Carbon-13 labelling strategy for studying the ATP metabolism in individual yeast cells by micro-arrays for mass spectrometry

Urban, Pawel L.; Schmidt, Anna Mareike; Fagerer, Stephan R.; Amantonico, Andrea; Ibáñez, Alfredo J.; Jefimovs, Konstantins; Heinemann, Matthias; Zenobi, Renato

doi:10.1039/c1mb05248a

Cited by 36 publications

(30 citation statements)

References 22 publications

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“…Using the MAMS platform, we can reach the level of 100 amol to 10 fmol-a range on the order of the metabolite levels in a single yeast cell (14,15).…”

Section: Resultsmentioning

confidence: 99%

“…MAMS represent a type of substrate for matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) recently introduced by our group (14,15). MAMS uses a combination of hydrophilic reservoirs surrounded by an omniphobic surface (SI Text) for massively parallel, automated sample spotting.…”

Section: Resultsmentioning

confidence: 99%

“…A number of analytical approaches were developed with detection limits low enough for single-cell metabolite analyses [e.g., nanostructured surfaces (7,8), postionization techniques (9,10), modified laser optics (11), the use of microsampling tools (12,13), microarrays for MS measurements (14,15), etc.]. Until now, however, most MS studies targeting single-cell metabolite analysis have only shown the analytical capabilities, but have not demonstrated that true biological information can be retrieved from studying the metabolism of single cells.…”

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confidence: 99%

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Mass spectrometry-based metabolomics of single yeast cells

Ibáñez¹,

Fagerer²,

Schmidt³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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216

123

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Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.single-cell measurements | MALDI mass spectrometry | baker's yeast E ven genetically identical cells present in the same microenvironment can express different phenotypes, for a number of reasons: cell-to-cell heterogeneity can stem from differences in the cell age and differences in the cell cycle stage, and stochastic effects together with feedback mechanisms can lead to distinctively different phenotypes, too (1-6). As population-level measurement techniques inherently average out such cell-to-cell differences, biochemical mechanisms underlying a studied system cannot be deduced from such measurements. Thus, to detect and exploit this heterogeneity, new analytical platforms with a sensitivity at the single-cell level and the ability to perform quantitative analyses must be developed and validated.Motivated by advances of mass spectrometry (MS) in metabolomics, the analytical chemistry community has stepped up its efforts toward realizing MS-based single-cell metabolomics (1, 2). A number of analytical approaches were developed with detection limits low enough for single-cell metabolite analyses [e.g., nanostructured surfaces (7, 8), postionization techniques (9, 10), modified laser optics (11), the use of microsampling tools (12, 13), microarrays for MS measurements (14, 15), etc.]. Until now, however, most MS studies targeting single-cell metabolite analysis have only shown the analytical capabilities, but have not demonstrated that true biological information can be retrieved from studying the metabolism of single cells.Here, using the unicellular eukaryotic model organism Saccharomyces cerevisiae, we present an analytical validation of a single-cell metabolite analysis using the microarrays for mass spectrometry (MAMS) platform. This validation concerns both the analytical methodology and the biological information, by monitoring expected cellular responses upon an environmental and a genetic perturbation. Furthermore, we present examples of biological insight that are only accessible with a platform such as MAMS. Specifically, we unravel metabolite-metabolite correlations, and visualize coexisting subpopulations in an isogenic cell culture. This technology can now be used to reveal metabolic differences in cells of isogenic cell populations, such as differences caused by cell cycles stages, cell ages, or stochastically induced phenotypic differences. Results and ...

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“…Using the MAMS platform, we can reach the level of 100 amol to 10 fmol-a range on the order of the metabolite levels in a single yeast cell (14,15).…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Mass spectrometry-based metabolomics of single yeast cells

Ibáñez¹,

Fagerer²,

Schmidt³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

216

123

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show abstract

“…For example, Nemes and co‐workers used a microfluidic platform (suitable for cell immobilization, and cultivation) and coupled it to a mass spectrometry to monitor secreted compounds . With respect to arrays, ionization of compounds by laser ablation and desorption directly from the predefined areas improves the overall sensitivity of the mass spectrometry, hence enhancing it in terms of throughput and data analysis .…”

Section: Available Technologies For Single‐cell Analysismentioning

confidence: 99%

Analysis of metabolites in single cells—what is the best micro‐platform?

Dittrich

Ibáñez

2015

Electrophoresis

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This review covers new innovations and developments in the field of single-cell level analysis of metabolites, involving the role of microfluidic and microarray platforms to manipulate and handle the cells prior their detection. Microfluidic and microarray platforms have shown great promise. The latest developments demonstrate their potential to identify a particular cell or even an ensemble of cells (sharing a common property or phenotype) that co-exist in a much larger cell population. The reason for this is the capability of these platforms to perform several complex analytical processes, such as: cleanup, sorting, derivatization, separation, and detection, with great robustness, speed, and reduced sample/reagent consumption. Here, we present several examples that illustrate the rapid strides that have been made for the routine analysis of metabolites by coupling different microfluidics and microarrays devices to a wide range of analytical detectors (e.g. fluorescent microscopy, electrochemical, and mass spectrometry). Herein, we also present selected examples detailing the use of microfluidics and microarrays in the visualization of the natural occurring cell-to-cell heterogeneity in isogenic populations, in particular during the response to external cues. The possibility to accurate monitor the cell-to-cell heterogeneity based on different levels of key metabolites is of clinical relevance, since cell-to-cell heterogeneity can influence, for example, the outcome of a drug treatment.

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“…A major disadvantage of MALDI-MS is its limited quantitative capability – a characteristic attributed to the limitations of sample preparation protocols, and ion suppression effects. When using MALDI-MS in the studies of metabolism, one possible solution to this problem is the implementation of stable-isotope labels [17], [18]. The in-vivo labeling of fruit flies with stable isotopes – in combination with LC-MS – has already gained an insight into the proteome of fruit fly [19].…”

Section: Introductionmentioning

confidence: 99%

Isotope Label-Aided Mass Spectrometry Reveals the Influence of Environmental Factors on Metabolism in Single Eggs of Fruit Fly

Tseng

Chen

et al. 2012

PLoS ONE

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In order to investigate the influence of light/dark cycle on the biosynthesis of metabolites during oogenesis, here we demonstrate a simple experimental protocol which combines in-vivo isotopic labeling of primary metabolites with mass spectrometric analysis of single eggs of fruit fly (Drosophila melanogaster). First, fruit flies were adapted to light/dark cycle using artificial white light. Second, female flies were incubated with an isotopically labeled sugar (13C6-glucose) for 12 h – either during the circadian day or the circadian night, at light or at dark. Third, eggs were obtained from the incubated female flies, and analyzed individually by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS): this yielded information about the extent of labeling with carbon-13. Since the incorporation of carbon-13 to uridine diphosphate glucose (UDP-glucose) in fruit fly eggs is very fast, the labeling of this metabolite was used as an indicator of the biosynthesis of metabolites flies/eggs during 12-h periods, which correspond to circadian day or circadian night. The results reveal that once the flies adapted to the 12-h-light/12-h-dark cycle, the incorporation of carbon-13 to UDP-glucose present in fruit fly eggs was not markedly altered by an acute perturbation to this cycle. This effect may be due to a relationship between biosynthesis of primary metabolites in developing eggs and an alteration to the intake of the labeled substrate – possibly related to the change of the feeding habit. Overall, the study shows the possibility of using MALDI-MS in conjunction with isotopic labeling of small metazoans to unravel the influence of environmental cues on primary metabolism.

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Carbon-13 labelling strategy for studying the ATP metabolism in individual yeast cells by micro-arrays for mass spectrometry

Abstract: Isotopic labelling of cellular metabolites, used in conjunction with high-density micro-arrays for mass spectrometry enables observation of ATP metabolism in single yeast cells.

Cited by 36 publications

References 22 publications

Mass spectrometry-based metabolomics of single yeast cells

Mass spectrometry-based metabolomics of single yeast cells

Analysis of metabolites in single cells—what is the best micro‐platform?

Isotope Label-Aided Mass Spectrometry Reveals the Influence of Environmental Factors on Metabolism in Single Eggs of Fruit Fly

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