Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

BACKGROUND: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. RESULTS: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. CONCLUSION: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress

Modelling the regulation of thermal adaptation in Candida albicans, a major fungal pathogen of humans

Peer reviewedPublisher PD

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

<p>Abstract</p> <p>Background</p> <p>Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization.</p> <p>Results</p> <p>Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity.</p> <p>Conclusions</p> <p>Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.</p

Minimization of Biosynthetic Costs in Adaptive Gene Expression Responses of Yeast to Environmental Changes

Yeast successfully adapts to an environmental stress by altering physiology and fine-tuning metabolism. This fine-tuning is achieved through regulation of both gene expression and protein activity, and it is shaped by various physiological requirements. Such requirements impose a sustained evolutionary pressure that ultimately selects a specific gene expression profile, generating a suitable adaptive response to each environmental change. Although some of the requirements are stress specific, it is likely that others are common to various situations. We hypothesize that an evolutionary pressure for minimizing biosynthetic costs might have left signatures in the physicochemical properties of proteins whose gene expression is fine-tuned during adaptive responses. To test this hypothesis we analyze existing yeast transcriptomic data for such responses and investigate how several properties of proteins correlate to changes in gene expression. Our results reveal signatures that are consistent with a selective pressure for economy in protein synthesis during adaptive response of yeast to various types of stress. These signatures differentiate two groups of adaptive responses with respect to how cells manage expenditure in protein biosynthesis. In one group, significant trends towards downregulation of large proteins and upregulation of small ones are observed. In the other group we find no such trends. These results are consistent with resource limitation being important in the evolution of the first group of stress responses

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

<p>Abstract</p> <p>Background</p> <p>Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements.</p> <p>Results</p> <p>We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer-approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in <it>Saccharomyces cerevisiae</it>. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast <it>Saccharomyces cerevisiae </it>to heat shock</p> <p>Conclusion</p> <p>Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.</p

Determination and characterization of genes involved in toxic mechanisms of the prymnesiophyte Prymnesium parvum

This thesis represents a study of the ecophysiology and toxicity of the prymnesiophyte Prymnesium parvum. The first aim was to investigate changes in the relative toxicity of P. parvum following a series of physiological shock treatments, meant to simulate environmental conditions under which harmful blooms of this species have been observed. As blooms of this haptophyte often occur in dynamic coastal brackish water systems, Prymnesium parvum is noted for its physiological flexibility, which may contribute to providing a competitive advantage over other coexisting species. Due to the unconfirmed nature of the compounds involved in toxigenic processes, two bioassays were employed to characterize changes in lytic capacity (extracellular vs. intracellular). These bioassays are considered physiologically relevant, as observed icthyotoxicity occurs through lysis of the gill cell membranes, rendering the fish unable to perform gas-exchange processes and obtain oxygen. Additionally, the gene expression of three polyketide synthase genes (PKS) were analyzed via quantitative PCR (qPCR), based on current chemical characterizations of toxic compounds produced by P. parvum. Low salinity and high irradiance were observed to alter the lytic effects of P. parvum on the sensitive cryptophyte Rhodomonas salina and erythrocytes. Furthermore, these two shock treatments were found to increase the transcript copy number in selected PKS genes, suggesting a possible correlation between toxicity and the PKS biosynthetic pathway. Allelochemical mediation has been suggested to affect competition and predatory relationships associated with formation of P. parvum blooms. As interactions between species are an integral part of understanding plankton ecology, interspecific interactions between P. parvum and three coexisting species were accordingly investigated. Combining bioassays with a functional genomic approach allowed differential characterization of cell-cell contact vs. waterborne cues depending on the organism with which incubated. A unique response on both the levels of toxicity, gene expression profile as well as PKS transcript copy number to the potential predator Oxhyrris marina suggest a fundamentally different type of interaction between the two species. Additionally, a dose-response time series experiment showed that changes in gene expression and toxicity did not occur immediately in P. parvum, rather after 60-90 minutes. Such a response by P. parvum may in fact signify a co-evolutionarily adaptive defense. Finally, examination of the effects of phosphorous limitation and low salinity stress on the gene expression profile and lytic capacity showed that the combination of these two stressors induces secretion or extracellular transport of toxic substances to a much higher degree than either stressor individually. Whether this observation is due to changes in membrane integrity due to homeostatic processes needs further research. The pattern of gene expression, however, revealed regulation of among others genes associated with active cellular transport processes, suggesting that maintenance of intracellular-extracellular homeostasis may play a role in the observed toxicity. In summary, these studies integrate the concepts of ecophysiology and functional genomics, providing a useful platform for further research regarding environmental factors associated with the toxicity of P. parvum. As functional genomic methods become more accessible, such approaches illustrate their potential application within the field of harmful algal research

Functional genomic insights into cellular processes related to harmful bloom formation in ichthyotoxic prymnesiophytes

Not much information is available about the genetic background of growth and toxicity- related processes in toxic Haptophyta species. The aim of my thesis was to contribute to better understanding of these issues using functional and comparative genomic approaches with the ichthyotoxic prymnesiophytes Chrysochromulina polylepis and Prymnesium parvum. In particular, I explored different gene-expression profiling methods in order to monitor the transcriptomic responses in these species to different environmental conditions. Through the sequencing of a cDNA library, a transcriptomic database (Expressed Sequence Tag library) was established for both prymnesiophyte species. Approximately 2900 and 6300 contigs were found in the Chrysochromulina polylepis and Prymnesium parvum datasets, respectively. The sequences were annotated and compared to similar data sets available from other Haptophyta species (Pavlova lutherii, Isochrysis galbana and Emiliania huxleyi). This analysis revealed a `core set` of approx. 1500 genes which were found in all Haptophyta species investigated in this study. Moreover, 67 and 362 genes were present only in C. polylepis and P. parvum, respectively. The physiological background and cellular regulation of synthesis and liberation of Chrysochromulina and Prymnesium toxin(s) is still poorly understood, but the involvement of PKS genes in the biosynthesis of certain compounds is likely. The presence of the conserved ketosynthase (KS) domains - an obligatory part of PKS genes were shown in both species, represented by fourteen and four copies in C. polylepis and P. parvum, respectively. In order to indirectly test the hypothesis invoking a role of PKS genes in toxin biosynthesis, the correlation between toxicity and PKS gene expression was monitored in both species. The observed positive correlation strengthens the hypothesis on the involvement of PKS genes in toxin production C. polylepis as well as in P. parvum. A gene expression microarray was generated based on the EST data originating from P. parvum, and this tool was used to monitor gene-expression changes during growth in nutrient replete and phosphorus (P)- or nitrogen (N)-deprived P. parvum cells. In accord with previously published data, elevated intracellular toxicity was observed in P-deprived cells, whereas it did not change in N-depleted or nutrient replete cells. As a response to P limitation, the upregulation of different genes related to transport and acquisition of phosphate could be observed. On the other hand, N limitation did not lead to such a clear effect on the gene expression level, since most genes likely involved in the uptake, storage and transport of N sources were not upregulated. Utilizing the tools of ecophysiology and functional genomics we identified gene-expression patterns indicative of physiological (nutrient, toxicity) and growth status of C. polylepis and P. parvum. With reference to this data set, knowledge about cellular processes in toxic Prymnesiophyceae species was expanded considerably, and pointed the way forward for incorporation of functional genomic approaches to determining regulatory factors involved in prymnesiophyte bloom dynamics through gene expression studies

Impact of high sugar content on metabolism and physiology of indigenous yeasts

This PhD project is part of an ARC Training Centre for Innovative Wine Production larger initiative to tackle the main challenges for the Australian wine industry. In particular, the aim is to address the implication of the increasing trend of sugar accumulation in ripe grapes that consequently results in high sugar musts and high ethanol wines. These increase the risk of sluggish and stuck fermentation, especially when only the indigenous microflora of yeast is exploited. At the beginning of fermentation, yeast cells must coordinate genome expression rapidly in response to external changes to maintain competitive fitness and cell survival. Understanding how cells modulate their adaptation strategies can be the key to predicting their capacity to survive in a harsh environment and consequently be able to influence wine composition. This project aims to give strategic advice to deal with fermentations by studying non-conventional yeast physiology in response to high sugar must and correlating it with growth and metabolism. Chapter 2 compares T. delbrueckii and S. cerevisiae oenological traits at a molecular level. The mechanisms behind the metabolic differences that exist between these two species were inspected using Next Generation Sequencing technology (ILLUMINA) and analysed by assembling RNA transcriptomes. In Chapter 3 two Australian indigenous yeast species genomes were sequenced with the newest Next Generation Sequencing (NGS) technology, Nanopore MinION. Chapter 4 further analyzed the global short-term stress adaptive response to grape must, implementing the technique previously used. The results, discussed in Chapter 5, summarize the improvements in high-throughput data analysis and reveal the genomic and physiological differences of these wine-related species.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 201