Suchergebnisse

Funding This work was supported by NIH NHGRI grant R01HG005220, NIDDK grant R24DK110499, NIDDK grant U54DE023798, and CMIT grant 6935956 to C.H., and by the European Research Council (ERC-STG project MetaPG-716575), MIUR "Futuro in Ricerca" RBFR13EWWI_001, the European Union (H2020-SFS-2018-1 project MASTER-818368 and H2020-SC1-BHC project ONCOBIOME-825410), and the National Cancer Institute of the National Institutes of Health (1U01CA230551) to N.S. Further support was provided by the Programma Ricerca Budget prestazioni Eurac 2017 of the Province of Bolzano, Italy to F.M., and by the EU-H2020 (DiMeTrack-707345) to E.P. and N.S. D.B., S.H.D., P.L., A.W.W. and The Rowett Institute received core funding support from the Scottish Government Rural and Environmental Sciences and Analytical Services (SG-RESAS). Availability of data and materials All datasets used in this study are publicly available and matched with their respective PMID (Additional file 5). The high-quality E. rectale MAGs in fasta format and a metadata file are available at http://segatalab.cibio.unitn.it/data/Erectale_Karcher_et_al.html and in the following Zenodo repository: https://doi.org/10.5281/zenodo.3763191 [80]. The two new isolate genomes L2–21 and T3BWe13 have been uploaded to NCBI and can be found in RefSeq under the accession numbers GCF_008122485.1 [81] and GCF_008123415.1 [82], respectively. ; Peer reviewed ; Publisher PDF

Prevotella copri is a common human gut microbe that has been both positively and negatively associated with host health. In a cross-continent meta-analysis exploiting >6,500 metagenomes, we obtained >1,000 genomes and explored the genetic and population structure of P. copri. P. copri encompasses four distinct clades (>10% inter-clade genetic divergence) that we propose constitute the P. copri complex, and all clades were confirmed by isolate sequencing. These clades are nearly ubiquitous and co-present in non-Westernized populations. Genomic analysis showed substantial functional diversity in the complex with notable differences in carbohydrate metabolism, suggesting that multi-generational dietary modifications may be driving reduced prevalence in Westernized populations. Analysis of ancient metagenomes highlighted patterns of P. copri presence consistent with modern non-Westernized populations and a clade delineation time pre-dating human migratory waves out of Africa. These findings reveal that P. copri exhibits a high diversity that is underrepresented in Western-lifestyle populations. ; This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 716575) to N.S. This work was also supported by the NIH NHGRI grant R01HG005220, the NIDDK grant R24DK110499, the NIDDK grant U54DE023798, and the CMIT grant 6935956 to C.H.; the NYU-HHC CTSI grant (1TL1TR001447) to H.F.P.; the US National Institute of Health grant R01-DK103358-01 to R.B. and D.R.L.; the Howard Hughes Medical Institute to D.R.L.; and the MIUR "Futuro in Ricerca" RBFR13EWWI_001, the European Union (H2020-SFS-2018-1 project MASTER-818368 and H2020-SC1-BHC project ONCOBIOME-825410) to N.S. Further support was provided by the Programma Ricerca Budget Eurac 2017 of the Province of Bolzano, Italy to F.M., and by the EU-H2020 (DiMeTrack-707345) to E.P. and N.S. ; Peer reviewed

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals. ; This paper emerged from the first two workshops of the Horizon 2020 project GLOBIS‐B (GLOBal Infrastructures for Supporting Biodiversity research; http://www.globis‐b.eu/). Financial support came from the European Commission (grant 654003). C. A. additionally received funding from the LifeWatchGreece infrastructure (MIS 384676), funded by the Greek Government under the General Secretariat of Research and Technology (GSRT), ESFRI Projects and National Strategic Reference Framework (NSRF). M. O. was supported by the Swedish LifeWatch project funded by the Swedish Research Council (Grant no. 829‐2009‐6278), and J.E. by the Australian Research Council (grant FT0991640).

The acquisition and development of the infant microbiome are key to establishing a healthy host-microbiome symbiosis. The maternal microbial reservoir is thought to play a crucial role in this process. However, the source and transmission routes of the infant pioneering microbes are poorly understood. To address this, we longitudinally sampled the microbiome of 25 mother-infant pairs across multiple body sites from birth up to 4 months postpartum. Strain-level metagenomic profiling showed a rapid influx of microbes at birth followed by strong selection during the first few days of life. Maternal skin and vaginal strains colonize only transiently, and the infant continues to acquire microbes from distinct maternal sources after birth. Maternal gut strains proved more persistent in the infant gut and ecologically better adapted than those acquired from other sources. Together, these data describe the mother-to-infant microbiome transmission routes that are integral in the development of the infant microbiome. ; his study was supported by Fondazione CARITRO fellowship Rif. Int. 2013.0239 to N.S. The work was also partially supported by the European Research Council (ERC-STG project MetaPG-716575), MIUR "Futuro in Ricerca" RBFR13EWWI_001, the People Program (Marie Curie Actions) of the European Union Seventh Framework Program (FP7/2007–2013) under REA grant agreement no. PCIG13-GA-2013-618833, the LEO Pharma Foundation to N.S., and a European Union H2020 Marie-Curie grant (707345) to E.P. ; Peer reviewed