Noninvasive Monitoring of Neural Activity With Bioluminescence
LIN, NING; LI, MINGCHANG; FRIEDLANDER, ROBERT M.
To understand and decipher the neural circuitry in the brain, it is important to correlate neuronal activation with behavior of the subject. Single or multi-electrode recording of neurophysiology is a proven method and has been widely used in animal and human studies.1–3 Optic-based imaging via 2-photon or multi-photon microscopy has shown great promise to capture single-neural activities during natural physiological responses.4–6 Surface electroencephalogram (EEG) is noninvasive and has seen improving special and temporal resolutions. Most recently, a group of scientists from Harvard University reported application of bioluminescence in real-time neuronal monitoring, adding yet another useful element to this expanding toolbox. The study,7 published in Nature Neuroscience, described the utilization of a synthetic, calcium-sensitive photoprotein to detect neuronal firing in specific regions of zebrafish brain.
The authors first constructed a chimeric fusion protein GFP-apoAequorin and used it as a calcium sensor in zebrafish neurons. Aequorin is naturally produced by the jellyfish Aequorea Victoria, and when it binds calcium, it facilitates the oxidation of substrate coelenterazine (CLZN) and photon emission.8 The efficiency of this reaction is enhanced if Aequorin is associated with green fluorescent protein (GFP), and the sensitivity of Ca2+ concentrations has been reportedly in the range of 100 nM to 10 uM.8 In this study, the fusion protein was expressed exclusively in zebrafish neurons via a neuro-β-tubulin promoter, and the zebrafish was treated with CLZN bath before neuroluminescence was monitored and recorded. The zebrafish was allowed to swim freely in a behavior chamber while the emitted photons were collected by a large-area photomultiplier tube and the fish movement was tracked simultaneously by an infrared camera (Figure A). The authors reported that neuroluminescence signals were stable for long-time monitoring (>24 hr) and the signal intensity coincident with spontaneous and evoked swim events (Figure B). The time-to-peak of signal intensity was estimated to be 5 to 10 ms and a slower decay time of 25 ms (Figure C), which were consistent with other synthetic Ca2+ indicators.
Next, the authors specifically expressed GFP-apoAequorin in hypocretin/orexin (HCRT) system, a group of neurons located in the hypothalamus that have been implicated in the function of arousal control (Figure D). The authors aimed to measure directly the activity of HCRT neurons during rest and wakefulness of zebrafish. During more than 24 hours of recording, they observed an increase in the frequency of neuroluminescent signals from HCRT neurons during morning active periods and decreased signal during rest or brief arousals at night. They also found that individual neuroluminescence signals produced by HCRT neurons can be categorized into two distinct groups by their amplitudes (cutoff = 200 photons/50 ms). Both large (signal amplitude > 200 photons/50 ms) and small events were associated with swim bouts, but the behavior latency, distance swum by the zebrafish, and peak swim velocity following either signal amplitude was consistently different. The authors concluded that HCRT neurons promote wakefulness and that neuroluminescence system has sufficient temporal resolution to study such questions in neurophysiology.
While this report described an impressive technology that allows real-time, noninvasive monitoring of neuronal activities, the neuroluminescence system does possess significant limitations. Bioluminescence, as the authors have realized, is a non-imaging technique, thus spatial resolution has to be sacrificed and single-neuron firing cannot be distinguished. Rather, it allows convenient and continuous recording of a cohort of genetically labeled neurons that may or may not be activated simultaneously during a specific behavior response. Nevertheless, neuroluminescence, along with electrode- and optic-based instruments, affords neuroscientist another tool to study the computational network of the brain.
ROBERT M. FRIEDLANDER
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