Biology subjects

Shaver, A. O.

Publications and source records attributed to Shaver, A. O..

10 recordsLinked to original sources

bioRxiv2026

Multiscale learning and topological analysis across complex postures enable robust nematode size quantification in pharmacological assays

Body size is an important trait that reflects animal development and physiology. In nematodes, precise measurement is valuable for linking variation in body dimensions to biological questions such as developmental timing, genetic regulation, and drug responses. However, robust size measurements can be difficult to obtain because nematodes can vary in curvature, have self-intersecting postures, and overlap with neighboring animals. Current image analysis software, such as CellProfiler, can measure isolated animals in straight postures but struggles with curly or overlapping animals. Here, we present NemaSize, an artificial intelligence (AI)-aided pipeline to measure Caenorhabditis nematode body sizes across complex postures using multi-scale learning and topology-aware skeletonization. Using You Only Look Once (YOLO) models trained at different spatial scales, NemaSize first identifies individual animals in a large field of view (FOV; 6.75 x 6.75 mm) and then performs high-resolution body segmentation in the region of interest (ROI). Next, NemaSize converts segmented body masks into topological graph representations, allowing curly and overlapping animals to be classified and skeletonized according to the body topology. NemaSize achieved less than 4% overall error in length and width measurements across all posture classes. Compared to CellProfiler, NemaSize demonstrated higher robustness for complex postures, including a 48% error reduction in length measurements for curly or self-overlapping animals. Application of NemaSize in high-throughput imaging assays further shows that NemaSize provides accurate quantification of Caenorhabditis briggsae larval development in response to the anthelmintic drug ivermectin, a task that was difficult for CellProfiler because of curly animal postures. Together, NemaSize provides a robust approach for automated body size quantification for Caenorhabditis nematodes and will support broad applications in high-throughput pharmacological and genetic screens. Beyond nematodes, NemaSize introduces a multiscale computational framework for analyzing elongated biological objects with complex topologies.

pharmacology and toxicology↗

bioRxiv2025

Caenorhabditis briggsae ancestral genomic hyper-diversity contrasts with globally distributed genome-wide haplotypes

Comparative genomics provides a powerful framework to uncover the molecular and evolutionary mechanisms that shape genetic diversity within and across species, revealing how shared and lineage-specific processes influence their evolutionary trajectories through time. The nematode Caenorhabditis briggsae is distributed world-wide and is a comparative model to Caenorhabditis elegans in the biology of development, cellular mechanisms, neurobiology, genetic mappings of complex traits, and genome evolution. Following massive collection efforts by the nematode research community, we present the isolation of over 2,000 wild strains and analyses of genome sequences that catalog over six million single-nucleotide and insertion-deletion variants. This genome and strain resource provide a powerful means to interrogate the causal genetic bases of phenotypic variation for diverse traits. Additionally, we describe its global population structure and discover new and genetically distinct groups within this primarily self-fertilizing species, including groups of highly related strains that were sampled across different continents. We leverage expansive genetic variation to decipher the effects of linkage and selection on the distribution of genetic diversity across the genome and across geographic regions. Within the species, we find genomic regions with extremely high levels of genetic variation similar to hyper-divergent regions found in C. elegans and other species. These regions harbor new genes and variation enriched for environmental sensing and pathogen responses. In comparison to the outbreeding sister species Caenorhabditis nigoni, we conclude that long-term balancing selection has maintained substantial functional variation since the divergence from their outbreeding ancestor, likely in response to differences in the ecological niche. Overall, this massive strain resource enables future comparative genetics and genomics studies, including genome-wide association studies between Caenorhabditis species.

genomics↗

bioRxiv2025

Natural variation suggests candidate genes underlying Caenorhabditis elegans susceptibility to diverse toxicants

Genetic differences among individuals shape how they respond to environmental toxicants, but the identification and validation of the genes responsible for this variation is difficult, particularly in humans. Consequently, our limited knowledge of the genes that influence susceptibility constrains our ability to accurately predict the risks posed by environmental toxicants. To identify genes underlying natural differences in toxicant susceptibilities, we measured the effects of 23 environmental toxicants on larval development across 195 genetically diverse Caenorhabditis elegans strains using a high-throughput imaging platform. We then combined these response data with whole-genome sequences to perform genome-wide association mappings, identifying 40 genomic regions where genetic variants are correlated with susceptibility differences. Many of these regions are enriched for genes involved in biological processes previously linked with toxicant responses, supporting the potential contributions of these genes to natural variation in susceptibility. Using a set of heuristics, we identified 94 candidate susceptibility genes, offering targets for experimental validation that could ultimately inform toxicant risk prediction and regulatory assessment by linking genetic variation to differences in susceptibility. Impact StatementAnalysis of natural genetic variation among 195 wild C. elegans strains identified 94 candidate genes putatively linked to differences in susceptibility to 23 environmental toxicants. These findings can inform the discovery of conserved susceptibility genes and the development of biomarkers that improve chemical risk assessment by accounting for genetic differences among humans.

pharmacology and toxicology↗

bioRxiv2025

Survey of benzimidazole resistance in ascarid parasites of poultry

Ascarid parasites, such as Ascaridia galli and Heterakis gallinarum, are nearly ubiquitous in poultry and can cause serious production losses. H. gallinarum is of particular concern because of its role as a vector for the protozoan Histomonas meleagridis, the cause of blackhead disease. Currently, only the benzimidazole anthelmintic, fenbendazole (FBZ), is approved for use in poultry, and recently, FBZ resistance has been discovered and validated in populations of the turkey ascarid Ascaridia dissimilis and in ascarid of gallinaceous birds H. gallinarum. Here, we further explore the prevalence of resistance in poultry ascarids by testing FBZ efficacy against thirteen isolates of A. galli and eight isolates of H. gallinarum. Isolates were used to infect day-old naive chickens. Four weeks after infection, animals to be treated received the label-recommended dosage of FBZ (SafeGuard Aquasol) for five days, per the manufacturers directions. One week after the fifth day of treatment, animals were euthanized and parasite burdens were counted to determine treatment efficacy between the untreated and treated groups. Resistance was identified and validated in a single isolate of A. galli, marking the first confirmed case in the species. All isolates of H. gallinarum were found to be resistant. The emergence of resistance in A. galli and the high prevalence of resistance in H. gallinarum highlight the growing concern of resistance in parasites of poultry. Without approved alternative treatments, the detrimental effects of infections cannot be mitigated in resistant populations, significantly impacting profit margins. Diagnostics that enable broader surveys are necessary to understand the full scope of the problem. However, we show that resistance is present across production species and should act as an impetus for the discovery of new treatments and the adoption of new management strategies.

microbiology↗

bioRxiv2025

Independent mechanisms of benzimidazole resistance across Caenorhabditis nematodes

Benzimidazoles, a widely used class of anthelmintic drugs, target beta-tubulin, disrupt microtubule formation, and delay nematode development. In parasitic nematodes, mutations in beta-tubulin genes are predicted to inhibit benzimidazole binding and are associated with resistance. In the free-living nematode Caenorhabditis elegans, loss-of-function mutations in the beta-tubulin gene ben-1 cause benzimidazole resistance. Although several beta-tubulin mutations serve as established markers of resistance, the prediction of the effects of novel variants in different nematode species remains challenging. Here, we identified novel beta-tubulin variants predicted to confer benzimidazole resistance across wild strains in three Caenorhabditis species: C. elegans, Caenorhabditis briggsae, and Caenorhabditis tropicalis. The three Caenorhabditis species are experimentally tractable, have characterized beta-tubulin gene complements, and defined natural niches, which allowed us to identify variants in beta-tubulin genes and test which variants are associated with resistance. We hypothesized that, if these species experienced similar selective pressures, they would evolve resistance to benzimidazoles by mutations in a beta-tubulin gene (tbb-1, tbb-2, mec-7, tbb-4, and ben-1). In the three Caenorhabditis species, we tested all strains harboring variants in the five conserved beta-tubulin genes for benzimidazole resistance. In C. elegans, we found that a heterogeneous set of variants in ben-1 were associated with resistance. By contrast, only two variants in C. briggsae ben-1 (W21stop and Q134H) were associated with resistance. C. tropicalis was distinct from the other two species, where no strains with variants in any beta-tubulin gene were resistant. We generated deletions of ben-1 in C. briggsae and C. tropicalis and confirmed that loss of ben-1 confers resistance in both species. Our findings reveal species-specific patterns of beta-tubulin-mediated benzimidazole resistance and emphasize that prediction of variants in beta-tubulin genes alone is not sufficient to predict resistance, especially across diverse nematode species. AUTHOR SUMMARYMutations in beta-tubulin genes have been associated with benzimidazole resistance across nematode species, yet predicting novel resistance variants remains challenging. Using wild strains from three Caenorhabditis species, we identified strains with variants in beta-tubulin genes and tested each strain for benzimidazole resistance. In C. elegans, a diverse set of loss-of-function variants in ben-1 were associated with resistance. Whereas in C. briggsae, only two ben-1 alleles were associated with resistance, suggesting selection acts differently in this species despite a similar niche as C. elegans. C. tropicalis had no strains with beta-tubulin variants that were resistant. Our results highlight species-specific patterns of benzimidazole resistance.

genetics↗

bioRxiv2024

Quantifying the fitness effects of resistance alleles with and without anthelmintic selection pressure using Caenorhabditis elegans

Albendazole and ivermectin are the two most commonly co-administered anthelmintic drugs in mass-drug administration programs worldwide. Despite emerging resistance, we do not fully understand the mechanisms of resistance to these drugs nor the consequences of delivering them in combination. Albendazole resistance has primarily been attributed to variation in the drug target, a beta-tubulin gene. Ivermectin targets glutamate-gated chloride channel (GluCl) genes, but it is unknown whether these genes are involved in ivermectin resistance in nature. Using Caenorhabditis elegans, we defined the fitness costs associated with loss of the drug target genes singly or in combinations of the genes that encode GluCl subunits. We quantified the loss-of-function effects on three traits: (i) multi-generational competitive fitness, (ii) fecundity, and (iii) development. In competitive fitness and development assays, we found that a deletion of the beta-tubulin gene ben-1 conferred albendazole resistance, but ivermectin resistance required loss of two GluCl genes (avr-14 and avr-15) or loss of three GluCl genes (avr-14, avr-15, and glc-1). The fecundity assays revealed that loss of ben-1 did not provide any fitness benefit in albendazole and that no GluCl deletion mutants were resistant to ivermectin. Next, we searched for evidence of multi-drug resistance across the three traits. Loss of ben-1 did not confer resistance to ivermectin, nor did loss of any single GluCl subunit or combination confer resistance to albendazole. Finally, we assessed the development of 124 C. elegans wild strains across six benzimidazoles and seven macrocyclic lactones to identify evidence of multi-drug resistance between the two drug classes and found a strong phenotypic correlation within a drug class but not across drug classes. Because each gene affects various aspects of nematode physiology, these results suggest that it is necessary to assess multiple fitness traits to evaluate how each gene contributes to anthelmintic resistance. AUTHOR SUMMARYControl of parasitic nematodes often depends on mass-drug administration (MDA) programs, where combinations of anthelmintics are distributed to at-risk populations. Two commonly co-administered anthelmintic drugs in MDA programs are albendazole and ivermectin, and resistance to both drugs has emerged. Although the mechanism of resistance (MoR) to albendazole has been primarily attributed to variation in a beta-tubulin gene, the MoR to ivermectin remains unknown. Ivermectin acts through pentameric glutamate-gated chloride channels (GluCls). However, it is unclear whether genes that encode GluCls are involved in ivermectin resistance in parasitic nematodes. Using Caenorhabditis elegans, we quantified the fitness costs associated with deletions of the beta-tubulin gene ben-1 and three genes encoding GluCl subunits avr-14, avr-15, and glc-1 on three traits: (i) multi-generational competitive fitness, (ii) fecundity, and (iii) development. We found different anthelmintic responses across strains and traits but no evidence of multi-drug resistance. Our results suggest that multiple traits should be considered to understand resistance comprehensively and that the determination of whether a gene plays a role in anthelmintic resistance depends on the trait measured. Understanding the quantitative effects and fitness-associated costs of each GluCl subunit in C. elegans can help explain the costs of mutations in these subunits in parasites.

genetics↗

bioRxiv2022

Variation in anthelmintic responses are driven by genetic differences among diverse C. elegans strains

Treatment of parasitic nematode infections in humans and livestock relies on a small arsenal of anthelmintic drugs that have historically reduced parasite burdens. However, anthelmintic resistance (AR) is increasing, and little is known about the molecular and genetic causes of resistance for most drugs. The free-living roundworm Caenorhabditis elegans has proven to be a tractable model to understand AR, where studies have led to the identification of molecular targets of all major anthelmintic drug classes. Here, we used genetically diverse C. elegans strains to perform dose-response analyses across 26 anthelmintic drugs that represent the three major anthelmintic drug classes (benzimidazoles, macrocyclic lactones, and nicotinic acetylcholine receptor agonists) in addition to seven other anthelmintic classes. First, we found that C. elegans strains displayed significant variation in anthelmintic responses across drug classes. Dose-response trends within a drug class showed that the C. elegans strains elicited similar responses within the benzimidazoles but variable responses in the macrocyclic lactones and nicotinic acetylcholine receptor agonists. Next, we compared the effective concentration estimates to induce a 10% maximal response (EC10) and slope estimates of each dose-response curve of each strain to the reference strain, N2, which enabled the identification of anthelmintics with population-wide differences to understand how genetics contribute to AR. Because genetically diverse strains displayed differential susceptibilities within and across anthelmintics, we show that C. elegans is a useful model for screening potential nematicides. Third, we quantified the heritability of responses to each anthelmintic and observed a significant correlation between exposure closest to the EC10 and the exposure that exhibited the most heritable responses. Heritable genetic variation can be explained by strain-specific anthelmintic responses within and across drug classes. These results suggest drugs to prioritize in genome-wide association studies, which will enable the identification of AR genes. AUTHOR SUMMARYParasitic nematodes infect most animal species and significantly impact human and animal health. Control of parasitic nematodes in host species relies on a limited collection of anthelmintic drugs. However, anthelmintic resistance is widespread, which threatens our ability to control parasitic nematode populations. Here, we used the non-parasitic roundworm Caenorhabditis elegans as a model to study anthelmintic resistance across 26 anthelmintics that span ten drug classes. We leveraged the genetic diversity of C. elegans to quantify anthelmintic responses across a range of doses, estimate dose-response curves, fit strain-specific model parameters, and calculate the contributions of genetics to these parameters. We found that genetic variation within a species plays a considerable role in anthelmintic responses within and across drug classes. Our results emphasize how the incorporation of genetically diverse C. elegans strains is necessary to understand anthelmintic response variation found in natural populations. These results highlight drugs to prioritize in future mapping studies to identify genes involved in anthelmintic resistance. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=125 HEIGHT=200 SRC="FIGDIR/small/518036v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@6222bborg.highwire.dtl.DTLVardef@d635a6org.highwire.dtl.DTLVardef@15c3935org.highwire.dtl.DTLVardef@1afe3fe_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2022

Ion Mobility for Unknown Metabolite Identification: Hope or Hype?

Ion mobility (IM) spectrometry provides semi-orthogonal data to mass spectrometry (MS), showing promise for identifying unknown metabolites in complex non-targeted metabolomics datasets. While current literature has showcased IM-MS for identifying unknowns under near ideal circumstances, less work has been conducted to evaluate the performance of this approach in metabolomics studies involving highly complex samples with difficult matrices. Here, we present a workflow incorporating de novo molecular formula annotation and MS/MS structure elucidation using SIRIUS 4 with experimental IM collision cross-section (CCS) measurements and machine learning CCS predictions to identify differential unknown metabolites in mutant strains of Caenorhabditis elegans. For many of those ion features this workflow enabled the successful filtering of candidate structures generated by in silico MS/MS predictions, though in some cases annotations were challenged by significant hurdles in instrumentation performance and data analysis. While for 37% of differential features we were able to successfully collect both MS/MS and CCS data, fewer than half of these features benefited from a reduction in the number of possible candidate structures using CCS filtering due to poor matching of the machine learning training sets, limited accuracy of experimental and predicted CCS values, and lack of candidate structures resulting from the MS/MS data. When using a CCS error cutoff of {+/-}3%, an average 28% of candidate structures could be successfully filtered. Herein, we identify and describe the bottlenecks and limitations associated with the identification of unknowns in non-targeted metabolomics using IM-MS to focus and provide insight on areas requiring further improvement.

biochemistry↗

bioRxiv2022

An anchored experimental design and meta-analysis approach to address batch effects in large-scale metabolomics

Large-scale untargeted metabolomics studies suffer from individual variation, batch effects and instrument variability, making comparisons of common spectral features across studies difficult. One solution is to compare studies after compound identification. However, compound identification is expensive and time consuming. We successfully identify common spectral features across multiple studies, with a generalizable experimental design approach. First, we included an anchor strain, PD1074, during sample and data collection. Second, we collected data in blocks with multiple controls. These anchors enabled us to successfully integrate three studies of Caenorhabditis elegans for nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS) data from five different assays. We found 34% and 14% of features to be significant in LC-MS and NMR, respectively. Between 20-50% of spectral features differ in a mutant and among a set of genetically diverse natural strains, suggesting this reduced set of spectral features are excellent targets for compound identification. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/485859v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@84abe1org.highwire.dtl.DTLVardef@3066fforg.highwire.dtl.DTLVardef@1ba166corg.highwire.dtl.DTLVardef@164cf0_HPS_FORMAT_FIGEXP M_FIG C_FIG Fourteen C. elegans strains are used in three individual studies. PD1074, the anchor control strain (orange), is grown alongside test strains (green, yellow, purple). Multiple biological replicates of PD1074 captures environmental variation in growth conditions. Non-polar and polar metabolic data across the three studies (i.e., natural strains, central metabolism mutants, and UGT mutants) were collected by nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Data acquisition controls in each block included biological reference material and pooled PD1074 samples. Biological replicates of PD1074 (n = 42 for LC-MS, n = 52 for NMR) were included in all batches. Meta-analysis provided comparable inferences to mixed effects models, and the estimated relative effects of each test strain to PD1074 and straightforward comparisons of test strains across experiments.

systems biology↗

bioRxiv2021

Long-Term Metabolomics Reference Material

The use of quality control samples in metabolomics ensures data quality, reproducibility and comparability between studies, analytical platforms and laboratories. Long-term, stable and sustainable reference materials (RMs) are a critical component of the QA/QC system, however, the limited selection of currently available matrix matched RMs reduce their applicability for widespread use. To produce a RM in any context, for any matrix that is robust to changes over the course of time we developed IBAT (Iterative Batch Averaging meThod). To illustrate this method, we generated 11 independently grown E. coli batches and made a RM over the course of 10 IBAT iterations. We measured the variance of these materials by NMR and showed that IBAT produces a stable and sustainable RM over time. This E. coli RM was then used as food source to produce a C. elegans RM for a metabolomics experiment. The metabolite extraction of this material alongside 41 independently grown individual C. elegans samples of the same genotype, allowed to estimate the proportion of sample variation in pre-analytical steps. From the NMR data, we found that 40% of the metabolite variance is due to the metabolite extraction process and analysis and 60% is due to sample-to-sample variance. The availability of RMs in untargeted metabolomics is one of the predominant needs of the metabolomics community that reach beyond quality control practices. IBAT addresses this need by facilitating the production of biologically relevant RMs and increasing their widespread use.

biochemistry↗