ABCC6 is a basolateral plasma membrane protein

RATIONALE:: ABCC6 plays a crucial role in ectopic calcification; mutations of the gene cause pseudoxanthoma elasticum and general arterial calcification of infancy. To elucidate the role of ABCC6 in cellular physiology and disease, it is crucial to establish the exact subcellular localization of the native ABCC6 protein. OBJECTIVE:: In a recent article in Circulation Research, ABCC6 was reported to localize to the mitochondria-associated membrane and not the plasma membrane. As the suggested mitochondrial localization is inconsistent with published data and the presumed role of ABCC6, we performed experiments to determine the cellular localization of ABCC6 in its physiological environment. METHODS AND RESULTS:: We performed immunofluorescent labeling of frozen mouse and human liver sections, as well as primary hepatocytes. We used several different antibodies recognizing human and mouse ABCC6. Our results unequivocally show that ABCC6 is in the basolateral membrane of hepatocytes and is not associated with the mitochondria, mitochondria-associated membrane, or the endoplasmic reticulum. CONCLUSIONS:: Our findings support the model that ABCC6 is in the basolateral membrane, mediating the sinusoidal efflux of a metabolite from the hepatocytes to systemic circulation. © 2013 American Heart Association, Inc

Multitemporal Very High Resolution from Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest

In this paper, the scientific outcomes of the 2016 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society are discussed. The 2016 Contest was an open topic competition based on a multitemporal and multimodal dataset, which included a temporal pair of very high resolution panchromatic and multispectral Deimos-2 images and a video captured by the Iris camera on-board the International Space Station. The problems addressed and the techniques proposed by the participants to the Contest spanned across a rather broad range of topics, and mixed ideas and methodologies from the remote sensing, video processing, and computer vision. In particular, the winning team developed a deep learning method to jointly address spatial scene labeling and temporal activity modeling using the available image and video data. The second place team proposed a random field model to simultaneously perform coregistration of multitemporal data, semantic segmentation, and change detection. The methodological key ideas of both these approaches and the main results of the corresponding experimental validation are discussed in this paper

Open Data for Global Multimodal Land Use Classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest

In this paper, we present the scientific outcomes of the 2017 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. The 2017 Contest was aimed at addressing the problem of local climate zones classification based on a multitemporal and multimodal dataset, including image (Landsat 8 and Sentinel-2) and vector data (from OpenStreetMap). The competition, based on separate geographical locations for the training and testing of the proposed solution, aimed at models that were accurate (assessed by accuracy metrics on an undisclosed reference for the test cities), general (assessed by spreading the test cities across the globe), and computationally feasible (assessed by having a test phase of limited time). The techniques proposed by the participants to the Contest spanned across a rather broad range of topics, and of mixed ideas and methodologies deriving from computer vision and machine learning but also deeply rooted in the specificities of remote sensing. In particular, rigorous atmospheric correction, the use of multidate images, and the use of ensemble methods fusing results obtained from different data sources/time instants made the difference

Machine learning for earth system observation and prediction

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Genomics and transcriptomics of Xanthomonas campestris species challenge the concept of core type III effectome

The bacterial species Xanthomonas campestris infects a wide range of Brassicaceae. Specific pathovars of this species cause black rot (pv. campestris), bacterial blight of stock (pv. incanae) or bacterial leaf spot (pv. raphani). In this study, we extended the genomic coverage of the species by sequencing and annotating the genomes of strains from pathovar incanae (CFBP 1606R and CFBP 2527R), pathovar raphani (CFBP 5828R) and a pathovar formerly named barbareae (CFBP 5825R). While comparative analyses identified a large core ORFeome at the species level, the core type III effectome was limited to only three putative type III effectors (XopP, XopF1 and XopAL1). In Xanthomonas, these effector proteins are injected inside the plant cells by the type III secretion system and contribute collectively to virulence. A deep and strand-specific RNA sequencing strategy was adopted in order to experimentally refine genome annotation for strain CFBP 5828R. This approach also allowed the experimental definition of novel ORFs and non-coding RNA transcripts. Using a constitutively active allele of hrpG, a master regulator of the type III secretion system, a HrpG-dependent regulon of 141 genes co-regulated with the type III secretion system was identified. Importantly, all these genes but seven are positively regulated by HrpG and 56 of those encode components of the Hrp type III secretion system and putative effector proteins. This dataset is an important resource to mine for novel type III effector proteins as well as for bacterial genes which could contribute to pathogenicity of X. campestris

Expression and In Vivo Rescue of Human ABCC6 Disease-Causing Mutants in Mouse Liver

Loss-of-function mutations in ABCC6 can cause chronic or acute forms of dystrophic mineralization described in disease models such as pseudoxanthoma elasticum (OMIM 26480) in human and dystrophic cardiac calcification in mice. The ABCC6 protein is a large membrane-embedded organic anion transporter primarily found in the plasma membrane of hepatocytes. We have established a complex experimental strategy to determine the structural and functional consequences of disease-causing mutations in the human ABCC6. The major aim of our study was to identify mutants with preserved transport activity but failure in intracellular targeting. Five missense mutations were investigated: R1138Q, V1298F, R1314W, G1321S and R1339C. Using in vitro assays, we have identified two variants; R1138Q and R1314W that retained significant transport activity. All mutants were transiently expressed in vivo, in mouse liver via hydrodynamic tail vein injections. The inactive V1298F was the only mutant that showed normal cellular localization in liver hepatocytes while the other mutants showed mostly intracellular accumulation indicating abnormal trafficking. As both R1138Q and R1314W displayed endoplasmic reticulum localization, we tested whether 4-phenylbutyrate (4-PBA), a drug approved for clinical use, could restore their intracellular trafficking to the plasma membrane in MDCKII and mouse liver. The cellular localization of R1314W was significantly improved by 4-PBA treatment, thus potentially rescuing its physiological function. Our work demonstrates the feasibility of the in vivo rescue of cellular maturation of some ABCC6 mutants in physiological conditions very similar to the biology of the fully differentiated human liver and could have future human therapeutic application

Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202

Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202