Comparing Sensitivity of Different Bee Species to Pesticides: A TKTD modeling approach.

Risk assessment for bees is mainly based on data for honey bees; however, risk assessment is intended to protect all bee species. This raises the question of whether data for honey bees are a good proxy for other bee species. This issue is not new and has resulted in several publications in which the sensitivity of bee species is compared based on the values of the 48-h median lethal dose (LD50) from acute test results. When this approach is used, observed differences in sensitivity may result both from differences in kinetics and from inherent differences in species sensitivity. In addition, the physiology of the bee, like its overall size, the size of the honey stomach (for acute oral tests), and the physical appearance (for acute contact tests) also influences the sensitivity of the bee. The recently introduced Toxicokinetic-Toxicodynamic (TKTD) model that was developed for the interpretation of honey bee tests (Bee General Uniform Threshold Model for Survival [BeeGUTS]) could integrate the results of acute oral tests, acute contact tests, and chronic tests within one consistent framework. We show that the BeeGUTS model can be calibrated and validated for other bee species and also that the honey bee is among the more sensitive bee species. In addition, we found that differences in sensitivity between species are smaller than previously published comparisons based on 48-h LD50 values. The time-dependency of the LD50 and the specifics of the bee physiology are the main causes of the wider variation found in the published literature. Environ Toxicol Chem 2024;00:1-11. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Towards Precision Ecotoxicology: Leveraging Evolutionary Conservation of Pharmaceutical and Personal Care Product Targets to Understand Adverse Outcomes Across Species and Life Stages.

Translation of environmental science to the practice aims to protect biodiversity and ecosystem services, and our future ability to do so relies on the development of a precision ecotoxicology approach wherein we leverage the genetics and informatics of species to better understand and manage the risks of global pollution. A little over a decade ago, a workshop focusing on the risks of pharmaceuticals and personal care products (PPCPs) in the environment identified a priority research question, "What can be learned about the evolutionary conservation of PPCP targets across species and life stages in the context of potential adverse outcomes and effects?" We review the activities in this area over the past decade, consider prospects of more recent developments, and identify future research needs to develop next-generation approaches for PPCPs and other global chemicals and waste challenges. Environ Toxicol Chem 2024;43:526-536. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Hopamine as Personalized Medicine for Persons with Parkinson's Disease.

Prescribing dopamine replacement therapy remains the most common approach used by physicians who strive to support persons with Parkinson's disease. In this viewpoint, we argue that instead of merely prescribing dopamine, healthcare professionals should particularly encourage and enable persons with Parkinson's disease to draft their own personalized prescription of "hopamine". The term hopamine is a self-invented neologism representing the uniquely personal set of hopes, desires, experiences, and skills of each individual with a dopamine deficit. As such, the concept of hopamine-as a reflection of the unique personal characteristics of each person with Parkinson's disease-really supplements that of dopamine-as a reflection of each person's unique physical characteristics. Whereas a prescription of dopamine replacement medication necessitates the diagnosed individual to lay his or her fate in the hands of medical professionals, adding a personalized dose of hopamine to the therapeutic mix empowers persons to self-manage daily life with Parkinson's disease. In this viewpoint, we argue that hopamine is a prerequisite for personalized medicine and offer several practical recommendations for how medical professionals can introduce the concept of hopamine in daily clinical practice.

Among-individual variation in the swimming behaviour of the amphipod Gammarus pulex under dark and light conditions.

In recent years, considerable computational advancements have been made allowing automated analysis of behavioural endpoints using video cameras. However, the results of such analyses are often confounded by a large variation among individuals, making it problematic to derive endpoints that allow distinguishing treatment effects in behavioural studies. In this study, we quantitatively analysed the effects of light conditions on the swimming behaviour of the freshwater amphipod Gammarus pulex by high-throughput tracking, and attempted to unravel among individual variation using size and sex. For this, we developed the R-package Kinematics, allowing for the rapid and reproducible analysis of the swimming behaviour (speed, acceleration, thigmotaxis, curvature and startle response) of G. pulex, as well as any other organism. Our results show a considerable amount of variation among individuals (standard deviation ranging between 5 and 115 % of the average swimming behaviour). The factors size and sex and the interaction between the two only explained a minor part of this found variation. Additionally, our study is the first to quantify the startle response in G. pulex after the light is switched on, and study the variability of this response between individuals. To analyse this startle response, we established two metrics: 1) startle response magnitude (the drop in swimming velocity directly after the light switches on), and 2) startle response duration (the time it takes to recover from the drop in swimming velocity to average swimming speed). Almost 80 % of the individuals showed a clear startle response and, therefore, these metrics demonstrate a great potential for usage in behavioural studies. The findings of this study are important for the development of appropriate experimental set-ups for behavioural experiments with G. pulex.

Effects of the antidepressant fluoxetine on the swimming behaviour of the amphipod Gammarus pulex: Comparison of short-term and long-term toxicity in the laboratory and the semi-field.

Fluoxetine is one of the worlds most prescribed antidepressant, and frequently detected in surface waters. Once present in the aquatic environment, fluoxetine has been shown to disrupt the swimming behaviour of fish and invertebrates. However, swimming behaviour is also known to be highly variable according to experimental conditions, potentially concealing relevant effects. Therefore, the aims of this study were two-fold: i) investigate the swimming and feeding behaviour of Gammarus pulex after exposure to the antidepressant fluoxetine (0.2, 2, 20, and 200 µg/L), and ii) assess to what degree the experimental test duration (short-term and long-term) and test location (laboratory and semi-field conditions) affect gammarid's swimming behaviour. We used automated video tracking and analysis to asses a range of swimming behaviours of G. pulex, including swimming speed, startle responses after light transition, acceleration, curvature and thigmotaxis. We found larger effects on the swimming behaviour of G. pulex due to experimental conditions than due to tested antidepressant concentrations. Gammarids swam faster, more straight and showed a stronger startle response during light transition when kept under semi-field conditions compared to the laboratory. Effects found for different test durations were opposite in the laboratory and semi-field. In the laboratory gammarids swam slower and spent more time at the inner zone of the arena after 2 days compared to 21 days while for the semi-field the reverse was observed. Fluoxetine had only minor impacts on the swimming behaviour of G. pulex, but experimental conditions influenced behavioural outcomes in response to fluoxetine exposure. Overall, our results highlight the importance of standardizing and optimizing experimental protocols that assess behaviour to achieve reproducible results in ecotoxicology.

Pharmacodynamics of Temocillin in Neutropenic Murine Infection Models.

Temocillin is used for the treatment of various infections caused by Enterobacterales. The pharmacokinetic (PK)/pharmacodynamic (PD) index that is best correlated with the activity of beta-lactams is the percentage of time that the unbound concentration exceeds the MIC (%fT>MIC). However, the %fT>MIC needed for a bacteriostatic or killing effect of temocillin is unknown in thigh and lung infection models. In the present study, we studied the temocillin PK in plasma and epithelial lining fluid (ELF) of infected neutropenic mice and determined the plasma exposure-response relationships for Escherichia coli and Klebsiella pneumoniae. Neutropenic murine thigh and lung infection models were used. The bacterial loads in the thighs or lungs were determined. A sigmoid maximum-effect model was used to fit the plasma exposure-response relationship. A one-compartment model with first-order absorption best described temocillin PK (clearance [CL], 1.03 L/h/kg; volume of distribution [V], 0.457 L/kg). Protein binding was 78.2% ± 1.3% across different plasma concentrations. A static effect was achieved for all strains in both the thigh and lung infection models. However, the median %fT>MIC needed for a static effect was much lower in the lung infection model (27.8% for E. coli and 38.2% for K. pneumoniae) than in the thigh infection model (65.2% for E. coli and 64.9% for K. pneumoniae). A 1-log kill was reached for all strains in the lung infection model (median %fT>MIC values of 42.1% for E. coli and 44.1% for K. pneumoniae) and 7 out of 8 strains in the thigh infection model (median %fT>MIC values of 85.4% for E. coli and 74.5% for K. pneumoniae). These data support the use of temocillin in patients with pneumonia.

Pharmacokinetic and pharmacodynamic properties of polymyxin B in Escherichia coli and Klebsiella pneumoniae murine infection models.

BACKGROUND: Although polymyxin B has been in use since the late 1950s, there have been limited studies done to unravel its pharmacokinetics (PK) and pharmacodynamics (PD) index. METHODS: We determined, in neutropenic infected mice, the PK, plasma protein binding and PK/PD index best correlating with efficacy for Escherichia coli and Klebsiella pneumoniae strains. RESULTS: The pharmacokinetic profile showed non-linear PK; dose was significantly correlated with absorption rate and clearance. The inhibitory sigmoid dose-effect model for the fCmax/MIC index of E. coli fitted best, but was only modestly higher than the R2 of %fT>MIC and fAUC/MIC (R2 0.91-0.93). For K. pneumoniae the fAUC/MIC index had the best fit, which was slightly higher than the R2 of %fT>MIC and fCmax/MIC (R2 0.85-0.91). Static targets of polymyxin B fAUC/MIC were 27.5-102.6 (median 63.5) and 5.9-60.5 (median 11.6) in E. coli and in K. pneumoniae isolates, respectively. A 1 log kill effect was only reached in two E. coli isolates and one K. pneumoniae. The PTA with the standard dosing was low for isolates with MIC >0.25 mg/L. CONCLUSIONS: This study confirms that fAUC/MIC can describe the exposure-response relationship for polymyxin B. The 1 log kill effect was achieved in the minority of the isolates whereas polymyxin B PK/PD targets cannot be attained for the majority of clinical isolates with the standard dosing regimen, indicating that polymyxin B may be not effective against serious infections as monotherapy.

Cefepime pharmacodynamic targets against Enterobacterales employing neutropenic murine lung infection and in vitro pharmacokinetic models.

BACKGROUND: Very limited studies, so far, have been conducted to identify the pharmacodynamic targets of cefepime, a well-established fourth-generation cephalosporin. As a result, conventional targets representing the cephalosporin class are used for cefepime target attainment analysis. OBJECTIVES: We employed both a neutropenic murine lung infection model and an in vitro pharmacokinetic model (IVPM) to determine cefepime's pharmacodynamic target [percentage of the dosing interval during which unbound drug concentrations remain higher than the MIC (%fT>MIC)] for bacteriostatic and 1 log10 kill effects. METHODS: Ten strains with cefepime MICs ranging from 0.03 to 16 mg/L were studied in the lung infection. In the IVPM, five cefepime-resistant strains with cefepime/tazobactam (fixed 8 mg/L) MICs ranging from 0.25 to 8 mg/L were included. Through 24 h dose fractionation, both in lung infection and IVPM (in the latter case, tazobactam 8 mg/L continuous infusion was used to protect cefepime), varying cefepime exposures and corresponding pharmacodynamic effect scenarios were generated to identify the pharmacodynamic targets. RESULTS: Using a non-linear sigmoidal maximum-effect (Emax) model, the cefepime's plasma fT>MIC for 1 log10 kill in lung infection ranged from 17% to 53.7% and a combined exposure-response plot yielded 30%. In the case of IVPM, T>MIC ranged from 6.9% to 75.4% with a mean value of 34.2% for 1 log10 kill. CONCLUSIONS: Both in vivo and in vitro studies showed that cefepime's pharmacodynamic requirements are lower than generally reported for cephalosporins (50%-70% fT>MIC). The lower requirement for cefepime could be linked with factors such as cefepime's better permeation properties and multiple PBP affinity-driven enhanced bactericidal action.

Pharmacodynamics of Flucloxacillin in a Neutropenic Murine Thigh Infection Model: A Piece of the Puzzle towards Evidence-Based Dosing.

For decades, flucloxacillin has been used to treat methicillin-susceptible Staphylococcus aureus (MSSA). Little is still known about its pharmacodynamics (PD). The present study aimed to determine the pharmacokinetic (PK)/PD index and the PD-index value minimally required for efficacy. MICs of 305 MSSA isolates were measured to determine the wild-type distribution. The PD of 8 S. aureus, 1 S. pyogenes, and 1 S. agalactiae isolates were evaluated in a neutropenic murine thigh infection model. Two S. aureus isolates were used in a dose-fractionation study and a dose−response analysis was performed additionally in the in vivo model. Data were analyzed with a population PK and sigmoid maximum effect model. The end of the wild-type distribution was 1 mg/L. The percentage of time the unbound concentration was above MIC (%fT > MIC) was best correlated with efficacy. For S. aureus, median %fT > 0.25 × MIC required for 1-log reduction was 15%. The value for S. pyogenes was 10%fT > MIC and for S. agalactiae 22%fT > 0.25xMIC for a 1-log reduction. The effect of flucloxacillin reached a 2-log reduction of S. aureus at 20%fT > 0.25xMIC and also for S. pyogenes and S. agalactiae, a reduction was reached. These data may serve to optimize dosing regimens currently used in humans.

(Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future.

Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects of chemicals on aquatic species and ecosystems. This is primarily because of the increasing number of (unknown) chemical stressors and mixture effects present in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal, population, or community level. We performed a literature search to obtain a state-of-the-art overview of ecotoxicological tests available for assessing impacts of chemicals to aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level, and 78 tests at the population- community- and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests at the community- and ecosystem-level were almost missing for organisms other than microorganisms and algae. In addition, we provide an overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemical stressors to aquatic ecosystems.

Differential binding of human and murine IgGs to catalytic and cell wall binding domains of Staphylococcus aureus peptidoglycan hydrolases.

Staphylococcus aureus is an opportunistic pathogen causing high morbidity and mortality. Since multi-drug resistant S. aureus lineages are nowadays omnipresent, alternative tools for preventive or therapeutic interventions, like immunotherapy, are urgently needed. However, there are currently no vaccines against S. aureus. Surface-exposed and secreted proteins are regarded as potential targets for immunization against S. aureus infections. Yet, many potential staphylococcal antigens of this category do not elicit protective immune responses. To obtain a better understanding of this problem, we compared the binding of serum IgGs from healthy human volunteers, highly S. aureus-colonized patients with the genetic blistering disease epidermolysis bullosa (EB), or immunized mice to the purified S. aureus peptidoglycan hydrolases Sle1, Aly and LytM and their different domains. The results show that the most abundant serum IgGs from humans and immunized mice target the cell wall-binding domain of Sle1, and the catalytic domains of Aly and LytM. Interestingly, in a murine infection model, these particular IgGs were not protective against S. aureus bacteremia. In contrast, relatively less abundant IgGs against the catalytic domain of Sle1 and the N-terminal domains of Aly and LytM were almost exclusively detected in sera from EB patients and healthy volunteers. These latter IgGs may contribute to the protection against staphylococcal infections, as previous studies suggest that serum IgGs protect EB patients against severe S. aureus infection. Together, these observations focus attention on the use of particular protein domains for vaccination to direct potentially protective immune responses towards the most promising epitopes within staphylococcal antigens.

The Role of Behavioral Ecotoxicology in Environmental Protection.

For decades, we have known that chemicals affect human and wildlife behavior. Moreover, due to recent technological and computational advances, scientists are now increasingly aware that a wide variety of contaminants and other environmental stressors adversely affect organismal behavior and subsequent ecological outcomes in terrestrial and aquatic ecosystems. There is also a groundswell of concern that regulatory ecotoxicology does not adequately consider behavior, primarily due to a lack of standardized toxicity methods. This has, in turn, led to the exclusion of many behavioral ecotoxicology studies from chemical risk assessments. To improve understanding of the challenges and opportunities for behavioral ecotoxicology within regulatory toxicology/risk assessment, a unique workshop with international representatives from the fields of behavioral ecology, ecotoxicology, regulatory (eco)toxicology, neurotoxicology, test standardization, and risk assessment resulted in the formation of consensus perspectives and recommendations, which promise to serve as a roadmap to advance interfaces among the basic and translational sciences, and regulatory practices.

Superior Efficacy of a Bedaquiline, Delamanid, and Linezolid Combination Regimen in a Mouse Tuberculosis Model.

BACKGROUND: The treatment success rate of drug-resistant (DR) tuberculosis is alarmingly low. Therefore, more effective and less complex regimens are urgently required. METHODS: We compared the efficacy of an all oral DR tuberculosis drug regimen consisting of bedaquiline (25 mg/kg), delamanid (2.5 mg/kg), and linezolid (100 mg/kg) (BDL) on the mycobacterial load in the lungs and spleen of tuberculosis-infected mice during a treatment period of 24 weeks. This treatment was compared with the standard regimen of isoniazid, rifampicin, pyrazinamide, and ethambutol (HRZE). Relapse was assessed 12 weeks after treatment. Two logistic regression models were developed to compare the efficacy of both regimens. RESULTS: Culture negativity in the lungs was achieved at 8 and 20 weeks of treatment with BDL and HRZE, respectively. After 14 weeks of treatment only 1 mouse had relapse in the BDL group, while in the HRZE group relapse was still observed at 24 weeks of treatment. Predictions from the final mathematical models showed that a 95% cure rate was reached after 20.5 and 28.5 weeks of treatment with BDL and HRZE, respectively. CONCLUSION: The BDL regimen was observed to be more effective than HRZE and could be a valuable option for the treatment of DR tuberculosis.

Cross-species extrapolation of chemical sensitivity.

Ecosystems are usually populated by many species. Each of these species carries the potential to show a different sensitivity towards all of the numerous chemical compounds that can be present in their environment. Since experimentally testing all possible species-chemical combinations is impossible, the ecological risk assessment of chemicals largely depends on cross-species extrapolation approaches. This review overviews currently existing cross-species extrapolation methodologies, and discusses i) how species sensitivity could be described, ii) which predictors might be useful for explaining differences in species sensitivity, and iii) which statistical considerations are important. We argue that risk assessment can benefit most from modelling approaches when sensitivity is described based on ecologically relevant and robust effects. Additionally, specific attention should be paid to heterogeneity of the training data (e.g. exposure duration, pH, temperature), since this strongly influences the reliability of the resulting models. Regarding which predictors are useful for explaining differences in species sensitivity, we review interspecies-correlation, relatedness-based, traits-based, and genomic-based extrapolation methods, describing the amount of mechanistic information the predictors contain, the amount of input data the models require, and the extent to which the different methods provide protection for ecological entities. We develop a conceptual framework, incorporating the strengths of each of the methods described. Finally, the discussion of statistical considerations reveals that regardless of the method used, statistically significant models can be found, although the usefulness, applicability, and understanding of these models varies considerably. We therefore recommend publication of scientific code along with scientific studies to simultaneously clarify modelling choices and enable elaboration on existing work. In general, this review specifies the data requirements of different cross-species extrapolation methods, aiming to make regulators and publishers more aware that access to raw- and meta-data needs to be improved to make future cross-species extrapolation efforts successful, enabling their integration into the regulatory environment.

Potential impact of chemical stress on freshwater invertebrates: A sensitivity assessment on continental and national scale based on distribution patterns, biological traits, and relatedness.

Current chemical risk assessment approaches rely on a standard suite of test species to assess toxicity to environmental species. Assessment factors are used to extrapolate from single species to communities and ecosystem effects. This approach is pragmatic, but lacks resolution in biological and environmental parameters. Novel modelling approaches can help improve the biological resolution of assessments by using mechanistic information to identify priority species and priority regions that are potentially most impacted by chemical stressors. In this study we developed predictive sensitivity models by combining species-specific information on acute chemical sensitivity (LC50 and EC50), traits, and taxonomic relatedness. These models were applied at two spatial scales to reveal spatial differences in the sensitivity of species assemblages towards two chemical modes of action (MOA): narcosis and acetylcholinesterase (AChE) inhibition. We found that on a relative scale, 46% and 33% of European species were ranked as more sensitive towards narcosis and AChE inhibition, respectively. These more sensitive species were distributed with higher occurrences in the south and north-eastern regions, reflecting known continental patterns of endemic macroinvertebrate biodiversity. We found contradicting sensitivity patterns depending on the MOA for UK scenarios, with more species displaying relative sensitivity to narcotic MOA in north and north-western regions, and more species with relative sensitivity to AChE inhibition MOA in south and south-western regions. Overall, we identified hotspots of species sensitive to chemical stressors at two spatial scales, and discuss data gaps and crucial technological advances required for the successful application of the proposed methodology to invertebrate scenarios, which remain underrepresented in global conservation priorities.

Moderators of the effect of psychosocial interventions on fatigue in women with breast cancer and men with prostate cancer: Individual patient data meta-analyses.

OBJECTIVE: Psychosocial interventions can reduce cancer-related fatigue effectively. However, it is still unclear if intervention effects differ across subgroups of patients. These meta-analyses aimed at evaluating moderator effects of (a) sociodemographic characteristics, (b) clinical characteristics, (c) baseline levels of fatigue and other symptoms, and (d) intervention-related characteristics on the effect of psychosocial interventions on cancer-related fatigue in patients with non-metastatic breast and prostate cancer. METHODS: Data were retrieved from the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) consortium. Potential moderators were studied with meta-analyses of pooled individual patient data from 14 randomized controlled trials through linear mixed-effects models with interaction tests. The analyses were conducted separately in patients with breast (n = 1091) and prostate cancer (n = 1008). RESULTS: Statistically significant, small overall effects of psychosocial interventions on fatigue were found (breast cancer: ß = -0.19 [95% confidence interval (95%CI) = -0.30; -0.08]; prostate cancer: ß = -0.11 [95%CI = -0.21; -0.00]). In both patient groups, intervention effects did not differ significantly by sociodemographic or clinical characteristics, nor by baseline levels of fatigue or pain. For intervention-related moderators (only tested among women with breast cancer), statistically significant larger effects were found for cognitive behavioral therapy as intervention strategy (ß = -0.27 [95%CI = -0.40; -0.15]), fatigue-specific interventions (ß = -0.48 [95%CI = -0.79; -0.18]), and interventions that only targeted patients with clinically relevant fatigue (ß = -0.85 [95%CI = -1.40; -0.30]). CONCLUSIONS: Our findings did not provide evidence that any selected demographic or clinical characteristic, or baseline levels of fatigue or pain, moderated effects of psychosocial interventions on fatigue. A specific focus on decreasing fatigue seems beneficial for patients with breast cancer with clinically relevant fatigue.

Significance testing and genomic inflation factor using high-density genotypes or whole-genome sequence data.

Significance testing for genome-wide association study (GWAS) with increasing SNP density up to whole-genome sequence data (WGS) is not straightforward, because of strong LD between SNP and population stratification. Therefore, the objective of this study was to investigate genomic control and different significance testing procedures using data from a commercial pig breeding scheme. A GWAS was performed in GCTA with data of 4,964 Large White pigs using medium density, high density or imputed whole-genome sequence data, fitting a genomic relationship matrix based on a leave-one-chromosome-out approach to account for population structure. Subsequently, genomic inflation factors were assessed on whole-genome level and the chromosome level. To establish a significance threshold, permutation testing, Bonferroni corrections using either the total number of SNPs or the number of independent chromosome fragments, and false discovery rates (FDR) using either the Benjamini-Hochberg procedure or the Benjamini and Yekutieli procedure were evaluated. We found that genomic inflation factors did not differ between different density genotypes but do differ between chromosomes. Also, the leave-one-chromosome-out approach for GWAS or using the pedigree relationships did not account appropriately for population stratification and gave strong genomic inflation. Regarding different procedures for significance testing, when the aim is to find QTL regions that are associated with a trait of interest, we recommend applying the FDR following the Benjamini and Yekutieli approach to establish a significance threshold that is adjusted for multiple testing. When the aim is to pinpoint a specific mutation, the more conservative Bonferroni correction based on the total number of SNPs is more appropriate, till an appropriate method is established to adjust for the number of independent tests.

Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits.

In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

Imputation to whole-genome sequence using multiple pig populations and its use in genome-wide association studies.

BACKGROUND: Use of whole-genome sequence data (WGS) is expected to improve identification of quantitative trait loci (QTL). However, this requires imputation to WGS, often with a limited number of sequenced animals for the target population. The objective of this study was to investigate imputation to WGS in two pig lines using a multi-line reference population and, subsequently, to investigate the effect of using these imputed WGS (iWGS) for GWAS. METHODS: Phenotypes and genotypes were available on 12,184 Large White pigs (LW-line) and 4943 Dutch Landrace pigs (DL-line). Imputed 660 K and 80 K genotypes for the LW-line and DL-line, respectively, were imputed to iWGS using Beagle v.4.1. Since only 32 LW-line and 12 DL-line boars were sequenced, 142 animals from eight commercial lines were added. GWAS were performed for each line using the 80 K and 660 K SNPs, the genotype scores of iWGS SNPs that had an imputation accuracy (Beagle R2) higher than 0.6, and the dosage scores of all iWGS SNPs. RESULTS: For the DL-line (LW-line), imputation of 80 K genotypes to iWGS resulted in an average Beagle R2 of 0.39 (0.49). After quality control, 2.5 × 106 (3.5 × 106) SNPs had a Beagle R2 higher than 0.6, resulting in an average Beagle R2 of 0.83 (0.93). Compared to the 80 K and 660 K genotypes, using iWGS led to the identification of 48.9 and 64.4% more QTL regions, for the DL-line and LW-line, respectively, and the most significant SNPs in the QTL regions explained a higher proportion of phenotypic variance. Using dosage instead of genotype scores improved the identification of QTL, because the model accounted for uncertainty of imputation, and all SNPs were used in the analysis. CONCLUSIONS: Imputation to WGS using the multi-line reference population resulted in relatively poor imputation, especially when imputing from 80 K (DL-line). In spite of the poor imputation accuracies, using iWGS instead of a lower density SNP chip increased the number of detected QTL and the estimated proportion of phenotypic variance explained by these QTL, especially when dosage scores were used instead of genotype scores. Thus, iWGS, even with poor imputation accuracy, can be used to identify possible interesting regions for fine mapping.