Substantial viral diversity in bats and rodents from East Africa: insights into evolution, recombination, and cocirculation.

BACKGROUND: Zoonotic viruses cause substantial public health and socioeconomic problems worldwide. Understanding how viruses evolve and spread within and among wildlife species is a critical step when aiming for proactive identification of viral threats to prevent future pandemics. Despite the many proposed factors influencing viral diversity, the genomic diversity and structure of viral communities in East Africa are largely unknown. RESULTS: Using 38.3 Tb of metatranscriptomic data obtained via ultradeep sequencing, we screened vertebrate-associated viromes from 844 bats and 250 rodents from Kenya and Uganda collected from the wild. The 251 vertebrate-associated viral genomes of bats (212) and rodents (39) revealed the vast diversity, host-related variability, and high geographic specificity of viruses in East Africa. Among the surveyed viral families, Coronaviridae and Circoviridae showed low host specificity, high conservation of replication-associated proteins, high divergence among viral entry proteins, and frequent recombination. Despite major dispersal limitations, recurrent mutations, cocirculation, and occasional gene flow contribute to the high local diversity of viral genomes. CONCLUSIONS: The present study not only shows the landscape of bat and rodent viromes in this zoonotic hotspot but also reveals genomic signatures driven by the evolution and dispersal of the viral community, laying solid groundwork for future proactive surveillance of emerging zoonotic pathogens in wildlife. Video Abstract.

Metagenomic analysis of individual mosquito viromes reveals the geographical patterns and drivers of viral diversity.

Mosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Here, using a meta-transcriptomic approach, we determined the viromes of 2,438 individual mosquitoes (81 species), spanning ~4,000 km along latitudes and longitudes in China. From these data we identified 393 viral species associated with mosquitoes, including 7 (putative) species of arthropod-borne viruses (that is, arboviruses). We identified potential mosquito species and geographic hotspots of viral diversity and arbovirus occurrence, and demonstrated that the composition of individual mosquito viromes was strongly associated with host phylogeny. Our data revealed a large number of viruses shared among mosquito species or genera, enhancing our understanding of the host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, perhaps reflecting long-distance mosquito dispersal. Together, these results greatly expand the known mosquito virome, linked viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the biogeography and diversity of viruses in insect vectors.

LINC01559 promotes lung adenocarcinoma metastasis by disrupting the ubiquitination of vimentin.

BACKGROUND: Distant metastasis is the major cause of lung adenocarcinoma (LUAD)-associated mortality. However, molecular mechanisms involved in LUAD metastasis remain to be fully understood. While the role of long non-coding RNAs (lncRNAs) in cancer development, progression, and treatment resistance is being increasingly appreciated, the list of dysregulated lncRNAs that contribute to LUAD pathogenesis is also rapidly expanding. METHODS: Bioinformatics analysis was conducted to interrogate publicly available LUAD datasets. In situ hybridization and qRT-PCR assays were used to test lncRNA expression in human LUAD tissues and cell lines, respectively. Wound healing as well as transwell migration and invasion assays were employed to examine LUAD cell migration and invasion in vitro. LUAD metastasis was examined using mouse models in vivo. RNA pulldown and RNA immunoprecipitation were carried out to test RNA-protein associations. Cycloheximide-chase assays were performed to monitor protein turnover rates and Western blotting was employed to test protein expression. RESULTS: The expression of the lncRNA LINC01559 was commonly upregulated in LUADs, in particular, in those with distant metastasis. High LINC01559 expression was associated with poor outcome of LUAD patients and was potentially an independent prognostic factor. Knockdown of LINC01559 diminished the potential of LUAD cell migration and invasion in vitro and reduced the formation of LUAD metastatic lesions in vivo. Mechanistically, LINC01559 binds to vimentin and prevents its ubiquitination and proteasomal degradation, leading to promotion of LUAD cell migration, invasion, and metastasis. CONCLUSION: LINC01559 plays an important role in LUAD metastasis through stabilizing vimentin. The expression of LINC01559 is potentially an independent prognostic factor of LUAD patients, and LINC01559 targeting may represent a novel avenue for the treatment of late-stage LUAD.

Association of COVID-19 and Lung Cancer: Short-Term and Long-Term Interactions.

Background: COVID-19 has been ravaging the globe for more than three years. Due to systemic immunosuppression of anti-tumor therapy, application of chemotherapy and adverse effects of surgery, the short- and long-term prognosis of cancer patients to COVID-19 are of significant concern. Method: This research included three parts of data. The first part of the data came from the public database that covered Veneto residents. The second part of the data included participants in Guangzhou. The third part of the data was used for MR analysis. We assessed the associations by logistic, linear or Cox regression when appropriate. Result: Lung cancer patients with COVID-19 had shorter progression-free survival (PFS) after COVID-19 (Model II: HR: 3.28, 95% CI: 1.6~6.72; Model III: HR: 3.39, 95% CI: 1.45~7.95), compared with lung cancer patients without COVID-19. Targeted therapy patients recovered from SARS-CoV-2 infection more quickly (Model I: ß: -0.58, 95% CI: -0.75~-0.41; Model II: ß: -0.59, 95% CI: -0.76~-0.41; Model III: ß: -0.57; 95% CI: -0.75~-0.40). Conclusions: PFS in lung cancer patients is shortened by COVID-19. The outcome of COVID-19 in lung cancer patients was not significantly different from that of the healthy population. In lung cancer patients, targeted therapy patients had a better outcome of COVID-19, while chemotherapy patients had the worst.

SNHG3/WISP2 Axis Promotes Hela Cell Migration and Invasion via Activating Wnt/ß-Catenin Signaling.

BACKGROUND/AIM: Cervical cancer (CC) poses a significant threat to women's health and has a relatively poor prognosis due to local invasion and metastasis. It is, therefore, crucial to elucidate the molecular mechanisms of CC metastasis. SNHG3 has been implicated in various tumor metastasis processes, but its involvement in CC has not been thoroughly studied. Our study aimed to investigate the role of SNHG3 in metastasis and elucidate its underlying mechanisms in CC. MATERIALS AND METHODS: LncRNA SNHG3 expression in CC tissues was analyzed using TCGA and GSE27469 databases. Normal cervical epithelial cells and CC cell lines were used to detect mRNA expression of SNHG3 via quantitative reverse transcription polymerase chain reaction (qRT-PCR). With RNA interference (RNAi) technology, antisense oligonucleotides (ASO) can act on HeLa cells to knockdown target gene expression. The influence of SNHG3 on cell migration and invasion were determined by wound healing and transwell assays. Transcriptome sequencing (RNA-seq) was used to seek abnormally expressed genes between SNHG3 knockdown cells and control cells. The expressions of epithelial-mesenchymal transition (EMT) and Wnt/ß-catenin signaling related proteins were detected using western blot. RESULTS: SNHG3 was obviously up-regulated in CC tissues and cell lines, and ectopic expression of SNHG3 was associated with lymph node metastasis of CC. Knockdown of SNHG3 significantly inhibited cell migration and invasion in CC. Further molecular mechanism studies showed that SNHG3 knockdown could down-regulate the expression of WNT1 Inducible Signaling Pathway Protein 2 (WISP2) so as to inhibit the activation of the Wnt/ß-catenin signaling pathway, and regulated the expression of EMT-related markers, that promoted the protein expression of E-cadherin, as well as decreased the expression of N-cadherin and vimentin. CONCLUSION: SNHG3 appears to exert a pro-metastatic effect in CC, as evidenced by inhibition of cell migration and invasion upon SNHG3 knockdown. EMT also appears to be attenuated. Of interest is the down-regulation of WISP2 following SNHG3 knockdown leads to the inactivation of the Wnt/ß-catenin signaling pathway.

Metagenomic analysis of individual mosquitos reveals the ecology of insect viruses.

Mosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Using a meta-transcriptomic approach, we analysed the virome of 2,438 individual mosquitos (79 species), spanning ~4000 km along latitudes and longitudes in China. From these data we identified 393 core viral species associated with mosquitos, including seven (putative) arbovirus species. We identified potential species and geographic hotspots of viral richness and arbovirus occurrence, and demonstrated that host phylogeny had a strong impact on the composition of individual mosquito viromes. Our data revealed a large number of viruses shared among mosquito species or genera, expanding our knowledge of host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, possibly facilitated by long-distance mosquito migrations. Together, our results greatly expand the known mosquito virome, linked the viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the ecology of viruses of insect vectors.

DeepLRR: An Online Webserver for Leucine-Rich-Repeat Containing Protein Characterization Based on Deep Learning.

Members of the leucine-rich repeat (LRR) superfamily play critical roles in multiple biological processes. As the LRR unit sequence is highly variable, accurately predicting the number and location of LRR units in proteins is a highly challenging task in the field of bioinformatics. Existing methods still need to be improved, especially when it comes to similarity-based methods. We introduce our DeepLRR method based on a convolutional neural network (CNN) model and LRR features to predict the number and location of LRR units in proteins. We compared DeepLRR with six existing methods using a dataset containing 572 LRR proteins and it outperformed all of them when it comes to overall F1 score. In addition, DeepLRR has integrated identifying plant disease-resistance proteins (NLR, LRR-RLK, LRR-RLP) and non-canonical domains. With DeepLRR, 223, 191 and 183 LRR-RLK genes in Arabidopsis (Arabidopsis thaliana), rice (Oryza sativa ssp. Japonica) and tomato (Solanum lycopersicum) genomes were re-annotated, respectively. Chromosome mapping and gene cluster analysis revealed that 24.2% (54/223), 29.8% (57/191) and 16.9% (31/183) of LRR-RLK genes formed gene cluster structures in Arabidopsis, rice and tomato, respectively. Finally, we explored the evolutionary relationship and domain composition of LRR-RLK genes in each plant and distributions of known receptor and co-receptor pairs. This provides a new perspective for the identification of potential receptors and co-receptors.