Municipal wastewater treatment plants (WWTPs) serve as global repositories for diverse and dynamic microbial communities, reflecting the complex interplay of human activities, environmental conditions, and public health challenges. Despite their importance, a comprehensive understanding of the global distribution, composition, and functional roles of these microbial ecosystems has remained elusive. Here, we present a comprehensive analysis of bacterial and viral diversities in global wastewater systems by examining 575 sampling sites across 74 cities in 60 countries. Through metagenomic analysis, we reconstructed 12,758 non-redundant bacterial metagenome-assembled genomes (MAGs) spanning 70 phyla, with 4,499 MAGs representing novel species. Despite considerable regional variation, we identified a consistent core microbiome present across 70% of global samples predominantly comprising Proteobacteria. We further assembled 1.7 million viral genomes, revealing unprecedented viral diversity with over 1.5 million species-level viral operational taxonomic units (vOTUs). Network analysis demonstrated that transport proteins play crucial roles in maintaining WWTP functional resilience against disturbances. Machine learning approaches effectively predicted continental origins of wastewater samples based on microbial signatures, confirming that microbial communities reflect local environmental and socioeconomic conditions while maintaining functional conservation. We observed significant variation in the antibiotic resistance gene (ARG) distribution, with elevated prevalence in certain African and Asian regions compared to Europe and North America. Our results establish wastewater microbiomes as important indicators of human activity and provide critical insights for advancing environmental monitoring, antimicrobial resistance surveillance, and wastewater-based epidemiology. IMPORTANCE: Intensifying urbanization and human activities have dramatically increased global wastewater generation, creating complex microbial ecosystems that significantly impact environmental and public health. This study presents the first large-scale, comprehensive characterization of bacterial and viral communities in wastewater treatment systems worldwide. By analyzing samples from diverse geographical, climatic, and socioeconomic contexts, we reveal how wastewater microbiomes serve as microbial fingerprints of human society, reflecting regional characteristics while maintaining functional conservation. Our findings demonstrate that these communities function as ecological extensions of human gut microbiota in the external environment, with important implications for the spread of antibiotic resistance and pathogens. The identification of viruses as key metabolic regulators in these systems provides new perspectives on microbial community dynamics. This global-scale analysis advances our understanding of wastewater microbiology and offers valuable insights for improving wastewater management, enhancing environmental monitoring systems, and strengthening public health surveillance through wastewater-based epidemiology.

Acute rejection (AR) after kidney transplantation, is a common and serious complication that occurs when the recipient’s immune system attacks the graft, and the specific genes and molecular mechanisms underlying the role of mitophagy are still unclear. This study integrated two transcriptomic datasets (GSE129166 and GSE25902) from the GEO database. Thirty differential mitophagy-related genes were identified by intersecting differentially expressed genes, module genes obtained through weighted gene co-expression network analysis and mitophagy-related genes. Functional enrichment analysis uncovered several biological processes and signaling pathways associated with these genes. Four candidate genes including CCND1, ZC3H15, RPL38, and ARPC4, were further identified through Random Forest and Support Vector Machine with recursive feature elimination. Internal, external datasets and a nomogram confirmed they could effectively predict AR. Moreover, these genes significantly correlated with the infiltration of multiple immune cells. Differential expressions of the four genes were also validated in patient’s peripheral blood and AR mice. These four mitophagy-related genes may be novel biomarkers for predicting the occurrence and diagnosis of AR.

In the process of oxygen reduction, reactive oxygen species (ROS) are generated as intermediates, including superoxide anion (O ²⁻ ), hydrogen peroxide (H ₂ O ₂ ), and hydroxyl radicals (OH ⁻ ). ROS can be destructive, and an imbalance between oxidants and antioxidants in the body can lead to pathological inflammation. Inappropriate ROS production can cause oxidative damage, disrupting the balance in the body and potentially leading to DNA damage in intestinal epithelial cells and beneficial bacteria. Microorganisms have evolved various enzymes to mitigate the harmful effects of ROS. Accurately predicting the types of ROS-scavenging enzymes (ROSes) is crucial for understanding the oxidative stress mechanisms and formulating strategies to combat diseases related to the “gut–organ axis.” Currently, there are no available ROSes databases (DBs). In this study, we propose a systematic workflow comprising three modules and employ a hierarchical multi-task deep learning approach to collect, expand, and explore ROSes-related entries. Based on this, we have developed the human gut microbiota ROSes DB ( http://39.101.72.186/ ), which includes 7,689 entries. This DB provides user-friendly browsing and search features to support various applications. With the assistance of ROSes DB, various communication-based microbial interactions can be explored, further enabling the construction and analysis of the evolutionary and complex networks of ROSes DB in human gut microbiota species. IMPORTANCE: Reactive oxygen species (ROS) is generated during the process of oxygen reduction, including superoxide anion, hydrogen peroxide, and hydroxyl radicals. ROS can potentially cause damage to cells and DNA, leading to pathological inflammation within the body. Microorganisms have evolved various enzymes to mitigate the harmful effects of ROS, thereby maintaining a balance of microorganisms within the host. The study highlights the current absence of a ROSes DB, emphasizing the crucial importance of accurately predicting the types of ROSes for understanding oxidative stress mechanisms and developing strategies for diseases related to the “gut–organ axis.” This research proposes a systematic workflow and employs a multi-task deep learning approach to establish the human gut microbiota ROSes DB. This DB comprises 7,689 entries and serves as a valuable tool for researchers to delve into the role of ROSes in the human gut microbiota.

A 65-year-old man presented with a giant ulcerative and malodorous genital mass rapidly growing for 5 months. On first presentation, he noticed a 3 cm × 2 cm cauliflower-like mass located in the penile dorsal shaft. But, he rejected any operation. Unfortunately, the lesion became aggressive and eventually destroyed the entire penile shaft and urethra within a five-month period. He underwent a radical penectomy, scrotal extended resection, formation of a perineal urethrostomy and left inguinal lymph node biopsy. Pathology revealed poor-differentiated invasive squamous cell carcinoma. The patient had an uneventful recovery.