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

Permutation test for periodicity in short time series data

Abstract Background Periodic processes, such as the circadian rhythm, are important factors modulating and coordinating transcription of genes governing key metabolic pathways. Theoretically, even small fluctuations in the orchestration of circadian gene expression patterns among different tissues may result in functional asynchrony at the organism level and may contribute to a wide range of pathologic disorders. Identification of circadian expression pattern in time series data is important, but equally challenging. Microarray technology allows estimation of relative expression of thousands of genes at each time point. However, this estimation often lacks precision and microarray experiments are prohibitively expensive, limiting the number of data points in a time series expression profile. The data produced in these experiments carries a high degree of stochastic variation, obscuring the periodic pattern and a limited number of replicates, typically covering not more than two complete periods of oscillation. Results To address this issue, we have developed a simple, but effective, computational technique for the identification of a periodic pattern in relatively short time series, typical for microarray studies of circadian expression. This test is based on a random permutation of time points in order to estimate non-randomness of a periodogram. The Permutated time, or Pt-test, is able to detect oscillations within a given period in expression profiles dominated by a high degree of stochastic fluctuations or oscillations of different irrelevant frequencies. We have conducted a comprehensive study of circadian expression on a large data set produced at PBRC, representing three different peripheral murine tissues. We have also re-analyzed a number of similar time series data sets produced and published independently by other research groups over the past few years. Conclusion The Permutated time test (Pt-test) is demonstrated to be effective for detection of periodicity in short time series typical for high-density microarray experiments. The software is a set of C++ programs available from the authors on the open source basis.</p

Analysis of circadian pattern reveals tissue-specific alternative transcription in leptin signaling pathway

*Background*&#xd;&#xa;It has been previously reported that most mammalian genes display a circadian oscillation in their baseline expression. Consequently, the phase and amplitude of each component of a signal transduction cascade has downstream consequences. &#xd;&#xa;&#xd;&#xa;*Results*&#xd;&#xa;We report our analysis of alternative transcripts in the leptin signaling pathway which is responsible for the systemic regulation of macronutrient storage and energy balance. We focused on the circadian expression pattern of a critical component of the leptin signaling system, suppressor of cytokine signaling 3 (SOCS3). On an Affymetrix GeneChip 430A2 microarray, this gene is represented by three probe sets targeting different regions within the 3&#x2019; end of the last exon. We demonstrate that in murine brown adipose tissue two downstream 3&#x2019; probe sets experience circadian baseline oscillation in counter-phase to the upstream probe set. Such differences in expression patterns are a telltale sign of alternative splicing within the last exon of SOCS3. In contrast, all three probe sets oscillated in a common phase in murine liver and white adipose tissue. This suggests that the regulation of SOCS3 expression in brown fat is tissue specific. Another component of the signaling pathway, Janus kinase (JAK), is directly regulated by SOCS and has alternative transcript probe sets oscillating in counter-phase in a white adipose tissue specific manner.&#xd;&#xa; &#xd;&#xa;*Conclusion*&#xd;&#xa;We hypothesize that differential oscillation of alternative transcripts may provide a mechanism to maintain steady levels of expression in spite of circadian baseline variation

Record linkage research and informed consent: who consents?

BACKGROUND: Linking computerized health insurance records with routinely collected survey data is becoming increasingly popular in health services research. However, if consent is not universal, the requirement of written informed consent may introduce a number of research biases. The participants of a national health survey in Taiwan were asked to have their questionnaire results linked to their national health insurance records. This study compares those who consented with those who refused. METHODS: A national representative sample (n = 14,611 adults) of the general adult population aged 20 years or older who participated in the Taiwan National Health Interview Survey (NHIS) and who provided complete survey information were used in this study. At the end of the survey, the respondents were asked if they would give permission to access their National Health Insurance records. Information given by the interviewees in the survey was used to analyze who was more likely to consent to linkage and who wasn't. RESULTS: Of the 14,611 NHIS participants, 12,911 (88%) gave consent, and 1,700 (12%) denied consent. The elderly, the illiterate, those with a lower income, and the suburban area residents were significantly more likely to deny consent. The aborigines were significantly less likely to refuse. No discrepancy in gender and self-reported health was found between individuals who consented and those who refused. CONCLUSION: This study is the first population-based study in assessing the consent pattern in a general Asian population. Consistent with people in Western societies, in Taiwan, a typical Asian society, a high percentage of adults gave consent for their health insurance records and questionnaire results to be linked. Consenters differed significantly from non-consenters in important aspects such as age, ethnicity, and educational background. Consequently, having a high consent rate (88%) may not fully eliminate the possibility of selection bias. Researchers should take this source of bias into consideration in their study design and investigate any potential impact of this source of bias on their results

Evaluating Gene Expression Dynamics Using Pairwise RNA FISH Data

Recently, a novel approach has been developed to study gene expression in single cells with high time resolution using RNA Fluorescent In Situ Hybridization (FISH). The technique allows individual mRNAs to be counted with high accuracy in wild-type cells, but requires cells to be fixed; thus, each cell provides only a “snapshot” of gene expression. Here we show how and when RNA FISH data on pairs of genes can be used to reconstruct real-time dynamics from a collection of such snapshots. Using maximum-likelihood parameter estimation on synthetically generated, noisy FISH data, we show that dynamical programs of gene expression, such as cycles (e.g., the cell cycle) or switches between discrete states, can be accurately reconstructed. In the limit that mRNAs are produced in short-lived bursts, binary thresholding of the FISH data provides a robust way of reconstructing dynamics. In this regime, prior knowledge of the type of dynamics – cycle versus switch – is generally required and additional constraints, e.g., from triplet FISH measurements, may also be needed to fully constrain all parameters. As a demonstration, we apply the thresholding method to RNA FISH data obtained from single, unsynchronized cells of Saccharomyces cerevisiae. Our results support the existence of metabolic cycles and provide an estimate of global gene-expression noise. The approach to FISH data presented here can be applied in general to reconstruct dynamics from snapshots of pairs of correlated quantities including, for example, protein concentrations obtained from immunofluorescence assays

Coherent multi-flavour spin dynamics in a fermionic quantum gas

Microscopic spin interaction processes are fundamental for global static and dynamical magnetic properties of many-body systems. Quantum gases as pure and well isolated systems offer intriguing possibilities to study basic magnetic processes including non-equilibrium dynamics. Here, we report on the realization of a well-controlled fermionic spinor gas in an optical lattice with tunable effective spin ranging from 1/2 to 9/2. We observe long-lived intrinsic spin oscillations and investigate the transition from two-body to many-body dynamics. The latter results in a spin-interaction driven melting of a band insulator. Via an external magnetic field we control the system's dimensionality and tune the spin oscillations in and out of resonance. Our results open new routes to study quantum magnetism of fermionic particles beyond conventional spin 1/2 systems.Comment: 9 pages, 5 figure

The Unfolded Protein Response Is Not Necessary for the G1/S Transition, but It Is Required for Chromosome Maintenance in Saccharomyces cerevisiae

BACKGROUND: The unfolded protein response (UPR) is a eukaryotic signaling pathway, from the endoplasmic reticulum (ER) to the nucleus. Protein misfolding in the ER triggers the UPR. Accumulating evidence links the UPR in diverse aspects of cellular homeostasis. The UPR responds to the overall protein synthesis capacity and metabolic fluxes of the cell. Because the coupling of metabolism with cell division governs when cells start dividing, here we examined the role of UPR signaling in the timing of initiation of cell division and cell cycle progression, in the yeast Saccharomyces cerevisiae. METHODOLOGY/PRINCIPAL FINDINGS: We report that cells lacking the ER-resident stress sensor Ire1p, which cannot trigger the UPR, nonetheless completed the G1/S transition on time. Furthermore, loss of UPR signaling neither affected the nutrient and growth rate dependence of the G1/S transition, nor the metabolic oscillations that yeast cells display in defined steady-state conditions. Remarkably, however, loss of UPR signaling led to hypersensitivity to genotoxic stress and a ten-fold increase in chromosome loss. CONCLUSIONS/SIGNIFICANCE: Taken together, our results strongly suggest that UPR signaling is not necessary for the normal coupling of metabolism with cell division, but it has a role in genome maintenance. These results add to previous work that linked the UPR with cytokinesis in yeast. UPR signaling is conserved in all eukaryotes, and it malfunctions in a variety of diseases, including cancer. Therefore, our findings may be relevant to other systems, including humans

Genome-scale modeling of the protein secretory machinery in yeast

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery

Disruption of reducing pathways is not essential for efficient disulfide bond formation in the cytoplasm of E. coli

<p>Abstract</p> <p>Background</p> <p>The formation of native disulfide bonds is a complex and essential post-translational modification for many proteins. The large scale production of these proteins can be difficult and depends on targeting the protein to a compartment in which disulfide bond formation naturally occurs, usually the endoplasmic reticulum of eukaryotes or the periplasm of prokaryotes. It is currently thought to be impossible to produce large amounts of disulfide bond containing protein in the cytoplasm of wild-type bacteria such as <it>E. coli </it>due to the presence of multiple pathways for their reduction.</p> <p>Results</p> <p>Here we show that the introduction of Erv1p, a sulfhydryl oxidase and FAD-dependent catalyst of disulfide bond formation found in the inter membrane space of mitochondria, allows the efficient formation of native disulfide bonds in heterologously expressed proteins in the cytoplasm of <it>E. coli </it>even without the disruption of genes involved in disulfide bond reduction, for example <it>trxB </it>and/or <it>gor</it>. Indeed yields of active disulfide bonded proteins were higher in BL21 (DE3) pLysSRARE, an <it>E. coli </it>strain with the reducing pathways intact, than in the commercial Δ<it>gor </it>Δ<it>trxB </it>strain rosetta-gami upon co-expression of Erv1p.</p> <p>Conclusions</p> <p>Our results refute the current paradigm in the field that disruption of at least one of the reducing pathways is essential for the efficient production of disulfide bond containing proteins in the cytoplasm of <it>E. coli </it>and open up new possibilities for the use of <it>E. coli </it>as a microbial cell factory.</p