Biology subjects

Connolly, K.

Publications and source records attributed to Connolly, K..

3 recordsLinked to original sources

bioRxiv2024

Efficient and durable gene activation by Cas9-mediated epigenome editing in vivo

Epigenome editing technology holds great promise for treating diverse genetic disorders. While a series of advances has been made on epigenetic silencing using programmable editors, little progress has been made in leveraging epigenetic activation for therapeutic application. Here we demonstrate epigenetic activation of the LAMA1 gene for the treatment of LAMA2-CMD, a severe congenital muscle dystrophy (CMD) caused by biallelic mutations in the LAMA2 gene. LAMA1 is a sister homologue that is known to compensate for the function of LAMA2. However, supplementing LAMA1 or LAMA2 gene via viral platform is not feasible due to the large size of their coding sequences. Through a single administration of our (Adeno-associated virus) AAV vector encoding all the necessary elements for epigenetic activation, a platform termed CRISPR guide-nucleotide directed modulation (GNDM), we observed significant LAMA1 gene upregulation and phenotype improvements in DyW mice, a severe disease model of LAMA2-CMD. Notably, sustained expression of the GNDM gene and subsequent activation of the LAMA1 gene persisted beyond analyzed period of one year despite immune recognition of the GNDM protein by the host immune system. Regulatory T (Treg) cells appeared to facilitate tolerance to GNDM in the transduced muscle tissue. The muscle-tropic AAV capsid exhibited desired vector biodistribution and promising pharmacodynamics with good safety profiles in adult non-human primates (NHPs). Moreover, administration to juvenile NHPs demonstrated superior pharmacodynamics compared to adults, even at half the adult dose, suggesting safer and more effective therapeutic outcomes in mostly pediatric LAMA2-CMD patients. Our approach holds broad applicability for a range of loss-of-function genetic disorders and could offer a therapeutic breakthrough where active epigenome brings clinical benefit.

bioengineering↗

bioRxiv2022

DeepTracer ID: De Novo Protein Identification from Cryo-EM Maps

The recent revolution in cryo-electron microscopy has made it possible to determine macromolecular structures directly from cell extracts. However, identifying the correct protein from the cryo-EM map is still challenging and often needs additional sequence information from other techniques, such as tandem mass spectrometry and/or bioinformatics. Here, we present DeepTracer-ID, a server-based approach to identify the candidate protein in a user-provided organism de novo from a cryo-EM map, without the need for additional information. Our method first uses DeepTracer to generate a protein backbone model that best represents the cryo-EM map, and this model is then searched against the library of AlphaFold2 predictions for all proteins in the given organism. This method is highly accurate and robust: in all 13 experimental maps tested blindly, DeepTracer-ID identified the correct proteins as the top candidates. Eight of the maps were of known structures, while the other five unpublished maps were validated by prior protein annotation and careful inspection of the model refined into the map. The program also showed promising results for both homomeric and heteromeric protein complexes. This platform is possible because of the recent breakthroughs in large-scale protein 3D structure prediction. Statement of SignificanceWhile it has now become routine for cryo-EM maps of proteins to reach a near-atomic resolution, potentially allowing for reliable atomic models to be built, there are a growing number of instances where the protein identity may not be known. Without knowing the protein sequence, it is impossible to build an atomic model. DeepTracer-ID is a server-based approach to surmount this problem by identifying the proteins in a given organism that are found in the cryo-EM map. A free web service for global academic access is provided.

biophysics↗

bioRxiv2020

Dynamic Vision Training Transfers Positively to Batting Performance Among Collegiate Baseball Batters

A growing body of evidence demonstrates visual, perceptual, and oculomotor abilities contribute to batting performance in baseball and there is interest in whether training such abilities can transfer positively to batting performance. The current study tested this question through a pre-registered randomized, and placebo-controlled intervention, conducted with 24 collegiate baseball players at two Division 1 universities. Athletes were randomized to receive either dynamic vision training consisting of stroboscopic, anticipatory timing, and eye quickness drills, or placebo drills stylized after control procedures in previous vision therapy studies. Generalized near-transfer was tested via a digital visual-motor task battery (n = 20), while sports-specific intermediate and far transfer of training were evaluated through instrumented batting practice metrics (n = 14) and box score performance in NCAA-sanctioned games (n = 12). The effects of training group were tested on these outcome measures while controlling for covariates such as pre-training expectations and site. Participants averaged 8.50 hours of training with no significant training group differences in adherence, expectations, or baseline assessments. ANCOVA revealed no group differences in measures of visual-motor skills or NCAA game statistics. However, batting practice demonstrated significant improvements in launch angle (p = 0.002, Cohens d = 0.74) and hit distance (p < 0.001, Cohens d = 0.70) for the active cohort relative to the placebo control. This controlled and pre-registered pilot study therefore provides preliminary evidence that vision training may improve batting practice performance, creating new opportunities for the transfer of skill training and warranting further study. Pre-RegistrationAt Open Science Framework on August 9, 2018. DOI 10.17605/OSF.IO/496RX. Accessible at https://osf.io/jxh8u

neuroscience↗