Biology subjects

Case, A.

Publications and source records attributed to Case, A..

3 recordsLinked to original sources

bioRxiv2025

The role of Akkermansia muciniphila sulfatases in colonic mucinutilisation

Akkermansia muciniphila, an obligate mucin degrader, is a major member of the human colonic microbiota and has been associated positive health outcomes. Mucins are complex glycoproteins that contain heavily sulfated O-glycans and form the protective colonic mucus layer. Bacterial carbohydrate sulfatases are required to metabolise these heavily sulfated mucin glycans and excessive bacterial foraging has been associated with several diseases. Sulfatases have been linked with inflammatory bowel disease, making these microbiota enzymes potential drug targets. A. muciniphila expresses carbohydrate sulfatases that can act on colonic mucins yet their roles in its metabolism remain opaque. Our data reveal that A. muciniphila requires glycopeptides/protein forms of colonic mucin for metabolism and its sulfatases have unique adaptations compared to Bacteroides species. Localisation studies reveal that desulfation of N-acetyl-D-glucosamine, but not D-galactose, is exclusively periplasmic. A cell surface sulfatase has a novel carbohydrate binding module that binds to colonic mucin. This paints a contrasting picture of sulfated mucin metabolism by Akkermansia muciniphila versus Bacteroides species. These data will be important for understanding the contexts for Akkermansia muciniphilas positive health correlations.

biochemistry↗

bioRxiv2025

Procrustean pseudo-landmark methods in Python to measure massive quantities of leaf shape data

PremiseWhen examining leaf shapes that are different from one another, it can be difficult to compare both the overall leaf shape and points along the leaf margin in biologically and statistically meaningful ways. MethodTo address this problem, we present a simple and user-friendly leaf shape analysis in Jupyter Notebook and Python that uses pseudo-landmarks and Generalized Procrustes Analysis to measure and compare the shape of any leaf. To demonstrate our analysis, we created a repository of real leaves gathered from eight experimental datasets. ResultsUsing our leaf repository, we explain how we can use pseudo-landmarks to compare all leaf shapes both within and between species using dimension reduction techniques like Principal Component Analysis and can predict leaf shapes using pseudo-landmarks through Linear Discriminant Analysis. Our leaf shape analysis also maps differences in shape as leaves grew around a rosette, showing the transition of shape across development (phyllotaxy). Finally, we showed how we can investigate the relationship between leaf shape variation and genetic diversity by combining shape with genetic data. DiscussionThrough the use of Generalized Procrustes Analysis and pseudo-landmarks, our leaf shape analysis presents a powerful tool for examining the shape of any leaf across multiple biological, ecological, evolutionary, and developmental scales.

plant biology↗

bioRxiv2024

Whole-Genome Sequencing of the Wild Barley Diversity Collection: A Resource for Identifying and Exploiting Genetic Variation for Cultivated Barley Improvement

To exploit allelic variation in Hordeum vulgare subsp. spontaneum, the Wild Barley Diversity Collection was evaluated for several agronomic traits and subjected to paired-end Illumina sequencing at [~]9X depth, generating 109.5 million single nucleotide polymorphisms after alignment to the Morex V3 assembly. A genome-wide association study of lemma color identified one marker-trait association (MTA) on chromosome 1HL close to HvBlp, the cloned gene controlling black lemma. Four MTAs were identified for stem rust resistance: one co-locating to the complex RMRL1-RMRL2 locus on 5HL, and three novel loci on 1HS, 1HL, and 5HL. Six MTAs for days to heading (DTH) on vernalized plants were identified on all chromosomes except 1H and 6H. Two MTAs for DTH on non-vernalized plants were identified on chromosomes 1HL and 2HS. All MTAs for DTH were novel. The whole genome sequence data described herein will facilitate the identification and utilization of new alleles for barley improvement.

genomics↗