Behavior of a Metabolic Cycling Population at the Single Cell Level as Visualized by Fluorescent Gene Expression Reporters

BACKGROUND: During continuous growth in specific chemostat cultures, budding yeast undergo robust oscillations in oxygen consumption that are accompanied by highly periodic changes in transcript abundance of a majority of genes, in a phenomenon called the Yeast Metabolic Cycle (YMC). This study uses fluorescent reporters of genes specific to different YMC phases in order to visualize this phenomenon and understand the temporal regulation of gene expression at the level of individual cells within the cycling population. METHODOLOGY: Fluorescent gene expression reporters for different phases of the YMC were constructed and stably integrated into the yeast genome. Subsequently, these reporter-expressing yeast were used to visualize YMC dynamics at the individual cell level in cultures grown in a chemostat or in a microfluidics platform under varying glucose concentrations, using fluorescence microscopy and quantitative Western blots. CONCLUSIONS: The behavior of single cells within a metabolic cycling population was visualized using phase-specific fluorescent reporters. The reporters largely recapitulated genome-specified mRNA expression profiles. A significant fraction of the cell population appeared to exhibit basal expression of the reporters, supporting the hypothesis that there are at least two distinct subpopulations of cells within the cycling population. Although approximately half of the cycling population initiated cell division in each permissive window of the YMC, metabolic synchrony of the population was maintained. Using a microfluidics platform we observed that low glucose concentrations appear to be necessary for metabolic cycling. Lastly, we propose that there is a temporal window in the oxidative growth phase of the YMC where the cycling population segregates into at least two subpopulations, one which will enter the cell cycle and one which does not

Robust Metabolic Responses to Varied Carbon Sources in Natural and Laboratory Strains of Saccharomyces cerevisiae

Understanding factors that regulate the metabolism and growth of an organism is of fundamental biologic interest. This study compared the influence of two different carbon substrates, dextrose and galactose, on the metabolic and growth rates of the yeast Saccharomyces cerevisiae. Yeast metabolic and growth rates varied widely depending on the metabolic substrate supplied. The metabolic and growth rates of a yeast strain maintained under long-term laboratory conditions was compared to strain isolated from natural condition when grown on different substrates. Previous studies had determined that there are numerous genetic differences between these two strains. However, the overall metabolic and growth rates of a wild isolate of yeast was very similar to that of a strain that had been maintained under laboratory conditions for many decades. This indicates that, at in least this case, metabolism and growth appear to be well buffered against genetic differences. Metabolic rate and cell number did not co-vary in a simple linear manner. When grown in either dextrose or galactose, both strains showed a growth pattern in which the number of cells continued to increase well after the metabolic rate began a sharp decline. Previous studied have reported that O2 consumption in S. cerevisiae grown in reduced dextrose levels were elevated compared to higher levels. Low dextrose levels have been proposed to induce caloric restriction and increase life span in yeast. However, there was no evidence that reduced levels of dextrose increased metabolic rates, measured by either O2 consumption or CO2 production, in the strains used in this study

Industrial Systems Biology of Saccharomyces cerevisiae Enables Novel Succinic Acid Cell Factory.

Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the alpha-keto-glutarate dehydrogenase catalyzed conversion of alpha-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals

Genome-Wide Analysis of Nucleotide-Level Variation in Commonly Used Saccharomyces cerevisiae Strains

Ten years have passed since the genome of Saccharomyces cerevisiae–more precisely, the S288c strain–was completely sequenced. However, experimental work in yeast is commonly performed using strains that are of unknown genetic relationship to S288c. Here, we characterized the nucleotide-level similarity between S288c and seven commonly used lab strains (A364A, W303, FL100, CEN.PK, ∑1278b, SK1 and BY4716) using 25mer oligonucleotide microarrays that provide complete and redundant coverage of the ∼12 Mb Saccharomyces cerevisiae genome. Using these data, we assessed the frequency and distribution of nucleotide variation in comparison to the sequenced reference genome. These data allow us to infer the relationships between experimentally important strains of yeast and provide insight for experimental designs that are sensitive to sequence variation. We propose a rational approach for near complete sequencing of strains related to the reference using these data and directed re-sequencing. These data and new visualization tools are accessible online in a new resource: the Yeast SNPs Browser (YSB; http://gbrowse.princeton.edu/cgi-bin/gbrowse/yeast_strains_snps) that is available to all researchers

Sugar-fermenting yeast as an organic source of carbon dioxide to attract the malaria mosquito Anopheles gambiae s.s.

<p>Abstract</p> <p>Background</p> <p>Carbon dioxide (CO₂) plays an important role in the host-seeking process of opportunistic, zoophilic and anthropophilic mosquito species and is, therefore, commonly added to mosquito sampling tools. The African malaria vector <it>Anopheles gambiae sensu stricto </it>is attracted to human volatiles augmented by CO₂. This study investigated whether CO₂, usually supplied from gas cylinders acquired from commercial industry, could be replaced by CO₂derived from fermenting yeast (yeast-produced CO₂).</p> <p>Methods</p> <p>Trapping experiments were conducted in the laboratory, semi-field and field, with <it>An. gambiae s.s</it>. as the target species. MM-X traps were baited with volatiles produced by mixtures of yeast, sugar and water, prepared in 1.5, 5 or 25 L bottles. Catches were compared with traps baited with industrial CO₂. The additional effect of human odours was also examined. In the laboratory and semi-field facility dual-choice experiments were conducted. The effect of traps baited with yeast-produced CO₂on the number of mosquitoes entering an African house was studied in the MalariaSphere. Carbon dioxide baited traps, placed outside human dwellings, were also tested in an African village setting. The laboratory and semi-field data were analysed by a χ²-test, the field data by GLM. In addition, CO₂concentrations produced by yeast-sugar solutions were measured over time.</p> <p>Results</p> <p>Traps baited with yeast-produced CO₂caught significantly more mosquitoes than unbaited traps (up to 34 h post mixing the ingredients) and also significantly more than traps baited with industrial CO₂, both in the laboratory and semi-field. Adding yeast-produced CO₂to traps baited with human odour significantly increased trap catches. In the MalariaSphere, outdoor traps baited with yeast-produced or industrial CO₂+ human odour reduced house entry of mosquitoes with a human host sleeping under a bed net indoors. <it>Anopheles gambiae s.s</it>. was not caught during the field trials. However, traps baited with yeast-produced CO₂caught similar numbers of <it>Anopheles arabiensis </it>as traps baited with industrial CO₂. Addition of human odour increased trap catches.</p> <p>Conclusions</p> <p>Yeast-produced CO₂can effectively replace industrial CO₂for sampling of <it>An. gambiae s.s</it>.. This will significantly reduce costs and allow sustainable mass-application of odour-baited devices for mosquito sampling in remote areas.</p

Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications

<p>Abstract</p> <p>Background</p> <p>The need for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering.</p> <p>Results</p> <p>In this work we performed whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between <it>Saccharomyces cerevisiae </it>strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the <it>Saccharomyces </it>Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,596 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being nonsynonymous (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (<it>GAL1</it>, <it>GAL10</it>) and ergosterol biosynthetic pathway (<it>ERG8</it>, <it>ERG9</it>). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function.</p> <p>Conclusions</p> <p>With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at <url>http://www.sysbio.se/cenpk</url>.</p

Neuroanatomical Study of the A11 Diencephalospinal Pathway in the Non-Human Primate

BACKGROUND: The A11 diencephalospinal pathway is crucial for sensorimotor integration and pain control at the spinal cord level. When disrupted, it is thought to be involved in numerous painful conditions such as restless legs syndrome and migraine. Its anatomical organization, however, remains largely unknown in the non-human primate (NHP). We therefore characterized the anatomy of this pathway in the NHP. METHODS AND FINDINGS: In situ hybridization of spinal dopamine receptors showed that D1 receptor mRNA is absent while D2 and D5 receptor mRNAs are mainly expressed in the dorsal horn and D3 receptor mRNA in both the dorsal and ventral horns. Unilateral injections of the retrograde tracer Fluoro-Gold (FG) into the cervical spinal enlargement labeled A11 hypothalamic neurons quasi-exclusively among dopamine areas. Detailed immunohistochemical analysis suggested that these FG-labeled A11 neurons are tyrosine hydroxylase-positive but dopa-decarboxylase and dopamine transporter-negative, suggestive of a L-DOPAergic nucleus. Stereological cell count of A11 neurons revealed that this group is composed by 4002±501 neurons per side. A 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) intoxication with subsequent development of a parkinsonian syndrome produced a 50% neuronal cell loss in the A11 group. CONCLUSION: The diencephalic A11 area could be the major source of L-DOPA in the NHP spinal cord, where it may play a role in the modulation of sensorimotor integration through D2 and D3 receptors either directly or indirectly via dopamine formation in spinal dopa-decarboxylase-positives cells