Biology subjects

Collins, K. A.

Publications and source records attributed to Collins, K. A..

3 recordsLinked to original sources

bioRxiv2025

Enhanced CB1 receptor function in GABAergic neurons mediates hyperexcitability and impaired sensory-driven synchrony of cortical circuits in Fragile X Syndrome model mice

Electroencephalographic (EEG) recordings in individuals with Fragile X Syndrome (FXS) and the mouse model of FXS (Fmr1 KO) display cortical hyperexcitability at rest, as well as deficits in sensory-driven cortical network synchrony. A form of circuit hyperexcitability is observed in ex vivo cortical slices of Fmr1 KO mice as prolonged persistent activity, or Up, states. It is unknown if the circuit mechanisms that cause prolonged Up states contribute to FXS-relevant EEG phenotypes. Here we examined the role of endocannabinoids (eCB) in prolonged Up states in slices and resting and sensory-driven EEG phenotypes in awake Fmr1 KO mice. Bidirectional changes in eCB function are reported in the Fmr1 KO that depend on synapse type (excitatory or inhibitory). We demonstrate that pharmacological or genetic reduction of Cannabinoid Receptor 1 (CB1R) in GABAergic neurons rescues prolonged cortical Up states and deficits in sensory-driven cortical synchrony in Fmr1 KO mice. In support of these findings, recordings from Fmr1 KO cortical Layer (L) 2/3 pyramidal neurons revealed enhanced CB1R-mediated suppression of inhibitory synaptic currents. In contrast, genetic reduction of Cnr1 in glutamatergic neurons did not affect Up state duration, but deletion of Fmr1 in the same neurons was sufficient to cause long Up states. These findings support a model where loss of Fmr1 in glutamatergic neurons leads to enhanced CB1R-mediated suppression of GABAergic synaptic transmission, prolonged cortical circuit activation and reduced sensory-driven circuit synchronization. Results suggest that antagonism of CB1Rs as a therapeutic strategy to correct sensory processing deficits in FXS.

neuroscience↗

bioRxiv2019

Modelling the population dynamics of Plasmodium falciparum gametocytes in humans during malaria infection

Every year over two hundred million people are infected with the malaria parasite. Renewed efforts to eliminate malaria has highlighted the potential to interrupt transmission from humans to mosquitoes which is mediated through the gametocytes. Reliable prediction of transmission requires an improved understanding of in vivo kinetics of gametocytes. Here we study the population dynamics of Plasmodium falciparum gametocytes in human hosts by establishing a framework which incorporates improved measurements of parasitaemia in humans, a novel mathematical model of gametocyte dynamics, and model validation using a Bayesian hierarchical inference method. We found that the novel mathematical model provides an excellent fit to the available clinical data from 17 volunteers infected with P. falciparum, and reliably predicts observed gametocyte levels. We estimated the P. falciparums sexual commitment rate and gametocyte sequestration time in humans to be 0.54% (95% credible interval: 0.30-1.00) per life cycle and 8.39 (6.54-10.59) days respectively. Furthermore, we used the data-calibrated model to predict the effects of those gametocyte dynamics parameters on human-to-mosquito transmissibility, providing a method to link within-human host kinetics of malaria infection to epidemiological-scale infection and transmission patterns.

bioinformatics↗

bioRxiv2017

Proteomic Analysis Defines Kinase Taxonomies Specific For Subtypes Of Breast Cancer

Multiplexed small molecule inhibitors covalently bound to Sepharose beads (MIBs) were used to capture functional kinases in luminal, HER2-enriched and triple negative, basal-like and claudin-low breast cancer cell lines and tumors. Kinase MIB-binding profiles at baseline without perturbation proteomically distinguished the four breast cancer subtypes. Kinases lacking defined functions in breast cancer were highly represented in the MIB-binding taxonomies. We show that these understudied kinases, whose disease associations and pharmacology are generally unexplored, are integrated in kinase signaling subnetworks with kinases that have been previously well characterized in breast cancer. Computationally it was possible to define subtypes using profiles of less than 50 of the more than 300 kinases bound to MIBs that included understudied as well as metabolic and lipid kinases. Furthermore, analysis of MIB-binding profiles established potential functional annotations for these understudied kinases. Thus, comprehensive MIBs-based capture of kinases provides a unique proteomics-based method for integration of poorly characterized kinases of the understudied kinome into functional subnetworks in breast cancer cells and tumors that is not possible using genomic strategies. The MIB-binding profiles readily defined subtype-selective differential adaptive kinome reprogramming in response to targeted kinase inhibition, demonstrating how MIB profiles can be used in determining dynamic kinome changes that result in subtype selective phenotypic state changes.

cancer biology↗