How yeast re-programmes its transcriptional profile in response to different nutrient impulses.

BACKGROUND: A microorganism is able to adapt to changes in its physicochemical or nutritional environment and this is crucial for its survival. The yeast, Saccharomyces cerevisiae, has developed mechanisms to respond to such environmental changes in a rapid and effective manner; such responses may demand a widespread re-programming of gene activity. The dynamics of the re-organization of the cellular activities of S. cerevisiae in response to the sudden and transient removal of either carbon or nitrogen limitation has been studied by following both the short- and long-term changes in yeast's transcriptomic profiles. RESULTS: The study, which spans timescales from seconds to hours, has revealed the hierarchy of metabolic and genetic regulatory switches that allow yeast to adapt to, and recover from, a pulse of a previously limiting nutrient. At the transcriptome level, a glucose impulse evoked significant changes in the expression of genes concerned with glycolysis, carboxylic acid metabolism, oxidative phosphorylation, and nucleic acid and sulphur metabolism. In ammonium-limited cultures, an ammonium impulse resulted in the significant changes in the expression of genes involved in nitrogen metabolism and ion transport. Although both perturbations evoked significant changes in the expression of genes involved in the machinery and process of protein synthesis, the transcriptomic response was delayed and less complex in the case of an ammonium impulse. Analysis of the regulatory events by two different system-level, network-based approaches provided further information about dynamic organization of yeast cells as a response to a nutritional change. CONCLUSIONS: The study provided important information on the temporal organization of transcriptomic organization and underlying regulatory events as a response to both carbon and nitrogen impulse. It has also revealed the importance of a long-term dynamic analysis of the response to the relaxation of a nutritional limitation to understand the molecular basis of the cells' dynamic behaviour.The authors greatly acknowledge the financial support for the research from the BBSRC (Grant BB/C505140/1 to SGO), and the travel grants for DD kindly provided by the Research Council of Turkey (TUBITAK) through the BDP programme and the Turkish State Planning Organization DPT09K120520. The research was also financially supported by Bogazici University Research Fund through Project No 631 and TUBITAK through Project No 106M444. Further support came from European Commission though the Coordination Action Project YSBN (Contract No.018942 to both BK and SGO) and UNICELLSYS Collaborative Project (No. 201142 to SGO)

CLUSTERnGO: a user-defined modelling platform for two-stage clustering of time-series data.

MOTIVATION: Simple bioinformatic tools are frequently used to analyse time-series datasets regardless of their ability to deal with transient phenomena, limiting the meaningful information that may be extracted from them. This situation requires the development and exploitation of tailor-made, easy-to-use and flexible tools designed specifically for the analysis of time-series datasets. RESULTS: We present a novel statistical application called CLUSTERnGO, which uses a model-based clustering algorithm that fulfils this need. This algorithm involves two components of operation. Component 1 constructs a Bayesian non-parametric model (Infinite Mixture of Piecewise Linear Sequences) and Component 2, which applies a novel clustering methodology (Two-Stage Clustering). The software can also assign biological meaning to the identified clusters using an appropriate ontology. It applies multiple hypothesis testing to report the significance of these enrichments. The algorithm has a four-phase pipeline. The application can be executed using either command-line tools or a user-friendly Graphical User Interface. The latter has been developed to address the needs of both specialist and non-specialist users. We use three diverse test cases to demonstrate the flexibility of the proposed strategy. In all cases, CLUSTERnGO not only outperformed existing algorithms in assigning unique GO term enrichments to the identified clusters, but also revealed novel insights regarding the biological systems examined, which were not uncovered in the original publications. AVAILABILITY AND IMPLEMENTATION: The C++ and QT source codes, the GUI applications for Windows, OS X and Linux operating systems and user manual are freely available for download under the GNU GPL v3 license at http://www.cmpe.boun.edu.tr/content/CnG. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.This work was supported by the Turkish State Planning Organization [DPT09K120520 to B.K.]; the Bogazici University Research Fund [10A05D4 to B.K., 08A506 to B.K., 6882-12A01D5 to A.T.C.]; TUBITAK [106M444 to B.K., 110E292 to A.T.C.], Biotechnology and Biological Sciences Research Council [BRIC2.2 grant BB/K011138/1 to S.G.O.]; and EU 7th Framework Programme [BIOLEDGE Contract No: 289126 to S.G.O.].This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/bioinformatics/btv53

Multi-Omics Analysis of Multiple Glucose-Sensing Receptor Systems in Yeast

The yeast Saccharomyces cerevisiae has long been used to produce alcohol from glucose and other sugars. While much is known about glucose metabolism, relatively little is known about the receptors and signaling pathways that indicate glucose availability. Here, we compare the two glucose receptor systems in S. cerevisiae. The first is a heterodimer of transporter-like proteins (transceptors), while the second is a seven-transmembrane receptor coupled to a large G protein (Gpa2) that acts in coordination with two small G proteins (Ras1 and Ras2). Through comprehensive measurements of glucose-dependent transcription and metabolism, we demonstrate that the two receptor systems have distinct roles in glucose signaling: the G-protein-coupled receptor directs carbohydrate and energy metabolism, while the transceptors regulate ancillary processes such as ribosome, amino acids, cofactor and vitamin metabolism. The large G-protein transmits the signal from its cognate receptor, while the small G-protein Ras2 (but not Ras1) integrates responses from both receptor pathways. Collectively, our analysis reveals the molecular basis for glucose detection and the earliest events of glucose-dependent signal transduction in yeast

Collective analysis of multiple high-throughput gene expression datasets

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonModern technologies have resulted in the production of numerous high-throughput biological datasets. However, the pace of development of capable computational methods does not cope with the pace of generation of new high-throughput datasets. Amongst the most popular biological high-throughput datasets are gene expression datasets (e.g. microarray datasets). This work targets this aspect by proposing a suite of computational methods which can analyse multiple gene expression datasets collectively. The focal method in this suite is the unification of clustering results from multiple datasets using external specifications (UNCLES). This method applies clustering to multiple heterogeneous datasets which measure the expression of the same set of genes separately and then combines the resulting partitions in accordance to one of two types of external specifications; type A identifies the subsets of genes that are consistently co-expressed in all of the given datasets while type B identifies the subsets of genes that are consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets. This contributes to the types of questions which can addressed by computational methods because existing clustering, consensus clustering, and biclustering methods are inapplicable to address the aforementioned objectives. Moreover, in order to assist in setting some of the parameters required by UNCLES, the M-N scatter plots technique is proposed. These methods, and less mature versions of them, have been validated and applied to numerous real datasets from the biological contexts of budding yeast, bacteria, human red blood cells, and malaria. While collaborating with biologists, these applications have led to various biological insights. In yeast, the role of the poorly-understood gene CMR1 in the yeast cell-cycle has been further elucidated. Also, a novel subset of poorly understood yeast genes has been discovered with an expression profile consistently negatively correlated with the well-known ribosome biogenesis genes. Bacterial data analysis has identified two clusters of negatively correlated genes. Analysis of data from human red blood cells has produced some hypotheses regarding the regulation of the pathways producing such cells. On the other hand, malarial data analysis is still at a preliminary stage. Taken together, this thesis provides an original integrative suite of computational methods which scrutinise multiple gene expression datasets collectively to address previously unresolved questions, and provides the results and findings of many applications of these methods to real biological datasets from multiple contexts.National Institute for Health Research (NIHR) and the Brunel College of Engineering, Design and Physical Science

Utilisation d'un fermenteur continu multi-étagé pour la compréhension des mécanismes d'adaptation de la levure à des ajouts d'azote en conditions oenologiques

Nous avons mis au point un fermenteur continu multi-étagé (MSCF) dans le but de reproduire les conditions de la fermentation alcoolique en conditions œnologiques. Ce bioréacteur permet de maintenir les levures dans un milieu stable et contrôlé tout en découplant la croissance et la phase stationnaire. Le système offre donc la possibilité d'obtenir des levures non croissantes dans un milieu de composition stable. Dans un premier temps, nous avons validé la pertinence du MSCF pour reproduire les conditions de fermentation du batch, par approche intégrée (des paramètres cinétiques, des métabolites intra et exo cellulaire et de l'expression génique). Nous avons ensuite utilisé ce bioréacteur pour étudier les mécanismes d'adaptation métabolique des microorganismes suite à un ajout d'azote, pratique largement répandue en œnologie. Plusieurs résultats originaux ont été obtenus concernant, notamment, la réorganisation du cycle TCA, le transport des sources azotées et la synthèse des alcools supérieurs et esters. La fiabilité de l'outil mis au point et l'originalité des données obtenues ouvrent des perspectives à l'utilisation du MSCF pour la compréhension du métabolisme et des mécanismes d'adaptation des levures.We set up a multi-stage continuous fermentor (MSCF) to mimic the conditions of alcoholic fermentation. In this bioreactor, the yeasts are in a steady and well controlled state representative of the growth and stationary phases of the batch. The ability of the MSCF to reproduce batch fermentation was assessed using an integrated approach (measurement of kinetic parameters, intra and exo-cellular metabolites and gene expression). We then used the MSCF to study the impact of nitrogen supplementation performed during the stationary phase, on yeasts metabolism. Several original results were obtained, concerning the TCA cycle, the transport of nitrogenous sources and the synthesis of higher alcohols and esters. This work points out the interest of using the MSCF to assess the effect of medium perturbations during alcoholic fermentation, especially during the stationary phase. More generally, the accuracy of the MSCF and the originality of the data obtained open new prospects for a better understanding of yeasts metabolism and regulation mechanisms.MONTPELLIER-SupAgro La Gaillarde (341722306) / SudocSudocFranceF

Proteomic analysis of Saccharomyces cerevisiae grown on glucose or glycerol

The goal of this research was to use two-dimensional electrophoresis to examine changes in abundance of enzymes of the glycolytic pathway in the yeast Saccharomyces cerevisiae grown on carbon sources that support either fermentation to ethanol or oxidative metabolism. Large-scale profiling of protein abundances (expression proteomics) often detects changes in protein abundance between physiological states. Such changes in enzyme abundance are often interpreted as evidence of metabolic change although most textbooks emphasise control of enzyme activities not enzyme amount. Two-dimensional difference gel electrophoresis (2DDIGE) was therefore used to examine differences in protein abundance between S. cerevisiae strain BY4741 grown on either glucose (fermentation) or glycerol. Growth on 2% glucose, but not on glycerol, was accompanied by extensive production of ethanol. Doubling times for growth were 2 h 5 min in glucose and 9 h 41 min in glycerol. Conditions for extraction and two-dimensional electrophoresis of proteins were established. One hundred and seventy nine proteins were identified by MALDI mass spectrometry of tryptic digests of protein spots excised from Coomassie stained gels. All of the enzymes for conversion of glucose to ethanol, except for the second enzyme of glycolysis phosphoglucose isomerase, were identified using twodimensional electrophoresis of 100 μg of protein from cells grown on 2% glucose. Identification of proteins excised from the DIGE gels was more challenging, partly because of the lower amount of protein. Eight of the proteins that showed statistically significant differences in abundance (≥ 2-fold, p ≤ 0.01) between glucose and glycerol were identified by mass spectrometry of proteins excised from the 2DDIGE gels, and a further 18 varying proteins were matched to proteins identified from the Coomassie stained gels. Of these total 26 identified or matched proteins, subunits of five of the enzymes for conversion of glucose to ethanol were more abundant from the fermentative cells grown on glucose. The more abundant glycolytic enzymes were phosphofructokinase 2, fructose-1,6-bisphosphate aldolase, triosephosphate isomerase and enolase, plus pyruvate decarboxylase that was required for conversion of the glycolytic product pyruvate to acetaldehyde. The alcohol dehydrogenases Adh1 and Adh4 that convert acetaldehyde to ethanol were detected but did not vary significantly between growth on glucose or glycerol. The results confirmed that in this case changes in abundance of some enzymes were consistent with the altered metabolic output. Future studies should examine whether changes in the abundance and activity of these enzymes are responsible for the differences in metabolism

Carbonaceous Resource Recovery Through Flexible Engineered Biological Systems and Platforms - Process Engineering and Systems Biology

This dissertation research represents efforts towards development of organic waste fueled bio-refineries, capable of achieving circular economy and resource recovery through conversion of the embedded chemical energy and nutrients present in the organic waste, into biochemical products of commercial value. The specific objectives were: 1. Evaluation of anaerobic fermentation derived volatile fatty acid as a recovery platform: Anaerobic fermentation of organic wastes is a cost and energy efficient way of recovering the inherent chemical energy potential associated with such waste streams. Additionally, since the carbon is recovered in the form of short chain volatile fatty acids (VFA), the high solubility in water results in fairly easy recovery and handling than the gas phase endpoints (methane, hydrogen). It also opens up the possibility to biologically or chemically redirect those VFA to high-value endpoints. Anaerobic fermentation of such streams to recover VFA also results in reducing the organic strength of the waste streams, thereby achieving waste treatment and sanitation in a far more sustainable manner than the existing practices of the organic waste management and wastewater treatment, which were inherently designed with the goal of removal of contaminants and are focused upon sequential removal of those undesirable ‘contaminants’ including carbon (energy), nitrogen and phosphorus. Therefore, the focus of this review was to evaluate the feasibility of anaerobic fermentation derived volatile fatty acids as a substrate for potential bio-conversion into products of high commercial value. The key advantage of such a pipeline would be to intrinsically couple applications such as sanitation or wastewater treatment with resource recovery in an energetically and economically neutral or positive manner. The pipeline consists of two major steps, namely (i) Production and recovery of carbon in the form of volatile fatty acids through anaerobic fermentation and, (ii) Biological or chemical conversion of VFA to other endpoints including but not limited to biofuels, bio-plastics, butanol, organic acids and solvents and dihydrogen. 2. Microbial conversion of synthetic and food waste-derived volatile fatty acids to lipids: Lipid accumulation in the oleaginous yeast Cryptococcus albidus was evaluated using mixtures of volatile fatty acids (VFA) as substrates. In general, batch growth under nitrogen limitation led to higher lipid accumulation using synthetic VFA. During batch growth, an initial COD:N ratio of 25:1 mg COD:mg-N led to maximum intracellular lipid accumulation (28.33±0.74% g/g dry cell weight), which is the maximum reported for C. albidus using VFA as the carbon source, without compromising growth kinetics. At this feed COD:N ratio, chemostat cultures fed with synthetic VFA yielded statistically similar intracellular lipid content as batch cultures (29.88±1.92%, g/g). However, batch cultures fed with VFA produced from the fermentation of food waste, yielded a lower lipid content (14.99±0.06%, g/g). The lipid composition obtained with synthetic and food-waste-derived VFA was similar to commercial biodiesel feedstock. We therefore demonstrate the feasibility of linking biochemical waste treatment and biofuel production using VFA as key intermediates. 3. Genome sequencing of oleaginous yeast Cryptococcus albidus and evaluation of its genetic and biotechnological potential: We reported the complete draft genome sequence of Cryptococcus albidus var. albidus, an oleaginous yeast, which can utilize various organic carbon sources for lipid synthesis. The basidiomycetous oleaginous yeast has been gaining popularity as a non-conventional yeast with the ability to metabolize and transform diverse organic substrates. The 24.8 Mb genome of C. albidus was sequenced and the metabolic reconstruction revealed that C. albidus contains several essential pathways for metabolism of various carbon sources (including glucose, sucrose, glycerol, acetic, propionic and butyric acids), accumulation of carbon compounds (tri-acyl glycerol (TAGs) and glycogen) and for assimilation of various nitrogen (ammonia, nitrate, nitrite, and urea) and sulfur sources (sulfate, sulfite, thiosulfate). It is also capable of secreting enzymes of industrial significance. Here, we presented a comprehensive overview of the biology and biotechnology of C. albidus, specifically focusing on its microbial physiology, metabolic pathways and its potential for production of commercially and industrially important chemicals. 4. Evaluation of the global transcriptomic and proteomic responses of the Cryptococcus albidus to nitrogen limitation: ‘Non-ideal’ carbon sources could be an ideal substrate for economically feasible lipid production by oleaginous yeast Cryptococcus albidus; however, there have been no studies thus far, on biochemical pathways governing its oleaginity and metabolism. Here, we report for the first time, a comprehensive account of the transcriptome and proteome level changes in continuous cultures of Cryptococcus albidus in response to nitrogen limitation. Proteome and differential gene expression data revealed a tight co-regulation of nitrogen and carbon metabolism, wherein nitrogen limitation resulted in a complete redistribution of carbon flux throughout the cellular processes, including nitrogenous compound recycling, autophagy and cessation of nucleic acid and ribosome biosynthesis. Lipid accumulation by C. albidus does not seem to involve transcriptional regulation but is a passive consequence of carbon flux redistribution during nitrogen limitation. This study therefore, provides a valuable resource to understand oleaginity and metabolism of alternate carbon sources by C. albidus and provides opportunities for metabolic re-engineering of its lipid production pathways. 5. Organic waste fueled biorefineries: future perspectives on production of chemicals of industrial significance from volatile fatty acids: The focus of this review was to propose alternate bio-based pipelines for recovery and conversion of organic waste streams into high value commercial products, using VFA as central precursors for further aerobic/anaerobic carbon cycling. Herein, we present various pathways, microorganisms, culture conditions and current status of bio-based production of certain building-block chemicals such as adipic acid, butanol, organic acids such as citric, malic and succinic acids. These chemicals have the highest potential to be economically produced from VFA since the pathways for their bioconversion either exist natively or have been metabolically engineered. Nevertheless further research would be needed to reduce the costs and enhance productivity. In conclusion, this dissertation represents the first attempt at a holistic evaluation of a VFA based resource recovery platform. In first phase, microbial conversion of volatile fatty acids into lipids by the yeast C. albidus was evaluated and nitrogen limitation was identified as the inducer of lipogenesis in C. albidus through operation of batch and chemostat cultures. Next, entire genome was sequenced and transcriptome and proteome level changes were evaluated in conjunction to understand the metabolic basis of nitrogen-mediated oleaginity in C. albidus. This genomic and the comparative transcriptome and proteome data is expected to help further elucidate factors driving lipid accumulation in C. albidus and contribute toward bioprocess development and optimization for engineered lipid production from ‘waste’ streams. Finally, the feasibility of microbial conversion of VFA into several other bio-based chemicals of commercial value was also evaluated

Psr1p interacts with SUN/sad1p and EB1/mal3p to establish the bipolar spindle

Regular Abstracts - Sunday Poster Presentations: no. 382During mitosis, interpolar microtubules from two spindle pole bodies (SPBs) interdigitate to create an antiparallel microtubule array for accommodating numerous regulatory proteins. Among these proteins, the kinesin-5 cut7p/Eg5 is the key player responsible for sliding apart antiparallel microtubules and thus helps in establishing the bipolar spindle. At the onset of mitosis, two SPBs are adjacent to one another with most microtubules running nearly parallel toward the nuclear envelope, creating an unfavorable microtubule configuration for the kinesin-5 kinesins. Therefore, how the cell organizes the antiparallel microtubule array in the first place at mitotic onset remains enigmatic. Here, we show that a novel protein psrp1p localizes to the SPB and plays a key role in organizing the antiparallel microtubule array. The absence of psr1+ leads to a transient monopolar spindle and massive chromosome loss. Further functional characterization demonstrates that psr1p is recruited to the SPB through interaction with the conserved SUN protein sad1p and that psr1p physically interacts with the conserved microtubule plus tip protein mal3p/EB1. These results suggest a model that psr1p serves as a linking protein between sad1p/SUN and mal3p/EB1 to allow microtubule plus ends to be coupled to the SPBs for organization of an antiparallel microtubule array. Thus, we conclude that psr1p is involved in organizing the antiparallel microtubule array in the first place at mitosis onset by interaction with SUN/sad1p and EB1/mal3p, thereby establishing the bipolar spindle.postprin