Co-expression network analysis identifies gonad- and embryo-associated protein modules in the sentinel species Gammarus fossarum

Proteogenomic reconstruction of organ-specific metabolic networks in an environmental sentinel species, the amphipod Gammarus fossarum

Metabolic pathways are affected by the impacts of environmental contaminants underlying a large variability of toxic effects across different species. However, the systematic reconstruction of metabolic pathways remains limited in environmental sentinel species due to the lack of available genomic data in many taxa of animal diversity. In this study we used a multi-omics approach to reconstruct the most comprehensive map of metabolic pathways for a crustacean model in biomonitoring, the amphipod Gammarus fossarum in order to improve the knowledge of the metabolism of this sentinel species. We revisited the assembly of RNA-seq data by de novo approaches to reduce RNA contaminants and transcript redundancy. We also acquired extensive mass spectrometry shotgun proteomic data on several organs from a reference population of G. fossarum males and females to identify organ-specific metabolic profiles. The G. fossarum metabolic pathway reconstruction (available through the metabolic database GamfoCyc) was performed by adapting the genomic tool CycADS and we identified 377 pathways representing 7630 annotated enzymes, 2610 enzymatic reactions and the expression of 858 enzymes was experimentally validated by proteomics. To our knowledge, our analysis provides for the first time a systematic metabolic pathway reconstruction and the proteome profiles of these pathways at the organ level in this sentinel species. As an example, we show an elevated abundance in enzymes involved in ATP biosynthesis and fatty acid beta-oxidation indicative of the high-energy requirement of the gills, or the key anabolic and detoxification role of the hepatopancreatic caeca, as exemplified by the specific expression of the retinoid biosynthetic pathways and glutathione synthesis. In conclusion, the multi-omics data integration performed in this study provides new resources to investigate metabolic processes in crustacean amphipods and their role in mediating the effects of environmental contaminant exposures in sentinel species. SYNOPSIS: This study provide the first evidence that it is possible to combine multiple omics data to exhaustively describe the metabolic network of a model species in ecotoxicology, Gammarus fossarum, for which a reference genome is not yet available.

ToF-SIMS imaging shows specific lipophilic vitamin alterations in chronic reprotoxicity caused by the emerging contaminant Pravastatin in Gammarus fossarum

Blood lipid-lowering agents, such as Pravastatin, are among the most frequently used pharmaceuticals released into the aquatic environment. Although their effects on humans are very well understood, their consequences on freshwater organisms are not well known, especially in chronic exposure conditions. Gammarus fossarum is commonly used as sentinel species in ecotoxicology because of its sensitivity to a wide range of environmental contaminants and the availability of standardized bioassays. Moreover, there is an increased interest in linking molecular changes in sentinel species, such as gammarids, to observed toxic effects. Here, we performed a reproductive toxicity assay on females exposed to different concentrations of pravastatin (30; 300; 3,000 and 30,000 ng L-1) during two successive reproductive cycles and we applied ToF-SIMS imaging to evaluate the effect of pravastatin on lipid homeostasis in gammarids. Reproductive bioassay showed that pravastatin could affect oocyte development in Gammarus fossarum inducing embryotoxicity in the second reproductive cycle. Mass spectrometry imaging highlighted the disruption in vitamin E production in the oocytes of exposed female gammarids at the second reproductive cycle, while limited alterations were observed in other lipid classes, regarding both production and tissue distribution. The results demonstrated the interest of applying spatially resolved lipidomics by mass spectrometry imaging to assess the molecular effects induced by long-term exposure to environmental pharmaceutical residues in sentinel species.

Editorial trend: adverse outcome pathway (AOP) and computational strategy - towards new perspectives in ecotoxicology

The adverse outcome pathway (AOP) has been conceptualized in 2010 as an analytical construct to describe a sequential chain of causal links between key events, from a molecular initiating event leading to an adverse outcome (AO), considering several levels of biological organization. An AOP aims to identify and organize available knowledge about toxic effects of chemicals and drugs, either in ecotoxicology or toxicology, and it can be helpful in both basic and applied research and serve as a decision-making tool in support of regulatory risk assessment. The AOP concept has evolved since its introduction, and recent research in toxicology, based on integrative systems biology and artificial intelligence, gave it a new dimension. This innovative in silico strategy can help to decipher mechanisms of action and AOP and offers new perspectives in AOP development. However, to date, this strategy has not yet been applied to ecotoxicology. In this context, the main objective of this short article is to discuss the relevance and feasibility of transferring this strategy to ecotoxicology. One of the challenges to be discussed is the level of organisation that is relevant to address for the AO (population/community). This strategy also offers many advantages that could be fruitful in ecotoxicology and overcome the lack of time, such as the rapid identification of data available at a time t, or the identification of "data gaps". Finally, this article proposes a step forward with suggested priority topics in ecotoxicology that could benefit from this strategy.

Development of a multi-omics extraction method for ecotoxicology: investigation of the reproductive cycle of Gammarus fossarum

Omics study exemplified by proteomics, lipidomics or metabolomics, provides the opportunity to get insight of the molecular modifications occurring in living organisms in response to contaminants or in different physiological conditions. However, individual omics discloses only a single layer of information leading to a partial image of the biological complexity. Multiplication of samples preparation and processing can generate analytical variations resulting from several extractions and instrumental runs. To get all the -omics information at the proteins, metabolites and lipids level coming from a unique sample, a specific sample preparation must be optimized. In this study, we streamlined a biphasic extraction procedure based on a MTBE/Methanol mixture to provide the simultaneous extraction of polar (proteins, metabolites) and apolar compounds (lipids) for multi-omics analyses from a unique biological sample by a liquid chromatography (LC)/mass spectrometry (MS)/MS-based targeted approach. We applied the methodology for the study of female amphipod Gammarus fossarum during the reproductive cycle. Multivariate data analyses including Partial Least Squares Discriminant Analysis and multiple factor analysis were applied for the integration of the multi-omics data sets and highlighted molecular signatures, specific to the different stages.

Gene expression networks and functionally enriched pathways involved in the response of domestic chicken to acute heat stress

Heat stress in poultry houses, especially in warm areas, is one of the main environmental factors that restrict the growth of broilers or laying performance of layers, suppresses the immune system, and deteriorates egg quality and feed conversion ratio. The molecular mechanisms underlying the response of chicken to acute heat stress (AHS) have not been comprehensively elucidated. Therefore, the main object of the current work was to investigate the liver gene expression profile of chickens under AHS in comparison with their corresponding control groups, using four RNA-seq datasets. The meta-analysis, GO and KEGG pathway enrichment, WGCNA, machine-learning, and eGWAS analyses were performed. The results revealed 77 meta-genes that were mainly related to protein biosynthesis, protein folding, and protein transport between cellular organelles. In other words, under AHS, the expression of genes involving in the structure of rough reticulum membrane and in the process of protein folding was adversely influenced. In addition, genes related to biological processes such as "response to unfolded proteins," "response to reticulum stress" and "ERAD pathway" were differentially regulated. We introduce here a couple of genes such as HSPA5, SSR1, SDF2L1, and SEC23B, as the most significantly differentiated under AHS, which could be used as bio-signatures of AHS. Besides the mentioned genes, the main findings of the current work may shed light to the identification of the effects of AHS on gene expression profiling of domestic chicken as well as the adaptive response of chicken to environmental stresses.

Identification of key genes involved in secondary metabolite biosynthesis in Digitalis purpurea

The medicinal plant Digitalis purpurea produces cardiac glycosides that are useful in the pharmaceutical industry. These bioactive compounds are in high demand due to ethnobotany's application to therapeutic procedures. Recent studies have investigated the role of integrative analysis of multi-omics data in understanding cellular metabolic status through systems metabolic engineering approach, as well as its application to genetically engineering metabolic pathways. In spite of numerous omics experiments, most molecular mechanisms involved in metabolic pathways biosynthesis in D. purpurea remain unclear. Using R Package Weighted Gene Co-expression Network Analysis, co-expression analysis was performed on the transcriptome and metabolome data. As a result of our study, we identified transcription factors, transcriptional regulators, protein kinases, transporters, non-coding RNAs, and hub genes that are involved in the production of secondary metabolites. Since jasmonates are involved in the biosynthesis of cardiac glycosides, the candidate genes for Scarecrow-Like Protein 14 (SCL14), Delta24-sterol reductase (DWF1), HYDRA1 (HYD1), and Jasmonate-ZIM domain3 (JAZ3) were validated under methyl jasmonate treatment (MeJA, 100 μM). Despite early induction of JAZ3, which affected downstream genes, it was dramatically suppressed after 48 hours. SCL14, which targets DWF1, and HYD1, which induces cholesterol and cardiac glycoside biosynthesis, were both promoted. The correlation between key genes and main metabolites and validation of expression patterns provide a unique insight into the biosynthesis mechanisms of cardiac glycosides in D. purpurea.

In silico-driven analysis of the Glossina morsitans morsitans antennae transcriptome in response to repellent or attractant compounds

BACKGROUND

High-throughput sequencing generates large volumes of biological data that must be interpreted to make meaningful inference on the biological function. Problems arise due to the large number of characteristics p (dimensions) that describe each record [n] in the database. Feature selection using a subset of variables extracted from the large datasets is one of the approaches towards solving this problem.

METHODOLOGY

In this study we analyzed the transcriptome of Glossina morsitans morsitans (Tsetsefly) antennae after exposure to either a repellant (δ-nonalactone) or an attractant (ε-nonalactone). We identified 308 genes that were upregulated or downregulated due to exposure to a repellant (δ-nonalactone) or an attractant (ε-nonalactone) respectively. Weighted gene coexpression network analysis was used to cluster the genes into 12 modules and filter unconnected genes. Discretized and association rule mining was used to find association between genes thereby predicting the putative function of unannotated genes.

RESULTS AND DISCUSSION

Among the significantly expressed chemosensory genes (FDR < 0.05) in response to Ɛ-nonalactone were gustatory receptors (GrIA and Gr28b), ionotrophic receptors (Ir41a and Ir75a), odorant binding proteins (Obp99b, Obp99d, Obp59a and Obp28a) and the odorant receptor (Or67d). Several non-chemosensory genes with no assigned function in the NCBI database were co-expressed with the chemosensory genes. Exposure to a repellent (δ-nonalactone) did not show any significant change between the treatment and control samples. We generated a coexpression network with 276 edges and 130 nodes. Genes CAH3, Ahcy, Ir64a, Or67c, Ir8a and Or67a had node degree values above 11 and therefore could be regarded as the top hub genes in the network. Association rule mining showed a relation between various genes based on their appearance in the same itemsets as consequent and antecedent.

Co-expression network analysis identifies novel molecular pathways associated with cadmium and pyriproxyfen testicular toxicity in Gammarus fossarum

Omics approaches are continuously providing new clues on the mechanisms of action of contaminants in species of environmental relevance, contributing to the emergence of molecular ecotoxicology. Co-expression network approaches represent a suitable methodological framework for studying the rich content of omics datasets. This study aimed to find evidence of key pathways and proteins related to the testicular toxicity in the sentinel crustacean species Gammarus fossarum exposed to endocrine disruptors using a weighted protein co-expression network analysis. From a shotgun proteomics dataset of male gonads of G. fossarum organisms exposed to cadmium (Cd), pyriproxyfen (Pyr) and methoxyfenozide (Met) in laboratory conditions, four distinct modules were identified as significantly correlated to contaminants' exposure. Protein set enrichment analysis identified modules involved in cytoskeleton organization and oxidative stress response associated with the Cd exposure. The module associated with Pyr exposure was associated with endoplasmic reticulum stress (ER) response, and the module correlated with Met exposure was characterized by a significant proportion of amphipod-restricted proteins whose functions are still not characterized. Our results show that co-expression networks are efficient and adapted tools to identify new potential mode of actions from environmental sentinel species, such as G. fossarum, using a proteogenomic approach, even without an annotated genome.

Identification of key genes associated with secondary metabolites biosynthesis by system network analysis in Valeriana officinalis

Valeriana officinalis is a medicinal plant, a source of bioactive chemical compounds and secondary metabolites which are applied in pharmaceutical industries. The advent of ethnomedicine has provided alternatives for disease treatment and has increased demands for natural products and bioactive compounds. A set of preliminary steps to answers for such demands can include integrative omics for systems metabolic engineering, as an approach that contributes to the understanding of cellular metabolic status. There is a growing trend of this approach for genetically engineering metabolic pathways in plant systems, by which natural and synthetic compounds can be produced. As in the case of most medicinal plants, there are no sufficient information about molecular mechanisms involved in the regulation of metabolic pathways in V. officinalis. In this research, systems biology was performed on the RNA-seq transcriptome and metabolome data to find key genes that contribute to the synthesis of major secondary metabolites in V. officinalis. The R Package Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to analyze the data. Based on the results, some major modules and hub genes were identified to be associated with the valuable secondary metabolites. In addition, some TF-encoding genes, including AP2/ERF-ERF, WRKY and NAC TF families, as well as some regulatory factors including protein kinases and transporters were identified. The results showed that several novel hub genes, such as PCMP-H24, RPS24B, ANX1 and PXL1, may play crucial roles in metabolic pathways. The current findings provide an overall insight into the metabolic pathways of V. officinalis and can expand the potential for engineering genome-scale pathways and systems metabolic engineering to increase the production of bioactive compounds by plants.

Weighted gene co-expression network analysis identifies modules and functionally enriched pathways in the lactation process

The exponential growth in knowledge has resulted in a better understanding of the lactation process in a wide variety of animals. However, the underlying genetic mechanisms are not yet clearly known. In order to identify the mechanisms involved in the lactation process, various mehods, including meta-analysis, weighted gene co-express network analysis (WGCNA), hub genes identification, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment at before peak (BP), peak (P), and after peak (AP) stages of the lactation processes have been employed. A total of 104, 85, and 26 differentially expressed genes were identified based on PB vs. P, BP vs. AP, and P vs. AP comparisons, respectively. GO and KEGG pathway enrichment analysis revealed that DEGs were significantly enriched in the "ubiquitin-dependent ERAD" and the "chaperone cofactor-dependent protein refolding" in BP vs. P and P vs. P, respectively. WGCNA identified five significant functional modules related to the lactation process. Moreover, GJA1, AP2A2, and NPAS3 were defined as hub genes in the identified modules, highlighting the importance of their regulatory impacts on the lactation process. The findings of this study provide new insights into the complex regulatory networks of the lactation process at three distinct stages, while suggesting several candidate genes that may be useful for future animal breeding programs. Furthermore, this study supports the notion that in combination with a meta-analysis, the WGCNA represents an opportunity to achieve a higher resolution analysis that can better predict the most important functional genes that might provide a more robust bio-signature for phenotypic traits, thus providing more suitable biomarker candidates for future studies.

Disentangling of the ecotoxicological signal using "omics" analyses, a lesson from the survey of the impact of cyanobacterial proliferations on fishes

Omics technologies offer unprecedented perspectives for the rational investigation of complex biological systems. Indeed, omics present the ability of offering an extensive perception of the biochemistry and physiology of the cell and of any perturbing consequences of contaminants through the joint investigation of thousands of molecular responses simultaneously; then it has recently conducted to a fervent attention by research ecotoxicologists. Beyond the presentation of latest advances, exemplified here by omics investigation of cyanobacterial deleterious effects on various fishes (at various experimental and biological scales and with various analytical tools and pipeline), the present review paper re-explores the promising perspectives and also the pitfalls of such holistic investigations of the ecotoxicological response of organisms for environmental assessment.

High-multiplexed monitoring of protein biomarkers in the sentinel Gammarus fossarum by targeted scout-MRM assay, a new vision for ecotoxicoproteomics

Ecotoxicoproteomics employs mass spectrometry-based approaches centered on proteins of sentinel organisms to assess for instance, chemical toxicity in fresh water. In this study, we combined proteogenomics experiments and a novel targeted proteomics approach free from retention time scheduling called Scout-MRM. This methodology will enable the measurement of simultaneously changes in the relative abundance of multiple proteins involved in key physiological processes and potentially impacted by contaminants in the freshwater sentinel Gammarus fossarum. The development and validation of the assay were performed to target 157 protein biomarkers of this non-model organism. We carefully chose and validated the transitions to monitor using conventional parameters (linearity, repeatability, LOD, LOQ). Finally, the potential of the methodology is illustrated by measuring 277-peptide-plex assay (831 transitions) in sentinel animals exposed in natura to different agricultural sites potentially exposed to pesticide contamination. Multivariate data analyses highlighted the modulation of several key proteins involved in feeding and molting. This multiplex-targeted proteomics assay paves the way for the discovery and the use of a large panel of novel protein biomarkers in emergent ecotoxicological models for environmental monitoring in the future. BIOLOGICAL SIGNIFICANCE: The study contributed to the development of Scout-MRM for the high-throughput quantitation of a large panel of proteins in the Gammarus fossarum freshwater sentinel. Increasing the number of markers in ecotoxicoproteomics is of most interest to assess the impact of pollutants in freshwater organisms. The development and validation of the assay enabled the monitoring of a large panel of reporter peptides of exposed gammarids. To illustrate the applicability of the methodology, animals from different agricultural sites were analysed. The application of the assay highlighted the modulation of some biomarker proteins involved in key physiological pathways, such as molting, feeding and general stress response. Increasing multiplexing capabilities and field test will provide the development of diagnostic protein biomarkers for emergent ecotoxicological models in future environmental biomonitoring programs.

Deep Transcriptomic Analysis Reveals the Dynamic Developmental Progression during Early Development of Channel Catfish (Ictalurus punctatus)

The transition from fertilized egg to larva in fish is accompanied with various biological processes. We selected seven early developmental stages in channel catfish, Ictalurus punctatus, for transcriptome analysis, and covered 22,635 genes with 590 million high-quality RNA-sequencing (seq) reads. Differential expression analysis between neighboring developmental timepoints revealed significantly enriched biological categories associated with growth, development and morphogenesis, which was most evident at 2 vs. 5 days post fertilization (dpf) and 5 vs. 6 dpf. A gene co-expression network was constructed using the Weighted Gene Co-expression Network Analysis (WGCNA) approach and four critical modules were identified. Among candidate hub genes, GDF10, FOXA2, HCEA and SYCE3 were involved in head formation, egg development and the transverse central element of synaptonemal complexes. CK1, OAZ2, DARS1 and UBE2V2 were mainly associated with regulation of cell cycle, growth, brain development, differentiation and proliferation of enterocytes. IFI44L and ZIP10 were critical for the regulation of immune activity and ion transport. Additionally, TCK1 and TGFB1 were related to phosphate transport and regulating cell proliferation. All these genes play vital roles in embryogenesis and regulation of early development. These results serve as a rich dataset for functional genomic studies. Our work reveals new insights of the underlying mechanisms in channel catfish early development.