Biology subjects

Oke, A.

Publications and source records attributed to Oke, A..

7 recordsLinked to original sources

bioRxiv2024

Analyzing high-throughput assay data to advance the rapid screening of environmental chemicals for human reproductive toxicity

While high-throughput (HTP) assays have been proposed as platforms to rapidly assess reproductive toxicity, there is currently a lack of established assays that specifically address germline development/function and fertility. We assessed the applicability domains of yeast (S. cerevisiae) and nematode (C. elegans) HTP assays in toxicity screening of 124 environmental chemicals, determining their agreement in identifying toxicants and their concordance with reproductive toxicity in vivo. We integrated data generated in the two models and compared results using a streamlined, semi-automated benchmark dose (BMD) modeling approach. We then extracted and modeled relevant mammalian in vivo data available for the matching chemicals included in the Toxicological Reference Database (ToxRefDB). We ranked potencies of common compounds using the BMD and evaluated correlation between the datasets using Pearson and Spearman correlation coefficients. We found moderate to good correlation across the three data sets, with r = 0.48 (95% CI: 0.28-1.00, p<0.001) and rs = 0.40 (p=0.002) for the parametric and rank order correlations between the HTP BMDs; r = 0.95 (95% CI: 0.76-1.00, p=0.0005) and rs = 0.89 (p=0.006) between the yeast assay and ToxRefDB BMDs; and r = 0.81 (95% CI: 0.28-1.00, p=0.014) and rs = 0.75 (p=0.033) between the worm assay and ToxRefDB BMDs. Our findings underscore the potential of these HTP assays to identify environmental chemicals that exhibit reproductive toxicity. Integrating these HTP datasets into mammalian in vivo prediction models using machine learning methods could further enhance the predictive value of these assays in future rapid screening efforts.

developmental biology↗

bioRxiv2024

A high-throughput method for quantifying Drosophila fecundity

Measurements of Drosophila fecundity are used in a wide variety of studies, such as investigations of stem cell biology, nutrition, behavior, and toxicology. In addition, because fecundity assays are performed on live flies, they are suitable for longitudinal studies such as investigations of aging or prolonged chemical exposure. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another; the RoboCam, a low-cost, custom built robotic camera to capture images of the wells automatically; and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period; and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth) In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high throughput egg laying assays that require exposing flies to multiple different media conditions.

genetics↗

bioRxiv2024

Screening and characterization of 133 physiologically-relevant environmental chemicals for reproductive toxicity

Reproduction is a functional outcome that relies on complex cellular, tissue, and organ interactions that span the developmental period to adulthood. Thus, the assessment of its disruption by environmental chemicals is remarkably painstaking in conventional toxicological animal models and does not scale up to the number of chemicals present in our environment and requiring testing. We adapted a previously described low-throughput in vivo chromosome segregation assay using C. elegans predictive of reproductive toxicity and leveraged available public data sources (ToxCast, ICE) to screen and characterize 133 physiologically-relevant chemicals in a high-throughput manner. The screening outcome was further validated in a second, independent in vivo assay assessing embryonic viability. In total, 13 chemicals were classified as reproductive toxicants with the two most active chemicals belonging to the large family of Quaternary Ammonium Compounds (QACs) commonly used as disinfectants but with limited available reproductive toxicity data. We compared the results from the C. elegans assay with ToxCast in vitro data compiled from 700+ cell response assays and 300+ signaling pathways-based assays. We did not observe a difference in the bioactivity or in average potency (AC50) between the top and bottom chemicals. However, the intended target categories were significantly different between the classified chemicals with, in particular, an over-representation of steroid hormone targets for the high Z-score chemicals. Taken together, these results point to the value of in vivo models that scale to high-throughput level for reproductive toxicity assessment and to the need to prioritize the assessment of QACs impacts on reproduction.

pharmacology and toxicology↗

bioRxiv2022

Phenotype to genotype mapping using supervised and unsupervised learning

The relationship between the genotype, the genetic instructions encoded into a genome, and phenotype, the macroscopic realization of such instructions, remains mostly uncharted. In addition, tools able to uncover the connection between the phenotype with a specific set of responsible genes are still under definition. In this work, we focus on yeast organelles called vacuoles, which are cell membrane compartments that vary size and shape in response to various stimuli, and we develop a framework relating changes of cellular morphology to genetic modification. The method is a combination of convolutional neural network (CNN) and an unsupervised learning pipeline, which employs a deep-learning based segmentation, classification, and anomaly detection algorithm. From the live 3D fluorescence vacuole images, we observe that different genetic mutations generate distinct vacuole phenotypes and that the same mutation might correspond to more than one vacuole morphology. We trained a Unet architecture to segment our cellular images and obtain precise, quantitative information in 2D depth-encoded images. We then used an unsupervised learning approach to cluster the vacuole types and to establish a correlation between genotype and vacuole morphology. Using this procedure, we obtained 4 phenotypic groups. We extracted a set of 131 morphological features from the segmented vacuoles images, reduced to 50 after a tree-based feature selection. We obtained a purity of 85% adopting a Fuzzy K-Means based algorithm on a random subset of 880 images, containing all the detected phenotypic groups. Finally, we trained a CNN on the labels assigned during clustering. The CNN has been used for prediction of a large dataset (6942 images) with high accuracy (80%). Our approach can be applied extensively for live fluorescence image analysis and most importantly can unveil the basic principles relating genotype to vacuole phenotype in yeast cell, which can be thought as a first step for inferring cell designing principles to generate organelles with a specific, desired morphology.

bioinformatics↗

bioRxiv2022

A high-throughput approach to identify reproductive toxicants among environmental chemicals using an in vivo evaluation of gametogenesis in budding yeast Saccharomyces cerevisiae

BackgroundEnvironmental chemical exposures are likely making important contributions to current levels of infertility and its increasing incidence. Yet the US produces high volumes of industrial chemicals for which there is limited data on their potential human reproduction toxicity. Current assays typically used in policy and regulatory settings involve costly and timeconsuming whole-animal rodent tests which limit the rapidity with which one can assess the thousands of chemicals yet to be tested. ObjectiveOur aim was to develop a fast and reliable strategy to evaluate a large number of chemicals for reproductive toxicity by developing a high-throughput toxicity assessment using the yeast S. cerevisiae. MethodsYeast are chronically exposed to each environmental chemical at two doses, 30 M and 100 M, in a 96-well plate-based format throughout gametogenesis. Non-gametes are removed and chemicals are washed away before gamete viability is measured using absorbance at 600 nm to produce growth curves. The difference in time at half-maximal saturation with and without exposure is used to determine the extent of reproductive toxicity. ResultsWe validated our assay using bisphenol A (BPA), a well-established mammalian reproductive toxicant. We find that BPA in yeast has similar detrimental effects in meiosis as shown in worms and mammals. Competition assays with BPA analogs reveal that two of out of 19 BPA analogs examined (bisphenol E and 17{beta}-estradiol) show synergistic effects with BPA at doses tested and none show antagonistic effects. Out of 179 additional environmental chemicals, we designated 57 chemicals as reproductively toxic. Finally, by comparing chemicals in our cohort that have been evaluated for reproductive toxicity in mammalian studies, we find a statistically significant association between toxic chemicals in yeast and mammals. ConclusionWe show that a high-throughput assay using yeast may be a useful approach for rapidly and reliably identifying chemicals that pose a reproductive risk.

pharmacology and toxicology↗

bioRxiv2021

A Role for Synaptonemal Complex in Meiotic Mismatch Repair

During meiosis a large subset of interhomolog recombination repair intermediates form within the physical context of the synaptonemal complex (SC), a protein-rich structure assembled at the interface of aligned homologous chromosomes. However, the functional relationship between SC structure and homologous recombination remains poorly defined. In prior work we determined that tripartite SC is dispensable for recombination in S. cerevisiae; SC central element proteins Ecm11 and Gmc2 instead limit the number of recombination events. Here we report that while dispensable for recombination per se, SC central element proteins influence the processing of interhomolog recombination intermediates in a manner that minimizes errors in mismatch correction. Failure to correct mis-paired bases within heteroduplex at meiotic recombination sites leads to genotypically sectored colonies (post meiotic segregation events) arising from mitotic proliferation of mismatch-containing spores. We discovered an increase in post-meiotic segregation at the THR1 locus in cells lacking Ecm11 or Gmc2, or in the SC-deficient but crossover recombination-proficient zip1[{Delta}21-163] mutant. High-throughput sequencing of octad meiotic products revealed a genome-wide increase in recombination events with uncorrected mismatches in ecm11 mutants relative to wild type. Meiotic cells missing Ecm11 also display longer gene conversion tracts, but tract length alone does not account for the higher frequency of uncorrected mismatches. Interestingly, the per-nucleotide mismatch frequency is elevated in ecm11 mutants when analyzing all gene conversion tracts, but is similar between wild type and ecm11 if one considers only those events with uncorrected mismatches. Our data suggest that a subset of recombination events is similarly susceptible to mismatch repair errors in both wild type and ecm11 strains, but in ecm11 mutants many more recombination events fall into this inefficient repair category. Finally, we observe elevated post-meiotic segregation at THR1 in mutants with a dual deficiency in MutS{gamma}-mediated crossover recombination and SC assembly, but not in the mlh3 mutant, which lacks MutS{gamma} crossovers but has abundant SC. We propose that SC structure promotes efficient mismatch repair of joint molecule recombination intermediates resolved via both MutS{gamma}-associated and MutS{gamma}-independent pathways, and is the molecular basis for elevated post-meiotic segregation in both MutS{gamma} crossover-proficient (ecm11, gmc2) and MutS{gamma} crossover-deficient (msh4, zip3) strains.

genetics↗

bioRxiv2019

A New Role for Telomerase in Promoting Meiotic Homolog Pairing Fidelity

We report a role for telomerase, beyond its known function of telomeric DNA end extension, in maintaining normal chromosome dynamics during meiosis in Saccharomyces cerevisiae. When telomerase at telomeres was reduced by various genetic means, increased frequencies of crossover and noncrossover recombination events occurred. To investigate the mechanism of this increased meiotic recombination, we examined the kinetics of meiosis events, and tracked the movement of chromosomes in live cells during meiotic prophase. Cytoskeletal forces acting on telomeres during meiosis have been shown to promote active chromosome motion needed to pair homologous chromosomes. Here we show that changes in telomerase interaction with telomeres using a tlc1-11 mutant result in altered meiotic motion. Specifically, reduction in telomerase at telomeres leads to a decreased frequency of high velocity chromosome pulls. In the tlc1-11 mutant, we see earlier synapsis and increased genome-wide recombination for the majority of the cells and lower gamete viability. Notably, homologous pairing is not delayed unlike other telomere binding mutants. Although synapsis initiates earlier, the overall timing of synapsis remains the same, except for a subset of cells that do not exit meiosis I. Together, these results suggest that the strong pulling component of the active chromosome motion promotes homolog pairing fidelity, likely by pulling apart improperly associated regions. Our combined observations are consistent with a model in which telomerase-mediated telomeric anchoring to the nuclear envelope helps engage and properly transmit cytoskeletal forces to chromosomes. Thus, telomerase contributes to efficient chromosome movements leading to normal gamete viability.

cell biology↗