Integrated signaling pathway and gene expression regulatory model to dissect dynamics of Escherichia coli challenged mammary epithelial cells

Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes—CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3—were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine–cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

The role of gene to gene interaction in the breast's genomic signature of pregnancy

Full-term pregnancy at an early age confers long-term protection against breast cancer. Published data shows a specific transcriptomic profile controlling chromatin remodeling that could play a relevant role in the pregnancy-induced protection. This process of chromatin remodeling, induced by the breast differentiation caused by the first full-term pregnancy, has mainly been measured by the expression level of genes individually considered. However, genes equally expressed during the process of chromatin remodeling may behave differently in their interaction with other genes. These changes at the gene cluster level could constitute an additional dimension of chromatin remodeling and therefore of the pregnancy-induced protection. In this research, we apply Information and Graph Theories, Differential Co-expression Network Analysis, and Multiple Regression Analysis, specially designed to examine structural and informational aspects of data sets, to analyze this question. Our findings demonstrate that, independently of the changes in the gene expression at the individual level, there are significant changes in gene-gene interactions and gene cluster behaviors. These changes indicate that the parous breast, through the process of early full-term pregnancy, generates more modules in the networks, with higher density, and a genomic structure performing additional and more complex functions than those found in the nulliparous breast.

Estimating Linear and Nonlinear Gene Coexpression Networks by Semiparametric Neighborhood Selection

Whereas nonlinear relationships between genes are acknowledged, there exist only a few methods for estimating nonlinear gene coexpression networks or gene regulatory networks (GCNs/GRNs) with common deficiencies. These methods often consider only pairwise associations between genes, and are, therefore, poorly capable of identifying higher-order regulatory patterns when multiple genes should be considered simultaneously. Another critical issue in current nonlinear GCN/GRN estimation approaches is that they consider linear and nonlinear dependencies at the same time in confounded form nonparametrically. This severely undermines the possibilities for nonlinear associations to be found, since the power of detecting nonlinear dependencies is lower compared to linear dependencies, and the sparsity-inducing procedures might favor linear relationships over nonlinear ones only due to small sample sizes. In this paper, we propose a method to estimate undirected nonlinear GCNs independently from the linear associations between genes based on a novel semiparametric neighborhood selection procedure capable of identifying complex nonlinear associations between genes. Simulation studies using the common DREAM3 and DREAM9 datasets show that the proposed method compares superiorly to the current nonlinear GCN/GRN estimation methods.

In silico genome-wide miRNA-QTL-SNPs analyses identify a functional SNP associated with mastitis in Holsteins

Background

Single-nucleotide polymorphisms (SNPs) in microRNAs (miRNAs) and their target binding sites affect miRNA function and are involved in biological processes and diseases, including bovine mastitis, a frequent inflammatory disease. Our previous study has shown that bta-miR-2899 is significantly upregulated in the mammary gland tissue of mastitis-infected cow than that of healthy cows.

Results

In the present study, we used a customized miRNAQTLsnp software and identified 5252 SNPs in 691 bovine pre-miRNAs, which are also located within the quantitative trait loci (QTLs) that are associated with mastitis and udder conformation-related traits. Using luciferase assay in the bovine mammary epithelial cells, we confirmed a candidate SNP (rs109462250, g. 42,198,087 G > A) in the seed region of bta-miR-2899 located in the somatic cell score (SCS)-related QTL (Chr.18: 33.9–43.9 Mbp), which affected the interaction of bta-miR-2899 and its putative target Spi-1 proto-oncogene (SPI1), a pivotal regulator in the innate and adaptive immune systems. Quantitative real-time polymerase chain reaction results showed that the relative expression of SPI1 in the mammary gland of AA genotype cows was significantly higher than that of GG genotype cows. The SNP genotypes were associated with SCS in Holstein cows.

Conclusions

Altogether, miRNA-related SNPs, which influence the susceptibility to mastitis, are one of the plausible mechanisms underlying mastitis via modulating the interaction of miRNAs and immune-related genes. These miRNA-QTL-SNPs, such as the SNP (rs109462250) of bta-miR-2899 may have implication for the mastitis resistance breeding program in Holstein cattle.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0749-5) contains supplementary material, which is available to authorized users.

Solexa sequencing and custom microRNA chip reveal repertoire of microRNAs in mammary gland of bovine suffering from natural infectious mastitis

Identification of microRNAs (miRNAs), target genes and regulatory networks associated with innate immune and inflammatory responses and tissue damage is essential to elucidate the molecular and genetic mechanisms for resistance to mastitis. In this study, a combination of Solexa sequencing and custom miRNA chip approaches was used to profile the expression of miRNAs in bovine mammary gland at the late stage of natural infection with Staphylococcus aureus, a widespread mastitis pathogen. We found 383 loci corresponding to 277 known and 49 putative novel miRNAs, two potential mitrons and 266 differentially expressed miRNAs in the healthy and mastitic cows' mammary glands. Several interaction networks and regulators involved in mastitis susceptibility, such as ALCAM, COL1A1, APOP4, ITIH4, CRP and fibrinogen alpha (FGA), were highlighted. Significant down-regulation and location of bta-miR-26a, which targets FGA in the mastitic mammary glands, were validated using quantitative real-time PCR, in situ hybridization and dual-luciferase reporter assays. We propose that the observed miRNA variations in mammary glands of mastitic cows are related to the maintenance of immune and defense responses, cell proliferation and apoptosis, and tissue injury and healing during the late stage of infection. Furthermore, the effect of bta-miR-26a in mastitis, mediated at least in part by enhancing FGA expression, involves host defense, inflammation and tissue damage.

On the importance of modelling the internal spatial dynamics of biological cells

Spatial effects such as cell shape have very often been considered negligible in models of cellular pathways, and many existing simulation infrastructures do not take such effects into consideration. Recent experimental results are reversing this judgement by showing that very small spatial variations can make a big difference in the fate of a cell. This is particularly the case when considering eukaryotic cells, which have a complex physical structure and many subtle control mechanisms, but bacteria are also interesting for the huge variation in shape both between species and in different phases of their lifecycle. In this work we perform simulations that measure the effect of three common bacterial shapes on the behaviour of model cellular pathways. To perform these experiments we develop ReDi-Cell, a highly scalable GPGPU cell simulation infrastructure for the modelling of cellular pathways in spatially detailed environments. ReDi-Cell is validated against known-good simulations, prior to its use in new work. We then use ReDi-Cell to conduct novel experiments that demonstrate the effect that three common bacterial shapes (Cocci, Bacilli and Spirilli) have on the behaviour of model cellular pathways. Pathway wavefront shape, pathway concentration gradients, and chemical species distribution are measured in the three different shapes. We also quantify the impact of internal cellular clutter on the same pathways. Through this work we show that variations in the shape or configuration of these common cell shapes alter model cell behaviour.