Analysis of gene expression profiles of Enterococcus faecalis induced by type I collagen

Enterococcus faecalis is an etiological agent of endodontic infections. The present study was performed to investigate the gene profiles of E. faecalis induced by type I collagen stimulation. E. faecalis ATCC 19433 was cultivated with [collagen (+)] or without type I collagen [collagen (−)], and transcriptome analysis was performed using high-throughput sequencing technology. A total of 3.6 gb of information was obtained by sequence analysis and 77 differentially expressed genes (DEGs) between the two culture conditions were identified. Among the 77 DEGs, 35 genes were upregulated in collagen (+) E. faecalis, whereas 42 genes were downregulated. Gene Ontology (GO) enrichment analysis was performed and 11 GO terms, including metalloendopeptidase activity (GO:0004222) and two related GO terms (GO:0031012, GO:0044421), were significantly enriched in the set of upregulated genes. We focused on an upregulated DEG belonging to the matrixin metalloprotease gene family, and matrix metalloprotease (MMP) activities of the bacterial cell were examined. The generic MMP, MMP-8, and MMP-9 activities of collagen (+) E. faecalis were significantly higher than those of collagen (−) E. faecalis. These results suggested that contact with type I collagen may alter the gene expression profile of E. faecalis, and upregulation of metalloprotease genes may result in enhanced MMP activities in E. faecalis.

The Role of miR-4256/HOXC8 Signaling Axis in the Gastric Cancer Progression: Evidence From lncRNA-miRNA-mRNA Network Analysis

Gastric cancer is a deadly human malignancy and the molecular mechanisms underlying gastric cancer pathophysiology are very complicated. Thus, further investigations are warranted to decipher the underlying molecular mechanisms. With the development of high-throughput screening and bioinformatics, gene expression profiles with large scale have been performed in gastric cancer. In the present study, we mined The Cancer Genome Atlas (TCGA) database and analyzed the gene expression profiles between gastric cancer tissues and normal gastric tissues. A series of differentially expressed lncRNAs, miRNAs and mRNAs between gastric cancer tissues and normal gastric tissues were identified. Based on the differentially expressed genes, we constructed miRNA-mRNA network, lncRNA-mRNA network and transcriptional factors-mRNA-miRNA-lncRNA network. Furthermore, the Kaplan survival analysis showed that high expression levels of EVX1, GBX2, GCM1, HOXC8, HOXC9, HOXC10, HOXC11, HOXC12 and HOXC13 were all significantly correlated with shorter overall survival of the patients with gastric cancer. On the other hand, low expression level of HOXA13 was associated with shorter overall survival of patients with gastric cancer. Among these hub genes, we performed the in vitro functional studies of HOXC8 in the gastric cancer cells. Knockdown of HOXC8 and overexpression of miR-4256 both significantly repressed the gastric cancer cell proliferation and migration, and miR-4256 repressed the expression of HOXC8 via targeting its 3’ untranslated region in gastric cancer cells. Collectively, our results revealed that a complex interaction networks of differentially expressed genes in gastric cancer, and further functional studies indicated that miR-4256/HOXC8 may be an important axis in regulating gastric cancer progression.

Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in an Alzheimer's disease model

Amyloid-β plaques and neurofibrillary tau tangles are the neuropathologic hallmarks of Alzheimer's disease (AD), but the spatiotemporal cellular responses and molecular mechanisms underlying AD pathophysiology remain poorly understood. Here we introduce STARmap PLUS to simultaneously map single-cell transcriptional states and disease marker proteins in brain tissues of AD mouse models at subcellular resolution (200 nm). This high-resolution spatial transcriptomics map revealed a core-shell structure where disease-associated microglia (DAM) closely contact amyloid-β plaques, whereas disease-associated astrocytes (DAA) and oligodendrocyte precursor cells (OPC) are enriched in the outer shells surrounding the plaque-DAM complex. Hyperphosphorylated tau emerged mainly in excitatory neurons in the CA1 region accompanied by the infiltration of oligodendrocyte subtypes into the axon bundles of hippocampal alveus. The integrative STARmap PLUS method bridges single-cell gene expression profiles with tissue histopathology at subcellular resolution, providing an unprecedented roadmap to pinpoint the molecular and cellular mechanisms of AD pathology and neurodegeneration.

Characteristic Features of the Transcriptome in a Rat Strain with Audiogenic Epilepsy

Audiogenic epilepsy (AE), developing in rodent strains in response to sound, is widely used as the model of generalized convulsive epilepsy, while the molecular mechanisms determining AE are currently poorly understood. The brain region that is crucial for AE development isthe inferior and superior colliculi (IC, SC). We compared IC-SC gene expression profiles in rats with different AE susceptibility using transcriptome analysis.The transcriptomes were obtained from the IC-SC of Wistar rats (with no AE), Krushinsky-Molodkina (KM) strain rats (100% AE susceptible), and ”0” strain rats (with no AE) selected from F2 KM x Wistar hybrids for AE absence. KM gene expression displayed characteristic differences inboth of the strains that were not susceptible to AE. There was increased expression of a number of genes responsible for positive regulation of the MAPK signaling cascade, as well as of genes responsible for the production of interferon and several other cytokines. An increase in the expression levels of theTTR gene was found in KM rats, as well as significantly lower expression of the Msh3 gene (involved in post-replicative DNA repair systems). AE was also describedin the 101/HY mouse strain with a mutation in the locus controlling DNA repair. The DNA repair system defects could be the primary factor leading to the accumulation of mutations, which, in turn, promote AE. Keywords: udiogenic seizure, KM strain, transcriptome, TTR gene, Msh3 gene, DNA repair

Comparative transcriptome profiles of Schistosoma japonicum larval stages: Implications for parasite biology and host invasion

Schistosoma japonicum is prevalent in Asia with a wide mammalian host range, which leads to highly harmful zoonotic parasitic diseases. Most previous transcriptomic studies have been performed on this parasite, but mainly focus on stages inside the mammalian host. Moreover, few larval transcriptomic data are available in public databases. Here we mapped the detailed transcriptome profiles of four S. japonicum larval stages including eggs, miracidia, sporocysts and cercariae, providing a comprehensive development picture outside of the mammalian host. By analyzing the stage-specific/enriched genes, we identified functional genes associated with the biological characteristic at each stage: e.g. we observed enrichment of genes necessary for DNA replication only in sporocysts, while those involved in proteolysis were upregulated in sporocysts and/or cercariae. This data indicated that miracidia might use leishmanolysin and neprilysin to penetrate the snail, while elastase (SjCE2b) and leishmanolysin might contribute to the cercariae invasion. The expression profile of stem cell markers revealed potential germinal cell conversion during larval development. Additionally, our analysis indicated that tandem duplications had driven the expansion of the papain family in S. japonicum. Notably, all the duplicated cathepsin B-like proteases were highly expressed in cercariae. Utilizing our 3rd version of S. japonicum genome, we further characterized the alternative splicing profiles throughout these four stages. Taken together, the present study provides compressive gene expression profiles of S. japonicum larval stages and identifies a set of genes that might be involved in intermediate and definitive host invasion.

Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer

Background: Gastric cancer (GC) is aggressive cancer with a poor prognosis. Previously bulk transcriptome analysis was utilized to identify key genes correlated with the development, progression and prognosis of GC. However, due to the complexity of the genetic mutations, there is still an urgent need to recognize core genes in the regulatory network of GC.Methods: Gene expression profiles (GSE66229) were retrieved from the GEO database. Weighted correlation network analysis (WGCNA) was employed to identify gene modules mostly correlated with GC carcinogenesis. R package ‘DiffCorr’ was applied to identify differentially correlated gene pairs in tumor and normal tissues. Cytoscape was adopted to construct and visualize the gene regulatory network.Results: A total of 15 modules were detected in WGCNA analysis, among which three modules were significantly correlated with GC. Then genes in these modules were analyzed separately by “DiffCorr”. Multiple differentially correlated gene pairs were recognized and the network was visualized by the software Cytoscape. Moreover, GEMIN5 and PFDN2, which were rarely discussed in GC, were identified as key genes in the regulatory network and the differential expression was validated by real-time qPCR, WB and IHC in cell lines and GC patient tissues.Conclusions: Our research has shed light on the carcinogenesis mechanism by revealing differentially correlated gene pairs during transition from normal to tumor. We believe the application of this network-based algorithm holds great potential in inferring relationships and detecting candidate biomarkers.

Supervised machine learning models and protein-protein interaction network analysis of gene expression profiles induced by omega-3 polyunsaturated fatty acids

Background: Omega-3 polyunsaturated fatty acids (PUFAs), such as eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids, have beneficial effects on human health, but their effect on gene expression in elderly individuals (age ≥ 65) is largely unknown. In order to examine this, the gene expression profiles were analyzed in the healthy subjects (n = 96) at baseline and after 26 weeks of supplementation with EPA+DHA to determine up-regulated and down-regulated dif-ferentially expressed genes (DEGs) triggered by PUFAs. The protein-protein interaction (PPI) networks were constructed by mapping these DEGs to a human interactome and linking them to the specific pathways. Objective: This study aimed to implement supervised machine learning models and protein-protein interaction network analysis of gene expression profiles induced by PUFAs. Methods: The transcriptional profile of GSE12375 was obtained from the Gene Expression Om-nibus database, which is based on the Affymetrix NuGO array. The probe cell intensity data were converted into the gene expression values, and the background correction was performed by the multi-array average algorithm. The LIMMA (Linear Models for Microarray Data) algo-rithm was implemented to identify relevant DEGs at baseline and after 26 weeks of supplemen-tation with a p-value < 0.05. The DAVID web server was used to identify and construct the en-riched KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways. Finally, the construction of machine learning (ML) models, including logistic regression, naïve Bayes, and deep neural networks, were implemented for the analyzed DEGs associated with the specific pathways. Results: The results revealed that up-regulated DEGs were associated with neurotrophin/MAPK signaling, whereas the down-regulated DEGs were linked to cancer, acute myeloid leukemia, and long-term depression pathways. Additionally, ML approaches were able to cluster the EPA/DHA-treated and control groups by the logistic regression performing the best. Conclusion: Overall, this study highlights the pivotal changes in DEGs induced by PUFAs and provides the rationale for the implementation of ML algorithms as predictive models for this type of biomedical data.

A comparative study of cellular diversity between the Xenopus pronephric and mouse metanephric nephron

The kidney is an essential organ that ensures bodily fluid homeostasis and removes soluble waste products from the organism. The functional units within the kidneys are epithelial tubules called nephrons. These tubules take in filtrate from the blood or coelom and selectively reabsorb nutrients through evolutionarily conserved nephron segments, leaving waste product to be eliminated in the urine. Genes coding for functional transporters are segmentally expressed, enabling nephrons to function as selective filters. The developmental patterning program that generates these segments is of great interest. The Xenopus embryonic kidney, the pronephros, has served as a valuable model to identify genes involved in nephron formation and patterning. Prior work has defined the gene expression profiles of Xenopus epithelial nephron segments via in situ hybridization strategies, but our understanding of the cellular makeup of the Xenopus pronephric kidney remains incomplete. Here, we scrutinize the cellular composition of the Xenopus pronephric nephron through comparative analyses with previous Xenopus studies and single-cell mRNA sequencing of the adult mouse kidney, this study reconstructs the cellular makeup of the pronephric kidney and identifies conserved cells, segments, and expression profiles. The data highlight significant conservation in podocytes, proximal and distal tubule cells and divergence in cellular composition underlying the evolution of the corticomedullary axis, while emphasizing the Xenopus pronephros as a model for physiology and disease.

Active RB causes visible changes in nuclear organization

RB restricts G1/S progression by inhibiting E2F. Here, we show that sustained expression of active RB, and prolonged G1 arrest, causes visible changes in chromosome architecture that are not directly associated with E2F inhibition. Using FISH probes against two euchromatin RB-associated regions, two heterochromatin domains that lack RB-bound loci, and two whole-chromosome probes, we found that constitutively active RB (ΔCDK-RB) promoted a more diffuse, dispersed, and scattered chromatin organization. These changes were RB dependent, were driven by specific isoforms of monophosphorylated RB, and required known RB-associated activities. ΔCDK-RB altered physical interactions between RB-bound genomic loci, but the RB-induced changes in chromosome architecture were unaffected by dominant-negative DP1. The RB-induced changes appeared to be widespread and influenced chromosome localization within nuclei. Gene expression profiles revealed that the dispersion phenotype was associated with an increased autophagy response. We infer that, after cell cycle arrest, RB acts through noncanonical mechanisms to significantly change nuclear organization, and this reorganization correlates with transitions in cellular state.