Biology subjects

Cooke, R.

Publications and source records attributed to Cooke, R..

5 recordsLinked to original sources

bioRxiv2024

Human melanoma cell lines that possess wild-type BRAF alleles but are dependent on ERBB4 and ERBB2

Metastatic skin cutaneous melanomas that contain wild-type BRAF alleles typically possess an activating mutation in a RAS allele or a loss-of-function mutation in an NF1 allele ("BRAF-WT&RAS/NF1-mutant melanomas"). Nonetheless, these tumors remain a significant clinical challenge; they are resistant to MEK and BRAF inhibitors, their response to immune checkpoint inhibitors is less robust than the response of BRAF mutant melanomas to these agents, and additional validated targets for therapeutic intervention have yet to be identified. Previous work from our laboratory has demonstrated that ERBB4 is required for the proliferation of the IPC-298, MEL-JUSO, MeWo, and SK-MEL-2 BRAF-WT&RAS/NF1-mutant melanoma cell lines. Surprisingly, the synthetic constitutively dimerized and active Q646C ERBB4 mutant allele appears to strongly inhibits the proliferation of BRAF-WT&RAS/NF1- mutant melanoma cell lines. Given that we have also previously demonstrated that ERBB4-ERBB2 and ERBB4-EGFR heterodimers are more potent drivers of proliferation than are ERBB4 homodimers, here we begin to test the hypothesis that ERBB4 heterodimers drive the proliferation of BRAF-WT&RAS/NF1-mutant melanoma cell lines. Here we demonstrate that the kinase-deficient (dominant-negative) ERBB2 K753A mutant allele inhibits the clonogenic proliferation of the IPC-298, MEL-JUSO, and MeWo ERBB4-dependent, BRAF-WT&RAS/NF1-mutant melanoma cell lines. Moreover, the kinase-deficient (dominant-negative) EGFR K721A mutant allele inhibits the clonogenic proliferation of the MeWo cell line, but not the IPC-298 or MEL-JUSO cell lines. Finally, the clonogenic proliferation of the SK-MEL-2 ERBB4-dependent, BRAF-WT&RAS/NF1-mutant melanoma cell line is unaffected by the ERBB2 K753A or EGFR K721A dominant-negative mutant alleles. We discuss these findings in the context of our hypothesis that ERBB4 heterodimers drive the proliferation of BRAF-WT&RAS/NF1-mutant melanoma cell lines.

cancer biology↗

bioRxiv2020

Archaeogenomic Distinctiveness of the Isthmo-Colombian Area

The recently enriched genomic history of Indigenous groups in the Americas is still meagre concerning continental Central America. Here, we report ten pre-Hispanic (plus two early colonial) genomes and 84 genome-wide profiles from seven groups presently living in Panama. Our analyses reveal that pre-Hispanic demographic changes and isolation events contributed to create the extensive genetic structure currently seen in the area, which is also characterized by a distinctive Isthmo-Colombian Indigenous component. This component drives these populations on a specific variability axis and derives from the local admixture of different ancestries of northern North American origin(s). Two of these ancestries were differentially associated to Pleistocene Indigenous groups that also moved into South America leaving heterogenous footprints. An additional Pleistocene ancestry was brought by UPopI, a still unsampled population that remained restricted to the Isthmian area, expanded locally during the early Holocene, and left genomic traces up to the present.

genomics↗

bioRxiv2019

iucn_sim - Improved predictions of future extinctions using IUCN status assessments

The ongoing environmental crisis poses an urgent need to forecast the who, where, and when of future species extinctions, as such information is crucial for targeting conservation efforts. Commonly, such forecasts are made based on conservation status assessments produced by the International Union for Conservation of Nature (IUCN). However, when researchers apply these IUCN conservation status data for predicting future extinctions, important information is often omitted, which can impact the accuracy of these predictions. Here we present a new approach and a software for simulating future extinctions based on IUCN conservation status information, which incorporates generation length information of individual species when modeling extinction risks. Additionally, we explicitly model future changes in conservation status for each species, based on status transition rates that we estimate from the IUCN assessment history of the last decades. Finally, we apply a Markov chain Monte Carlo algorithm to estimate extinction rates for each species, based on the simulated future extinctions. These estimates inherently incorporate the chances of conservation status changes and the generation length for each given species and are specific to the simulated time frame. We demonstrate the utility of our approach by estimating extinction rates for all bird species. Our average extinction risk estimate for the next 100 years across all birds is 6.98 x 10-4 extinctions per species-year, and we predict an expected biodiversity loss of between 669 to 738 bird species within that time frame. Further, the rate estimates between species sharing the same IUCN status show larger variation than the rates estimated with alternative approaches, which reflects expected differences in extinction risk among taxa of the same conservation status. Our method demonstrates the utility of applying species-specific information to the estimation of extinction rates, rather than assuming equal extinction risks for species assigned to the same conservation status.

evolutionary biology↗

bioRxiv2019

Automated Cytogenetic Biodosimetry at Population-Scale

IntroductionThe dicentric chromosome (DC) assay accurately quantifies exposure to radiation, however manual and semi-automated assignment of DCs has limited its use for a potential large-scale radiation incident. The Automated Dicentric Chromosome Identifier and Dose Estimator Chromosome (ADCI) software automates unattended DC detection and determines radiation exposures, fulfilling IAEA criteria for triage biodosimetry. We present high performance ADCI (ADCI-HT), with the requisite throughput to stratify exposures of populations in large scale radiation events.\n\nMethodsADCI-HT streamlines dose estimation by optimal scheduling of DC detection, given that the numbers of samples and metaphase cell images in each sample vary. A supercomputer analyzes these data in parallel, with each processor handling a single image at a time. Processor resources are managed hierarchically to maximize a constant stream of sample and image analysis. Metaphase data from populations of individuals with clinically relevant radiation exposures after simulated large nuclear incidents were analyzed. Sample counts were derived from US Census data. Analysis times and exposures were quantified for 15 different scenarios.\n\nResultsProcessing of metaphase images from 1,744 samples (500 images each) used 16,384 CPUs and was completed in 1hr 11min 23sec, with radiation dose of all samples determined in 32 sec with 1,024 CPUs. Processing of 40,000 samples with varying numbers of metaphase cells, 10 different exposures from 5 different biodosimetry labs met IAEA accuracy criteria (dose estimate differences were < 0.5 Gy; median = 0.07) and was completed in ~25 hours. Population-scale metaphase image datasets within radiation contours of nuclear incidents were defined by exposure levels (either >1 Gy or >2 Gy). The time needed to analyze samples of all individuals receiving exposures from a high yield airborne nuclear device ranged from 0.6-7.4 days, depending on the population density.\n\nConclusionADCI-HT delivers timely and accurate dose estimates in a simulated population-scale radiation incident.

bioinformatics↗

bioRxiv2018

Mavacamten stabilizes a folded-back sequestered super-relaxed state of β-cardiac myosin

SummaryMutations in {beta}-cardiac myosin, the predominant motor protein for human heart contraction, can alter power output and cause cardiomyopathy. However, measurements of the intrinsic force, velocity and ATPase activityof myosin have not provided a consistent mechanism to link mutations to muscle pathology. An alternative modelpositsthat mutations in myosin affect the stability ofa sequestered, super-relaxed state (SRX) of the proteinwith very slow ATP hydrolysis and thereby change the number of myosin heads accessible to actin. Here, using a combination of biochemical and structural approaches, we show that purified myosin enters aSRX thatcorresponds to a folded-back conformation, which in muscle fibersresults insequestration of heads around the thick filament backbone. Mutations that cause HCM destabilize this state, while the small molecule mavacamtenpromotes it. These findings provide a biochemical and structural link between the genetics and physiology ofcardiomyopathywith implications for therapeutic strategies.

biochemistry↗