Exometabolic and transcriptional response in relation to phenotype and gene copy number in respiration-related deletion mutants of S. cerevisiae.

The transcriptional and metabolic impact of deleting one or both copies of a respiration-related gene has been studied in glucose-limited chemostats. Integration of literature information on phenotype with our exometabolome and transcriptome data enabled the identification of novel relationships between gene copy number, transcriptional regulation and phenotype. We found that the effect of complete respiratory deficiency on transcription was limited to downregulation of genes involved in oxidoreductase activity and iron assimilation. Partial respiratory deficiency had no significant impact on gene transcription. Changes in the copy number of two transcription-factor genes, HAP4 and MIG1, had a major impact on genes involved in mitochondrial function. Regulation of respiratory chain components encoded in the nucleus and mitochondria appears to be divided between Hap4p and Oxa1p, respectively. Similarly, repression of respiration may be imposed by the action of Mig1p and Mba1p on nuclear and mitochondrial gene expression, respectively. However, it is not clear whether Oxa1p and Mba1p regulate mitochondrial gene expression via their interaction with mitochondrial ribosomes or by some indirect means. The phenotype of nuclear petite mutants may not simply be due to the absence of respiration; e.g. Oxa1p or Bcs1p may play a role in the regulation of ribosome assembly in the nucleolus. Integration between respiration and cell growth may also result from the action of a single transcription factor. Thus, Hap4p targets genes that are required for respiration and for fitness in nutrient-limited conditions. This suggests that Hap4p may enable cells to adapt to nutrient limitation as well as diauxy.

Integration of metabolic modeling and phenotypic data in evaluation and improvement of ethanol production using respiration-deficient mutants of Saccharomyces cerevisiae.

Flux balance analysis and phenotypic data were used to provide clues to the relationships between the activities of gene products and the phenotypes resulting from the deletion of genes involved in respiratory function in Saccharomyces cerevisiae. The effect of partial or complete respiratory deficiency on the ethanol production and growth characteristics of hap4Delta/hap4Delta, mig1Delta/mig1Delta, qdr3Delta/qdr3Delta, pdr3Delta/pdr3Delta, qcr7Delta/qcr7Delta, cyt1Delta/cyt1Delta, and rip1Delta/rip1Delta mutants grown in microaerated chemostats was investigated. The study provided additional evidence for the importance of the selection of a physiologically relevant objective function, and it may improve quantitative predictions of exchange fluxes, as well as qualitative estimations of changes in intracellular fluxes. Ethanol production was successfully predicted by flux balance analysis in the case of the qdr3Delta/qdr3Delta mutant, with maximization of ethanol production as the objective function, suggesting an additional role for Qdr3p in respiration. The absence of similar changes in estimated intracellular fluxes in the qcr7Delta/qcr7Delta mutant compared to the rip1Delta/rip1Delta and cyt1Delta/cyt1Delta mutants indicated that the effect of the deletion of this subunit of complex III was somehow compensated for. Analysis of predicted flux distributions indicated self-organization of intracellular fluxes to avoid NAD(+)/NADH imbalance in rip1Delta/rip1Delta and cyt1Delta/cyt1Delta mutants, but not the qcr7Delta/qcr7Delta mutant. The flux through the glycerol efflux channel, Fps1p, was estimated to be zero in all strains under the investigated conditions. This indicates that previous strategies for improving ethanol production, such as the overexpression of the glutamate synthase gene GLT1 in a GDH1 deletion background or deletion of the glycerol efflux channel gene FPS1 and overexpression of GLT1, are unnecessary in a respiration-deficient background.

Effect of carbon source perturbations on transcriptional regulation of metabolic fluxes in Saccharomyces cerevisiae.

BACKGROUND: Control effective flux (CEF) of a reaction is the weighted sum of all fluxes through that reaction, derived from elementary flux modes (EFM) of a metabolic network. Change in CEFs under different environmental conditions has earlier been proven to be correlated with the corresponding changes in the transcriptome. Here we use this to investigate the degree of transcriptional regulation of fluxes in the metabolism of Saccharomyces cerevisiae. We do this by quantifying correlations between changes in CEFs and changes in transcript levels for shifts in carbon source, i.e. between the fermentative carbon source glucose and nonfermentative carbon sources like ethanol, acetate, and lactate. The CEF analysis is based on a simple stoichiometric model that includes reactions of the central carbon metabolism and the amino acid metabolism. RESULTS: The effect of the carbon shift on the metabolic fluxes was investigated for both batch and chemostat cultures. For growth on glucose in batch (respiro-fermentative) cultures, EFMs with no by-product formation were removed from the analysis of the CEFs, whereas those including any by-products (ethanol, glycerol, acetate, succinate) were omitted in the analysis of growth on glucose in chemostat (respiratory) cultures. This resulted in improved correlations between CEF changes and transcript levels. A regression correlation coefficient of 0.60 was obtained between CEF changes and gene expression changes in the central carbon metabolism for the analysis of 5 different perturbations. Out of 45 data points there were no more than 6 data points deviating from the correlation. Additionally, up- or down-regulation of at least 75% of the genes were in qualitative agreement with the CEF changes for all perturbations studied. CONCLUSION: The analysis indicates that changes in carbon source are associated with a high degree of hierarchical regulation of metabolic fluxes in the central carbon metabolism as the change in fluxes are correlating directly with the change in transcript levels of genes encoding their corresponding enzymes. For amino acid biosynthesis there was, however, not found to exist a similar correlation, and this may point to either post-transcriptional and/or metabolic regulation, or be due to the absence of a direct perturbation on the amino acid pathways in these experiments.

Understanding signaling in yeast: Insights from network analysis.

Reconstruction of protein interaction networks that represent groups of proteins contributing to the same cellular function is a key step towards quantitative studies of signal transduction pathways. Here we present a novel approach to reconstruct a highly correlated protein interaction network and to identify previously unknown components of a signaling pathway through integration of protein-protein interaction data, gene expression data, and Gene Ontology annotations. A novel algorithm is designed to reconstruct a highly correlated protein interaction network which is composed of the candidate proteins for signal transduction mechanisms in yeast Saccharomyces cerevisiae. The high efficiency of the reconstruction process is proved by a Receiver Operating Characteristic curve analysis. Identification and scoring of the possible linear pathways enables reconstruction of specific sub-networks for glucose-induction signaling and high osmolarity MAPK signaling in S. cerevisiae. All of the known components of these pathways are identified together with several new "candidate" proteins, indicating the successful reconstructions of two model pathways involved in S. cerevisiae. The integrated approach is hence shown useful for (i) prediction of new signaling pathways, (ii) identification of unknown members of documented pathways, and (iii) identification of network modules consisting of a group of related components that often incorporate the same functional mechanism.

Annotation of unknown yeast ORFs by correlation analysis of microarray data and extensive literature searches.

Changes in the expression of genes were used to elucidate the metabolic pathways and regulatory mechanisms that respond to environmental or genetic modifications. Results from previously published chemostat datasets were merged with novel data generated in the present study. ORFs displaying significant changes in expression that correlated with those of other ORFs were analysed using GO mapping tools and supplemented by literature information. The strategy developed was used to propose annotations for ORFs of unknown function. The following ORFs were assigned functions as a result of this study: YMR090w, YGL157w, YGR243w, YLR327c, YER121w, YFR017c, YGR067c, YKL187c, YGR236c (SPG1), YMR107w (SPG4), YMR206w, YER067w, YJL103c, YNL175C (NOP13) YJL200C, YDL070C (FMP16) and YGR173W.

Integrative investigation of metabolic and transcriptomic data.

BACKGROUND: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. RESULTS: Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures--PLS) using PLS toolbox in Matlab. CONCLUSION: The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

A simple structured model for biomass and extracellular enzyme production with recombinant Saccharomyces cerevisiae YPB-G.

A simple structured model is proposed for simulating batch cultivation data on growth, substrate utilization, and heterologous enzyme production of recombinant Saccharomyces cerevisiae YPB-G. The enzyme is a fusion protein displaying alpha-amylase and glucoamylase activities. Cell growth is modulated mainly by intracellular substrate and ethanol concentrations. Intracellular substrate concentration is evaluated by means of the extracellular substrate and biomass concentrations. Extracellular alpha-amylase and glucoamylase activities are taken to depend on biomass concentration. The nine parameters of the proposed model are determined using nonlinear estimation techniques, and the model is validated against experiments not used in parameter determination. The model developed simulates glucose consumption, cell mass, alpha-amylase and glucoamylase production in a batch system. Simulation and experimental results are found to be in good agreement.

High-level production of TaqI restriction endonuclease by three different expression systems in Escherichia coli cells using the T7 phage promoter.

Three different expression systems were constructed for the high-level production of TaqI restriction endonuclease in recombinant Escherichia colicells. In system [R], the TaqI endonuclease gene was cloned and expressed under the control of the strong T7 RNA polymerase promoter. To protect cellular DNA, methylase protection was provided by constitutive co-expression of TaqI methylase activity either by cloning the TaqI methylase gene on a second plasmid (system [R,M]) or by constructing a recombinant plasmid harboring both the endonuclease and methylase genes (system [R+M]). In batch shake flasks containing complex media, co-expression of the methylase gene in systems [R,M] and [R+M] resulted in a 2- and 3-fold increase in volumetric productivity over system [R], yielding activities of 250x10(6) U l(-1) and 350x10(6) U l(-1), which were 28 and 39 times higher than the data in the literature, respectively. Under controlled bioreactor conditions in chemically defined medium, co-expression of methylase activity greatly improved the yield and specific TaqI endonuclease productivity of the recombinant cells, and reduced acetic acid excretion levels. System [R,M] is preferable for high expression levels at longer operation periods, while system [R+M] is well-suited for high expression levels in short-term bioreactor operation.

Modeling of recombinant yeast cells: reduction of phase space.

The mechanism of starch fermentation by recombinant Saccharomyces cerevisiae in batch reactor is studied. Experiments were carried in the presence and absence of oxygen, with different initial starch concentrations. A variety of data concerning biotic and abiotic phases are collected. Nonlinear data analysis techniques are used to determine the block diagram of the system under study. Data analysis and processing reported here, are believed to form a basis in further work in structured modeling of biological systems, recombinant yeast cultures in particular.

Auditory profile analysis of harmonic signals.

Spectral shape discrimination for harmonic complexes with 100-, 200-, or 400-Hz fundamental was investigated in two sets of experiments. In the first set, the signal was an increment in a single component of an otherwise equal-amplitude complex. The results of these experiments showed nearly a 30-dB increase in thresholds as the signal frequencies increased from 1000 to 5000 Hz. A transformation of data based on the assumption that the critical detection quantity is the change in the level in a critical band centered at the signal frequency was applied to remove the effects of the nonsignal components. The corrected thresholds have a bowl-like shape similar to that seen in studies of spectral shape discrimination of stimuli with components equally spaced on a logarithmic frequency scale. Additional experiments examined the effects of the number of components in the complex and the relative phase of the components of the harmonic complex. In the second set of experiments, the effects of local masking were examined either by increasing the level of several adjacent components, or by removing nonsignal components near a single signal component. Again, the results with harmonic signals are similar to those obtained with components spaced at equal intervals on a logarithmic frequency scale, if one calculates the increment in the level produced in a critical band centered at the signal frequency.

Spectral shape discrimination of narrow-band sounds.

Measurements are reported on the detectability of signals added to narrow-band sounds. The narrow-band sounds had a bandwidth of 20 Hz and were either Gaussian noise with flat amplitude spectra or sets of equal-amplitude sinusoidal components whose phases were chosen at random. Four different kinds of sinusoidal signals were used. Two signals produced symmetric changes in the audio spectrum adding a component either at the center of the spectrum or at both ends. The other two signals produced asymmetric changes adding a component at either end of the spectrum. The overall level of the sound was randomly varied on each presentation, so that the presence of a signal was largely unrelated to the absolute level of the signal component(s). A model is proposed that assumes the detection of the symmetric signals is based on changes in the shape of the power spectrum of the envelope. Such changes in the envelope power spectrum are probably heard as changes in the "roughness" or "smoothness" of the narrow-band sound. The predictions of this model were obtained from computer simulations. For the asymmetric signals, the most probable detection cues were changes in the pitch of the narrow-band sound. Results from a variety of different experiments using three listeners support these conjectures.

Sensitivity to envelope coherence.

Measurements are reported on the ability of observers to discriminate whether the envelope of two amplitude-modulated sinusoids are in phase or out of phase. Spacing between the two carriers was either 2/3 or 4/3 octave, and the depth of modulation was varied to determine threshold. Discrimination performance improved as the level of the carriers increases up to about 60 dB SPL. The frequency locus of the two carriers (geometric mean of the two frequencies), which varied from 500 to 8000 Hz in different experiments, had little effect on discrimination accuracy. Discrimination performance was relatively constant for modulation rates below 100 Hz and deteriorates for higher modulation rates. These results are compared with data obtained from comodulation masking release experiments.

Signal uncertainty and psychometric functions in profile analysis.

Experiment 1 was conducted to compare the effects of signal frequency uncertainty on the detection of a change in spectral shape and on the detection of a tone in wideband noise. Results indicate that for both tasks the uncertainty effect was small, being on average about 3 dB. In a second experiment, psychometric functions were measured for the detection of changes in the spectral shape of multicomponent complexes. Psychometric functions for profile tasks have a 25-dB range and are similar to those measured for the detection of an increment in the level of a single sinusoid. These psychometric functions are different from those found when detecting a signal in noise, which typically have a 10-dB range. Three equations for the shape of the psychometric functions were compared. The difference in the resulting fits was small, thus preventing an unambiguous choice of functional form.

Auditory profile analysis: potential pitch cues.

The ability to detect changes in spectral shape, or profile analysis, was measured for both complex and simple changes in the power spectrum of a complex equal-amplitude standard. In an effort to determine whether detectability was mediated by changes in pitch that are concomitant with changes in spectral shape, the pitch of the stimuli were altered on a trial by trial basis. For moderate-range pitch randomizations, thresholds were on average 3 dB poorer than when no pitch randomization was employed. For large-range pitch randomizations, threshold changes were larger, but performance levels remained above chance levels. The psychophysical data, coupled with computer simulations of Feth's envelope-weighted average instantaneous frequency pitch model, indicate that changes in pitch contribute little to the discriminability of complex spectra.

Frequency effects in profile analysis and detecting complex spectral changes.

Seven experiments on the detectability of intensity changes in complex multitonal acoustic spectra are reported. Two general questions organize the experimental efforts. The first question is how the detectability of a change in a flat (equal energy) spectrum depends on the frequency region where a single intensive change is made. The answer is that frequency region plays a relatively minor role. Frequency changes in the midregion of the spectrum are the easiest to hear, but thresholds increase by only about 5 dB over the range from 200 to 5000 Hz. For all frequencies, the psychometric function is of the form d' = k(delta p), where k is a constant and delta p is the change in pressure. The second question is how can we predict the detectability of complex changes over the entire frequency range from the detectability of change at each separate region. Thresholds for detecting a change from a flat spectrum to a spectrum whose amplitude varies in sinusoidal ("rippled") fashion over logarithmic frequency are measured at different frequencies of ripple. The thresholds are found to be independent of ripple frequency and are 7 dB higher than predicted on the basis of an optimum combination rule.