Biology subjects

Hudson, M. L.

Publications and source records attributed to Hudson, M. L..

4 recordsLinked to original sources

bioRxiv2023

Linked OXTR Variants Are Associated with Social Behavior Differences in Bonobos (Pan paniscus)

Single-nucleotide polymorphisms (SNPs) in forkhead box protein P2 (FOXP2), oxytocin receptor (OXTR), and arginine vasopressin receptor gene 1A (AVPR1A) have been associated with linguistic and social development in humans, as well as symptom severity in autism. Studying biobehavioral mechanisms in the species most closely related to humans can provide insights into the origins of human communication, and the impact of genetic variation on complex behavioral phenotypes. Here, we tested the hypothesis that similar genetic factors underlie social communication differences in both bonobos (Pan paniscus) and humans. We analyzed Sanger sequencing results to determine if bonobos exhibit individual variation at 10 loci across FOXP2, OXTR, and AVPR1A that have been implicated in human social development and behavior. We identified a novel variant in bonobo FOXP2, as well as three novel variants in bonobo OXTR that were 19-184 base pairs away from the target human SNPs. We also found a linked SNP combination (TGA) across the 3 novel bonobo OXTR sites at high frequency (65%) in the study population, including 6 homozygous bonobos. When comparing the combined OXTR genotypes, we found significant group differences in social behavior; bonobos with two copies of the TGA combination were more social than bonobos with one copy and bonobos with zero copies of the TGA combination. Taken together, our findings suggest that these OXTR variants may influence individual-level social behavior in bonobos and support the notion that linked genetic variants are promising biomarkers for differences in human social communication. Revision SummaryThe original manuscript version underwent peer-review at Frontiers in Behavioral Neuroscience. As a part of this process, a reviewer requested that the sequence files be included in the manuscript. While preparing these files, Dr. Hudson identified several errors in his work regarding the individual bonobo genotypes reported in the original version of the manuscript. Upon discovery of the errors, Dr. Skiba and Dr. Taglialatela conducted a new genetic analysis using the raw files and subsequently corrected the misreported information - updating the editorial team and including the raw sequences with the revised manuscript. In addition to requested edits for improvement and clarity by the peer-reviewers, this revised manuscript corrects several errors in the human and bonobo reference genomes, the SNP locations, and the individual genotypes reported in the original manuscript. Information in the figures, main text, and supplementary materials has been corrected in this revised version. Dr. Hudson and his lab member, Mr. Hansen, were unable to identify how the errors in data reporting occurred, and neither party contributed to the revised version of this manuscript. The co-author list has been adjusted to reflect contributions to the corrected analyses and revised manuscript. We are deeply grateful to the editorial team and reviewers at Frontiers in Behavioral Neuroscience for their thorough peer-review of this work - improving the overall quality of the manuscript and leading to the discovery and correction of substantial errors in the original version.

evolutionary biology↗

bioRxiv2020

Evaluating Performance of Drug Repurposing Technologies

Drug repurposing technologies are growing in number and maturing. However, comparison to each other and to reality is hindered due to lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross platform comparability, enabling us to continuously strive towards optimal repurposing by decreasing time and cost of drug discovery and development.

bioinformatics↗

bioRxiv2020

Multiscale virtual screening optimization for shotgun drug repurposing using the CANDO platform

Drug repurposing, the practice of utilizing existing drugs for novel clinical indications, has tremendous potential for improving human health outcomes and increasing therapeutic development efficiency. The goal of multidisease multitarget drug repurposing, also known as shotgun drug repurposing, is to develop platforms that assess the therapeutic potential of each existing drug for every clinical indication. Our Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget repurposing implements several pipelines via large scale modelling and simulation of interactions between comprehensive libraries of drugs/compounds and protein structures. In these pipelines, each drug is described by an interaction signature that is then compared to all other signatures that are then sorted and ranked based on similarity. Pipelines within the platform are benchmarked based on their ability to recover known drugs for all indications in our library, and predictions are generated based on the hypothesis that (novel) drugs with similar signatures may be repurposed for the same indication(s). The drug-protein interactions in the platform used to create the drug-proteome signatures may be determined by any screening or docking method but the primary approach used thus far has been an in house similarity docking protocol. In this study, we calculated drug-proteome interaction signatures using the publicly available molecular docking method Autodock Vina and created hybrid decision tree pipelines that combined our original bio- and cheminformatic approach with the goal of assessing and benchmarking their drug repurposing capabilities and performance. The hybrid decision tree pipeline outperformed the corresponding two docking-based pipelines it was synthesized from, yielding an average indication accuracy of 13.3% at the top10 cutoff (the most stringent), relative to 10.9% and 7.1% for its constituent pipelines, and a random control accuracy of 2.2%. We demonstrate that docking based virtual screening pipelines have unique performance characteristics and that the CANDO shotgun repurposing paradigm is not dependent on a specific docking method. Our results also provide further evidence that multiple CANDO pipelines can be synthesized to enhance drug repurposing predictive capability relative to their constituent pipelines. Overall, this study indicates that pipelines consisting of varied docking based signature generation methods can capture unique and useful signal for accurate comparison of drug-proteome interaction signatures, leading to improvements in the benchmarking and predictive performance of the CANDO shotgun drug repurposing platform.

bioinformatics↗

bioRxiv2020

Chasing the origin of SARS-CoV-2 in Canada's COVID-19 cases: A genomics study

The emergence and global spread of SARS-CoV-2 has had profound social and economic consequences and has shed light on the importance of continued and additional investment in global health and infectious disease surveillance. Identifying changes in viral genomes provides key insights into viral diversity, how viruses spread within populations, and viral strategies for evasion of host immune systems. Here we report twenty-five SARS-CoV-2 genome sequences collected from some of the first COVID-19 cases in eastern Ontario, Canada (March 18-30, 2020). The reported genomes belong to the S-clade (n=2) and G-clade (n=23) of SARS-CoV-2 and contain 45 polymorphic sites including one shared missense and three unique synonymous variants in the gene encoding the spike protein. A phylogenetic analysis enabled the tracing of viral origin and potential transmission into and within Canada. There may be as many as sixteen unique infection events represented in these samples, including at least three that were likely introduced from Europe and seven from the USA. In addition, four separate genomes are each shared by multiple patients, suggesting a common origin or community spread even during this early stage of infection. These results demonstrate how molecular epidemiology and evolutionary phylogenetics can help local health units track origins and vectors of spread for emerging diseases like SARS-CoV-2. Earlier detection and screening in this way could improve the effectiveness of regional public health interventions to prevent future pandemics.

microbiology↗