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

Albendazole (a benzimidazole) and ivermectin (a macrocyclic lactone) 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 channels (GluCls), but it is unknown whether GluCl 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 the loss of two GluCl genes (avr-14 and avr-15). The fecundity assays revealed that loss of ben-1 did not provide any fitness benefit in albendazole conditions 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.

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.

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

Treatment of parasitic nematode infections in humans and livestock relies on a limited 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 similar anthelmintic responses within drug classes and significant variation across drug classes. 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 laboratory reference strain, 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 before applications to helminths. Third, we quantified the levels of anthelmintic response variation caused by genetic differences among individuals (heritability) to each drug and observed a significant correlation between exposure closest to the EC10 and the exposure that exhibited the most heritable responses. These results suggest drugs to prioritize in genome-wide association studies, which will enable the identification of AR genes.

Unknown Metabolite Identification Using Machine Learning Collision Cross-Section Prediction and Tandem Mass Spectrometry.

Ion mobility (IM) spectrometry provides semiorthogonal data to mass spectrometry (MS), showing promise for identifying unknown metabolites in complex non-targeted metabolomics data sets. 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%, on 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 insights into areas requiring further improvement.

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

Untargeted metabolomics studies are unbiased but identifying the same feature across studies is complicated by environmental variation, batch effects, and instrument variability. Ideally, several studies that assay the same set of metabolic features would be used to select recurring features to pursue for identification. Here, we developed an anchored experimental design. This generalizable approach enabled us to integrate three genetic studies consisting of 14 test strains of Caenorhabditis elegans prior to the compound identification process. An anchor strain, PD1074, was included in every sample collection, resulting in a large set of biological replicates of a genetically identical strain that anchored each study. This enables us to estimate treatment effects within each batch and apply straightforward meta-analytic approaches to combine treatment effects across batches without the need for estimation of batch effects and complex normalization strategies. We collected 104 test samples for three genetic studies across six batches to produce five analytical datasets from two complementary technologies commonly used in untargeted metabolomics. Here, we use the model system C. elegans to demonstrate that an augmented design combined with experimental blocks and other metabolomic QC approaches can be used to anchor studies and enable comparisons of stable spectral features across time without the need for compound identification. This approach is generalizable to systems where the same genotype can be assayed in multiple environments and provides biologically relevant features for downstream compound identification efforts. All methods are included in the newest release of the publicly available SECIMTools based on the open-source Galaxy platform.

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 quality assurance/quality control (QA/QC) system; however, the limited selection of currently available matrix-matched RMs reduces their applicability for widespread use. To produce an RM in any context, for any matrix that is robust to changes over the course of time, we developed iterative batch averaging method (IBAT). To illustrate this method, we generated 11 independently grown Escherichia coli batches and made an RM over the course of 10 IBAT iterations. We measured the variance of these materials by nuclear magnetic resonance (NMR) and showed that IBAT produces a stable and sustainable RM over time. This E. coli RM was then used as a food source to produce a Caenorhabditis 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 us to estimate the proportion of sample variation in preanalytical 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.

Culture and Assay of Large-Scale Mixed-Stage Caenorhabditis elegans Populations.

Caenorhabditis elegans (C. elegans) has been and remains a valuable model organism to study developmental biology, aging, neurobiology, and genetics. The large body of work on C. elegans makes it an ideal candidate to integrate into large-population, whole-animal studies to dissect the complex biological components and their relationships with another organism. In order to use C. elegans in collaborative -omics research, a method is needed to generate large populations of animals where a single sample can be split and assayed across diverse platforms for comparative analyses. Here, a method to culture and collect an abundant mixed-stage C. elegans population on a large-scale culture plate (LSCP) and subsequent phenotypic data is presented. This pipeline yields sufficient numbers of animals to collect phenotypic and population data, along with any data needed for -omics experiments (i.e., genomics, transcriptomics, proteomics, and metabolomics). In addition, the LSCP method requires minimal manipulation to the animals themselves, less user preparation time, provides tight environmental control, and ensures that handling of each sample is consistent throughout the study for overall reproducibility. Lastly, methods to document population size and population distribution of C. elegans life stages in a given LSCP are presented.

Social status alters immune regulation and response to infection in macaques.

Social status is one of the strongest predictors of human disease risk and mortality, and it also influences Darwinian fitness in social mammals more generally. To understand the biological basis of these effects, we combined genomics with a social status manipulation in female rhesus macaques to investigate how status alters immune function. We demonstrate causal but largely plastic social status effects on immune cell proportions, cell type-specific gene expression levels, and the gene expression response to immune challenge. Further, we identify specific transcription factor signaling pathways that explain these differences, including low-status-associated polarization of the Toll-like receptor 4 signaling pathway toward a proinflammatory response. Our findings provide insight into the direct biological effects of social inequality on immune function, thus improving our understanding of social gradients in health.

Efficient Genome-Wide Sequencing and Low-Coverage Pedigree Analysis from Noninvasively Collected Samples.

Research on the genetics of natural populations was revolutionized in the 1990s by methods for genotyping noninvasively collected samples. However, these methods have remained largely unchanged for the past 20 years and lag far behind the genomics era. To close this gap, here we report an optimized laboratory protocol for genome-wide capture of endogenous DNA from noninvasively collected samples, coupled with a novel computational approach to reconstruct pedigree links from the resulting low-coverage data. We validated both methods using fecal samples from 62 wild baboons, including 48 from an independently constructed extended pedigree. We enriched fecal-derived DNA samples up to 40-fold for endogenous baboon DNA and reconstructed near-perfect pedigree relationships even with extremely low-coverage sequencing. We anticipate that these methods will be broadly applicable to the many research systems for which only noninvasive samples are available. The lab protocol and software ("WHODAD") are freely available at www.tung-lab.org/protocols-and-software.html and www.xzlab.org/software.html, respectively.

Wolbachia do not live by reproductive manipulation alone: infection polymorphism in Drosophila suzukii and D. subpulchrella.

Drosophila suzukii recently invaded North America and Europe. Populations in Hawaii, California, New York and Nova Scotia are polymorphic for Wolbachia, typically with <20% infection frequency. The Wolbachia in D. suzukii, denoted wSuz, is closely related to wRi, the variant prevalent in continental populations of D. simulans. wSuz is also nearly identical to Wolbachia found in D. subpulchrella, plausibly D. suzukii's sister species. This suggests vertical Wolbachia transmission through cladogenesis ('cladogenic transmission'). The widespread occurrence of 7-20% infection frequencies indicates a stable polymorphism. wSuz is imperfectly maternally transmitted, with wild infected females producing on average 5-10% uninfected progeny. As expected from its low frequency, wSuz produces no cytoplasmic incompatibility (CI), that is, no increased embryo mortality when infected males mate with uninfected females, and no appreciable sex-ratio distortion. The persistence of wSuz despite imperfect maternal transmission suggests positive fitness effects. Assuming a balance between selection and imperfect transmission, we expect a fitness advantage on the order of 20%. Unexpectedly, Wolbachia-infected females produce fewer progeny than do uninfected females. We do not yet understand the maintenance of wSuz in D. suzukii. The absence of detectable CI in D. suzukii and D. subpulchrella makes it unlikely that CI-based mechanisms could be used to control this species without transinfection using novel Wolbachia. Contrary to their reputation as horizontally transmitted reproductive parasites, many Wolbachia infections are acquired through introgression or cladogenesis and many cause no appreciable reproductive manipulation. Such infections, likely to be mutualistic, may be central to understanding the pervasiveness of Wolbachia among arthropods.