A genetically encoded FRET lactate sensor and its use to detect the Warburg effect in single cancer cells - PubMed (original) (raw)

A genetically encoded FRET lactate sensor and its use to detect the Warburg effect in single cancer cells

Alejandro San Martín et al. PLoS One. 2013.

Abstract

Lactate is shuttled between and inside cells, playing metabolic and signaling roles in healthy tissues. Lactate is also a harbinger of altered metabolism and participates in the pathogenesis of inflammation, hypoxia/ischemia, neurodegeneration and cancer. Many tumor cells show high rates of lactate production in the presence of oxygen, a phenomenon known as the Warburg effect, which has diagnostic and possibly therapeutic implications. In this article we introduce Laconic, a genetically-encoded Forster Resonance Energy Transfer (FRET)-based lactate sensor designed on the bacterial transcription factor LldR. Laconic quantified lactate from 1 µM to 10 mM and was not affected by glucose, pyruvate, acetate, betahydroxybutyrate, glutamate, citrate, α-ketoglutarate, succinate, malate or oxalacetate at concentrations found in mammalian cytosol. Expressed in astrocytes, HEK cells and T98G glioma cells, the sensor allowed dynamic estimation of lactate levels in single cells. Used in combination with a blocker of the monocarboxylate transporter MCT, the sensor was capable of discriminating whether a cell is a net lactate producer or a net lactate consumer. Application of the MCT-block protocol showed that the basal rate of lactate production is 3-5 fold higher in T98G glioma cells than in normal astrocytes. In contrast, the rate of lactate accumulation in response to mitochondrial inhibition with sodium azide was 10 times lower in glioma than in astrocytes, consistent with defective tumor metabolism. A ratio between the rate of lactate production and the rate of azide-induced lactate accumulation, which can be estimated reversibly and in single cells, was identified as a highly sensitive parameter of the Warburg effect, with values of 4.1 ± 0.5 for T98G glioma cells and 0.07 ± 0.007 for astrocytes. In summary, this article describes a genetically-encoded sensor for lactate and its use to measure lactate concentration, lactate flux, and the Warburg effect in single mammalian cells.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Laconic, a FRET lactate sensor based on the transcriptional regulator LldR.

(A) Crystallographic structure of LldR from Corynebacterium glutamicum, and 3D-structure of LldR from Escherichia coli predicted using LldR from C. glutamicum and FadR from E. coli as templates (M4T Server 3.0 from the Fiser Laboratory

http://www.fiserlab.org/servers\_table.htm

). (B) General design: the transcriptional regulator LldR is sandwiched between fluorescent proteins mTFP and Venus, with artificial peptides separating the proteins (blue and orange linkers). (C) Effect of 10 mM lactate on the fluorescence ratio of 8 variants of the lactate sensor based on LldR from either E. coli or C. glutamicum. The most responsive of the constructs, indicated by the arrow, was used in the rest of the study.

Figure 2

Figure 2. In vitro characterization of Laconic.

(A) Emission spectra in the absence and presence of 10 mM lactate. (B) The ratio between mTFP and Venus fluorescence (at 430 nm excitation) was measured at 0, 0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 5 and 10 mM lactate. The continuous line corresponds to the best fit of a double rectangular hyperbola to the data, with apparent dissociation constant (KD) values of 8 ± 2 µM and 830 ± 160 µM, and respective maximum ΔR values of 8 ± 0.4% and 11 ± 0.4%. (C) Lactate dose-response curves were measured at the indicated pH values. The continuous line corresponds to the best fit of a double rectangular hyperbola to the data at pH .4. (D) Response of the sensor to 5 mM of lactate, pyruvate, acetate, glutamate, β-hydroxy-butyrate and glucose, 1 mM of α-ketoglutarate, succinate, malate or oxalacetate, or increasing concentrations of citrate (0.01, 0.1 and 1 mM). In panels E to I, lactate dose-response curves were measured in the presence of 1 mM acetate, glutamate, β-hydroxy-butyrate or glucose (E), in 1 mM of α-ketoglutarate, succinate, malate or oxalacetate (F), in 0.25, 1 mM or 10 mM pyruvate (G), in 0.01, 0.1 mM or 1 mM citrate (H), and in 0.2 µM NADH, 100 µM NAD+, or 0.2 µM NADH plus 100 µM NAD+ (I). The continuous lines correspond to the best fit of a double rectangular hyperbola to control data.

Figure 3

Figure 3. Imaging of cytosolic lactate.

(A) HEK293 cells expressing Laconic imaged at 440 excitation/535 emission). Scale bar is 20 µm. (B) Fluorescence ratio was measured at 0.01, 0.1, 1 and 10 mM extracellular lactate in HEK293 cells treated with metabolic inhibitors and permeabilized to H+ as described in Material and Methods. (C) The time course of mTFP and Venus fluorescences were measured in the presence of 2 mM glucose/1 mM lactate or 10 mM pyruvate, as indicated. A cell with low expression of the sensor requiring strong illumination was chosen to demonstrate the insensitivity of the fluorescence ratio to photobleaching. The fluorescence ratio was converted into lactate concentration using the ratio in pyruvate (zero lactate) as described in the text.

Figure 4

Figure 4. Determination of metabolic fluxes.

(A) Diagram of lactate metabolism. The cytosolic concentration of lactate depends on the balance between glycolytic production, mitochondrial consumption of pyruvate and lactate, and the exchange with the extracellular lactate pool via MCTs. (B) Intracellular lactate was monitored in individual HEK293 cells during transient exposures to phloretin (50 µM), in the presence of 25 mM glucose (top panel) or 1 mM lactate (bottom panel). (C) The responses of intracellular lactate to transient inhibitions of the MCT with phloretin (50 µM) or pCMBS (500 µM) were sequentially measured in the same HEK293 cell in the presence of 25 mM glucose. The straight lines represent slopes of lactate accumulation fitted by linear regression during the first minute of exposure. The bar graph summarizes data from three experiments. (D) The effect of 5 mM sodium azide was measured in an astrocyte during exposure to 50 µM phloretin.

Figure 5

Figure 5. Metabolic characterization of tumor cells.

(A) An astrocyte expressing Laconic was sequentially exposed to 5 mM azide, 50 µM phloretin and 500 µM pCMBS. The straight lines represent initial slopes of lactate accumulation fitted by linear regression within the same range of ratio values. (B) A T98G glioma cell expressing Laconic was sequentially exposed to 5 mM azide, 50 µM phloretin and 500 µM pCMBS. The straight lines represent initial slopes of lactate accumulation fitted by linear regression within the same range of ratio values. (C) Summary of the initial slopes (Δ ratio/min) obtained in three experiments of the type shown in A and B. (D) Correlation plot between the rates of lactate accumulation (Δ ratio/min) in azide and in pCMBS. Symbols represent single astrocytes (white), HEK293 cells (gray) or T98G cells (black). (E) The Warburg Index was estimated as the ratio between the rates of lactate production with pCMBS and lactate accumulation with azide, and used to color the silhouette of each cell according to the 16-color look up table. The inset shows an isolated cell that was located about 100 µm from the cluster. The bar graph summarizes data from 3 experiments in each cell type. Scale bars are 20 µm. *, p < 0.05 between every cell type.

Similar articles

Cited by

References

    1. Gladden LB (2004) Lactate metabolism: a new paradigm for the third millennium. J Physiol 558: 5–30. - PMC - PubMed
    1. Brooks GA (2009) Cell-cell and intracellular lactate shuttles. J Physiol 587: 5591–5600. jphysiol.2009.178350 [pii];10.1113/jphysiol.2009.178350 [doi]. - DOI - PMC - PubMed
    1. Pellerin L, Bouzier-Sore AK, Aubert A, Serres S, Merle M, et al. (2007) Activity-dependent regulation of energy metabolism by astrocytes: an update. Glia 55: 1251–1262. - PubMed
    1. Barros LF, Deitmer JW (2010) Glucose and lactate supply to the synapse. Brain Res Rev 63: 149–159. - PubMed
    1. Belanger M, Allaman I, Magistretti PJ (2011) Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation. Cell Metab 14: 724–738 S1550-4131(11)00420-7 [pii];10.1016/j.cmet.2011.08.016 - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources