Biology subjects

Howell, K. L.

Publications and source records attributed to Howell, K. L..

5 recordsLinked to original sources

bioRxiv2021

Reprogramming adult tendon healing using regenerative neonatal regulatory T cells

Tendinopathy is a common clinical problem leading to significant musculoskeletal disability. Using a neonatal mouse model of tendon regeneration compared to adult tendon fibrosis, we identified a unique immune profile in regeneration that is associated with type 2 macrophage polarization and regulatory T cell (Treg) infiltration. Neonatal Treg ablation resulted in a dysregulated immune response leading to failed tenocyte recruitment and loss of functional regeneration. Transcriptional profiling of adult and neonatal tendon Tregs revealed distinct type 1 and type 2 immune signatures that facilitate macrophage polarization following injury. Finally, adoptive transfer of mouse and human neonatal Tregs was sufficient to improve functional regeneration, in contrast to adult Treg transfer. Collectively, these studies uncover a critical role for neonatal Tregs in controlling immune polarization to promote an environment permissive for tendon regeneration. Our findings provide a basis for immune modulating therapies to facilitate regenerative adult tendon healing.

immunology↗

bioRxiv2021

Macrophage depletion impairs neonatal tendon regeneration

Tendons are dense connective tissues that transmit muscle forces to the skeleton. After adult injury, healing potential is generally poor and dominated by scar formation. Although the immune response is a key feature of healing, the specific immune cells and signals that drive tendon healing have not been fully defined. In particular, the immune regulators underlying tendon regeneration are almost completely undetermined due to a paucity of tendon regeneration models. Using a mouse model of neonatal tendon regeneration, we screened for immune-related markers and identified upregulation of several genes associated with inflammation, macrophage chemotaxis, and TGF{beta} signaling after injury. Depletion of macrophages using AP20187 treatment of MaFIA mice resulted in impaired functional healing, reduced cell proliferation, reduced ScxGFP+ neo-tendon formation, and altered tendon gene expression. Collectively, these results show that inflammation is a key component of neonatal tendon regeneration and demonstrate a requirement for macrophages in effective functional healing.

immunology↗

bioRxiv2019

TGFβ signaling is required for tenocyte recruitment and functional neonatal tendon regeneration

Tendon injuries are common with poor healing potential. The paucity of therapies for tendon is due to our limited understanding of the cells and molecules that drive tendon regeneration. Using a model of neonatal mouse tendon regeneration, we determined the molecular basis for regeneration and identify TGF{beta} signaling as a major pathway. Through targeted gene deletion, small molecule inhibition, and lineage tracing, we elucidated TGF{beta}-dependent and -independent mechanisms underyling tendon regeneration. Importantly, functional recovery depended on TGF{beta} signaling and loss of function is due to impaired tenogenic cell recruitment from both Scxlin and non-Scxlin sources. We show that TGF{beta} signaling is required directly in neonatal tenocytes for recruitment and that TGF{beta} is positively regulated in tendons. Collectively, these results are the first to show a functional role for TGF{beta} signaling in tendon regeneration and offer new insights toward the divergent cellular activities that may lead to regenerative vs fibrotic healing.

developmental biology↗

bioRxiv2019

A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses

Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure follows the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem.

ecology↗

bioRxiv2019

Modelling marine larval dispersal: a cautionary deep-sea tale for ecology and conservation

Larval dispersal data are increasingly sought after in ecology and marine conservation, the latter often requiring information under time limited circumstances. Basic estimates of dispersal are often used in these situations acknowledging their oversimplified nature. Larval dispersal models (LDMs) are now becoming more popular and may be a tempting way of refining predictions, but prior to targeted groundtruthing their predictions are of unknown worth. This case study uses deep-sea LDMs to compare predictions of dispersal. Two LDMs driven by different example hydrodynamic models are compared, along with an informed estimate based on mean current speed and planktonic larval duration (PLD) to provide insight into predictive variability. LDMs were found to be more conservative in dispersal distance than an estimate. This difference increased with PLD which may result in a bigger disparity for deep-sea species predictions. Although LDMs were more spatially targeted than an estimate, the two LDM predictions were also significantly different from each other and would result in contrasting advice for marine conservation. These results show a greater potential for model variability than previously appreciated by ecologists and strongly advocates groundtruthing predictions before use in management. Advice is offered for improved model selection and interpretation of predictions.

ecology↗