Assembling systems biology, embryo development and teratogenesis: What do we know so far and where to go next?

New candidate genes potentially involved in Zika virus teratogenesis

Despite efforts to elucidate Zika virus (ZIKV) teratogenesis, still several issues remain unresolved, particularly on the molecular mechanisms behind the pathogenesis of Congenital Zika Syndrome (CZS). To answer this question, we used bioinformatics tools, animal experiments and human gene expression analysis to investigate genes related to brain development potentially involved in CZS. Searches in databases for genes related to brain development and CZS were performed, and a protein interaction network was created. The expression of these genes was analyzed in a CZS animal model and secondary gene expression analysis (DGE) was performed in human cells exposed to ZIKV. A total of 2610 genes were identified in the databases, of which 1013 were connected. By applying centrality statistics of the global network, 36 candidate genes were identified, which, after selection resulted in nine genes. Gene expression analysis revealed distinctive expression patterns for PRKDC, PCNA, ATM, SMC3 as well as for FGF8 and SHH in the CZS model. Furthermore, DGE analysis altered expression of ATM, PRKDC, PCNA. In conclusion, systems biology are helpful tools to identify candidate genes to be validated in vitro and in vivo. PRKDC, PCNA, ATM, SMC3, FGF8 and SHH have altered expression in ZIKV-induced brain malformations.

Bioinformatics Methods for Transcriptome Analysis on Teratogenesis Testing

Teratogenesis testing can be challenging due to the limitations of both in vitro and in vivo models. Test-systems, based especially on human embryonic cells, have been helping to overcome the difficulties when allied to omics strategies, such as transcriptomics. In these test-systems, cells exposed to different compounds are then analyzed in microarray or RNA-seq platforms regarding the impacts of the potential teratogens in the gene expression. Nevertheless, microarray and RNA-seq dataset processing requires computational resources and bioinformatics knowledge. Here, a pipeline for microarray and RNA-seq processing is presented, aiming to help researchers from any field to interpret the main transcriptome results, such as differential gene expression, enrichment analysis, and statistical interpretation. This chapter also discusses the main difficulties that can be encountered in a transcriptome analysis and the better alternatives to overcome these issues, describing both programming codes and user-friendly tools. Finally, specific issues in the teratogenesis field, such as time-course analysis, are also described, demonstrating how the pipeline can be applied in these studies.

Anticonvulsants and Chromatin-Genes Expression: A Systems Biology Investigation

Embryofetal development is a critical process that needs a strict epigenetic control, however, perturbations in this balance might lead to the occurrence of congenital anomalies. It is known that anticonvulsants potentially affect epigenetics-related genes, however, it is not comprehended whether this unbalance could explain the anticonvulsants-induced fetal syndromes. In the present study, we aimed to evaluate the expression of epigenetics-related genes in valproic acid, carbamazepine, or phenytoin exposure. We selected these three anticonvulsants exposure assays, which used murine or human embryonic stem-cells and were publicly available in genomic databases. We performed a differential gene expression (DGE) and weighted gene co-expression network analysis (WGCNA), focusing on epigenetics-related genes. Few epigenetics genes were differentially expressed in the anticonvulsants' exposure, however, the WGCNA strategy demonstrated a high enrichment of chromatin remodeling genes for the three drugs. We also identified an association of 46 genes related to Fetal Valproate Syndrome, containing SMARCA2 and SMARCA4, and nine genes to Fetal Hydantoin Syndrome, including PAX6, NEUROD1, and TSHZ1. The evaluation of stem-cells under drug exposure can bring many insights to understand the drug-induced damage to the embryofetal development. The candidate genes here presented are potential biomarkers that could help in future strategies for the prevention of congenital anomalies.

Systems Biology Approaches Reveal Potential Phenotype-Modifier Genes in Neurofibromatosis Type 1

Neurofibromatosis type (NF1) is a syndrome characterized by varied symptoms, ranging from mild to more aggressive phenotypes. The variation is not explained only by genetic and epigenetic changes in the NF1 gene and the concept of phenotype-modifier genes in extensively discussed in an attempt to explain this variability. Many datasets and tools are already available to explore the relationship between genetic variation and disease, including systems biology and expression data. To suggest potential NF1 modifier genes, we selected proteins related to NF1 phenotype and NF1 gene ontologies. Protein–protein interaction (PPI) networks were assembled, and network statistics were obtained by using forward and reverse genetics strategies. We also evaluated the heterogeneous networks comprising the phenotype ontologies selected, gene expression data, and the PPI network. Finally, the hypothesized phenotype-modifier genes were verified by a random-walk mathematical model. The network statistics analyses combined with the forward and reverse genetics strategies, and the assembly of heterogeneous networks, resulted in ten potential phenotype-modifier genes: AKT1, BRAF, EGFR, LIMK1, PAK1, PTEN, RAF1, SDC2, SMARCA4, and VCP. Mathematical models using the random-walk approach suggested SDC2 and VCP as the main candidate genes for phenotype-modifiers.

CRL4-Cereblon complex in Thalidomide Embryopathy: a translational investigation

The Cereblon-CRL4 complex has been studied predominantly with regards to thalidomide treatment of multiple myeloma. Nevertheless, the role of Cereblon-CRL4 in Thalidomide Embryopathy (TE) is still not understood. Not all embryos exposed to thalidomide develop TE, hence here we evaluate the role of the CRL4-Cereblon complex in TE variability and susceptibility. We sequenced CRBN, DDB1, CUL4A, IKZF1, and IKZF3 in individuals with TE. To better interpret the variants, we suggested a score and a heatmap comprising their regulatory effect. Differential gene expression after thalidomide exposure and conservation of the CRL4-Cereblon protein complex were accessed from public repositories. Results suggest a summation effect of Cereblon variants on pre-axial longitudinal limb anomalies, and heatmap scores identify the CUL4A variant rs138961957 as potentially having an effect on TE susceptibility. CRL4-Cereblon gene expression after thalidomide exposure and CLR4-Cereblon protein conservation does not explain the difference in Thalidomide sensitivity between species. In conclusion, we suggest that CRL4-Cereblon variants act through several regulatory mechanisms, which may influence CRL4-Cereblon complex assembly and its ability to bind thalidomide. Human genetic variability must be addressed not only to further understand the susceptibility to TE, but as a crucial element in therapeutics, including in the development of pharmacogenomics strategies.