Multi-scale observations during the 2024 mass coral bleaching event on Heron Reef, Australia - Devin A. Rowell; Nicholas M. Hammerman; Kirsten M. Golding; Tania Marie Kenyon; Zoe Meziere; Courtney Morgans; Kristen Taylor Brown; Faye F. Diederiks; David E. Carrasco Rivera; Karen Eigeland; Roima Paewai-Huggins; Kathryn Markey; et al. (Marine Biology, 2026)

Isolation and characterisation of two epithelial-like cell lines from the gills of Chrysophrys auratus (Australasian snapper) and Oncorhynchus tshawytscha (Chinook salmon) and their use in aquatic toxicology - Björn Böhmert; Gavril L. W. Chong; Kim Lo; Michael Algie; Damon Colbert; Melissa D. Jordan; Gabriella Stuart; Lyn M. Wise; Lucy E. J. Lee; Niels C. Bols; Georgina C. Dowd (In Vitro Cellular & Developmental Biology - Animal, 2025)
In vitro gill models are becoming increasingly important in aquatic toxicology, yet the fish gill invitrome is underrepresented, encompassing approximately 0.1% of extant species. Here, we describe the establishment and characterisation of two gill-derived, epithelial-like cell lines isolated from fish species of significant importance to New Zealand: Chrysophrys auratus (Australasian snapper) and Oncorhynchus tshawytscha (Chinook salmon). Designated CAgill1PFR ( Chrysophrys auratus, gill 1 , P lant & F ood R esearch) and OTgill1PFR ( Oncorhynchus tshawytscha, gill 1 , P lant & F ood R esearch), these cell lines have each been passaged greater than each 70 times over several years and are considered spontaneously immortalised. Both cell lines required serum for growth and exhibited differential responses to basal media formulations. CAgill1PFR was sensitive to low temperatures (4 °C) but replicated at high temperatures (30 °C), whereas OTgill1PFR was sensitive to high temperatures but remained viable at low temperatures, mirroring the natural environment of their host species. Immunostaining revealed expression of epithelial cell markers cytokeratin and E-cadherin, alongside positivity for the mesenchymal cell marker, vimentin. CAgill1PFR was more sensitive to the environmental toxin 3,4 dichloroaniline than OTgill1PFR through measurements of metabolic activity, membrane integrity, and lysosomal function. Furthermore, CAgill1PFR produced less CYP1A activity, indicative of ongoing biotransformation processes, in response to beta-naphthoflavone than OTgill1PFR. These cell lines expand the toolbox of resources and emphasise the need for species-specific aquatic toxicology research.

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series - Maria Dornelas; Laura H. Antão; Amanda E. Bates; Viviana Brambilla; Jonathan M. Chase; Cher F. Y. Chow; Ada Fontrodona‐Eslava; Anne E. Magurran; Inês S. Martins; Faye Moyes; Alban Sagouis; Samuel Adu‐Acheampong; et al. (Global Ecology and Biogeography, 2025)
Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

BioTIME: A database of biodiversity time series for the Anthropocene - Maria Dornelas; Laura H. Antão; Faye Moyes; Amanda E. Bates; Anne E. Magurran; Dušan Adam; Asem A. Akhmetzhanova; Ward Appeltans; José Manuel Arcos; Haley Arnold; Narayanan Ayyappan; Gal Badihi; et al. (Global Ecology and Biogeography, 2018)
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 grain BioTIME 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. Software format .csv and .SQL.

Ferrichrome utilization in a mesorhizobial population: microevolution of a three‐locus system - Timothy M. Carlton; John T. Sullivan; Gabriella S. Stuart; Karla Hutt; Iain L. Lamont; Clive W. Ronson (Environmental Microbiology, 2007)
Summary The ability to utilize the siderophore ferrichrome as an iron source was found to be a variable trait in a field population of mesorhizobia. To investigate the genetic basis of this variation, genes required for ferrichrome utilization ( fhu genes) were characterized in Mesorhizobium strain R88B, an Fhu + member of the population. Functional fhu genes were present at three loci. Two genes of the ferrichrome ABC transporter, fhuBD , were identified at an fhu1 locus downstream of the symbiosis island that was integrated at the phe‐tRNA gene. The fhuA gene encoding the ferrichrome outer membrane receptor was located in the fhu2 locus together with non‐functional fhuDB genes, while the fhuC gene encoding the ATPase required for ferrichrome transport was part of the fhu3 locus that included genes required to form a functional TonB complex. None of the fhu genes were present in the sequenced Mesorhizobium loti strain MAFF303099. Comparisons with MAFF303099 suggested that the fhu2 and fhu3 loci evolved through small‐scale ( fhu loci were coordinately regulated in response to iron availability. Within the mesorhizobial population, the ability to utilize ferrichrome was most strongly correlated with the presence of the fhuA gene. We hypothesize that the ferrichrome transport system evolved through cycles of gene acquisition and deletion, with the positive selection pressure of an iron‐poor or siderophore‐rich environment being offset by the negative pressure of the outer membrane receptor being a target for phage.