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Biology subjects

Wiggins, S.

Publications and source records attributed to Wiggins, S..

3 recordsLinked to original sources

Transforming avian to mammalian modes of digit patterning

How a conserved embryonic organiser--the Sonic hedgehog (Shh)-expressing Zone of Polarising Activity (ZPA)--generates diverse limb architectures in amniotes remains a central problem in evolutionary and developmental biology. The principal difference across species lies in the number of digits produced from ZPA tissue: two in mammals1, one in the chick leg2 and none in the chick wing2. Here we show that this divergence is governed by a Shh-p27Kip1 pathway operating in avian, but not mammalian ZPAs. In chick wing ZPA explants, attenuation of this pathway reveals an intrinsic digit-forming programme, enabling cells to self-organise signalling networks and generate digits after grafting into a host wing bud. Guided by these findings, we redirected the chick leg, which retains stem amniote digit identities, to follow a mammalian-like developmental trajectory. Precise temporal restriction of Shh signalling transforms chick legs into pentadactyl limbs with digit identities characteristic of mammals and their therapsid ancestors, with two digits arising from the ZPA. These findings establish a unifying framework for how Shh controls both digit number and identity across amniotes.

developmental biology↗

Light-induced Extracellular Vesicle Adsorption

The role of extracellular vesicles (EVs) in human health and disease has garnered considerable attention over the past two decades. However, while several types of EVs are known to interact dynamically with the extracellular matrix and there is great potential value in producing high-fidelity EV micropatterns, there are currently no label-free, high-resolution, and tunable platform technologies with this capability. We introduce Light-induced Extracellular Vesicle Adsorption (LEVA) as a powerful solution to rapidly advance the study of matrix- and surface-bound EVs and other particles. The versatility of LEVA is demonstrated using commercial GFP-EV standards, EVs from glioblastoma bioreactors, and E. coli outer membrane vesicles (OMVs), with the resulting patterns used for single EV characterization, single cell migration on migrasome-mimetic trails, and OMV-mediated neutrophil swarming. LEVA will enable rapid advancements in the study of matrix- and surface-bound EVs and other particles, and should encourage researchers from many disciplines to create novel diagnostic, biomimetic, immunoengineering, and therapeutic screening assays.

bioengineering↗

St. Jude Cloud a Pediatric Cancer Genomic Data Sharing Ecosystem

Effective data sharing is key to accelerating research that will improve the precision of diagnoses, efficacy of treatments and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem developed via collaboration between St. Jude Childrens Research Hospital, DNAnexus, and Microsoft, for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients, long-term survivors of pediatric cancer and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabyes on St. Jude Cloud include 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes, which are freely available to researchers worldwide. The resource is expanding rapidly with regular data uploads from St. Judes prospective clinical genomics programs, providing public access as soon as possible rather than holding data back until publication. Three interconnected apps within the St. Jude Cloud ecosystem--Genomics Platform, Pediatric Cancer Knowledgebase (PeCan) and Visualization Community--provide a unique experience for simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the St. Jude Cloud ecosystem through use cases that classify 48 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 subtypes of pediatric cancer.

cancer biology↗