The pore-forming subunit MCU of the mitochondrial Ca2+ uniporter is required for normal glucose-stimulated insulin secretion in vitro and in vivo in mice.

AIMS/HYPOTHESIS: Mitochondrial oxidative metabolism is central to glucose-stimulated insulin secretion (GSIS). Whether Ca2+ uptake into pancreatic beta cell mitochondria potentiates or antagonises this process is still a matter of debate. Although the mitochondrial Ca2+ importer (MCU) complex is thought to represent the main route for Ca2+ transport across the inner mitochondrial membrane, its role in beta cells has not previously been examined in vivo. METHODS: Here, we inactivated the pore-forming subunit of the MCU, encoded by Mcu, selectively in mouse beta cells using Ins1Cre-mediated recombination. Whole or dissociated pancreatic islets were isolated and used for live beta cell fluorescence imaging of cytosolic or mitochondrial Ca2+ concentration and ATP production in response to increasing glucose concentrations. Electrophysiological recordings were also performed on whole islets. Serum and blood samples were collected to examine oral and i.p. glucose tolerance. RESULTS: Glucose-stimulated mitochondrial Ca2+ accumulation (p< 0.05), ATP production (p< 0.05) and insulin secretion (p< 0.01) were strongly inhibited in beta cell-specific Mcu-null (ßMcu-KO) animals, in vitro, as compared with wild-type (WT) mice. Interestingly, cytosolic Ca2+ concentrations increased (p< 0.001), whereas mitochondrial membrane depolarisation improved in ßMcu-KO animals. ßMcu-KO mice displayed impaired in vivo insulin secretion at 5 min (p< 0.001) but not 15 min post-i.p. injection of glucose, whilst the opposite phenomenon was observed following an oral gavage at 5 min. Unexpectedly, glucose tolerance was improved (p< 0.05) in young ßMcu-KO (<12 weeks), but not in older animals vs WT mice. CONCLUSIONS/INTERPRETATION: MCU is crucial for mitochondrial Ca2+ uptake in pancreatic beta cells and is required for normal GSIS. The apparent compensatory mechanisms that maintain glucose tolerance in ßMcu-KO mice remain to be established.

Slice-illuminated optical projection tomography.

To improve the imaging performance of optical projection tomography (OPT) in live samples, we have explored a parallelized implementation of semi-confocal line illumination and detection to discriminate against scattered photons. Slice-illuminated OPT (sl-OPT) improves reconstruction quality in scattering samples by reducing interpixel crosstalk at the cost of increased acquisition time. For in vivo imaging, this can be ameliorated through the use of compressed sensing on angularly undersampled OPT data sets. Here, we demonstrate sl-OPT applied to 3D imaging of bead phantoms and live adult zebrafish.

Single-shot optical projection tomography for high-speed volumetric imaging of dynamic biological samples.

A single-shot adaptation of Optical Projection Tomography (OPT) for high-speed volumetric snapshot imaging of dynamic mesoscopic biological samples is presented. Conventional OPT has been applied to in vivo imaging of animal models such as D. rerio, but the sequential acquisition of projection images typically requires samples to be immobilized during the acquisition. A proof-of-principle system capable of single-shot tomography of a ~1 mm3 volume is presented, demonstrating camera-limited rates of up to 62.5 volumes/s, which has been applied to 3D imaging of a freely swimming zebrafish embryo. This is achieved by recording eight projection views simultaneously on four low-cost CMOS cameras. With no stage required to rotate the sample, this single-shot OPT system can be implemented with a component cost of under £5000. The system design can be adapted to different sized fields of view and may be applied to a broad range of dynamic samples, including high throughput flow cytometry applied to model organisms and fluid dynamics studies.

Long-Duration and Non-Invasive Photoacoustic Imaging of Multiple Anatomical Structures in a Live Mouse Using a Single Contrast Agent.

Long-duration in vivo simultaneous imaging of multiple anatomical structures is useful for understanding physiological aspects of diseases, informative for molecular optimization in preclinical models, and has potential applications in surgical settings to improve clinical outcomes. Previous studies involving simultaneous imaging of multiple anatomical structures, for example, blood and lymphatic vessels as well as peripheral nerves and sebaceous glands, have used genetically engineered mice, which require expensive and time-consuming methods. Here, an IgG4 isotype control antibody is labeled with a near-infrared dye and injected into a mouse ear to enable simultaneous visualization of blood and lymphatic vessels, peripheral nerves, and sebaceous glands for up to 3 h using photoacoustic microscopy. For multiple anatomical structure imaging, peripheral nerves and sebaceous glands are imaged inside the injected dye-labeled antibody mass while the lymphatic vessels are visualized outside the mass. The efficacy of the contrast agent to label and localize deep medial lymphatic vessels and lymph nodes using photoacoustic computed tomography is demonstrated. The capability of a single injectable contrast agent to image multiple structures for several hours will potentially improve preclinical therapeutic optimization, shorten discovery timelines, and enable clinical treatments.

Convolutional neural networks for reconstruction of undersampled optical projection tomography data applied to in vivo imaging of zebrafish.

Optical projection tomography (OPT) is a 3D mesoscopic imaging modality that can utilize absorption or fluorescence contrast. 3D images can be rapidly reconstructed from tomographic data sets sampled with sufficient numbers of projection angles using the Radon transform, as is typically implemented with optically cleared samples of the mm-to-cm scale. For in vivo imaging, considerations of phototoxicity and the need to maintain animals under anesthesia typically preclude the acquisition of OPT data at a sufficient number of angles to avoid artifacts in the reconstructed images. For sparse samples, this can be addressed with iterative algorithms to reconstruct 3D images from undersampled OPT data, but the data processing times present a significant challenge for studies imaging multiple animals. We show here that convolutional neural networks (CNN) can be used in place of iterative algorithms to remove artifacts-reducing processing time for an undersampled in vivo zebrafish dataset from 77 to 15 minutes. We also show that using CNN produces reconstructions of equivalent quality to compressed sensing with 40% fewer projections. We further show that diverse training data classes, for example, ex vivo mouse tissue data, can be used for CNN-based reconstructions of OPT data of other species including live zebrafish.