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Metagenomics is a culture-independent method for studying the microbes inhabiting a particular environment. Comparing the composition of samples (functionally/taxonomically), either from a longitudinal study or cross-sectional studies, can provide clues into how the microbiota has adapted to the environment. However, a recurring challenge, especially when comparing results between independent studies, is that key metadata about the sample and molecular methods used to extract and sequence the genetic material are often missing from sequence records, making it difficult to account for confounding factors. Nevertheless, these missing metadata may be found in the narrative of publications describing the research. Here, we describe a machine learning framework that automatically extracts essential metadata for a wide range of metagenomics studies from the literature contained in Europe PMC. This framework has enabled the extraction of metadata from 114,099 publications in Europe PMC, including 19,900 publications describing metagenomics studies in European Nucleotide Archive (ENA) and MGnify. Using this framework, a new metagenomics annotations pipeline was developed and integrated into Europe PMC to regularly enrich up-to-date ENA and MGnify metagenomics studies with metadata extracted from research articles. These metadata are now available for researchers to explore and retrieve in the MGnify and Europe PMC websites, as well as Europe PMC annotations API. [ABSTRACT FROM AUTHOR]

[Display omitted] • MGnify Genomes is a free-to-use resource for biome-specific microbial genomes. • Each genome catalogue is non-redundant and includes extensive functional annotations. • Users can search their own sequences against the resource to assess their novelty. • MGnify Genomes can be accessed via the website, the FTP server and the API. • The resource provides insight into previously uncultured species and novel proteins. An increasingly common output arising from the analysis of shotgun metagenomic datasets is the generation of metagenome-assembled genomes (MAGs), with tens of thousands of MAGs now described in the literature. However, the discovery and comparison of these MAG collections is hampered by the lack of uniformity in their generation, annotation and storage. To address this, we have developed MGnify Genomes, a growing collection of biome-specific non-redundant microbial genome catalogues generated using MAGs and publicly available isolate genomes. Genomes within a biome-specific catalogue are organised into species clusters. For species that contain multiple conspecific genomes, the highest quality genome is selected as the representative, always prioritising an isolate genome over a MAG. The species representative sequences and annotations can be visualised on the MGnify website and the full catalogue and associated analysis outputs can be downloaded from MGnify servers. A suite of online search tools is provided allowing users to compare their own sequences, ranging from a gene to sets of genomes, against the catalogues. Seven biomes are available currently, comprising over 300,000 genomes that represent 11,048 non-redundant species, and include 36 taxonomic classes not currently represented by cultured genomes. MGnify Genomes is available at https://www.ebi.ac.uk/metagenomics/browse/genomes/. [ABSTRACT FROM AUTHOR]

We analyze the redshift- and luminosity-dependent sizes of dropout galaxy candidates in the redshift range z ∼ 7-12 using deep images from the 2012 Hubble Ultra Deep Field (UDF12) campaign, which offers two advantages over that used in earlier work. First, we utilize the increased signal-to-noise ratio offered by the UDF12 imaging to provide improved measurements for known galaxies at z ≃ 6.5-8 in the HUDF. Second, because the UDF12 data have allowed the construction of the first robust galaxy sample in the HUDF at z > 8, we have been able to extend the measurement of average galaxy size out to higher redshifts. Restricting our measurements to sources detected at >15σ, we confirm earlier indications that the average half-light radii of z ∼ 7-12 galaxies are extremely small, 0.3-0.4 kpc, comparable to the sizes of giant molecular associations in local star-forming galaxies. We also confirm that there is a clear trend of decreasing half-light radius with increasing redshift, and provide the first evidence that this trend continues beyond z ≃ 8. Modeling the evolution of the average half-light radius as a power law, ∝(1 + z)s, we obtain a best-fit index of over z ∼ 4-12. A clear size-luminosity relation is evident in our dropout samples. This relation can be interpreted in terms of a constant surface density of star formation over a range in luminosity of . The average star formation surface density in dropout galaxies is 2-3 orders of magnitude lower than that found in extreme starburst galaxies, but is comparable to that seen today in the centers of normal disk galaxies. [ABSTRACT FROM AUTHOR]

We present a catalog of high-redshift star-forming galaxies selected to lie within the redshift range z ≃ 7-8 using the Ultra Deep Field 2012 (UDF12), the deepest near-infrared (near-IR) exposures yet taken with the Hubble Space Telescope (HST). As a result of the increased near-IR exposure time compared to previous HST imaging in this field, we probe ~0.65 (0.25) mag fainter in absolute UV magnitude, at z ~ 7 (8), which increases confidence in a measurement of the faint end slope of the galaxy luminosity function. Through a 0.7 mag deeper limit in the key F105W filter that encompasses or lies just longward of the Lyman break, we also achieve a much-refined color-color selection that balances high redshift completeness and a low expected contamination fraction. We improve the number of dropout-selected UDF sources to 47 at z ~ 7 and 27 at z ~ 8. Incorporating brighter archival and ground-based samples, we measure the z ≃ 7 UV luminosity function to an absolute magnitude limit of MUV = -17 and find a faint end Schechter slope of α = -1.87+0.18-0.17. Using a similar color-color selection at z ≃ 8 that takes our newly added imaging in the F140W filter into account, and incorporating archival data from the HIPPIES and BoRG campaigns, we provide a robust estimate of the faint end slope at z ≃ 8, α = -1.94+0.21-0.24. We briefly discuss our results in the context of earlier work and that derived using the same UDF12 data but with an independent photometric redshift technique. [ABSTRACT FROM AUTHOR]

Understanding cosmic reionization requires the identification and characterization of early sources of hydrogenionizing photons. The 2012 Hubble Ultra Deep Field (UDF12) campaign has acquired the deepest infrared images with the Wide Field Camera 3 aboard Hubble Space Telescope and, for the first time, systematically explored the galaxy population deep into the era when cosmic microwave background (CMB) data indicate reionization was underway. The UDF12 campaign thus provides the best constraints to date on the abundance, luminosity distribution, and spectral properties of early star-forming galaxies. We synthesize the new UDF12 results with the most recent constraints from CMB observations to infer redshift-dependent ultraviolet (UV) luminosity densities, reionization histories, and electron scattering optical depth evolution consistent with the available data. Under reasonable assumptions about the escape fraction of hydrogen-ionizing photons and the intergalactic medium clumping factor, we find that to fully reionize the universe by redshift z ~ 6 the population of star-forming galaxies at redshifts z ~ 7-9 likely must extend in luminosity below the UDF12 limits to absolute UV magnitudes of MUV ~ -13 or fainter. Moreover, low levels of star formation extending to redshifts z ~ 15-25, as suggested by the normal UV colors of z≃7-8 galaxies and the smooth decline in abundance with redshift observed by UDF12 to z ≃ 10, are additionally likely required to reproduce the optical depth to electron scattering inferred from CMB observations. [ABSTRACT FROM AUTHOR]