Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis

The transmembrane and cytosolic domains of equine herpesvirus type 1 glycoprotein D determine Golgi retention by regulating vesicle formation

Accumulating evidence underscores the pivotal role of envelope proteins in viral secondary envelopment. However, the intricate molecular mechanisms governing this phenomenon remain elusive. To shed light on these mechanisms, we investigated a Golgi-retained gD of EHV-1 (gDEHV-1), distinguishing it from its counterparts in Herpes Simplex Virus-1 (HSV-1) and Pseudorabies Virus (PRV). To unravel the specific sequences responsible for the Golgi retention phenotype, we employed a gene truncation and replacement strategy. The results suggested that Golgi retention signals in gDEHV-1 exhibiting a multi-domain character. The extracellular domain of gDEHV-1 was identified as an endoplasmic reticulum (ER)-resident domain, the transmembrane domain and cytoplasmic tail (TM-CT) of gDEHV-1 were integral in facilitating the protein's residence within the Golgi complex. Deletion or replacement of either of these dual domains consistently resulted in the mutant gDEHV-1 being retained in an ER-like structure. Moreover, (TM-CT)EHV-1 demonstrated a preference for binding to endomembranes, inducing the generation of a substantial number of vesicles, potentially originate from the Golgi complex or the ER-Golgi intermediate compartment. In conclusion, our findings provide insights into the intricate molecular mechanisms governing the Golgi retention of gDEHV-1, facilitating the comprehension of the processes underlying viral secondary envelopment.

Relative Frequency of Blood-Borne Viruses in Hemodialysis-Dependent and Kidney Transplant Recipients in Iran

Background:

Hemodialysis (HD) patients and kidney transplant (KT) recipients are exposed to be infected by blood-borne viruses (BBVs). Current study was conducted to evaluate the prevalence of BBVs in HD and KT patients in the whole Iranian population.

Methods:

From Jan 2016 to Dec 2017, 174 hemodialysis and 139 kidney transplant recipients enrolled in this survey. After blood sampling, serum samples were detected for HBV, HCV, HCMV, HIV and HTLV antibodies. Seropositive samples confirmed by Polymerase chain reaction (PCR) method.

Results:

Overall, 6 (3.44%) and 3 (2.15%) of hemodialysis-dependent and transplantation patients had evidence of HCV infection, whereas no patients were HIV and HBV positive, two cases (1.14%) of hemodialysis and one case (0.71%) of transplantation patients demonstrated the HTLV-1 infection. 52 (37.4%) of patients received graft were positive for HCMV antibody. In addition, our study showed a co-infection of HCMV with HCV (3 patients, 2.15%) in transplantation patients.

Conclusion:

Prevalence of BBVs infection was lower in comparison to the previous studies. The current strict infection control practices in Iran appear to be effective in limiting dialysis and related infections after transplantation. Because BBVs infections constantly occur especially in dialysis and after transplantation units, our data will be useful to build a new strategic plan for the elimination of BBVs infection in kidney therapycenters.

Network meta-analysis correlates with analysis of merged independent transcriptome expression data

Background

Using meta-analysis, high-dimensional transcriptome expression data from public repositories can be merged to make group comparisons that have not been considered in the original studies. Merging of high-dimensional expression data can, however, implicate batch effects that are sometimes difficult to be removed. Removing batch effects becomes even more difficult when expression data was taken using different technologies in the individual studies (e.g. merging of microarray and RNA-seq data). Network meta-analysis has so far not been considered to make indirect comparisons in transcriptome expression data, when data merging appears to yield biased results.

Results

We demonstrate in a simulation study that the results from analyzing merged data sets and the results from network meta-analysis are highly correlated in simple study networks. In the case that an edge in the network is supported by multiple independent studies, network meta-analysis produces fold changes that are closer to the simulated ones than those obtained from analyzing merged data sets. Finally, we also demonstrate the practicability of network meta-analysis on a real-world data example from neuroinfection research.

Conclusions

Network meta-analysis is a useful means to make new inferences when combining multiple independent studies of molecular, high-throughput expression data. This method is especially advantageous when batch effects between studies are hard to get removed.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2705-9) contains supplementary material, which is available to authorized users.

Transcriptome analysis of peripheral blood mononuclear cells from chronic hepatitis B and hepatocellular carcinoma patients: a network-based attitude

Aim: The aim of the study was constructing a protein–protein interaction network for chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC) patients. Materials & methods: Comprehensive gene expression profile of peripheral blood mononuclear cells of CHB and HCC were obtained from Gene Expression Omnibus/NCBI database. Differentially expressed genes (DEGs) of samples were analyzed using GEO2R web application. Results: The majority of DEGs in both CHB and HCC has been enriched in immune system responses. However, there was a significant disparity between the enrichment of these genes (especially genes associated with Toll-like receptor-and-TNF) in CHB-HCC compared with normal-CHB. Conclusion: The transcriptome properties of peripheral blood mononuclear cells are changed in patients with HBV-HCC. The immune response genes are the most deregulated genes in HCC patients.

[Formula: see text]