Single-Cell Mass Spectrometry of Metabolites ... - ACS Publications

Subscriber access provided by UB + Fachbibliothek Chemie | (FU-Bibliothekssystem)

Article

Single-cell mass spectrometry of metabolites extracted from live cells by fluidic force microscopy Orane Guillaume-Gentil, Timo Rey, Patrick Kiefer, Alfredo J. Ibanez, Robert Steinhoff, Rolf Brönnimann, Livie Dorwling-Carter, Tomaso Zambelli, Renato Zenobi, and Julia Anne Vorholt Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b00367 • Publication Date (Web): 31 Mar 2017 Downloaded from http://pubs.acs.org on April 1, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Analytical Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

Single-cell mass spectrometry of metabolites extracted from live cells by fluidic force microscopy Orane Guillaume-Gentil,§,˧,* Timo Rey,§,˧ Patrick Kiefer,§ Alfredo J. Ibáñez,ǂ,† Robert Steinhoff,ǂ Rolf Brönnimann,‡ Livie Dorwling-Carter,⁑ Tomaso Zambelli,⁑ Renato Zenobi,ǂ Julia A. Vorholt§,* §

Department of Biology, Institute of Microbiology, ETH Zurich, 8093 Zurich, Switzerland

ǂ

Department of Chemistry and Applied Biosciences, Laboratory of Organic Chemistry, ETH Zurich,

8093 Zurich, Switzerland ‡

Swiss Federal Laboratories for Material Science and Technology EMPA, 8600 Dübendorf,

Switzerland ⁑

Department of Information Technology and Electrical Engineering, Institute for Biomedical

Engineering, ETH Zurich, 8093 Zurich, Switzerland

ABSTRACT: Single-cell metabolite analysis provides valuable information on cellular function and response to external stimuli. While recent advances in mass spectrometry reached the sensitivity required to investigate metabolites in single cells, current methods commonly isolate and sacrifice cells, inflicting a perturbed state and preventing complementary analyses. Here, we propose a two-step approach that combines non-destructive and quantitative withdrawal of intracellular fluid with subpicoliter

resolution

using

fluidic

force

microscopy,

followed

by

matrix-assisted

laser

desorption/ionization time-of-flight mass spectrometry. The developed method enabled the detection and identification of 20 metabolites recovered from the cytoplasm of individual HeLa cells. The approach was further validated in

13

C-glucose feeding experiments which showed incorporation of

labeled carbon atoms into different metabolites. Metabolite sampling followed by mass spectrometry measurements enabled the preservation of the physiological context and the viability of the analyzed cell, providing opportunities for complementary analyses of the cell before, during, and after metabolite analysis.

1 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 17


Page 3 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Cell-to-cell heterogeneity prevails in virtually any given cell population and has fostered the development of advanced sampling and analytical approaches to enable studies at the single-cell level. Working with subcellular amounts of DNA and RNA has now become feasible through the straightforward amplification of polynucleotides by PCR, which allows current detection systems to reach the necessary limit of detection.1 Single-cell metabolomics, however, is still in its infancy.2 Because the metabolome represents the most immediate and dynamic indicator of a cell phenotype, there is great interest to overcome current limitations. Metabolites are the most intricate type of molecule to measure due to their large chemical diversity, wide range of concentrations, and instability; additionally, because of their small size, they can rarely be labeled without interfering with their biological function.3 Analytical methods such as nuclear magnetic resonance (NMR) or mass spectrometry (MS) are needed to detect and structurally investigate metabolites4,5 for targeted and untargeted investigations.6 While NMR sensitivity is currently too low for the detection of metabolites at the single-cell level, MS has high sensitivity and is the method of choice to cover the wide range of chemical compounds constituting the metabolome.7 For single-cell metabolic studies, optimization of each step in current MS workflows is essential for reaching sufficient sensitivity. Although the most abundant metabolites such as ATP are present in mM concentrations inside the cell, due to the small volumes of most cells, only amol to fmol quantities are present in single mammalian cells.8,9 Besides the stringent analytical requirements needed to reach the sensitivity for detecting metabolites in individual cells, the analyte sampling method is also critical. Due to the metabolome's rapid response to changes in the environment,10 it is crucial to minimize perturbations upon metabolite sampling. Over the last few years, different MS-based approaches have been developed to profile metabolites in single cells. These methods usually rely on the ionization of entire, isolated cells. Following isolation of whole cells and solvent extraction of the intracellular analytes, Sweedler and co-workers used capillary electrophoresis coupled to electrospray ionization MS (CE-ESI-MS) for single-cell metabolic profiling.11,12 The approach enabled the identification of ~30 metabolites in individual, large, sea slug neurons. The same group also explored another strategy, in which individual cells dispensed on a target for matrix-assisted laser desorption/ionization (MALDI) were pre-localized by optical microscopy to automate the subsequent analysis by MALDI mass spectrometry. The increased analytic throughput allowed for rapid analysis of more than 3000 cells, making it possible to investigate metabolic heterogeneity and unravel cellular subtypes in tissueisolated cell populations.13,14 Another strategy developed for increased throughput by single-cell MALDI-MS measurement makes use of micro-arrays for mass spectrometry (MAMS), which feature hydrophilic reservoirs in an otherwise omniphobic surface. The MAMS substrate, which also serves as the MALDI target, enables the rapid and efficient singularization of large numbers of cells.15 Such high-density single-cell arrays have been successfully implemented for metabolic analyses of single yeast cells16 and unicellular algae.17



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 4 of 17

These different approaches have demonstrated the analytical capabilities of MS for studies at the single-cell level, and provided the first biological insights into intercellular metabolic heterogeneity. They present, however, several limitations, including the need to separate the cells from their native environment before analysis, and the fact that extraction of the cell contents for MS measurements is destructive. The removal of the cells from their physiological environment not only results in the loss of spatial context information, but also disrupts a cell's interaction with its neighbors and with its extracellular microenvironment, causing unknown perturbations in cellular metabolism.10 The subsequent sacrifice of the cell for MS measurement further prevents complementary analyses of the cell after the acquisition of metabolite data, such as genomic or transcriptomic analyses. An attractive alternative to address these shortcomings has been pioneered by Masujima and colleagues. They inserted a nano-electrospray ionization (nanoESI) tip into live cells in tissue culture to withdraw the intracellular metabolites, before spraying the capillary content into a MS system.18 This approach enables spatially-defined metabolite analyses of living cells, and has been effectively applied for metabolic studies of single human cells19,20 and even single-cell organelles.21,22 Similar approaches have recently been reported, which also rely on micro-sized probes both for retrieving the metabolites upon intracellular insertion and for their delivery to an MS instrument for metabolic analysis of single live cells.23-25 Alternatively, Aerts et al. used a glass capillary to sequentially perform whole-cell patch clamp recording and sample the cell cytoplasm for CE-MS, enabling combined electrophysiological recording and chemical content analysis of single neurons.26 Here, we explore metabolite extraction from single live cells by fluidic force microscopy (FluidFM) for subsequent analysis by MALDI- MS. A method enabling the collection of soluble intracellular molecules using FluidFM was recently established in our laboratory.27 Compared to microcapillaries, the FluidFM probes have a smaller size and an advantageous pyramidal geometry preventing membrane damage.28,29 In addition, the probes are driven by an atomic force microscope (AFM), which provides an accurate and gentle way to insert them into mammalian cells.27,30 These features enable minimal cell perturbation and high efficiency upon intracellular insertion, even allowing the quantitative extraction of intracellular molecules without affecting cell viability. Analyses of the collected fL to pL extracts showed recovery of intact transcripts and proteins, while complementary observations indicated the collection of all the soluble intracellular molecules smaller than the probe aperture (400 nm).


Page 5 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


EXPERIMENTAL Cells. Human cervical cancer cells (HeLa) were maintained in high glucose Dulbecco's Modified Eagle's Medium (DMEM; ThermoFisher) supplemented with 10 % foetal bovine serum (Chemie Brunschwig AG) and 1 % penicillin/streptomycin (Chemie Brunschwig AG), at 37 °C in a humidified incubator at 5 % CO2. Two to four days prior to extraction, HeLa cells were transfected with pmaxGFP (Amaxa) using Lipofectamine 2000 (Invitrogen) following the manufacturer’s protocol. Transfected cells were then trypsinized and seeded onto 50-mm diameter glass dishes (WillCo Well B.V.). For labeling experiments, HeLa cells were grown for 2 days in glucose- and pyruvate-free DMEM (ThermoFisher) supplemented with 25 mM uniformly labeled Laboratories),

10

%

dialyzed

fetal

bovine

serum

13

(FBS;

C-glucose (Cambridge Isotope Sigma-Aldrich),

and

1

%

penicillin/streptomycin. Medium was replaced with fresh medium 1 day after trypsinization. All media were filter-sterilized (0.22 µm) prior to use. Microarrays for Mass Spectrometry Chip Fabrication. Microarrays for mass spectrometry15,31 (MAMS) were prepared as follows: transparent indium tin oxide coated glass chips (75 mm × 25 mm × 1.1 mm) with a resistivity of 8–12 Ω·sq−1 (Sigma-Aldrich) were spray coated (Eposint) with a ∼2to 3-µm-thick polysilazane coating (CAG 37; Clariant). The polysilazane layer was then structured using a laser ablation system with a picosecond laser (SuperRapid, Lumera Laser) and a scan head (HurryScan 10, Scanlab) equipped with a telecentric lens (f = 100 mm). The lens focused the beam on a 10 µm spot on the polysilazane layer. The pulse duration was 10 ps and the set pulse energy 2 µJ, corresponding to an average power of 100 mW at 50 kHz. For structuring circular recipients, the laser beam wrote a crosshatch structure. The distance between hatch lines was set to 5 µm and the writing speed to 5 µm/pulse (250 mm/s), ensuring a good overlap. A quadratic array of 13 × 13 circular recipient sites, 95 µm in diameter, with a site-to-site distance of 500 µm in both dimensions was created by laser ablation. Recipient sites of larger size (2.2 mm in diameter) were created outside the 13 × 13 array for depositing mass calibrants. The process took about 1 h per array. Before use, the slides were cleaned by ultrasonication, first with acetone for 10 min, and then with millipore water for 10 min, followed by N2-blow drying. Fluidic force microscopy setup. The fluidic force microscopy (FluidFM) system consisted of a FlexAFM-NIR scan head and a C3000 controller driven by the EasyScan2 software (Nanosurf), and a pressure controller unit operated by a digital controller software (Cytosurge). A syringe pressure kit with a three-way valve (Cytosurge) was used in addition to the digital pressure controller to apply under- and overpressure differences larger than -800 and +1,000 mbar. The scan head was mounted on an Axio Observer Z1 inverted microscope equipped with a temperature-controlled incubation chamber (Zeiss). 10× and 40× Plan-Neofluar objectives, a Colibri LED light source, and an AxioCam MRm R3 camera with AxioVision software (ZEISS) were used. For GFP fluorescence imaging, samples were illuminated with a 470 nm LED using a 480/17 excitation filter. FluidFM Rapid Prototyping probes



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 6 of 17

made of silicon nitride were obtained from Cytosurge. The dimensions of the hollow cantilevers were 200 µm × 36 µm, with a microchannel height of 1 µm. A 400 nm wide triangular aperture was custommilled by a focused ion beam near the apex of the pyramidal tips and imaged by scanning electron microscopy. The FluidFM probes were plasma treated for 1 min (Harrick Plasma) and coated with Sigmacote (Sigma-Aldrich) on the inside and outside with heat stabilization for ≥ 45 min at 100 °C prior to use (see ref 27 for a detailed protocol). Extraction by Fluidic force microscopy. Following spring constant calibration (k = 1.0 ± 0.1 N/m) the microchannel of the FluidFM probe was filled with mineral oil by application of overpressure. The probe was then immersed in the cell sample growth medium, and the probe sensitivity was calibrated (β = 69 ± 11 nm/V). A HeLa cell was selected under the optical microscope, and the probe was positioned next to the cell for conducting a force-controlled approach in contact-mode and retraction to 5 µm above the substrate. The tip of the probe was then moved above the cell cytoplasm and AFM force spectroscopy was initiated with a preset force of 500 nN at 0.5 µm/s. Once inserted, the tip was maintained inside the cytoplasm by maintaining a constant force. Maximum underpressure was applied to collect cytoplasmic fluid into the probe until the desired amount of extract was collected. The extraction of 1 pL-samples lasted 2-3 min (extraction flow rate of 400 ± 100 fL per min).27 The pressure was then switched back to zero, and the probe was retracted out of the cell. Following the extraction, the probe was immersed in Millipore water to wash away residual growth medium. Extract dispensing on MALDI target. Following cell extraction, the FluidFM cantilever probe containing a cytoplasmic extract was carefully wiped and air-dried, before initiating a force-controlled approach in contact mode onto a selected MAMS well. A pulse at maximum overpressure was applied to dispense the extract onto the spot. The deposited pL-extracts dried instantly on the hydrophilic spots. Exchanging the cell sample for the MALDI target took approximatively 1 min, and extract dispensing lasted 2-3 min. Following multiple depositions on a MALDI target, 0.5 µL of bulk HeLa cell lysates were dispensed onto the larger MAMS spots to aid later calibration of the laser power. The cell lysates were prepared according to the protocol of Martano et al.9 and tested at variable dilutions (6 to 6000 cell equivalent/µL). The substrate was then stored in a desiccator under vacuum until matrix deposition. Matrix application. A solution of the MALDI matrix 9-aminoacridine (9AA, Sigma-Aldrich) at 10 mg/mL in 60 % aqueous methanol was prepared and spun down for 1 min with a table-top centrifuge at -10 ºC. One mL of the supernatant was sprayed onto the samples using an airbrush held at 25 cm from the sample and propelled with nitrogen at 2 bar. The internal standards 8iodo-ATP, ADP-ribose and/or dATP were spiked into the 9AA solution resulting in concentrations of 0.5 µM, 1 µM and 1 µM, respectively, and co-sprayed on the target. MALDI-TOF-MS. MALDI-TOF MS analysis was conducted using a 5800 MALDI-TOF/TOF instrument (AB Sciex) equipped with an Optibeam on-axis Laser. Measurements were conducted in negative ion mode, with an analyzed mass range set to 60 < m/z < 900. The samples were ablated


Page 7 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


using 150 shots (15 shots in 10 subspectra) with a center-biased shooting pattern. The molecular ion signal intensities between samples were corrected using the calibrants’ molecular ion signals, hence correcting for variances in the matrix coverage. For single-cell measurements, it was usually set to 5600 or 5700 (arb. units). MALDI-TOF/TOF was operated using ToF/ToF™ Series Explorer™ software. Data analysis. Prior to metabolite identification, three processing steps were carried out: mass calibration, peak centroiding, and blank subtraction. Cubic spline fitting for mass calibration was performed as previously described.32 Peaks originating from the 9AA, spiked standards, and universal metabolites were used. The analysis of labeled samples was carried out without internal standards and labeled species were considered for mass calibration. Peaks were centroided and spectra were denoised using the openMS PeakPickerHighRes algorithm, applying a S/N threshold of 3. For blank subtraction, calibrated and centroided spectra from blanks were subtracted after peak normalization to total ion current. The limit of detection was set to 3 times the normalized blank intensity, and the maximum allowed ∆m/z was set to 50 ppm. Next, the remaining peaks were mapped to the human metabolome database for deprotonated molecular ions [M-H]-. To analyze 13C-labeled cell extracts, m/z values of all possible mass isotopologues due to 13C incorporation were calculated for previously identified metabolites and the resulting list of m/z values was used for targeted peak extraction applying a maximum allowed ∆m/z of 50 ppm.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 17

RESULTS AND DISCUSSION As recently reported, soluble intracellular molecules can be sampled directly from live mammalian cells using FluidFM,27 circumventing the need to lyse the cell to retrieve the intracellular analytes. In this study, we developed a protocol for coupling FluidFM extraction to metabolite detection (Figure 1). To this end, extraction and dispensing by FluidFM was combined with MALDI MS, using a chipbased approach that has been shown to provide high sensitivity for single-cell metabolite analysis.16,17,31

Figure 1. Schematic of the method for single-cell metabolic analysis using FluidFM and MALDI-TOF MS. A) Metabolite sampling using FluidFM, B) dispensing of the cytoplasmic extract onto a selected MAMS spot, C) spraying of the 9AA matrix, and D) acquisition of MS spectra. Extraction of cytoplasmic molecules. The pyramidal tip of a FluidFM probe with a 400 nm large aperture was first inserted into the cytoplasm of a targeted HeLa cell through forward force spectroscopy following the recently developed FluidFM-based extraction approach. The tip was then maintained inside the cell at the pre-set force value, while underpressure was applied to flow the soluble cytoplasmic molecules into the probe microchannel (Figure 1 A). The extraction process and amount of intracellular fluid collected in the semi-transparent cantilever was followed by optical microscopy in real time (Figure 2 A-C). The amount collected ranged from 0.8 to 2.7 pL, volumes shown to preserve cell viability.27 The withdrawal of GFP, produced in the targeted cells, was monitored by fluorescence microscopy, allowing us to follow the extracted cellular content in the cantilever and cell cytoplasm depletion. Once the desired amount of cytoplasmic fluid was collected, the pressure was set back to zero before withdrawal of the cantilever-probe from the cell. Extract dispensing onto MALDI target substrate. The FluidFM technology allows not only the quantitative sampling of intracellular fluid, but also the subsequent handling and release of the pL samples recovered in the probe. We selected microarrays for mass spectrometry15 (MAMS) substrates featuring 95 µm diameter spots as MALDI target. The MAMS were prepared by laser ablation of an omniphobic adlayer deposited on a transparent and conductive ITO substrate. The micro-structured substrate made it possible to dispense the minute samples effectively through microscopic observation, confine them upon matrix application, and locate the sample upon transfer into the MALDI mass


Page 9 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


spectrometer. For cell extract dispensing, the cantilever probe was approached onto a selected spot of the MAMS substrate with force-control, before applying overpressure to release the cytoplasmic extract onto the spot (Figure 1 B and Figure 2 D-F). The pL-deposits spread onto the ITO surface over areas of 100 to 200 µm2. They dried promptly in air and thus presumably resulted in immediate quenching of metabolite converting enzymes present in the cytoplasmic extracts.

Figure 2. Extraction of cytoplasmic molecules and dispensing onto MALDI target by FluidFM. GFPexpressing HeLa cell before (A), during (B), and after (C) cytoplasmic extraction; cell extract collected in the cantilever probe (D), force-controlled approach onto a MAMS spot (E), and extract released onto the spot (F). Phase contrast (PhC), GFP, and merge images are shown. The arrows in (A), (B), and (C) indicate the analyzed cell. MALDI-TOF MS measurement. Following the deposition of the extracts onto the MALDI target, 9AA matrix was applied by spray deposition (Figure 1 C). Due to its basicity, 9AA favors negative ion formation from proton donating compounds such as phosphoric acid groups and carboxylic acids.33 It yields high sensitivity for low molecular weight compounds, and has previously been used for singlecell metabolomics in yeast.16,31 The sprayed 9AA solution resulted in small, heterogeneously dispersed crystals. To analyze the metabolites recovered by cytoplasmic extraction, the samples were then inserted into the MALDI-TOF mass spectrometer and mass spectra were acquired (Figure 1 D). The coordinates of wells with deposited extracts were readily relocated using the x-y stage of the MALDI mass spectrometer and a source camera. Wells on the same MAMS substrate but without deposited extracts were measured as blank, allowing to subtract peaks originating from matrix compounds and chemical noise from the recorded cell-extract spectra. We first analyzed cytoplasmic samples extracted from HeLa cells cultured under standard conditions (n=4). After blank subtraction, a total of 20 different metabolites were detected and identified in at least 2 out of 4 cytoplasmic samples (see Table 1 and Table S-1). Detected acids and phosphorylated compounds included ribonucleotides (cGMP, UDP, ADP, ATP), activated sugars (UDP-GlcNAc, UDP-Glc), amino acids (aspartate, glutamate), and



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 17

glutathione. These findings are in line with the ionization capability of 9AA, the abundance of these metabolites in HeLa cells,34 and the MALDI MS data from single yeast cells.31 Table 1: Metabolites detected in single-cell extracts of HeLa cells cultured under standard conditions. Limit of detection was set to a signal-to-noise ratio (S/N) of 3.0 for blanks and samples. Sample peaks were corrected with blank measurements by subtracting 3 times respective maximum values normalized to TIC and measured in corresponding blank data set from sample values. m/z0: m/z value of monoisotopic peak; CID: PubChem Compound Identification; S/N: signal to noise ratio SD: standard deviation. Compound

m/z0

mean m/z0 ± SD

∆m (ppm)

CID

S/N ± SD

N° out of 4

Succinic acid

117.0193

117.024 ± 0.002

39.9

1110

69.3 ± 31.1

2

Taurine

124.0074

124.010± 0.002

21.1

1123

54.5 ± 13.7

2

Asparagic acid

132.0302

132.032 ± 0.001

13.4

5960

58.8 ± 5.1

3

Threonic acid

135.0299

135.030 ± 0.004

0.7

151152

18.8 ± 14.1

2

L-glutamic acid

146.0459

146.046 ± 0.003

0.8

33032

92.8 ± 49.7

4

Cysteic acid

167.9972

167.000 ± 0.002

16.6

25701

42.6 ± 18.4

3

Formylglutamic acid

174.0408

174.042 ± 0.008

6.9

439376

39.0 ± 6.6

2

Glycerophosphorylethanolamine

214.0486

214.056 ± 0.004

34.6

22833510

4.1 ± 1.5

2

Cytidine

242.0782

242.080 ± 0.012

7.2

6175

22.0 ± 23.1

2

Glutaconylcarnitine

272.1140

272.114 ± 0.002

0.1

53481620

6.4 ± 2.9

2

Glutathione

306.0765

306.078 ± 0.006

4.8

124886

52.8 ± 25.4

2

Lactaminic acid

308.0987

308.094 ± 0.006

-15.3

445063

14.1 ± 3.5

3

cyclic GMP

344.0402

344.040 ± 0.018

-0.5

24316

15.1 ± 11.3

2

UDP

402.9949

403.002 ± 0.005

17.6

6031

29.3 ± 6.6

3

ADP

426.0221

426.029 ± 0.002

16.1

6022

31.5 ± 8.4

2

ATP

505.9885

505.985 ± 0.004

-6.9

5957

9.4 ± 5.2

2

UDP-glucose

565.0478

565.054 ± 0.013

11.1

53477679

20.8 ± 4.9

3

UDP-glucuronate

579.0270

579.026 ± 0.008

-1.7

17473

18.1 ± 0.3

2

UDP-acetylglucosamine

606.0743

606.072 ± 0.005

-3.8

445675

29.8 ± 9.8

4

L-glutathione (oxidized)

611.1447

611.161 ± 0.007

26.7

975

13.3 ± 3.5

3

13

C-labeling. To further validate our approach for subcellular metabolite sampling and analysis, we

performed a stable isotopic tracer experiment with 13C-glucose feeding. Labeled nutrients such as 13Cglucose are commonly used as tracers to investigate the operation of metabolic pathways and the nutrient contribution to the production of different metabolites, or to examine intracellular fluxes. Like most cancer cells, HeLa cells undergo Warburg metabolism, consuming an increased amount of glucose compared to normal differentiated cells. While most glucose carbons are excreted as lactate, carbon is also incorporated into different biomass components such as proteins, peptides, sugars, lipids, and nucleotides in the presence of the rich precursor supply provided in the standard medium.35 Following the procedure described above, we analyzed extracts from HeLa cells grown in the presence of uniformly labeled

13

C-glucose (U-13C-glucose) (n=2) for 48 hours. Different metabolites were


Page 11 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


effectively detected and identified, and several of them were isotopically enriched (Table 2, Figure 3, and Table S-2).

Table 2: Metabolites detected in single-cell extracts of HeLa cells grown on U-13C-glucose Compound

m/z [M-H]-

Number of 13C

Measured ∆m (ppm*) Replicate #1

Measured ∆m (ppm*) Replicate #2

Glutamate

146.0459

0

146.043 (-19.7)

n .d.

GMP

367.0675

5

367.059 (-23.2)

367.075 (20.43)

UDP

408.0117

5

n .d.

408.0163 (11.3)

ADP

431.0389

5

431.039 (0.2)

431.037 (-4.4)

GDP

447.0338

5

447.033 (-1.9)

447.025 (-19.8)

UTP

487.9780

5

487.986 (16.3)

487.983 (10.2)

ATP

511.0052

5

511.003 (-4.4)

511.012 (13.2)

UDP-glucose

576.0847

11

576.079 (-9.8)

576.092 (12.7)

UDP-acetylglucosamine

617.1112

11

617.108 (-5.2)

n. d.

Glutathione

611.1447

0

611.147 (3.8)

n. d.

*ppm values were calculated with accurate theoretical m/z values

In general, only one mass isotopologue per compound was detected. This can be explained by the relatively low signal abundances, as well as by the fact that U-13C-glucose was applied as a carbon source, resulting mainly in uniformly labeled intermediates of glycolysis and the pentose phosphate pathway. Analogously, monoisotopic peaks were almost exclusively detected for natural labeled samples. Peaks were detected at a mass shift of +5 for the ribonucleotides (GMP, UDP, ADP, GDP, UTP, ATP) and at +11 for the activated sugars (UDP-glucose, UDP-GlcNAc), whereas no mass shift was observed for the peaks assigned to glutamate and glutathione. The mass shift of +5 observed for ribonucleotides correlates to fully 13C-labeled ribose with unlabeled purine and pyrimidine bases, in agreement with the study of Chen et al. The latter showed that, in bulk experiments, the prominent flux of the taken-up 13C-glucose via the pentose phosphate pathway results in the incorporation of the glucose carbons into activated ribose, whereas the biosynthesis of the bases can rely on unlabeled metabolites from the growth medium.35 With a mass shift of +11, the peaks attributed to 13C-labeled activated sugars conformed to fully labeled ribose and hexose. As expected, no mass shift was observed for the amino acid glutamate, which is directly derived from the unlabeled glutamine supplemented in the cell medium, or for glutathione, which is synthesized from glutamate, cysteine, and glycine.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 12 of 17

Figure 3. MS analysis of extracts from HeLa cells cultured in naturally labeled and U-13C-labeled glucose. MS spectra of a blank sample, an unlabeled sample, and a 13C-labeled sample are shown for each presented metabolite. The blank samples were acquired from adjacent empty wells on the same MAMS substrate as the respective unlabeled samples. The arrows indicate the peaks attributed to the selected metabolites. * Peak attributed to Glutathione. ** Peak attributed to 13C-UDP-GlcNAc [M+13H]-.


Page 13 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


CONCLUSIONS We developed a method that enables the analysis of cytoplasmic metabolites from single live cells. In contrast to the approaches previously reported for single-cell metabolic studies, the intracellular metabolites can be retrieved and analyzed without removing the cell from its environment and without compromising cell viability. Thus, this approach allows the minimizing of physiological perturbations and the preservation of cellular context, in addition to offering attractive opportunities for analyzing intracellular metabolites at multiple time points and for analyzing different types of molecules from an individual cell (e.g. combined transcriptional readouts and metabolite profiling). Alternative probe design could also be explored to allow for the collection of small organelles36 and their metabolites, currently excluded from the extract.

ASSOCIATED CONTENT Supporting Information Supporting Information for Publication. Detailed information about the compound peaks detected in natural labeled (Table S-1) and 13Clabeled (Table S-2) samples extracted from single HeLa cells by Fluidic Force Microscopy.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 17

AUTHOR INFORMATION Corresponding Authors *

Address: ETH Zurich, Institute of Microbiology, Vladimir-Prelog-Weg 1-5/10, HCI F 429, 8093

Zurich, Switzerland. Phone: +41 44 632 55 24. E-mail: [email protected] *

Address: ETH Zurich, Institute of Microbiology, Vladimir-Prelog-Weg 1-5/10, HCI F 437, 8093

Zurich, Switzerland. Phone: +41 44 632 36 54. E-mail: [email protected] Present Address †

Instituto de Ciencias Ómicas y Biotecnologia Aplicada (ICOBA-PUCP), Pontificia Universidad

Católica del Perú, Lima 32, Lima, Perú Author Contributions ˧

These authors contributed equally.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS This research was supported by ETH Zurich, the Swiss Innovation Promotion Agency CTI-KTI (no. 14336.1 PFNM-NM to T.Z. and J.A.V. and 18511.1 PFNM-NM to T.Z.) and the Swiss National Science Foundation (PZ00P3_142615 to A.J.I.). We are grateful to János Vörös (LBB, ETHZ), Michael Gabi, Pascal Behr, Pablo Dörig (Cytosurge), and Patrick Frederix (Nanosurf) for their constant support. We thank Sean Kilian for support in generating Figure 1.


Page 15 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


REFERENCES (1) Tang, F. C.; Lao, K. Q.; Surani, M. A. Nat. Methods 2011, 8 (4), S6-S11. (2) Fessenden, M. Nature 2016, 540 (7631), 153-155. (3) Zenobi, R. Science 2013, 342 (6163), 1243259. (4) Pan, Z. Z.; Raftery, D. Anal. Bioanal. Chem. 2007, 387 (2), 525-527. (5) Svatos, A. Anal. Chem. 2011, 83 (13), 5037-5044. (6) Bowen, B. P.; Northen, T. R. J. Am. Soc. Mass Spectrom. 2010, 21 (9), 1471-1476. (7) Heinemann, M.; Zenobi, R. Curr. Opin. Biotechnol. 2011, 22 (1), 26-31. (8) Amantonico, A.; Oh, J. Y.; Sobek, J.; Heinemann, M.; Zenobi, R. Angew. Chem. Int. Edit. 2008, 47 (29), 5382-5385. (9) Martano, G.; Delmotte, N.; Kiefer, P.; Christen, P.; Kentner, D.; Bumann, D.; Vorholt, J. A. Nat. Protoc. 2015, 10 (1), 1-11. (10) Tachibana, C. Science 2014, 345, 1519-1521. (11) Nemes, P.; Knolhoff, A. M.; Rubakhin, S. S.; Sweedler, J. V. Anal. Chem. 2011, 83 (17), 6810-6817. (12) Nemes, P.; Knolhoff, A. M.; Rubakhin, S. S.; Sweedler, J. V. ACS Chem. Neurosci. 2012, 3 (10), 782-792. (13) Ong, T. H.; Kissick, D. J.; Jansson, E. T.; Comi, T. J.; Romanova, E. V.; Rubakhin, S. S.; Sweedler, J. V. Anal. Chem. 2015, 87 (14), 7036-7042. (14) Janson, E. T.; Comi, T. J.; Rubakhin, S. S.; Sweedler, J. V. ACS Chem. Biol. 2016, 11 (9), 2588-2595. (15) Urban, P. L.; Jefimovs, K.; Amantonico, A.; Fagerer, S. R.; Schmid, T.; Madler, S.; Puigmarti-Luis, J.; Goedecke, N.; Zenobi, R. Lab Chip 2010, 10 (23), 3206-3209. (16) Ibanez, A. J.; Fagerer, S. R.; Schmidt, A. M.; Urban, P. L.; Jefimovs, K.; Geiger, P.; Dechant, R.; Heinemann, M.; Zenobi, R. Proc. Natl. Acad. Sci. U.S.A. 2013, 110 (22), 87908794. (17) Krismer, J.; Steinhoff, R. F.; Zenobi, R. Chimia 2016, 70 (4), 236-239. (18) Masujima, T. Anal. Sci. 2009, 25 (8), 953-960. (19) Date, S.; Mizuno, H.; Tsuyama, N.; Harada, T.; Masujima, T. Anal. Sci. 2012, 28 (3), 201-203. (20) Fukano, Y.; Tsuyama, N.; Mizuno, H.; Date, S.; Takano, M.; Masujima, T. Nanomedicine 2012, 7 (9), 1365-1374. (21) Mizuno, H.; Tsuyama, N.; Date, S.; Harada, T.; Masujima, T. Anal. Sci. 2008, 24 (12), 1525-1527. (22) Esaki, T.; Masujima, T. Anal. Sci. 2015, 31 (12), 1211-1213. (23) Gong, X. Y.; Zhao, Y. Y.; Cai, S. Q.; Fu, S. J.; Yang, C. D.; Zhang, S. C.; Zhang, X. R. Anal. Chem. 2014, 86 (8), 3809-3816. (24) Pan, N.; Rao, W.; Kothapalli, N. R.; Liu, R. M.; Burgett, A. W. G.; Yang, Z. B. Anal. Chem. 2014, 86 (19), 9376-9380. (25) Zhang, L. W.; Vertes, A. Anal. Chem. 2015, 87 (20), 10397-10405. (26) Aerts, J. T.; Louis, K. R.; Crandall, S. R.; Govindaiah, G.; Cox, C. L.; Sweedler, J. V. Anal. Chem. 2014, 86 (6), 3203-3208. (27) Guillaume-Gentil, O.; Grindberg, R. V.; Kooger, R.; Dorwling-Carter, L.; Martinez, V.; Ossola, D.; Pilhofer, M.; Zambelli, T.; Vorholt, J. A. Cell 2016, 166 (2), 506-516. (28) Meister, A.; Gabi, M.; Behr, P.; Studer, P.; Voros, J.; Niedermann, P.; Bitterli, J.; PoleselMaris, J.; Liley, M.; Heinzelmann, H.; Zambelli, T. Nano Lett. 2009, 9 (6), 2501-2507. (29) Guillaume-Gentil, O.; Potthoff, E.; Ossola, D.; Franz, C. M.; Zambelli, T.; Vorholt, J. A. Trends Biotechnol. 2014, 32 (7), 381-388. (30) Guillaume-Gentil, O.; Potthoff, E.; Ossola, D.; Dorig, P.; Zambelli, T.; Vorholt, J. A. Small 2013, 9 (11), 1904-1907. 15 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 17

(31) Schmidt, A. M.; Fagerer, S. R.; Jefimovs, K.; Buettner, F.; Marro, C.; Siringil, E. C.; Boehlen, K. L.; Pabst, M.; Ibanez, A. J. Analyst 2014, 139 (22), 5709-5717. (32) Jeffries, N. Bioinformatics 2005, 21 (14), 3066-3073. (33) Vermillion-Salsbury, R. L.; Hercules, D. M. Rapid Commun. Mass Sp. 2002, 16 (16), 1575-1581. (34) Kentner, D.; Martano, G.; Callon, M.; Chiquet, P.; Brodmann, M.; Burton, O.; Wahlander, A.; Nanni, P.; Delmotte, N.; Grossmann, J.; Limenitakis, J.; Schlapbach, R.; Kiefer, P.; Vorholt, J. A.; Hiller, S.; Bumann, D. Proc. Natl. Acad. Sci. U.S.A. 2014, 111 (27), 9929-9934. (35) Chen, Y. J.; Huang, X. J.; Mahieu, N. G.; Cho, K.; Schaefer, J.; Patti, G. J. Biochemistry 2014, 53 (29), 4755-4757. (36) Actis, P.; Maalouf, M. M.; Kim, H. J.; Lohith, A.; Vilozny, B.; Seger, R. A.; Pourmand, N. ACS Nano 2014, 8 (1), 546-553.


Page 17 of 17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


TABLE OF CONTENTS For TOC only


Single-Cell Mass Spectrometry of Metabolites ... - ACS Publications

Recommend Documents