Single-cell imaging tools for brain energy metabolism: a review

Abstract

Neurophotonics comes to light at a time in which advances in microscopy and improved calcium reporters are paving the way toward high-resolution functional mapping of the brain. This review relates to a parallel revolution in metabolism. We argue that metabolism needs to be approached both in vitro and in vivo, and that it does not just exist as a low-level platform but is also a relevant player in information processing. In recent years, genetically encoded fluorescent nanosensors have been introduced to measure glucose, glutamate, ATP, NADH, lactate, and pyruvate in mammalian cells. Reporting relative metabolite levels, absolute concentrations, and metabolic fluxes, these sensors are instrumental for the discovery of new molecular mechanisms. Sensors continue to be developed, which together with a continued improvement in protein expression strategies and new imaging technologies, herald an exciting era of high-resolution characterization of metabolism in the brain and other organs.

Keywords: Förster resonance energy transfer; glycolysis; membrane transport; metabolic flux; mitochondria; optogenetics.

Fig. 1

Organization of metabolism. The living organism is represented as a hierarchical stack of modular systems. Interactions at any level are stronger than at higher levels, which is the basis for dissectability. In this example regarding metabolism, the enzyme hexokinase (represented by a blue oval) is shown to be constituted by amino acids (black ovals). In the next level up, hexokinase associates with other enzymes and cofactors to constitute the glycolytic machinery (green oval). Further up the organizational ladder, the glycolytic machinery associates with organelles and other structures to form an astrocyte (yellow oval), which in turn interacts with neurons and vessels to shape the neurogliovascular unit (orange oval) [after J. G. Miller’s generalized living system¹³].

Fig. 2

Examples of the use of genetically encoded nanosensors for the estimation of metabolite levels, concentrations, and fluxes in single cells. (a) Two adjacent astrocytes expressing ATeam 1.03 were exposed to the mitochondrial blocker sodium azide (5 mM). Although the metabolic depletion in one of them appears to be stronger, this may not be the case (see text). (b) An astrocyte expressing Peredox in the cytosol was exposed to a rise in extracellular ${\mathrm{K}}^{+}$ from 3 to 12 mM. The observed increase in $\mathrm{NADH}/{\mathrm{NAD}}^{+}$ ratio is consistent with a primary stimulation of glycolytic NADH production, but not with a stimulation of mitochondrial NADH consumption. (c) The uptake of 5 mM lactate was measured in a T98G glioma cell using Laconic in the absence or presence of the MCT blockers phloretin (50 μM) and pCMBS (500 μM). The partial inhibitory effect of phloretin becomes evident. (d) Determination of metabolic fluxes with inhibitor-stop protocols. In the steady state, the cytosolic concentrations of glucose, lactate, and pyruvate are constant. Interruption of the steady state with a blocker of the glucose transporter GLUT (cytochalasin B) or of the monocarboxylate transporter MCT (AR-C155858) produces depletion or accumulation at an initial rate equal to the steady-state flux of the pathway. The right panels provide examples of astrocytic glucose consumption estimated with 20 μM cytochalasin B, HEK293 lactate production estimated with 1 μM AR-C155858, and astrocytic pyruvate consumption estimated in the absence of glucose and lactate with 1 μM AR-C155858, as detailed in Ref. . Rates are indicated.

Fig. 3

Mammalian metabolic networks. Schematic representation of mammalian metabolism. Points correspond to metabolites and lines to chemical transformations (from Alberts et al., 1983, cited in Ref. 129). The network location of the six metabolites that have been imaged in mammalian cells is indicated: glucose (glc), pyruvate (pyr), lactate (lac), glutamate (glu), NADH, and ATP.