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- Dornelas, M., et al.
(author)
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BioTIME: A database of biodiversity time series for the Anthropocene
- 2018
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In: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 27:7, s. 760-786
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Journal article (peer-reviewed)abstract
- Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
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- Pagano, G., et al.
(author)
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Fanconi anaemia proteins : Major roles in cell protection against oxidative damage
- 2003
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In: Bioessays. - : Wiley. - 0265-9247 .- 1521-1878. ; 25:6, s. 589-595
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Research review (peer-reviewed)abstract
- Fanconi anaemia (FA) is a cancer-prone genetic disorder that is characterised by cytogenetic instability and redox abnormalities. Although rare subtypes of FA (B, D1 and D2) have been implicated in DNA repair through links with BRCA1 and BRCA2, such a role has yet to be demonstrated for gene products of the common subtypes. Instead, these products have been strongly implicated in xenobiotic metabolism and redox homeostasis through interactions of FANCC with cytochrome P-450 reductase and with glutathione S-transferase, and of FANCG with cytochrome P-450 2E1, as well as redox-dependent signalling through an interaction between FANCA and Akt kinase. We hypothesise that FA proteins act directly (via FANCC and FANCG) and indirectly (via FANCA, BRCA2 and FANCD2) with the machinery of cellular defence to modulate oxidative stress. The latter interactions may co-ordinate the link between the response to DNA damage and oxidative stress parameters (3, 6-12). © 2003 Wiley Periodicals, Inc.
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- Mas-Lloret, J, et al.
(author)
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Gut microbiome diversity detected by high-coverage 16S and shotgun sequencing of paired stool and colon sample
- 2020
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In: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7:1, s. 92-
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Journal article (peer-reviewed)abstract
- The gut microbiome has a fundamental role in human health and disease. However, studying the complex structure and function of the gut microbiome using next generation sequencing is challenging and prone to reproducibility problems. Here, we obtained cross-sectional colon biopsies and faecal samples from nine participants in our COLSCREEN study and sequenced them in high coverage using Illumina pair-end shotgun (for faecal samples) and IonTorrent 16S (for paired feces and colon biopsies) technologies. The metagenomes consisted of between 47 and 92 million reads per sample and the targeted sequencing covered more than 300 k reads per sample across seven hypervariable regions of the 16S gene. Our data is freely available and coupled with code for the presented metagenomic analysis using up-to-date bioinformatics algorithms. These results will add up to the informed insights into designing comprehensive microbiome analysis and also provide data for further testing for unambiguous gut microbiome analysis.
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- Obon-Santacana, M, et al.
(author)
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Meta-Analysis and Validation of a Colorectal Cancer Risk Prediction Model Using Deep Sequenced Fecal Metagenomes
- 2022
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In: Cancers. - : MDPI AG. - 2072-6694. ; 14:17
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Journal article (peer-reviewed)abstract
- The gut microbiome is a potential modifiable risk factor for colorectal cancer (CRC). We re-analyzed all eight previously published stool sequencing data and conducted an MWAS meta-analysis. We used cross-validated LASSO predictive models to identify a microbiome signature for predicting the risk of CRC and precancerous lesions. These models were validated in a new study, Colorectal Cancer Screening (COLSCREEN), including 156 participants that were recruited in a CRC screening context. The MWAS meta-analysis identified 95 bacterial species that were statistically significantly associated with CRC (FDR < 0.05). The LASSO CRC predictive model obtained an area under the receiver operating characteristic curve (aROC) of 0.81 (95%CI: 0.78–0.83) and the validation in the COLSCREEN dataset was 0.75 (95%CI: 0.66–0.84). This model selected a total of 32 species. The aROC of this CRC-trained model to predict precancerous lesions was 0.52 (95%CI: 0.41–0.63). We have identified a signature of 32 bacterial species that have a good predictive accuracy to identify CRC but not precancerous lesions, suggesting that the identified microbes that were enriched or depleted in CRC are merely a consequence of the tumor. Further studies should focus on CRC as well as precancerous lesions with the intent to implement a microbiome signature in CRC screening programs.
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