expression variability. At a second locus, cis-regulatory polymorphisms increased mean expression of the Mup1p methionine permease, causing increased expression variability in trans. These results demonstrate that an expression quantitative trait locus (eQTL) can simultaneously have a deterministic effect in cis and a probabilistic effect in trans. Our observations indicate that the evolution of transmembrane transporter genes can tune intraclonal variation and may therefore be implicated in both reactive and anticipatory strategies of adaptation.

Single cell heterogeneity: why unstable genomes are incompatible with average profiles

Multi-level heterogeneity is a fundamental but underappreciated feature of cancer. Most technical and analytical methods either completely ignore heterogeneity or do not fully account for it, as heterogeneity has been considered noise that needs to be eliminated. We have used single-cell and population-based assays to describe an instability-mediated mechanism where genome heterogeneity drastically affects cell growth and cannot be accurately measured using conventional averages. First, we show that most unstable cancer cell populations exhibit high levels of karyotype heterogeneity, where it is difficult, if not impossible, to karyotypically clone cells. Second, by comparing stable and unstable cell populations, we show that instability-mediated karyotype heterogeneity leads to growth heterogeneity, where outliers dominantly contribute to population growth and exhibit shorter cell cycles. Predictability of population growth is more difficult for heterogeneous cell populations than for homogenous cell populations. Since "outliers" play an important role in cancer evolution, where genome instability is the key feature, averaging methods used to characterize cell populations are misleading. Variances quantify heterogeneity; means (averages) smooth heterogeneity, invariably hiding it. Cell populations of pathological conditions with high genome instability, like cancer, behave differently than karyotypically homogeneous cell populations. Single-cell analysis is thus needed when cells are not genomically identical. Despite increased attention given to single-cell variation mediated heterogeneity of cancer cells, continued use of average-based methods is not only inaccurate but deceptive, as the "average" cancer cell clearly does not exist. Genome-level heterogeneity also may explain population heterogeneity, drug resistance, and cancer evolution.

Phenotypic heterogeneity is a selected trait in natural yeast populations subject to environmental stress

Populations of genetically uniform microorganisms exhibit phenotypic heterogeneity, where individual cells have varying phenotypes. Such phenotypes include fitness-determining traits. Phenotypic heterogeneity has been linked to increased population-level fitness in laboratory studies, but its adaptive significance for wild microorganisms in the natural environment is unknown. Here, we addressed this by testing heterogeneity in yeast isolates from diverse environmental sites, each polluted with a different principal contaminant, as well as from corresponding control locations. We found that cell-to-cell heterogeneity (in resistance to the appropriate principal pollutant) was prevalent in the wild yeast isolates. Moreover, isolates with the highest heterogeneity were consistently observed in the polluted environments, indicating that heterogeneity is positively related to survival in adverse conditions in the wild. This relationship with survival was stronger than for the property of mean resistance (IC(50)) of an isolate. Therefore, heterogeneity could be the major determinant of microbial survival in adverse conditions. Indeed, growth assays indicated that isolates with high heterogeneities had a significant competitive advantage during stress. Analysis of yeasts after cultivation for ≥ 500 generations additionally showed that high heterogeneity evolved as a heritable trait during stress. The results showed that environmental stress selects for wild microorganisms with high levels of phenotypic heterogeneity.

Genetic variation and the evolution of epigenetic regulation

Epigenetic variation has been observed in a range of organisms, leading to questions of the adaptive significance of this variation. In this study, we present a model to explore the ecological and genetic conditions that select for epigenetic regulation. We find that the rate of temporal environmental change is a key factor controlling the features of this evolution. When the environment fluctuates rapidly between states with different phenotypic optima, epigenetic regulation may evolve but we expect to observe low transgenerational inheritance of epigenetic states, whereas when this fluctuation occurs over longer time scales, regulation may evolve to generate epigenetic states that are inherited faithfully for many generations. In all cases, the underlying genetic variation at the epigenetically regulated locus is a crucial factor determining the range of conditions that allow for evolution of epigenetic mechanisms.

Genetic and nongenetic determinants of cell growth variation assessed by high-throughput microscopy

In microbial populations, growth initiation and proliferation rates are major components of fitness and therefore likely targets of selection. We used a high-throughput microscopy assay, which enables simultaneous analysis of tens of thousands of microcolonies, to determine the sources and extent of growth rate variation in the budding yeast (Saccharomyces cerevisiae) in different glucose environments. We find that cell growth rates are regulated by the extracellular concentration of glucose as proposed by Monod (1949), but that significant heterogeneity in growth rates is observed among genetically identical individuals within an environment. Yeast strains isolated from different geographic locations and habitats differ in their growth rate responses to different glucose concentrations. Inheritance patterns suggest that the genetic determinants of growth rates in different glucose concentrations are distinct. In addition, we identified genotypes that differ in the extent of variation in growth rate within an environment despite nearly identical mean growth rates, providing evidence that alleles controlling phenotypic variability segregate in yeast populations. We find that the time to reinitiation of growth (lag) is negatively correlated with growth rate, yet this relationship is strain-dependent. Between environments, the respirative activity of individual cells negatively correlates with glucose abundance and growth rate, but within an environment respirative activity and growth rate show a positive correlation, which we propose reflects differences in protein expression capacity. Our study quantifies the sources of genetic and nongenetic variation in cell growth rates in different glucose environments with unprecedented precision, facilitating their molecular genetic dissection.

Measuring competitive fitness in dynamic environments

Most yeast genes are dispensable for optimal growth in laboratory cultures. However, this apparent lack of fitness contribution is difficult to reconcile with the theory of natural selection. Here we use stochastic modeling to show that environmental fluctuations can select for a genetic mechanism that does not affect growth in static laboratory environments. We then present a novel experimental platform for measuring the fitness levels of specific genotypes in fluctuating environments. We test this platform by monitoring a mixed culture of two yeast strains that differ in their ability to respond to changes in carbon source yet exhibit the same fitness level in static conditions. When the sugar in the growth medium was switched between galactose and glucose, the wild-type strain gained a growth advantage over the mutant strain. Interestingly, both our computational and experimental results show that the strength of the adaptive advantage conveyed by the wild-type genotype depends on the total number of carbon source switches, not on the frequency of these fluctuations. Our results illustrate the selective power of environmental fluctuations on seemingly slight phenotypic differences in cellular response dynamics and underscore the importance of dynamic processes in the evolution of species.

The details in the distributions: why and how to study phenotypic variability

Phenotypic variability is present even when genetic and environmental differences between cells are reduced to the greatest possible extent. For example, genetically identical bacteria display differing levels of resistance to antibiotics, clonal yeast populations demonstrate morphological and growth-rate heterogeneity, and mouse blastomeres from the same embryo have stochastic differences in gene expression. However, the distributions of phenotypes present among isogenic organisms are often overlooked; instead, many studies focus on population aggregates such as the mean. The details of these distributions are relevant to major questions in diverse fields, including the evolution of antimicrobial-drug and chemotherapy resistance. We review emerging experimental and statistical techniques that allow rigorous analysis of phenotypic variability and thereby may lead to advances across the biological sciences.

Adaptive noise

In biology, noise implies error and disorder and is therefore something which organisms may seek to minimize and mitigate against. We argue that such noise can be adaptive. Recent studies have shown that gene expression can be noisy, noise can be genetically controlled, genes and gene networks vary in how noisy they are and noise generates phenotypic differences among genetically identical cells. Such phenotypic differences can have fitness benefits, suggesting that evolution can shape noise and that noise may be adaptive. For example, gene networks can generate bistable states resulting in phenotypic diversity and switching among individual cells of a genotype, which may be a bet hedging strategy. Here, we review the sources of noise in gene expression, the extent to which noise in biological systems may be adaptive and suggest that applying evolutionary rigour to the study of noise is necessary to fully understand organismal phenotypes.

Differential regulation of white-opaque switching by individual subunits of Candida albicans mediator

The multisubunit eukaryotic Mediator complex integrates diverse positive and negative gene regulatory signals and transmits them to the core transcription machinery. Mutations in individual subunits within the complex can lead to decreased or increased transcription of certain subsets of genes, which are highly specific to the mutated subunit. Recent studies suggest a role for Mediator in epigenetic silencing. Using white-opaque morphological switching in Candida albicans as a model, we have shown that Mediator is required for the stability of both the epigenetic silenced (white) and active (opaque) states of the bistable transcription circuit driven by the master regulator Wor1. Individual deletions of eight C. albicans Mediator subunits have shown that different Mediator subunits have dramatically diverse effects on the directionality, frequency, and environmental induction of epigenetic switching. Among the Mediator deletion mutants analyzed, only Med12 has a steady-state transcriptional effect on the components of the Wor1 circuit that clearly corresponds to its effect on switching. The MED16 and MED9 genes have been found to be among a small subset of genes that are required for the stability of both the white and opaque states. Deletion of the Med3 subunit completely destabilizes the opaque state, even though the Wor1 transcription circuit is intact and can be driven by ectopic expression of Wor1. The highly impaired ability of the med3 deletion mutant to mate, even when Wor1 expression is ectopically induced, reveals that the activation of the Wor1 circuit can be decoupled from the opaque state and one of its primary biological consequences.

Single-cell phenomics reveals intra-species variation of phenotypic noise in yeast

Background

Most quantitative measures of phenotypic traits represent macroscopic contributions of large numbers of cells. Yet, cells of a tissue do not behave similarly, and molecular studies on several organisms have shown that regulations can be highly stochastic, sometimes generating diversified cellular phenotypes within tissues. Phenotypic noise, defined here as trait variability among isogenic cells of the same type and sharing a common environment, has therefore received a lot of attention. Given the potential fitness advantage provided by phenotypic noise in fluctuating environments, the possibility that it is directly subjected to evolutionary selection is being considered. For selection to act, phenotypic noise must differ between contemporary genotypes. Whether this is the case or not remains, however, unclear because phenotypic noise has very rarely been quantified in natural populations.

Results

Using automated image analysis, we describe here the phenotypic diversity of S. cerevisiae morphology at single-cell resolution. We profiled hundreds of quantitative traits in more than 1,000 cells of 37 natural strains, which represent various geographical and ecological origins of the species. We observed abundant trait variation between strains, with no correlation with their ecological origin or population history. Phenotypic noise strongly depended on the strain background. Noise variation was largely trait-specific (specific strains showing elevated noise for subset of traits) but also global (a few strains displaying elevated noise for many unrelated traits).

Conclusions

Our results demonstrate that phenotypic noise does differ quantitatively between natural populations. This supports the possibility that, if noise is adaptive, microevolution may tune it in the wild. This tuning may happen on specific traits or by varying the degree of global phenotypic buffering.

Evolution in microbes

This review presents a broad survey of experimental microbial evolution, covering diverse topics including trade-offs, epistasis, fluctuating conditions, spatial dynamics, cooperation, aging, and stochastic switching. Emphasis is placed on examples that highlight key conceptual points or address theoretical predictions. Experimental evolution is discussed from two points of view. First, population trajectories are described as adaptive walks on a fitness landscape, whose genetic structure can be probed by experiments. Second, populations are viewed from a physiological perspective, and their nongenetic heterogeneity is examined. Bringing together these two viewpoints remains a major challenge for the future.

Aneuploidy underlies a multicellular phenotypic switch

Although microorganisms are traditionally used to investigate unicellular processes, the yeast Saccharomyces cerevisiae has the ability to form colonies with highly complex, multicellular structures. Colonies with the "fluffy" morphology have properties reminiscent of bacterial biofilms and are easily distinguished from the "smooth" colonies typically formed by laboratory strains. We have identified strains that are able to reversibly toggle between the fluffy and smooth colony-forming states. Using a combination of flow cytometry and high-throughput restriction-site associated DNA tag sequencing, we show that this switch is correlated with a change in chromosomal copy number. Furthermore, the gain of a single chromosome is sufficient to switch a strain from the fluffy to the smooth state, and its subsequent loss to revert the strain back to the fluffy state. Because copy number imbalance of six of the 16 S. cerevisiae chromosomes and even a single gene can modulate the switch, our results support the hypothesis that the state switch is produced by dosage-sensitive genes, rather than a general response to altered DNA content. These findings add a complex, multicellular phenotype to the list of molecular and cellular traits known to be altered by aneuploidy and suggest that chromosome missegregation can provide a quick, heritable, and reversible mechanism by which organisms can toggle between phenotypes.

Diversity training for signal transduction: leveraging cell-to-cell variability to dissect cellular signaling, differentiation and death

Populations of 'identical' cells are rarely truly identical. Even when in the same state of differentiation, isogenic cells may vary in expression of key signaling regulators, activate signal transduction at different thresholds, and consequently respond heterogeneously to a given stimulus. Here, we review how new experimental and analytical techniques are suited to connect these different levels of variability, quantitatively mapping the effects of cell-to-cell variability on cellular decision-making. In particular, we summarize how this helps classify signaling regulators according to the impact of their variability on biological functions. We further discuss how variability can also be leveraged to shed light on the molecular mechanisms regulating cellular signaling, from the individual cell to the population of cells as a whole.

A novel single-cell screening platform reveals proteome plasticity during yeast stress responses

Unprecedented proteome plasticity in response to stress in yeast is revealed using a novel screening platform that allows tracking of protein localization and abundance at single-cell resolution.

Uncovering the mechanisms underlying robust responses of cells to stress is crucial for our understanding of cellular physiology. Indeed, vast amounts of data have been collected on transcriptional responses in Saccharomyces cerevisiae. However, only a handful of pioneering studies describe the dynamics of proteins in response to external stimuli, despite the fact that regulation of protein levels and localization is an essential part of such responses. Here we characterized unprecedented proteome plasticity by systematically tracking the localization and abundance of 5,330 yeast proteins at single-cell resolution under three different stress conditions (DTT, H₂O₂, and nitrogen starvation) using the GFP-tagged yeast library. We uncovered a unique “fingerprint” of changes for each stress and elucidated a new response arsenal for adapting to radical environments. These include bet-hedging strategies, organelle rearrangement, and redistribution of protein localizations. All data are available for download through our online database, LOQATE (localization and quantitation atlas of yeast proteome).

Evolutionary systems biology: what it is and why it matters

Evolutionary systems biology (ESB) is a rapidly growing integrative approach that has the core aim of generating mechanistic and evolutionary understanding of genotype-phenotype relationships at multiple levels. ESB's more specific objectives include extending knowledge gained from model organisms to non-model organisms, predicting the effects of mutations, and defining the core network structures and dynamics that have evolved to cause particular intracellular and intercellular responses. By combining mathematical, molecular, and cellular approaches to evolution, ESB adds new insights and methods to the modern evolutionary synthesis, and offers ways in which to enhance its explanatory and predictive capacities. This combination of prediction and explanation marks ESB out as a research manifesto that goes further than its two contributing fields. Here, we summarize ESB via an analysis of characteristic research examples and exploratory questions, while also making a case for why these integrative efforts are worth pursuing.

Use of agent-based modeling to explore the mechanisms of intracellular phosphorus heterogeneity in cultured phytoplankton

There can be significant intraspecific individual-level heterogeneity in the intracellular P of phytoplankton, which can affect the population-level growth rate. Several mechanisms can create this heterogeneity, including phenotypic variability in various physiological functions (e.g., nutrient uptake rate). Here, we use modeling to explore the contribution of various mechanisms to the heterogeneity in phytoplankton grown in a laboratory culture. An agent-based model simulates individual cells and their intracellular P. Heterogeneity is introduced by randomizing parameters (e.g., maximum uptake rate) of daughter cells at division. The model was calibrated to observations of the P quota of individual cells of the centric diatom Thalassiosira pseudonana, which were obtained using synchrotron X-ray fluorescence (SXRF). A number of simulations, with individual mechanisms of heterogeneity turned off, then were performed. Comparison of the coefficient of variation (CV) of these and the baseline simulation (i.e., all mechanisms turned on) provides an estimate of the relative contribution of these mechanisms. The results show that the mechanism with the largest contribution to variability is the parameter characterizing the maximum intracellular P, which, when removed, results in a CV of 0.21 compared to a CV of 0.37 with all mechanisms turned on. This suggests that nutrient/element storage capabilities/mechanisms are important determinants of intrapopulation heterogeneity.

A model for generating several adaptive phenotypes from a single genetic event: Saccharomyces cerevisiae GAP1 as a potential bet-hedging switch

Microbial populations adapt to environmental fluctuations through random switching of fitness-related traits in individual cells. This increases the likelihood that a subpopulation will be adaptive in a future milieu. However, populations are particularly challenged when several environment factors change simultaneously. We suggest that a population can rapidly adapt to multiple environmental changes if individual members stochastically flip a hub-switch that controls a set of adaptive phenotypes in a single event. This mechanism of coupling phenotypic outcomes via a hub-switch can protect a population against large fluctuations in size. Here we report that the general amino acid transporter Gap1 is a potential hub-switch. The GAP1 gene is flanked by two direct repeats that can lead to GAP1 deletions (∆gap1) and a self-replicating GAP1 circle. Thus, an isogenic GAP1 population can differentiate into two variant, reversible genotypes, ∆gap1 or GAP1 (circle). These subpopulations have different phenotypic advantages. A ∆gap1 population has a selective advantage on allantoin or ammonium as a nitrogen source and high stress tolerance. Advantages of the GAP1 population include amino acid uptake, fast energy recruitment by trehalose mobilization, and in some cases, adherent biofilm growth. Our proposed model of a hub-switch locus enhances the bet-hedging model of population dynamics.

Towards metagenome-scale models for industrial applications--the case of Lactic Acid Bacteria

We review the uses and limitations of modelling approaches that are in use in the field of Lactic Acid Bacteria (LAB). We describe recent developments in model construction and computational methods, starting from application of such models to monocultures. However, since most applications in food biotechnology involve complex nutrient environments and mixed cultures, we extend the scope to discuss developments in modelling such complex systems. With metagenomics and meta-functional genomics data becoming available, the developments in genome-scale community models are discussed. We conclude that exploratory tools are available and useful, but truly predictive mechanistic models will remain a major challenge in the field.

Biocompatible microfabrication of 3D isolation chambers for targeted confinement of individual cells and their progeny

We describe a technique to physically isolate single/individual cells from their surrounding environment by fabricating three-dimensional microchambers around selected cells under biocompatible conditions. Isolation of targeted cells is achieved via rapid fabrication of protein hydrogels from a biocompatible precursor solution using multiphoton lithography, an intrinsically 3D laser direct write microfabrication technique. Cells remain chemically accessible to environmental cues enabling their propagation into well-defined, high density populations. We demonstrate this methodology on gram negative (E. coli), gram positive (S. aureus), and eukaryotic (S. cerevisiae) cells. The opportunities to confine viable, single/individual-cells and small populations within user-defined microenvironments afforded by this approach should facilitate the study of cell behaviors across multiple generations.