Czechia

Pesticides are indispensable in agriculture and have become ubiquitous in aquatic environments. Pesticides in natural environments can cause many negative impacts on aquatic species, ranging from mortality to sub-lethal physiological and behavioural changes. The complex sub-lethal impacts of pesticides are routinely tested on model species, with zebrafish (Danio rerio) being regularly used as a behavioural model. Although behavioural ecotoxicology research using zebrafish is increasing rapidly, we lack quantitative evidence to support which pesticides have been tested and how study designs are carried out. This shortcoming not only limits the deliberate planning for future primary studies to fill the knowledge gaps but also hinders evidence synthesis. To provide quantitative evidence of what pesticides are currently studied and what study designs are used, we combined a systematic evidence map approach and bibliometric analysis. This novel method has been coined research weaving and allows us to elicit gaps and clusters in our evidence base, whilst showing connections between authors and institutions. The methodology can be summarised in five primary steps: literature searching, screening, extraction, data analysis and bibliometric analysis. We identified four areas where research on the sub-lethal effects of pesticide exposure on zebrafish is lacking. First, some widely used pesticides, such as neonicotinoids, are understudied. Second, most studies do not report important elements of the study design, namely the sex and the life-stage of the zebrafish. Third, some behaviours, such as impacts of pesticide exposure on zebrafish cognition, are underexplored. And last, we revealed through the bibliometric analysis that most of the research is conducted in developed countries and there is limited cross country co-authorships. Upon identifying these gaps, we offer solutions for each limitation, emphasizing the importance of diverse global research output and cross-country co-authorships. Our systematic evidence map and bibliometric analysis provide valuable insights for helping to guide future research, which can be used to help support evidence-based policy decisions.

SEB Conference 2024

A systematic evidence map and bibliometric analysis of the behavioural impacts of pesticide exposure on zebrafish.

meta-science

chemical pollution

pesticide

fish

animal behaviour

animal behavior

bibliometrics

systematic mapping

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The AOAC Annual Meeting & Exposition provides unparalleled professional development, networking, and collaboration in methods-based science.

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Metabolism lies at the core of life-history theory. To thrive, organisms must adapt and exploit the resources offered by the environment. Mitochondria are key for metabolic adaptation, as they are central hubs for both energy transduction and intermediary metabolism in eukaryotes — a major determinant of all aspects of fitness including development, growth, and reproductive success. Despite its key role, oxidative phosphorylation is uniquely vulnerable to disruption, as it depends on components encoded by two different genomes, mitochondrial (mt) and nuclear (n), which must interact harmoniously to preserve bioenergetic efficiency. Whilst coevolution is vital, mitonuclear interactions are perpetually stressed by their very different evolutionary dynamics. Here I will give some evidence on how these mitonuclear interactions can modulate resource allocation, affecting growth and development in Drosophila melanogaster natural populations, and how these effects are modulated by a changing environment (via nutrition and temperature). Results indicate that intergenomic epistasis can have a strong physiological impact at different level of biological hierarchies: from cells to individuals, and that ecological stressors stemming from an unpredictable world could exacerbate these incompatibilities, amplifying fitness breakdown in admixed cybrid populations. 
To finish, I will present some preliminary data from the curios case of the stalked-eye fly (Teleopsis dalmanni), where a selfish genetic element has caused a large shift in resource allocation affecting mitochondrial physiology and life-history traits. 


Genomic constraints of resource allocation

Flying insects can achieve remarked and robust flapping aerodynamic performance and flight stability in various environments partially owing to the passive mechanisms of their wings and bodies, but a careful analysis associated with flexible wing hinge for forward flight is missing. Here we develop a fluid-structure interaction (FSI) model that couples one-torsional-spring-based elastic wing-hinge dynamics and flapping aerodynamics to study the aerodynamics and flight stability of hawkmoth Manduca Sexta with flexible wing hinge in various flight velocities. The results show that the leading-edge vortex (LEV), the body vortex (BV) and their interactions are responsible for augmenting the vertical force production interactively in all flight velocities, enabling a 6.5% increase in fast flight; the elastic storage in concern with flexible wing hinge exhibits a J-curve, achieving high power efficiency in intermediate forward flight. It is verified that the realistic wing-hinge stiffness can lead to an optimal aerodynamic performance in terms of vertical force production and power cost; external disturbance-rejection based on flexible wing hinge is of high robustness in multiple directions independent of forward flight velocities. This study thus points to the importance and significance of flexible wing hinge in biomimetic designs for flapping micro aerial vehicles.

Hawkmoth forward flight with flexible wing hinge: aerodynamics and flight stability

Tracking the pose of a swarm of insects in free flight is an important challenge necessary both for behavioural studies at scale, and also for testing interventions for the management of species harmful to human and animal health, including mosquitoes. Multi-camera techniques such as convex hull reconstruction have reconstructed pose of the limbs, head, body, wings and other parts of the animal in a lab setting successfully, but tracking in the field remains an important and difficult open question.
Here we will demonstrate a promising new approach for background subtraction and state estimation of a mosquito in free flight in a variety of conditions. We use both camera recordings and synthetic ray-traced data to train a convolutional neural network to recognise a variety of backgrounds and estimate the state of a mosquito in free flight, showing robust performance with a variety of natural and artificial backgrounds.

Using neural networks to track mosquito pose

Among marine renewable energy (MRE) producers, offshore wind farms are currently booming and are seen as a key energy source for energy transition. Wind farm can induce noise, vibrations, interruptions to ecological continuity and generate electromagnetic fields at the level of submarine electric cables. They can affect behavior of electro- and magneto- sensitive species which use natural electromagnetic fiels to move and feed. The increasing number of offshore windfarms is likely to amplify these effects, while existing information on their impact on ichtyological communities remains patchy. Studies have been limited to a few species of commercial interest and exposure to electromagnetic fields is relatively short-lived. Submarine electric cables can transmit alternating current (AC) or direct current (DC) , depending on the function, power, length of the wind turbine transmission line. Currently, wind farms located less than 50km from the coast use AC current whearas furutre more powerful wind farms will be located more than 50 km away and will use DC current. In this context, our study aims to identify and evaluate the effects of magnetic fields in AC and DC current on the survival, development, growth and behavior of elasmobranchs, an elero-sensitive species at conservation risk. The results will enable us to understand how elasmobranchs react to electromagnetic fields, depending on their intensity and the type of current, and thus the type of offshore wind farm (fixed or floating). They will provide managers and decision-makers information they need to meet the challenges of developing MREs without harming marine biodiversity.

Impact of electromagnetic fields from offshore windfarm submarine electric cables on the development, biology and behavior ofScyliorhinus canicula

This study reports a waterflow sensor for marine biologging and examples of its application to sea turtles. The relative waterflow velocity is one of the most important indicators for evaluating the swimming movements of marine animals. Propeller-type sensors have been used as conventional sensors for marine biologging. However, the sensors' moving parts are easily affected by suspended marine debris and attached organisms. Therefore, long-term and high-temporal resolution measurements of the velocity have been challenging.
Therefore, we have developed a pitot-type waterflow sensor that enables long-term and high-temporal resolution measurement. A rubber film is glued on the inlets, and silicone oil fills inside the flow channel. The film prevents debris from entering, and the oil prevents sensor destruction due to water pressure. In addition, the sensor detects waterflow by measuring the flow-generated pressure without moving parts. These features provide the sensor with high resistance to the harsh marine environment and enable high-temporal resolution measurement.
Finally, we experimentally proved that the developed sensor can be used for biologging. This sensor was connected to a logger and attached to a wild loggerhead turtle. The turtle was equipped with parachutes that generated drag force. The relative waterflow velocity of the turtle was measured for two hours, and the parachute was detached one hour after the start. The sensor measured the waterflow with a high-temporal resolution of 6.25 Hz. Furthermore, we were able to measure the change in the turtle's velocity due to the attachment and detachment of the parachute.


High time-resolution measurement of a sea turtle's relative waterflow velocity using a pitot-type waterflow sensor

Elevations in atmospheric carbon dioxide (CO2) have been measured by experts for decades. These atmospheric elevations cause changes in aquatic environments as increased CO2 reduces pH. Acidification has been shown to cause changes to the behaviour of many fish species including reducing homing behaviour, foraging behaviour, and predator avoidance. Our study aimed to identify whether elevated levels of CO2 affects the behaviour of Japanese Medaka (Oryzias latipes). To test this, we exposed a total of 300 fish to varying levels of CO2 (2500 µatm, 5500 µatm, 8500 µatm) at varying times (0, 5, 10, 15, 20 d). Two behavioural tests were performed, the first, where we placed individual fish into circular arenas, measured cumulative distance moved, immobility duration, and percent of time spent in the outer zone. For the second test, we placed 6 fish at a time into a small tank where half of the tank was marked with a black line. We then measured the amount of time spent over the line and the number of crosses above the line for individual fish. Our results showed that there were no differences in any behaviour between CO2 treatments; however, there was evidence of acclimation around day 10 in the highest CO2 treatment. Our study suggests that CO2 does not change behaviours of Japanese Medaka, and thus Japanese Medaka may be unaffected by rising atmospheric CO2.

Elevated carbon dioxide does not change behaviour of Japanese Medaka 

Rice (Oryza sativa L.) is one of the important cereal grains and a staple food for more than 50% of the population in many countries. Increases in global temperatures will make crop productivity challenges worse. In this study, a total of 204 accessions from the Bengal and Assam Aus Panel (BAAP) were screened for resistance to heat stress. A total of eight replicate plants per accession were grown in the greenhouse until maturity; thereafter, five replicate plants were randomly selected, their panicles at anthesis stage marked and transferred to a large growth room at 38°C for 24 hours to assess high-temperature treatments. Three replicates plants were not heat treated. Fertility was assessed as the proportion of flowers filled. Genome wide association mapping was conducted using ~ 2 million SNPs. Two promising QTLs and 7 genes were detected for resistance under the ratio; which is the proportion of (control/heat treatment) on chromosome 2 and 6. The combine GWA mapping and RNA-seq allowed us to identify excellent candidate genes for heat tolerance in the aus subpopulation of rice. These genes were found in our significant QTLs on chromosome 2 and 6; Hsp20, SEC14, AP2/ERF, OsDjC56, ZOS6-06, WRKY28 and miRNA156. Altered fluorescence of detached leaves was also assessed under a 1 hr 47°C treatment. The two heat tolerance phenotypes were not correlated (P=0.193). This implies that leaf-level tolerance to high temperature is not genetically related to tolerance at the flowering stage.

Genome-Wide Association Mapping and transcriptome analysis for heat tolerance in Bengal and Assam Aus Panel in the flowering stage

Plant stress phenotyping based on image-analysis techniques can facilitate targeted interventions and optimize management practices. However, considering abiotic stresses – especially under the influence of climate changes – various technical challenges still need to be overcome, and there is a need to identify functional traits that can be used as markers to monitor plants health status accurately and rapidly. This study aimed to develop a machine learning model able to detect salt stress status in Phaseolus vulgaris, by combining image-based approaches and minimal morpho-physiological/biochemical analyses. Therefore, a flexible pipeline was created, starting with the data acquisition and analysis (feature extraction) followed by the feature selection phase, which involved statistical approaches such as principal component analysis and correlation analysis. Finally, two predictive models based on decision trees were developed to detect stress presence (2-class model) and intensity (3-class model). Specific biochemical parameters and image-analysis-derived traits, like malondialdehyde content, chroma difference and chroma ratio indexes, resulted as key features in categorizing both non-stressed and stressed plants (model’s precision: 0.91) as well as stress intensity (model’s precision: 0.84). These results highlighted the potential of machine learning techniques and automated image-based analysis in plant science. In the future, the models’ reliability and accuracy will be improved by adjusting the pipeline to different plant growth stages and specific leaf characteristics, and testing the model across different plant species and abiotic stresses (e.g. drought, temperature).

Enhancing plant stress phenotyping with machine learning: a novel approach for salt stress detection in Phaseolus vulgaris

Maize is one of the most produced cereals worldwide. Many studies have been conducted to decipher the genetic basis of several traits of agronomic relevance. In crops such as maize, where the commercial varieties are F1 hybrids, the optimal populations to screen would theoretically consist of hybrids. However, researchers often use populations composed of inbred lines, which are arguably insufficient for understanding the mechanisms that play a role in hybrid performances. In this study, we have developed a recombinant intercross (RIX) population by crossing pairs of recombinant inbred lines (RILs) belonging to a multi-parental Advanced Generation Inter-Cross (MAGIC) population to perform QTL mapping using a hybrid genetic background. We phenotyped 214 RIX genotypes along with the MAGIC founder inbreds for 10 agronomic traits, including Fusarium Ear Rot (FER) resistance indexes in two consecutive years. The genotypes of RIXs were reconstructed in silico starting from the corresponding RILs’ reconstructed genotype probabilities. For this task, we used a panel of about 74K SNP markers obtained using Single Primer Enrichment Technology (SPET).
Results of the QTL mapping in the hybrid population revealed several genomic regions associated with agronomic traits and FER resistance. Suggestive candidate genes were identified in the mapped intervals. The understanding of their role is currently ongoing. Our findings represent a proof-of-concept that RIX populations are potentially outstanding materials to understand the genetic control of complex quantitative traits in hybrid genetic backgrounds. This kind of resource and the information gathered would provide a future platform to support and accelerate maize improvement.




Mapping Fusarium Ear Rot resistance using recombinant hybrids developed from the MAGIC maize population

Enhancing fertilizer use efficiency is a key aspect in attaining sustainable agriculture objectives, aiming to curtail costs, mitigate greenhouse gas emissions, and alleviate pollution stemming from nutrient runoff. While extensive research has delved into fertilizer utilization in cereal crops, understanding the broader monocot plant community could unveil novel insights. In this study, we investigated nitrogen uptake efficiency across three species—Anthurium andreanum, Epipremnum aureum, and Philodendron scandens—belonging to the Araceae family. Like maize, these species are characterized by root development from both subterranean and aerial tissues. Employing 15N-labeled sources of nitrate, ammonium, and glycine, we assessed nitrogen uptake capacity in both aerial and soil-originating roots, juxtaposed with similar investigations conducted on maize brace roots from field-grown plants. Intriguingly, our findings revealed a positive correlation between nitrogen uptake capacity and root thickness across all species. Notably, nitrate exhibited the strongest correlation with root thickness, succeeded by ammonium, while glycine uptake displayed variable patterns among species. Further examination of species-specific traits encompassing growth form, anatomy, and physiological attributes elucidates finer nuances in nitrogen uptake dynamics. Unravelling these parallels and distinctions among diverse species not only informs translational advancements in crop breeding but also underscores opportunities for enhancing urban greenspaces.

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Genomic constraints of resource allocation

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Pesticides in California’s Adult-Use Cannabis Market: Prevalence, Analytical Challenges and Concerns, and Regulatory/Market Solutions

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