The Promises and the Challenges of Integrating Multi-Omics and Systems Biology in Comparative Stress Biology

Evaluating the performance of multi-omics integration: a thyroid toxicity case study

Multi-omics data integration has been repeatedly discussed as the way forward to more comprehensively cover the molecular responses of cells or organisms to chemical exposure in systems toxicology and regulatory risk assessment. In Canzler et al. (Arch Toxicol 94(2):371-388. https://doi.org/10.1007/s00204-020-02656-y ), we reviewed the state of the art in applying multi-omics approaches in toxicological research and chemical risk assessment. We developed best practices for the experimental design of multi-omics studies, omics data acquisition, and subsequent omics data integration. We found that multi-omics data sets for toxicological research questions were generally rare, with no data sets comprising more than two omics layers adhering to these best practices. Due to these limitations, we could not fully assess the benefits of different data integration approaches or quantitatively evaluate the contribution of various omics layers for toxicological research questions. Here, we report on a multi-omics study on thyroid toxicity that we conducted in compliance with these best practices. We induced direct and indirect thyroid toxicity through Propylthiouracil (PTU) and Phenytoin, respectively, in a 28-day plus 14-day recovery oral rat toxicity study. We collected clinical and histopathological data and six omics layers, including the long and short transcriptome, proteome, phosphoproteome, and metabolome from plasma, thyroid, and liver. We demonstrate that the multi-omics approach is superior to single-omics in detecting responses at the regulatory pathway level. We also show how combining omics data with clinical and histopathological parameters facilitates the interpretation of the data. Furthermore, we illustrate how multi-omics integration can hint at the involvement of non-coding RNAs in post-transcriptional regulation. Also, we show that multi-omics facilitates grouping, and we assess how much information individual and combinations of omics layers contribute to this approach.

Overtraining Syndrome as a Complex Systems Phenomenon

The phenomenon of reduced athletic performance following sustained, intense training (Overtraining Syndrome, and OTS) was first recognized more than 90 years ago. Although hundreds of scientific publications have focused on OTS, a definitive diagnosis, reliable biomarkers, and effective treatments remain unknown. The present review considers existing models of OTS, acknowledges the individualized and sport-specific nature of signs/symptoms, describes potential interacting predisposing factors, and proposes that OTS will be most effectively characterized and evaluated via the underlying complex biological systems. Complex systems in nature are not aptly characterized or successfully analyzed using the classic scientific method (i.e., simplifying complex problems into single variables in a search for cause-and-effect) because they result from myriad (often non-linear) concomitant interactions of multiple determinants. Thus, this review 1) proposes that OTS be viewed from the perspectives of complex systems and network physiology, 2) advocates for and recommends that techniques such as trans-omic analyses and machine learning be widely employed, and 3) proposes evidence-based areas for future OTS investigations, including concomitant multi-domain analyses incorporating brain neural networks, dysfunction of hypothalamic-pituitary-adrenal responses to training stress, the intestinal microbiota, immune factors, and low energy availability. Such an inclusive and modern approach will measurably help in prevention and management of OTS.

Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens

Soybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application ( https://soyfungigcn.venanciogroup.uenf.br/ ) and an R/Shiny package ( https://github.com/almeidasilvaf/SoyFungiGCN ) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.

Evolutionary physiology at 30+: Has the promise been fulfilled?: Advances in Evolutionary Physiology: Advances in Evolutionary Physiology

Three decades ago, interactions between evolutionary biology and physiology gave rise to evolutionary physiology. This caused comparative physiologists to improve their research methods by incorporating evolutionary thinking. Simultaneously, evolutionary biologists began focusing more on physiological mechanisms that may help to explain constraints on and trade-offs during microevolutionary processes, as well as macroevolutionary patterns in physiological diversity. Here we argue that evolutionary physiology has yet to reach its full potential, and propose new avenues that may lead to unexpected advances. Viewing physiological adaptations in wild animals as potential solutions to human diseases offers enormous possibilities for biomedicine. New evidence of epigenetic modifications as mechanisms of phenotypic plasticity that regulate physiological traits may also arise in coming years, which may also represent an overlooked enhancer of adaptation via natural selection to explain physiological evolution. Synergistic interactions at these intersections and other areas will lead to a novel understanding of organismal biology.

Trends in the Application of "Omics" to Ecotoxicology and Stress Ecology

Our ability to predict and assess how environmental changes such as pollution and climate change affect components of the Earth's biome is of paramount importance. This need positioned the fields of ecotoxicology and stress ecology at the center of environmental monitoring efforts. Advances in these interdisciplinary fields depend not only on conceptual leaps but also on technological advances and data integration. High-throughput "omics" technologies enabled the measurement of molecular changes at virtually all levels of an organism's biological organization and thus continue to influence how the impacts of stressors are understood. This bibliometric review describes literature trends (2000-2020) that indicate that more different stressors than species are studied each year but that only a few stressors have been studied in more than two phyla. At the same time, the molecular responses of a diverse set of non-model species have been investigated, but cross-species comparisons are still rare. While transcriptomics studies dominated until 2016, a shift towards proteomics and multiomics studies is apparent. There is now a wealth of data at functional omics levels from many phylogenetically diverse species. This review, therefore, addresses the question of how to integrate omics information across species.

Integrating omics to characterize eco-physiological adaptations: How moose diet and metabolism differ across biogeographic zones

With accelerated land conversion and global heating at northern latitudes, it becomes crucial to understand, how life histories of animals in extreme environments adapt to these changes. Animals may either adapt by adjusting foraging behavior or through physiological responses, including adjusting their energy metabolism or both. Until now, it has been difficult to study such adaptations in free-ranging animals due to methodological constraints that prevent extensive spatiotemporal coverage of ecological and physiological data.Through a novel approach of combining DNA-metabarcoding and nuclear magnetic resonance (NMR)-based metabolomics, we aim to elucidate the links between diets and metabolism in Scandinavian moose Alces alces over three biogeographic zones using a unique dataset of 265 marked individuals.Based on 17 diet items, we identified four different classes of diet types that match browse species availability in respective ecoregions in northern Sweden. Individuals in the boreal zone consumed predominantly pine and had the least diverse diets, while individuals with highest diet diversity occurred in the coastal areas. Males exhibited lower average diet diversity than females.We identified several molecular markers indicating metabolic constraints linked to diet constraints in terms of food availability during winter. While animals consuming pine had higher lipid, phospocholine, and glycerophosphocholine concentrations in their serum than other diet types, birch- and willow/aspen-rich diets exhibit elevated concentrations of several amino acids. The individuals with highest diet diversity had increased levels of ketone bodies, indicating extensive periods of starvation for these individuals.Our results show how the adaptive capacity of moose at the eco-physiological level varies over a large eco-geographic scale and how it responds to land use pressures. In light of extensive ongoing climate and land use changes, these findings pave the way for future scenario building for animal adaptive capacity.

Family-effects in the epigenomic response of red blood cells to a challenge test in the European sea bass (Dicentrarchus labrax, L.)

Abstract

Background

In fish, minimally invasive blood sampling is widely used to monitor physiological stress with blood plasma biomarkers. As fish blood cells are nucleated, they might be a source a potential new markers derived from ‘omics technologies. We modified the epiGBS (epiGenotyping By Sequencing) technique to explore changes in genome-wide cytosine methylation in the red blood cells (RBCs) of challenged European sea bass (Dicentrarchus labrax), a species widely studied in both natural and farmed environments.

Results

We retrieved 501,108,033 sequencing reads after trimming, with a mean mapping efficiency of 73.0% (unique best hits). Minor changes in RBC methylome appeared to manifest after the challenge test and a family-effect was detected. Only fifty-seven differentially methylated cytosines (DMCs) close to 51 distinct genes distributed on 17 of 24 linkage groups (LGs) were detected between RBCs of pre- and post-challenge individuals. Thirty-seven of these genes were previously reported as differentially expressed in the brain of zebrafish, most of them involved in stress coping differences. While further investigation remains necessary, few DMC-related genes associated to the Brain Derived Neurotrophic Factor, a protein that favors stress adaptation and fear memory, appear relevant to integrate a centrally produced stress response in RBCs.

Conclusion

Our modified epiGBS protocol was powerful to analyze patterns of cytosine methylation in RBCs of D. labrax and to evaluate the impact of a challenge using minimally invasive blood samples. This study is the first approximation to identify epigenetic biomarkers of exposure to stress in fish.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07420-9.