Failures of nerve regeneration caused by aging or chronic denervation are rescued by restoring Schwann cell c-Jun.

After nerve injury, myelin and Remak Schwann cells reprogram to repair cells specialized for regeneration. Normally providing strong regenerative support, these cells fail in aging animals, and during chronic denervation that results from slow axon growth. This impairs axonal regeneration and causes significant clinical problems. In mice, we find that repair cells express reduced c-Jun protein as regenerative support provided by these cells declines during aging and chronic denervation. In both cases, genetically restoring Schwann cell c-Jun levels restores regeneration to control levels. We identify potential gene candidates mediating this effect and implicate Shh in the control of Schwann cell c-Jun levels. This establishes that a common mechanism, reduced c-Jun in Schwann cells, regulates success and failure of nerve repair both during aging and chronic denervation. This provides a molecular framework for addressing important clinical problems, suggesting molecular pathways that can be targeted to promote repair in the PNS

TWEAK/Fn14 signalling promotes cholangiocarcinoma niche formation and progression.

Background & Aims: Cholangiocarcinoma (CCA) is a cancer of the hepatic bile ducts that is rarely resectable and is associated with poor prognosis. Tumour necrosis factor-like weak inducer of apoptosis (TWEAK) is known to signal via its receptor fibroblast growth factor-inducible 14 (Fn14) and induce cholangiocyte and myofibroblast proliferation in liver injury. We aimed to characterise its role in CCA. Methods: The expression of the TWEAK ligand and Fn14 receptor was assessed immunohistochemically and by bulk RNA and single cell transcriptomics of human liver tissue. Spatiotemporal dynamics of pathway regulation were comprehensively analysed in rat and mouse models of thioacetamide (TAA)-mediated CCA. Flow cytometry, qPCR and proteomic analyses of CCA cell lines and conditioned medium experiments with primary macrophages were performed to evaluate the downstream functions of TWEAK/Fn14. In vivo pathway manipulation was assessed via TWEAK overexpression in NICD/AKT-induced CCA or genetic Fn14 knockout during TAA-mediated carcinogenesis. Results: Our data reveal TWEAK and Fn14 overexpression in multiple human CCA cohorts, and Fn14 upregulation in early TAA-induced carcinogenesis. TWEAK regulated the secretion of factors from CC-SW-1 and SNU-1079 CCA cells, inducing polarisation of proinflammatory CD206+ macrophages. Pharmacological blocking of the TWEAK downstream target chemokine monocyte chemoattractant protein 1 (MCP-1 or CCL2) significantly reduced CCA xenograft growth, while TWEAK overexpression drove cancer-associated fibroblast proliferation and collagen deposition in the tumour niche. Genetic Fn14 ablation significantly reduced inflammatory, fibrogenic and ductular responses during carcinogenic TAA-mediated injury. Conclusion: These novel data provide evidence for the action of TWEAK/Fn14 on macrophage recruitment and phenotype, and cancer-associated fibroblast proliferation in CCA. Targeting TWEAK/Fn14 and its downstream signals may provide a means to inhibit CCA niche development and tumour growth. Lay summary: Cholangiocarcinoma is an aggressive, chemotherapy-resistant liver cancer. Interactions between tumour cells and cells that form a supportive environment for the tumour to grow are a source of this aggressiveness and resistance to chemotherapy. Herein, we describe interactions between tumour cells and their supportive environment via a chemical messenger, TWEAK and its receptor Fn14. TWEAK/Fn14 alters the recruitment and type of immune cells in tumours, increases the growth of cancer-associated fibroblasts in the tumour environment, and is a potential target to reduce tumour formation

Senolytic treatment preserves biliary regenerative capacity lost through cellular senescence during cold storage

Liver transplantation is the only curative option for patients with end-stage liver disease. Despite improvements in surgical techniques, nonanastomotic strictures (characterized by the progressive loss of biliary tract architecture) continue to occur after liver transplantation, negatively affecting liver function and frequently leading to graft loss and retransplantation. To study the biological effects of organ preservation before liver transplantation, we generated murine models that recapitulate liver procurement and static cold storage. In these models, we explored the response of cholangiocytes and hepatocytes to cold storage, focusing on responses that affect liver regeneration, including DNA damage, apoptosis, and cellular senescence. We show that biliary senescence was induced during organ retrieval and exacerbated during static cold storage, resulting in impaired biliary regeneration. We identified decoy receptor 2 (DCR2)–dependent responses in cholangiocytes and hepatocytes, which differentially affected the outcome of those populations during cold storage. Moreover, CRISPR-mediated DCR2 knockdown in vitro increased cholangiocyte proliferation and decreased cellular senescence but had the opposite effect in hepatocytes. Using the p21KO model to inhibit senescence onset, we showed that biliary tract architecture was better preserved during cold storage. Similar results were achieved by administering senolytic ABT737 to mice before procurement. Last, we perfused senolytics into discarded human donor livers and showed that biliary architecture and regenerative capacities were better preserved. Our results indicate that cholangiocytes are susceptible to senescence and identify the use of senolytics and the combination of senotherapies and machine-perfusion preservation to prevent this phenotype and reduce the incidence of biliary injury after transplantation.This work was supported by the UK Medical Research MRC (MR/K017047/1) (to S.J.F.), the Computational and Chemical Biology of Stem Cell Niche (MR/L012766/1) (to S.J.F.), the UK Regenerative Medicine Platform (MR/K026666/1) (to S.J.F.), and the Wellcome Trust Institutional Translational Partnership Award (WT iTPA) (to S.F.-G.). J.M.B. was supported by the Spanish Carlos III Health Institute (ISCIII) (PI15/01132, PI18/01075, and Miguel Servet Program CON14/00129 and CPII19/00008) cofinanced by “Fondo Europeo de Desarrollo Regional” (FEDER); “Instituto de Salud Carlos III” (CIBERehd), Spain; “Euskadi RIS3” (2019222054 and 2020333010); and the Department of Industry of the Basque Country (Elkartek: KK-2020/00008). This research was funded in whole or in part by The Wellcome Trust (grant number 209710/Z/17/Z), a cOAlition S organization

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

MCOIN: a novel heuristic for determining transcription factor binding site motif width

BACKGROUND: In transcription factor binding site discovery, the true width of the motif to be discovered is generally not known a priori. The ability to compute the most likely width of a motif is therefore a highly desirable property for motif discovery algorithms. However, this is a challenging computational problem as a result of changing model dimensionality at changing motif widths. The complexity of the problem is increased as the discovered model at the true motif width need not be the most statistically significant in a set of candidate motif models. Further, the core motif discovery algorithm used cannot guarantee to return the best possible result at each candidate width. RESULTS: We present MCOIN, a novel heuristic for automatically determining transcription factor binding site motif width, based on motif containment and information content. Using realistic synthetic data and previously characterised prokaryotic data, we show that MCOIN outperforms the current most popular method (E-value of the resulting multiple alignment) as a predictor of motif width, based on mean absolute error. MCOIN is also shown to choose models which better match known sites at higher levels of motif conservation, based on ROC analysis. CONCLUSIONS: We demonstrate the performance of MCOIN as part of a deterministic motif discovery algorithm and conclude that MCOIN outperforms current methods for determining motif width

Characterizing domain-specific open educational resources by linking ISCB Communities of Special Interest to Wikipedia

30th Annual Conference on Intelligent Systems for Molecular Biology (ISMB) -- JUL 10-14, 2022 -- Madison, WIMotivation Wikipedia is one of the most important channels for the public communication of science and is frequently accessed as an educational resource in computational biology. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further improvement in quality, especially when compared to related scientific fields such as genetics and medicine. Facilitating involvement of members from ISCB Communities of Special Interest (COSIs) would improve a vital open education resource in computational biology, additionally allowing COSIs to provide a quality educational resource highly specific to their subfield. Results We generate a list of around 1500 English Wikipedia articles relating to computational biology and describe the development of a binary COSI-Article matrix, linking COSIs to relevant articles and thereby defining domain-specific open educational resources. Our analysis of the COSI-Article matrix data provides a quantitative assessment of computational biology representation on Wikipedia against other fields and at a COSI-specific level. Furthermore, we conducted similarity analysis and subsequent clustering of COSI-Article data to provide insight into potential relationships between COSIs. Finally, based on our analysis, we suggest courses of action to improve the quality of computational biology representation on Wikipedia.Harvard Medical School Master of Biomedical Informatics (MBI) Program; ISCBWe thank ISCB CEO Diane E. Kovats and ISCB Student Council members Nazeefa Fatima, Aishwarya Alex and Bart Cuypers for their support in organizing the 2021 ISCB SCS Wikipedia Hackathon. We thank the ISCB and the Harvard Medical School Master of Biomedical Informatics (MBI) Program for sponsoring the hackathon. We thank Aparna Chauhan and Nusrat Jahan Lily for hackathon participation, Russell Schwartz for useful discussion and Alex Bateman and ISMB reviewers for manuscript comments