Convincing studies demonstrated that vaginal flora is one of the most impactful key components for the well-being of the genital tract in women. Nevertheless, the potential capability of vaginal-derived bacterial communities as biomarkers to monitor cervical carcinogenesis (CC) has yet to be studied actively compared to those of bacterial vaginosis (BV). We hypothesized that vaginal microbiota might be associated with the progression of CC. In this study, we enrolled 23 participants, including healthy controls (HC group; n = 7), patients with cervical intraepithelial neoplasia (CIN) 2 and 3 (CIN group, n = 8), and patients with invasive cervical cancer (CAN group; n = 8). Amplicon sequencing was performed using the Ion Torrent PGM to characterize the vaginal microbiota. Patients with CIN and CAN presented vaginal microbiota dysbiosis compared with HC. The alpha diversity analysis revealed that CC has a trend to be increased in terms of diversity indexes. Moreover, CC was associated with the abundance of specific microbes, of which Lactobacillus and Gardnerella were the most significantly different between HC and CIN, whereas Streptococcus was differentially abundant in CAN compared with CIN. We then evaluated their diagnostic abilities. Testing in terms of diagnostic ability using the three genera revealed considerably high performance with an area under the receiver-operating characteristic curve of 0.982, 0.953, and 0.922. The current study suggests that the presence of Gardnerella and Streptococcus may be involved in the advancment of CC.

The fecal microbiota is being increasingly implicated in the diagnosis of various diseases. However, evidence on changes in the fecal microbiota in invasive cervical cancer (ICC) remains scarce. Here, we aimed to investigate the fecal microbiota of our cohorts, develop a diagnostic model for predicting early ICC, and identify potential fecal microbiota-derived biomarkers using amplicon sequencing data. We obtained fecal samples from 29 healthy women (HC) and 17 women with clinically confirmed early ICC (CAN). Although Shannon’s diversity index was not reached at statistical significance, the Chao1 and Observed operational taxonomic units (OTUs) in fecal microbiota was significantly different between CAN and HC group. Furthermore, there were significant differences in the taxonomic profiles between HC and CAN; Prevotella was significantly more abundant in the CAN group and Clostridium in the HC group. Linear discriminant analysis effect size (LEfSe) analysis was applied to validate the taxonomic differences at the genus level. Furthermore, we identified a set of seven bacterial genera that were used to construct a machine learning (ML)-based classifier model to distinguish CAN from patients with HC. The model had high diagnostic utility (area under the curve [AUC] = 0.913) for predicting early ICC. Our study provides an initial step toward exploring the fecal microbiota and helps clinicians diagnose.

Although emerging evidence revealed that the gut microbiome served as a tool and as biomarkers for predicting and detecting specific cancer or illness, it is yet unknown if vaginal microbiome-derived bacterial markers can be used as a predictive model to predict the severity of CIN. In this study, we sequenced V3 region of 16S rRNA gene on vaginal swab samples from 66 participants (24 CIN 1−, 42 CIN 2+ patients) and investigated the taxonomic composition. The vaginal microbial diversity was not significantly different between the CIN 1− and CIN 2+ groups. However, we observed Lactobacillus amylovorus dominant type (16.7%), which does not belong to conventional community state type (CST). Moreover, a minimal set of 33 bacterial species was identified to maximally differentiate CIN 2+ from CIN 1− in a random forest model, which can distinguish CIN 2+ from CIN 1− (area under the curve (AUC) = 0.952). Among the 33 bacterial species, Lactobacillus iners was selected as the most impactful predictor in our model. This finding suggests that the random forest model is able to predict the severity of CIN and vaginal microbiome may play a role as biomarker.

Peach gummosis disease has been identified as a serious challenge in Korean agriculture and has developed to become a major cause of agricultural productivity losses. However, treatments for gummosis have not been systemically established and studies of the microbiome closely related to this plant disease are lacking. Therefore, we analyzed the bacterial and fungal communities in the bark and rhizosphere soil of healthy peach trees and those with gummosis. Through high-throughput sequencing, we obtained unprecedented insights into the bacterial and fungal dynamics of each group, including their diversity and taxonomic classification, as well as network analyses. We found that the presence of gummosis drives a significantly higher alpha diversity in the bark bacterial community. Peach gummosis bark mycobiomes included greater numbers of opportunistic pathogens such as Ascochyta, Botryosphaeria, Saccharomyces, Nectriaceae_NA, Trametes, and Valsaceae_NA. However, the microbiome also included bacteria beneficial to plant growth and the production of polysaccharides—namely, 1174-901-12, Catenibacterium, Cutibacterium, Friedmanniella, Methylobacterium-Methylorubrum, Pseudomonas, Rhodobacter, and Sphingomonas. Furthermore, we confirmed that gummosis induced a more complex structure in the bark microbiome network. We conclude that the findings of this study provide a valuable aid in profiling the overall peach tree microbial ecosystem, which can be utilized to develop precise biomarkers for the early diagnosis of gummosis.

Skin aging involves biomechanical changes like decreased elasticity, increased wrinkle formation, and altered barrier function. The skin microbiome significantly impacts this process. Here, we investigated the effects of decreased Cutibacterium acnes abundance and increase in other skin microorganisms on skin biomechanical properties in 60 healthy Koreans from Seoul, divided into younger (20–29 years) and older (60–75 years) groups. Metagenomic sequencing and skin assessments showed that the older group exhibited decreased C. acnes dominance and increased microbial diversity, correlating with reduced skin elasticity and increased wrinkles. In the younger age group, the enriched pathways included zeatin biosynthesis, distinct biotin metabolism pathways, and cofactor and vitamin metabolism in the younger age group, whereas pathways related to lipid metabolism, energy metabolism, and responses to environmental stressors, including UV damage and pollution, were enriched in the older group, according to functional analysis results. Network analysis indicated higher microbial connectivity in the younger group, suggesting a more stable community, whereas the older group’s community displayed higher modularity, indicating more independent and specialized clusters. This study enhances our understanding of the impact of skin microbiome changes on skin aging, particularly the anti-aging effects of C. acnes. Future research should focus on the physiological mechanisms of skin microbiota on skin aging and explore therapeutic potentials to enhance skin health.

Livestock odors are unavoidable problems in modern industrial society. We foresaw a role for fermented organic wastes in controlling odorous gases. In this study, we applied fermented coffee grounds to the floor area of a dairy cow barn and assessed alterations in odor compounds and a microbial shift over a period of three weeks. The treatment dramatically reduced ten odor compounds (more than 50%), highlighting the utility of fermented coffee grounds as an excellent product to reduce odors derived from cow manure. By the end of the treatment, the microbial consortium showed increases in rare families whose prevalence and abundance before the treatment had been low. Network analysis manifested 23 bacterial families dominant in fermented coffee grounds, negatively connected with odorous compounds, indicating potential odor-reducing bacterial families. This study provides an insight into using bacteria at the community level as a treatment to solve an environmental issue; simultaneously, it suggests proper usage of organic wastes by recycling them as fermenters for beneficial bacteria.