Unraveling the role of tissue colonized microbiome in ovarian cancer progression.

BACKGROUND: Ovarian cancer (OC) is found to be the third most common gynecologic malignancy over the world, having the highest mortality rate among such tumors. Emerging studies underscore the presence of microorganisms within tumor tissues, with certain pathogens intricately linked to disease onset and progression. Disruption of the microbiome frequently precipitates disturbances in host metabolic and immune pathways, thereby fostering the development of cancer. METHODS: In this study, we initiated the investigation by conducting microbial reannotation on the RNA sequencing data derived from ovarian cancer tissues. Subsequently, a comprehensive array of analyses on tissue microbes was executed. These analyses encompassed the assessment of intergroup variations in microbial diversity, differential microbiological analysis, exploration of the association between host gene expression and microbial abundance, as well as an enrichment analysis of functional pathways linked to host genes associated with microbes. RESULTS: The analysis results revealed that Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes were the main components at phylum level in ovarian tissue. Notably, the microbial composition of ovarian cancer tissue significantly diverged from that of normal ovarian tissue e, exhibiting markedly lower alpha diversity and distinct beta diversity. Besides, pathogenic microorganisms Achromobacter xylosoxidans and Enterobacter hormaechei were enriched in cancer tissue. Host genes associated with these pathogens were enriched in key pathways including "JAK-STAT signaling pathway", "Transcriptional misregulation in cancer", and "Th1 and Th2 cell differentiation", suggesting their role in ovarian cancer progression through microbial dysbiosis and immune response interaction. CONCLUSION: Abundance of pathogenic microorganisms in ovarian cancer tissue could modulate the expression of host genes, consequently impacting cancer-related signaling pathways and fostering cancer progression.

Molecular and Morphological Identification of Monilia yunnanensis Causing Brown Rot on Chinese Quince and Peach in Yunnan, China.

More than 30% of fruits of Chinese Quince (Chaenomeles speciosa) and peach (Prunus persica) showed circular, water-soaked and brown spots in July 2022 in Kunming, Yunnan, China. The center of these spots was covered by a large number of earthy brown and oblate sporogeneous mycelium containing conidiophore and conidia, which were one-celled, limoniform, hyaline (13.73 to 22.77 x 8.17 to 12.84 µm, n=50). By September 2022, almost 100% of fruits showed symptoms. Later, most of them fell or a few stiff, black and mummified fruits were left on the trees. Fungal isolates were isolated by single-spore technique on Potato Dextrose agar (PDA) from the diseased fruits, and incubated at room temperature (20-28 °C) in darkness for 14 days. The colony was gray, smooth at margins, 7.6-8.0 cm in diameter. To fullfill Koch's postulates, mycelial plugs of one representative isolate YHD611 from Chinese Quince and another YHD610 from peach were used to inoculate three wounded and three non-wounded surface-disinfected fruits of both hosts at room temperature (19-27 °C), respectively. Three wounded and three non-wounded fruits inoculated with sterile PDA plugs served as the control. The wounded peaches appeared water-soaked and had brown lesions after three days of inoculation, then completely decayed after nine days, while non-wounded fruits showed symptoms after five days. The wounded fruits of Chinese Quince developed similar symptoms after eight days of inoculation, and completely decayed after 13 days, while non-wounded fruits showed obvious symptoms after 15 days. In a subsequent study, isolate YHD611 was inoculated to peach while isolate YHD610 was inoculated to Chinese Quince to understand host specificity of the isolates. The results showed that when peaches were infected with YHD611, symptoms were observed on wounded fruits after three days while on non-wounded fruits after five days. When Chinese Quince was infected with YHD610, symptoms were observed on wounded fruits after 14 days while on non-wounded fruits after 21 days. Fungal isolates from symptomatic fruits were identical to the original isolates. There were no symptoms on the control fruits of both hosts. Molecular identification was confirmed based on the sequences of internal transcribed spacer (ITS, primers ITS1 and ITS4) and ß-tubulin (TUB2, primers Bt2a and Bt2b) genes (Niu et al. 2016). BLASTn analysis of the ITS (OQ15519and OQ155196) and TUB2 (OQ185202 and OQ185201) of YHD611 and YHD610 revealed a 100% sequence identity, respectively, to Monilia yunnanensis AH7-2 (KT735924.1 for ITS, KT736008.1 for TUB2). In the phylogenetic analyses based on ITS and TUB2 sequence data, the isolates YHD611 and YHD610 belonged to the M. yunnanensis clade. Based on morphological and molecular identification, both isolates were identified as M. yunnanensis, which was reported as the pathogen causing brown rot of plum, peach, apple and pear in Yunnan, China (Hu et al. 2011; Yin et al. 2015). To our knowledge, this is the first report of M. yunnanensis causing brown rot on the fruits of Chinese Quince in Yunnan, China. This study also reports that M. yunnanensis from Chinese Quince can infect peach, and the pathogen from peach can infect Chinese Quince. These findings suggest that M. yunnanensis can transfer from one host to another and causing serious economic losses in multiple fruit crops in Yunnan, China. References: Hu, M. J., et al. 2011. PLoS One. 6:e24990. Niu, C. W., et al. 2016. Mycosystema, 35(10):1. Yin, L. F., et al. 2015. Plant Dis. 99:1775.

eccDB: a comprehensive repository for eccDNA-mediated chromatin contacts in multi-species.

SUMMARY: We developed the eccDB database to integrate available resources for extrachromosomal circular DNA (eccDNA) data. eccDB is a comprehensive repository for storing, browsing, searching, and analyzing eccDNAs from multispecies. The database provides regulatory and epigenetic information on eccDNAs, with a focus on analyzing intrachromosomal and interchromosomal interactions to predict their transcriptional regulatory functions. Moreover, eccDB identifies eccDNAs from unknown DNA sequences and analyzes the functional and evolutionary relationships of eccDNAs among different species. Overall, eccDB offers web-based analytical tools and a comprehensive resource for biologists and clinicians to decipher the molecular regulatory mechanisms of eccDNAs. AVAILABILITY AND IMPLEMENTATION: eccDB is freely available at http://www.xiejjlab.bio/eccDB.

microbioTA: an atlas of the microbiome in multiple disease tissues of Homo sapiens and Mus musculus.

microbioTA (http://bio-annotation.cn/microbiota) was constructed to provide a comprehensive, user-friendly resource for the application of microbiome data from diseased tissues, helping users improve their general knowledge and deep understanding of tissue-derived microbes. Various microbes have been found to colonize cancer tissues and play important roles in cancer diagnoses and outcomes, with many studies focusing on developing better cancer-related microbiome data. However, there are currently no independent, comprehensive open resources cataloguing cancer-related microbiome data, which limits the exploration of the relationship between these microbes and cancer progression. Given this, we propose a new strategy to re-align the existing next-generation sequencing data to facilitate the mining of hidden sequence data describing the microbiome to maximize available resources. To this end, we collected 417 publicly available datasets from 25 human and 14 mouse tissues from the Gene Expression Omnibus database and use these to develop a novel pipeline to re-align microbiome sequences facilitating in-depth analyses designed to reveal the microbial profile of various cancer tissues and their healthy controls. microbioTA is a user-friendly online platform which allows users to browse, search, visualize, and download microbial abundance data from various tissues along with corresponding analysis results, aimimg at providing a reference for cancer-related microbiome research.