Biology subjects

Darby, C.

Publications and source records attributed to Darby, C..

4 recordsLinked to original sources

bioRxiv2024

Novel sulfatase cancer therapeutics negatively impact Bacteroidota of the colonic microbiota in a non-sulfatase dependent manner

Excessive degradation of the colonic mucin layer by Bacteroides within the human gut microbiota drives inflammatory bowel disease in mice. Bacterial carbohydrate sulfatases are key enzymes in gut colonization, as they are elevated in human inflammatory bowel disease and correlate with disease severity. Selective inhibitors of carbohydrate sulfatases could function as sulfatase-selective drugs, allowing precise control of sulfatase activity while preserving these otherwise beneficial bacteria. Arylsulfamates are covalent inhibitors that target a catalytic formylglycine residue of steroid sulfatases, a residue that is also conserved in carbohydrate sulfatases. Here, we find that a library of aryl- and carbohydrate sulfamates is ineffective against Bacteroides carbohydrate sulfatases, yet can inhibit human gut microbiota species grown on sulfated glycans. Leveraging thermal proteome profiling, we identify a lipid kinase as the target responsible for these effects. This work highlights the imperative for developing specific inhibitors targeting carbohydrate sulfatases and reveals the adverse effects that arylsulfamates have on Bacteroides species of the human gut microbiota. Significance statementArylsulfamates are currently the only effective class of sulfatase inhibitors available and offer a potential strategy to treat inflammatory bowel disease driven by gut microbiota carbohydrate sulfatases. Although arylsulfamates inhibit the growth of microbiota Bacteroides species on sulfated glycans, this is not mediated through carbohydrate sulfatases but, via a conserved lipid kinase. Carbohydrate sulfatases are resistant to arylsulfamates whilst steroid sulfatases are susceptible despite a conserved active site. Finally, selected complex plant glycans confer a resistant/protective phenotype against the harmful effects of arylsulfamates. These data guide the future development of targeted carbohydrate sulfatase inhibitors and potential drug-prebiotic pairings.

biochemistry↗

bioRxiv2023

Chromosome-scale assembly of the African yam bean genome

Genomics-informed breeding of locally adapted, nutritious, albeit underutilised African crops can help mitigate food and nutrition insecurity challenges in Africa, particularly against the backdrop of climate change. However, utilisation of modern crop improvement tools including genomic selection and genome editing for many African indigenous crops is hampered by the scarcity of genetic and genomic resources. Here we report on the assembly of the genome of African yam bean (Sphenostylis stenocarpa), a tuberous legume crop that is indigenous to Africa. By combining long and short read sequencing with Hi-C scaffolding, we produced a chromosome-scale assembly with an N50 of 69.5 Mbp and totalling 649 Mbp in length (77 - 81% of the estimated genome size based on flow cytometry). Using transcriptome evidence from Nanopore RNA-Seq and homology evidence from related crops, we annotated 31,614 putative protein coding genes. We further show how this resource improves anchoring of markers, genome-wide association analysis and candidate gene analyses in Africa yam bean. This genome assembly provides a valuable resource for genetic research in Africa yam bean.

genomics↗

bioRxiv2022

De novo assembly and annotation of the Patagonian toothfish (Dissostichus eleginoides) genome

Patagonian toothfish (Dissostichus eleginoides) is an economically and ecologically important fish species in the family Nototheniidae, found at depths between 70 and 2,500 meters on the southern shelves and slopes around the sub-Antarctic islands of the Southern Ocean. Genomic sequence data for this species is limited. Here, we report a high-quality assembly and annotation of the D. eleginoides genome, generated using a combination of Illumina, PacBio and Omni-C sequencing technologies. To aid the genome annotation, the transcriptome derived from a variety of toothfish tissues was also generated using both short and long read sequencing methods. The final genome assembly was 797.8 Mb with a N50 scaffold length of 3.5 Mb. Approximately 31.7% of the genome consisted of repetitive elements. A total of 35,543 putative protein-coding regions were identified, of which 50% have been functionally annotated. Transcriptomics analysis showed that approximately 64% of the predicted genes (22,617 genes) were found to be expressed in the tissues sampled. Comparative genomics analysis revealed that the anti-freeze glycoprotein (AFGP) locus of D. eleginoides does not contain any AFGP proteins compared to the same locus in the Antarctic toothfish (Dissostichus mawsoni). This is in agreement with previously published results looking at hybridization signals and confirms that Patagonian toothfish do not possess AFGP coding sequences in their genome. The high-quality genome assembly of the Patagonian toothfish will provide a valuable genetic resource for ecological and evolutionary studies on this and other closely related species.

genomics↗

bioRxiv2020

Integrated analysis of multimodal single-cell data

The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce weighted-nearest neighbor analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. AvailabilityInstallation instructions, documentation, tutorials, and CITE-seq datasets are available at http://www.satijalab.org/seurat

genomics↗