Biology subjects

O'Neil, D.

Publications and source records attributed to O'Neil, D..

4 recordsLinked to original sources

bioRxiv2025

Acute AMPK activation does not adequately stimulate insulin signaling in skeletal muscle models of Myotonic Dystrophy Type 1

Myotonic Dystrophy Type 1 (DM1) is a multisystemic neuromuscular disorder characterized by skeletal muscle weakness, muscle atrophy, myotonia, cognitive impairments, gastrointestinal complications, and insulin resistance. While insulin resistance is well characterized in type 2 diabetes, its pathomechanism in DM1 remains unclear. Our study aims to elucidate the pathomechanism of insulin resistance in DM1 and how the pathway responds to AMPK stimulation. Proteomic analysis from sedentary wildtype and sedentary HSA-LR mice, a common DM1 mouse model, revealed downregulation of the AMPK-PGC-1 axis. Analysis of sedentary HSA-LR mice and exercised HSA-LR mice revealed activation of the AMPK-PGC-1 axis in exercised animals. To investigate this pathway, we treated WT and HSA-LR mice with the AMPK activator AICAR to examine the impact of AMPK stimulation on insulin signaling in DM1. This revealed impaired responses in the insulin pathway activation in the HSA-LR mice. Next, we examined whether these differences extended to a human model by treating control and DM1 myotubes with insulin and/or AICAR. In DM1 myotubes, both treatments produced dampened responses of key insulin signaling intermediates compared to controls. Taken together, these results suggest impaired activation of insulin signaling pathways in DM1 models and confirm the presence of insulin resistance with an impaired response to acute AMPK stimulation.

molecular biology↗

bioRxiv2025

Gene-specific response to MuSK agonist antibody in the treatment of Congenital Myasthenic Syndromes

Congenital myasthenic syndromes (CMS) are a group of rare disorders characterized by fatigable muscle weakness and caused by impaired neuromuscular junction (NMJ) function. CMS symptoms are highly variable, but can be detrimental and lead to death. There are over 40 different genetic subtypes, including Agrn-CMS and ColQ-CMS. Agrn encodes for neural AGRIN, which is released from the nerve terminal and triggers muscle-specific kinase phosphorylation (pMuSK). pMuSK is essential for NMJ development and maintenance, thus AGRIN deficiency causes NMJ impairment. ColQ encodes for collagenous subunit Q (ColQ), which anchors acetylcholinesterase and stabilizes MuSK. As a result, ColQ deficiency results in NMJ degeneration from prolonged transmission signals and decreased pMuSK. Current treatments for Agrn-CMS and ColQ-CMS are limited, highlighting the importance of finding more efficient therapies. Recently, a MuSK agonist antibody with high affinity for the Frizzled-like domain showed remarkable rescue of a Dok7-CMS mouse model. We hypothesized a similar antibody could benefit Agrn- and ColQ-CMS mouse models. Agrn-CMS mice were treated at postnatal day 5 (P5), P15 and P35, and ColQ-CMS mice were treated weekly from P22 to P57. In Agrn-CMS mice, 3B2 treatment rescued survival, bodyweight, fibre type switching and pMuSK levels, and improved grip strength and NMJ morphology. In ColQ-CMS mice, 3B2 treatment was unable to rescue deficits observed. Our findings suggest that MuSK agonists may benefit patients with Agrn-CMS, which should be tested in clinical trials. Our study emphasizes that effective CMS treatment is gene-dependent and relies on an accurate genetic diagnosis.

molecular biology↗

bioRxiv2024

Leveraging protein language and structural modelsfor early prediction of antibodies with fast clearance

Monoclonal antibodies (mAbs) with long systemic persistence are widely used as therapeutics. However, antibodies with atypically fast clearance require more dosing, limiting their clinical usefulness. Deep learning can facilitate using sequence-based modeling to predict potential pharmacokinetic (PK) liabilities before antibody generation. Assembling a dataset of 103 mAbs with measured nonspecific clearance in cynomolgus monkeys (cyno), and using transfer learning from large protein language models, we developed multiple machine learning models to predict mAb clearance as fast/slow clearing. Focusing on minimizing misclassification of potentially promising molecules as fast clearing, our results show that using physicochemical properties yielded up to 73.1+/-1.1% classification accuracy on hold-out test data (precision 65.2+/-2.3%). Using only sequence-based features from deep learning protein language models yielded a comparable performance of 71+/-1.4% (precision 65.5+/-2.5%). Combining structural and deep learning derived features yielded a similar accuracy of 73.9+/-1.1%, and slightly improved precision (68.3+/-2.4%). Features important for classifying fast/slow clearance point to charge, moment, and surface area properties at pH 7.4 as well as deep learning derived features. These results suggest that the protein language models provide comparable information and predictive performance of clearance as physicochemical features. This work provides a foundation for in silico prediction of protein pharmacokinetics to inform antibody candidate generation and early deprioritization of designs with high risk of fast clearance. More generally, it illustrates the value of transfer learning-based application of protein language models to address characteristics of importance for protein therapeutics.

pharmacology and toxicology↗

bioRxiv2023

Uterine secretome initiates growth of gynecologic tissues in ectopic locations.

Endosalpingiosis (ES) and endometriosis (EM) refer to the growth of tubal and endometrial epithelium respectively, outside of their site of origin. We hypothesize that uterine secretome factors drive ectopic growth. To test this, we developed a mouse model of ES and EM using tdTomato (tdT) transgenic fluorescent mice as donors. To block implantation factors, progesterone knockout (PKO) tdT mice were created. Post-ovulatory endometrium was induced hormonally in donor tdT and wild-type (WT) female mice. tdT oviductal cells and WT endometrium were harvested for intraperitoneal injection into synchronized recipient WT mice. Ectopic lesions were identified using fluorescence in-vivo imaging and then harvested for histological evaluation. Fluorescent lesions were present after oviduct implantation with and without WT endometrium. Implantation was increased (p<0.05) when tdt oviductal tissue was implanted with endometrium compared to oviductal tissue alone. Implantation was reduced (p<0.0005) in animals implanted with minced tdT oviductal tissue with PKO tdT endometrium compared to WT endometrium. In conclusion, endometrial derived implantation factors are necessary to initiate ectopic tissue growth. We have developed an animal model of ectopic growth of gynecologic tissues in a WT mouse which will potentially allow for development of new prevention and treatment modalities.

cancer biology↗