COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package

Genetic Probe for Visualizing Glutamatergic Synapses and Vesicles by 3D Electron Microscopy

Communication between neurons relies on the release of diverse neurotransmitters, which represent a key-defining feature of a neuron's chemical and functional identity. Neurotransmitters are packaged into vesicles by specific vesicular transporters. However, tools for labeling and imaging synapses and synaptic vesicles based on their neurochemical identity remain limited. We developed a genetically encoded probe to identify glutamatergic synaptic vesicles at the levels of both light and electron microscopy (EM) by fusing the mini singlet oxygen generator (miniSOG) probe to an intralumenal loop of the vesicular glutamate transporter-2. We then used a 3D imaging method, serial block-face scanning EM, combined with a deep learning approach for automatic segmentation of labeled synaptic vesicles to assess the subcellular distribution of transporter-defined vesicles at nanometer scale. These tools represent a new resource for accessing the subcellular structure and molecular machinery of neurotransmission and for transmitter-defined tracing of neuronal connectivity

Sex disparate gut microbiome and metabolome perturbations precede disease progression in a mouse model of Rett syndrome.

Rett syndrome (RTT) is a regressive neurodevelopmental disorder in girls, characterized by multisystem complications including gut dysbiosis and altered metabolism. While RTT is known to be caused by mutations in the X-linked gene MECP2, the intermediate molecular pathways of progressive disease phenotypes are unknown. Mecp2 deficient rodents used to model RTT pathophysiology in most prior studies have been male. Thus, we utilized a patient-relevant mouse model of RTT to longitudinally profile the gut microbiome and metabolome across disease progression in both sexes. Fecal metabolites were altered in Mecp2e1 mutant females before onset of neuromotor phenotypes and correlated with lipid deficiencies in brain, results not observed in males. Females also displayed altered gut microbial communities and an inflammatory profile that were more consistent with RTT patients than males. These findings identify new molecular pathways of RTT disease progression and demonstrate the relevance of further study in female Mecp2 animal models

CDeep3M—Plug-and-Play cloud-based deep learning for image segmentation

As biomedical imaging datasets expand, deep neural networks are considered vital for image processing, yet community access is still limited by setting up complex computational environments and availability of high-performance computing resources. We address these bottlenecks with CDeep3M, a ready-to-use image segmentation solution employing a cloud-based deep convolutional neural network. We benchmark CDeep3M on large and complex two-dimensional and three-dimensional imaging datasets from light, X-ray, and electron microscopy

Microglial Gi-dependent dynamics regulate brain network hyperexcitability.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating MgPTX mice to genetically inhibit Gi in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases

Microglial Gi-dependent dynamics regulate brain network hyperexcitability.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating MgPTX mice to genetically inhibit Gi in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases

Spatial mapping of mitochondrial networks and bioenergetics in lung cancer.

Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells1. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity2,3. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours

Spatial mapping of mitochondrial networks and bioenergetics in lung cancer.

Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells1. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity2,3. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours

Spatial mapping of mitochondrial networks and bioenergetics in lung cancer.

Acknowledgements: We thank C. Zamilpa, D. Abeydeera and J. Collins, at UCLA’s Crump Imaging Technology Center, for assistance with PET–CT imaging of the mice. We thank the Translational Pathology Core Laboratory at UCLA’s DGSOM for assistance with tumour sample preparation and processing. We also thank M. McCaffery for assistance with electron microscopy imaging on in vitro-cultured cells and J. Castillo for assistance with graphics. This research was supported by the NIH National Center for Advancing Translational Science UCLA CTSI grant number UL1TR001881. D.B.S. was supported by the UCLA CTSI KL2 Translational Science Award grant number KL2TR001882 at the UCLA David Geffen School of Medicine, the UCLA Jonsson Comprehensive Cancer Center grant P30 CA016042, NIH/NCI R01 CA208642-01, American Cancer Society grant numbers RSG-16-234-01-TBG and MBG-19-172-01-MBG, and Department of Defense LCRP grant numbers W81XWH-13-1-0439 and W81XWH-18-1-0295. M.H. was supported by NIH/NCI R01 CA208642-01. A.L. was supported by grant NIH-NCI K08 CA245249-01A1 and a LUNGevity 2019 Career Development Award. M. Momcilovic was supported by American Cancer Society grant numbers RSG-16-234-01-TBG and MBG-19-172-01-MBG. A.G. was supported by an NIH/NCI R01 CA208642-01 diversity supplement. J.T.L. was supported by NIH/NCI P30 CA016042. D.M.W. is supported by EMBO long-term fellowship ALTF 828-2021. This research was supported by the Joyce and Saul Brandman Fund for Medical Research. We extend our heartfelt thanks and appreciation to the Scott family and the Carrie Strong Foundation as well as B. and D. Goldfarb for their generous support.Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells1. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity2,3. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours

Spatial mapping of mitochondrial networks and bioenergetics in lung cancer.

Acknowledgements: We thank C. Zamilpa, D. Abeydeera and J. Collins, at UCLA’s Crump Imaging Technology Center, for assistance with PET–CT imaging of the mice. We thank the Translational Pathology Core Laboratory at UCLA’s DGSOM for assistance with tumour sample preparation and processing. We also thank M. McCaffery for assistance with electron microscopy imaging on in vitro-cultured cells and J. Castillo for assistance with graphics. This research was supported by the NIH National Center for Advancing Translational Science UCLA CTSI grant number UL1TR001881. D.B.S. was supported by the UCLA CTSI KL2 Translational Science Award grant number KL2TR001882 at the UCLA David Geffen School of Medicine, the UCLA Jonsson Comprehensive Cancer Center grant P30 CA016042, NIH/NCI R01 CA208642-01, American Cancer Society grant numbers RSG-16-234-01-TBG and MBG-19-172-01-MBG, and Department of Defense LCRP grant numbers W81XWH-13-1-0439 and W81XWH-18-1-0295. M.H. was supported by NIH/NCI R01 CA208642-01. A.L. was supported by grant NIH-NCI K08 CA245249-01A1 and a LUNGevity 2019 Career Development Award. M. Momcilovic was supported by American Cancer Society grant numbers RSG-16-234-01-TBG and MBG-19-172-01-MBG. A.G. was supported by an NIH/NCI R01 CA208642-01 diversity supplement. J.T.L. was supported by NIH/NCI P30 CA016042. D.M.W. is supported by EMBO long-term fellowship ALTF 828-2021. This research was supported by the Joyce and Saul Brandman Fund for Medical Research. We extend our heartfelt thanks and appreciation to the Scott family and the Carrie Strong Foundation as well as B. and D. Goldfarb for their generous support.Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells1. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity2,3. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours