Downregulation of FTO in the hippocampus is associated with mental disorders induced by fear stress during pregnancy.

Mental disorders (MD), such as anxiety, depression, and cognitive impairment, are very common during pregnancy and predispose to adverse pregnancy outcomes; however, the underlying mechanisms are still under intense investigation. Although the most common RNA modification in epigenetics, N6-methyladenosine (m6A) has been widely studied, its role in MD has not been investigated. Here, we observed that fat mass and obesity-associated protein (FTO) are downregulated in the hippocampus of pregnant rats with MD induced by fear stress and demonstrated that FTO participates in and regulates MD induced by fear stress. In addition, we identified four genes with anomalous modifications and expression (double aberrant genes) that were directly regulated by FTO, namely Angpt2, Fgf10, Rpl21, and Adcy7. Furthermore, we found that these genes might induce MD by regulating the PI3K/Akt and Rap1 signaling pathways. It appears that FTO-mediated m6A modification is a key regulatory mechanism in MD caused by fear stress during pregnancy.

Integrated bioinformatic analysis and experimental validation for exploring the key molecular of brain inflammaging.

Aims: Integrating bioinformatics and experimental validation to explore the mechanisms of inflammaging in the Brain. Method: After dividing the GSE11882 dataset into aged and young groups, we identified co-expressed differentially expressed genes (DEGs) in different brain regions. Enrichment analysis revealed that the co-expressed DEGs were mainly associated with inflammatory responses. Subsequently, we identified 12 DEGs that were related to the inflammatory response and used the DGIdb website for drug prediction. By using both the least absolute shrinkage and selection operator (LASSO) and random forest (RF), four biomarkers were screened and an artificial neural network (ANN) was developed for diagnosis. Subsequently, the biomarkers were validated through animal studies. Then we utilized AgeAnno to investigate the roles of biomarkers at the single cell level. Next, a consensus clustering approach was used to classify the aging samples and perform differential analysis to identify inflammatory response-related genes. After conducting a weighted gene co-expression network analysis (WGCNA), we identified the genes that are correlated with both four brain regions and aging. Wayne diagrams were used to identify seven inflammaging-related genes in different brain regions. Finally, we performed immuno-infiltration analysis and identified macrophage module genes. Key findings: Inflammaging may be a major mechanism of brain aging, and the regulation of macrophages by CX3CL1 may play a role in the development of inflammaging. Significance: In summary, targeting CX3CL1 can potentially delay inflammaging and immunosenescence in the brain.

Discovery of grey matter lesion-related immune genes for diagnostic prediction in multiple sclerosis.

Background: Multiple sclerosis (MS) is a chronic debilitating disease characterized by inflammatory demyelination of the central nervous system. Grey matter (GM) lesions have been shown to be closely related to MS motor deficits and cognitive impairment. In this study, GM lesion-related genes for diagnosis and immune status in MS were investigated. Methods: Gene Expression Omnibus (GEO) databases were utilized to analyze RNA-seq data for GM lesions in MS. Differentially expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) algorithm and protein-protein interaction (PPI) network were used to screen related gene modules and candidate genes. The abundance of immune cell infiltration was analyzed by the CIBERSORT algorithm. Candidate genes with strong correlation with immune cell types were determined to be hub genes. A diagnosis model of nomogram was constructed based on the hub genes. Gene set enrichment analysis (GSEA) was performed to identify the biological functions of hub genes. Finally, an MS mouse model was induced to verify the expression levels of immune hub genes. Results: Nine genes were identified by WGCNA, LASSO regression and PPI network. The infiltration of immune cells was significantly different between the MS and control groups. Four genes were identified as GM lesion-related hub genes. A reliable prediction model was established by nomogram and verified by calibration, decision curve analysis and receiver operating characteristic curves. GSEA indicated that the hub genes were mainly enriched in cell adhesion molecules, cytokine-cytokine receptor interaction and the JAK-STAT signaling pathway, etc. Conclusions: TLR9, CCL5, CXCL8 and PDGFRB were identified as potential biomarkers for GM injury in MS. The effectively predicted diagnosis model will provide guidance for therapeutic intervention of MS.

Integrating RNA-seq and scRNA-seq to explore the mechanism of macrophage ferroptosis associated with COPD.

Aims: Our study focused on whether macrophages ferroptosis is associated with the pathogenesis of chronic obstructive pulmonary disease (COPD) or not. Main methods: We first identified macrophage module genes by weighted gene co-expression network analysis (WGCNA) in RNA sequencing (RNA-seq) date from COPD, and then identified macrophage marker genes by comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from COPD macrophages. There were 126 macrophage marker genes identified, and functional enrichment analyses indicated that ferroptosis pathway genes were significantly enriched. Secondly, we identified eight macrophage ferroptosis related genes and based on these eight genes, we performed co-expression analysis and drug prediction. Thirdly, two biomarkers (SOCS1 and HSPB1) were screened by the least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine-recursive feature elimination (SVM-RFE) and established an artificial neural network (ANN) for diagnosis. Subsequently, the biomarkers were validated in the dataset and validation set. These two biomarkers were then subjected to single gene-gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) analysis, and the ceRNA network was constructed. Finally, we carried out molecular validation with COPD models in vitro for cell counting kit-8 (CCK8) experiments, Western blot and quantitative real-time PCR (qRT-PCR) analysis and transmission electron microscopy (TEM). Key findings: This study revealed the vital role of macrophage ferroptosis in COPD, and novel biomarkers (SOCS1 and HSPB1) may be involved in the pathogenesis of COPD by regulating macrophage ferroptosis. Significance: Taken together, our results suggest that targeting SOCS1 and HSPB1 could treat COPD by inhibiting macrophage ferroptosis.

Applicability of a General Analytical Approach for Detection of Genetically Modified Organisms: Collaborative Trial.

BACKGROUND: With the commercialization of genetically modified organisms (GMOs) in the market, laboratories have undergone a significantly increased workload. A universal analytical approach was designed to achieve cost-efficient and high-throughput GMOs screening with high specificity and accuracy. The approach provides accurate qualification of authorized and unauthorized GMOs. OBJECTIVE: This article describes the assessment of this analytical approach developed to detect the majority of commercialized GMOs over the world. METHOD: Seven elements and three events were detected by qPCR in a single laboratory to detect 59 commercialized GMOs. Certificated reference materials and food/feed samples from the Chinese market were also evaluated for the specificity, conformity, and robustness of this approach and were challenged in the interlaboratory study. RESULTS: The results showed that elements and events selected can best detect GMO presence with good specificity and sensitivity. The results showed a concordance between 97.5 and 99.56% and the variance between 0.65 and 12.88%, which is in line with the minimum requirement of analytical methods of GMO testing. CONCLUSIONS: The approach validated here can be used to manipulate GMO presence in food and feed and showed the capacity to manipulate GMO trace in the trade and domestic agriculture market in China. HIGHLIGHTS: A universal analytical approach used to track GMO presence was evaluated for its specificity, sensitivity, and robustness.

Blue Native/SDS-PAGE and iTRAQ-Based Chloroplasts Proteomics Analysis of Nicotiana tabacum Leaves Infected with M Strain of Cucumber Mosaic Virus Reveals Several Proteins Involved in Chlorosis Symptoms.

Virus infection in plants involves necrosis, chlorosis, and mosaic. The M strain of cucumber mosaic virus (M-CMV) has six distinct symptoms: vein clearing, mosaic, chlorosis, partial green recovery, complete green recovery, and secondary mosaic. Chlorosis indicates the loss of chlorophyll which is highly abundant in plant leaves and plays essential roles in photosynthesis. Blue native/SDS-PAGE combined with mass spectrum was performed to detect the location of virus, and proteomic analysis of chloroplast isolated from virus-infected plants was performed to quantify the changes of individual proteins in order to gain a global view of the total chloroplast protein dynamics during the virus infection. Among the 438 proteins quantified, 33 showed a more than twofold change in abundance, of which 22 are involved in the light-dependent reactions and five in the Calvin cycle. The dynamic change of these proteins indicates that light-dependent reactions are down-accumulated, and the Calvin cycle was up-accumulated during virus infection. In addition to the proteins involved in photosynthesis, tubulin was up-accumulated in virus-infected plant, which might contribute to the autophagic process during plant infection. In conclusion, this extensive proteomic investigation on intact chloroplasts of virus-infected tobacco leaves provided some important novel information on chlorosis mechanisms induced by virus infection.

A temperature-tolerant multiplex elements and genes screening system for genetically modified organisms based on dual priming oligonucleotide primers and capillary electrophoresis.

High throughput screening systems are the preferred solution to meet the urgent requirement of increasing number of genetically modified organisms (GMOs). In this study, we have successfully developed a multiplex GMO element screening system with dual priming oligonucleotide (DPO) primers. This system can detect the cauliflower mosaic virus 35S (CaMV 35S), terminator of nopaline synthase gene (NOS), figwort mosaic virus 35S (FMV 35S) promoter, neomycin phosphotransferaseII (NPTII), Bt Cry 1Ab, phosphinothricin acetyltransferase genes (bar) and Streptomyces viridochromogenes (pat) simultaneously, which covers more than 90% of all authorized GMO species worldwide. This system exhibits a high tolerance to annealing temperatures, high specificity and a limit of detection equal to conventional PCR. A total of 214 samples from markets, national entry-exit agencies, the Institute for Reference Materials and Measurement (IRMM) and the American Oil Chemists' Society (AOCS) were also tested for applicability. This screening system is therefore suitable for GMO screening.

The detection of hydrogen peroxide involved in plant virus infection by fluorescence spectroscopy.

The production of reactive oxygen species (ROS) forms part of the defense reaction of plants against invading pathogens. ROS have multifaceted signaling functions in mediating the establishment of multiple responses. To verify whether hydrogen peroxide (H2 O2 ) contributes to plant virus infection and the development of induced symptoms, we used fluorescence to monitor the generation of H2 O2 and confocal laser scanning microscopy (CLSM) to investigate the subcellular distribution of H2 O2 in leaves. In this study, the M strain of Cucumber mosaic virus (M-CMV) induced heavy chlorotic symptoms in Nicotiana tabacum cv. white burley during systemic infection. Compared with mock-inoculated leaves, H2 O2 accumulation in inoculated leaves increased after inoculation, then decreased after 4 days. For systemically infected leaves that showed chlorotic symptoms, H2 O2 accumulation was always higher than in healthy leaves. Subcellular H2 O2 localization observed using CLSM showed that H2 O2 in inoculated leaves was generated mainly in the chloroplasts and cell wall, whereas in systemically infected leaves H2 O2 was generated mainly in the cytosol. The levels of coat protein in inoculated and systemically infected leaves might be associated with changes in the level of H2 O2 and symptom development. Further research is needed to elucidate the generation mechanism and the relationship between coat protein and oxidative stress during infection and symptom development. Copyright © 2016 John Wiley & Sons, Ltd.

Development and application of absolute quantitative detection by duplex chamber-based digital PCR of genetically modified maize events without pretreatment steps.

The possibility of the absolute quantitation of GMO events by digital PCR was recently reported. However, most absolute quantitation methods based on the digital PCR required pretreatment steps. Meanwhile, singleplex detection could not meet the demand of the absolute quantitation of GMO events that is based on the ratio of foreign fragments and reference genes. Thus, to promote the absolute quantitative detection of different GMO events by digital PCR, we developed a quantitative detection method based on duplex digital PCR without pretreatment. Moreover, we tested 7 GMO events in our study to evaluate the fitness of our method. The optimized combination of foreign and reference primers, limit of quantitation (LOQ), limit of detection (LOD) and specificity were validated. The results showed that the LOQ of our method for different GMO events was 0.5%, while the LOD is 0.1%. Additionally, we found that duplex digital PCR could achieve the detection results with lower RSD compared with singleplex digital PCR. In summary, the duplex digital PCR detection system is a simple and stable way to achieve the absolute quantitation of different GMO events. Moreover, the LOQ and LOD indicated that this method is suitable for the daily detection and quantitation of GMO events.

A highly sensitive and specific method for the screening detection of genetically modified organisms based on digital PCR without pretreatment.

Digital PCR has developed rapidly since it was first reported in the 1990 s. It was recently reported that an improved method facilitated the detection of genetically modified organisms (GMOs). However, to use this improved method, the samples must be pretreated, which could introduce inaccuracy into the results. In our study, we explored a pretreatment-free digital PCR detection method for the screening for GMOs. We chose the CaMV35s promoter and the NOS terminator as the templates in our assay. To determine the specificity of our method, 9 events of GMOs were collected, including MON810, MON863, TC1507, MIR604, MIR162, GA21, T25, NK603 and Bt176. Moreover, the sensitivity, intra-laboratory and inter-laboratory reproducibility of our detection method were assessed. The results showed that the limit of detection of our method was 0.1%, which was lower than the labeling threshold level of the EU. The specificity and stability among the 9 events were consistent, respectively. The intra-laboratory and inter-laboratory reproducibility were both good. Finally, the perfect fitness for the detection of eight double-blind samples indicated the good practicability of our method. In conclusion, the method in our study would allow more sensitive, specific and stable screening detection of the GMO content of international trading products.

Transcriptome analysis of Nicotiana tabacum infected by Cucumber mosaic virus during systemic symptom development.

Virus infection of plants may induce a variety of disease symptoms. However, little is known about the molecular mechanism of systemic symptom development in infected plants. Here we performed the first next-generation sequencing study to identify gene expression changes associated with disease development in tobacco plants (Nicotiana tabacum cv. Xanthi nc) induced by infection with the M strain of Cucumber mosaic virus (M-CMV). Analysis of the tobacco transcriptome by RNA-Seq identified 95,916 unigenes, 34,408 of which were new transcripts by database searches. Deep sequencing was subsequently used to compare the digital gene expression (DGE) profiles of the healthy plants with the infected plants at six sequential disease development stages, including vein clearing, mosaic, severe chlorosis, partial and complete recovery, and secondary mosaic. Thousands of differentially expressed genes were identified, and KEGG pathway analysis of these genes suggested that many biological processes, such as photosynthesis, pigment metabolism and plant-pathogen interaction, were involved in systemic symptom development. Our systematic analysis provides comprehensive transcriptomic information regarding systemic symptom development in virus-infected plants. This information will help further our understanding of the detailed mechanisms of plant responses to viral infection.