New insight into the microbiome, resistome, and mobilome on the dental waste water in the context of heavy metal environment.

Object: Hospital sewage have been associated with incorporation of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) into microbes, which is considered as a key indicator for the spread of antimicrobial resistance (AMR). The compositions of dental waste water (DWW) contain heavy metals, the evolution of AMR and its effects on the water environment in the context of heavy metal environment have not been seriously investigated. Thus, our major aims were to elucidate the evolution of AMR in DWW. Methods: DWW samples were collected from a major dental department. The presence of microbial communities, ARGs, and MGEs in untreated and treated (by filter membrane and ozone) samples were analyzed using metagenomics and bioinformatic methods. Results: DWW-associated resistomes included 1,208 types of ARGs, belonging to 29 antibiotic types/subtypes. The most abundant types/subtypes were ARGs of multidrug resistance and of antibiotics that were frequently used in the clinical practice. Pseudomonas putida, Pseudomonas aeruginosa, Chryseobacterium indologenes, Sphingomonas laterariae were the main bacteria which hosted these ARGs. Mobilomes in DWW consisted of 93 MGE subtypes which belonged to 8 MGE types. Transposases were the most frequently detected MGEs which formed networks of communications. For example, ISCrsp1 and tnpA.5/4/11 were the main transposases located in the central hubs of a network. These significant associations between ARGs and MGEs revealed the strong potential of ARGs transmission towards development of antimicrobial-resistant (AMR) bacteria. On the other hand, treatment of DWW using membranes and ozone was only effective in removing minor species of bacteria and types of ARGs and MGEs. Conclusion: DWW contained abundant ARGs, and MGEs, which contributed to the occurrence and spread of AMR bacteria. Consequently, DWW would seriously increase environmental health concerns which may be different but have been well-documented from hospital waste waters.

Metagenomic evidence for antibiotics-driven co-evolution of microbial community, resistome and mobilome in hospital sewage.

Overconsumption of antibiotics is an immediate cause for the emergence of antimicrobial resistance (AMR) and antibiotic resistant bacteria (ARB), though its environmental impact remains inadequately clarified. There is an urgent need to dissect the complex links underpinning the dynamic co-evolution of ARB and their resistome and mobilome in hospital sewage. Metagenomic and bioinformatic methods were employed to analyze the microbial community, resistome and mobilome in hospital sewage, in relation to data on clinical antibiotic use collected from a tertiary-care hospital. In this study, resistome (1,568 antibiotic resistance genes, ARGs, corresponding to 29 antibiotic types/subtypes) and mobilome (247 types of mobile genetic elements, MGEs) were identified. Networks connecting co-occurring ARGs with MGEs encompass 176 nodes and 578 edges, in which over 19 types of ARGs had significant correlations with MGEs. Prescribed dosage and time-dependent antibiotic consumption were associated with the abundance and distributions of ARGs, and conjugative transfer of ARGs via MGEs. Variation partitioning analyses show that effects of conjugative transfer were most likely the main contributors to transient propagation and persistence of AMR. We have presented the first evidence supporting idea that use of clinical antibiotics is a potent driving force for the development of co-evolving resistome and mobilome, which in turn supports the growth and evolution of ARB in hospital sewage. The use of clinical antibiotics calls for greater attention in antibiotic stewardship and management.

The Role of Fecal Fusobacterium nucleatum and pks+ Escherichia coli as Early Diagnostic Markers of Colorectal Cancer.

BACKGROUND: Accurate analysis of intestinal microbiota will facilitate establishment of an evaluating system for assessing colorectal cancer (CRC) risk and prognosis. This study evaluates the potential role of Fusobacterium nucleatum (F. nucleatum) and Escherichia coli with a pks gene (pks+ E. coli) in early CRC diagnosis. METHODS: We recruited 139 patients, including CRC (n = 60), colorectal adenomatous polyposis (CAP) (n = 37), and healthy individuals (n = 42) based on their colonoscopy examinations. We collected stool and serum samples from the participants and measured the relative abundance of F. nucleatum and pks+ E. coli in fecal samples by quantitative PCR. Receiver operating characteristic curve (ROC) analyses were used to analyze the diagnostic value of single or combined biomarkers. RESULTS: Fecal F. nucleatum and pks+ E. coli levels were higher in the CRC group in either the CAP group or healthy controls (P = 0.02; 0.01). There was no statistical difference in the distribution of F. nucleatum and pks+ E. coli in patients with different tumor sites (P > 0.05). The combination of F. nucleatum+pks+ E. coli+CEA+CA19-9+FOBT was chosen as the optimal panel in differentiating both CRC and CAP from the controls. The combination of F. nucleatum, pks+ E. coli, and FOBT improved diagnostic efficiency. However, there was difficulty in differentiating CRC from CAP. CONCLUSION: Our results suggested that combining bacterial markers with conventional tumor markers improves the diagnostic efficiency for noninvasive diagnosis of CRC.

Antimicrobial resistance bacteria and genes detected in hospital sewage provide valuable information in predicting clinical antimicrobial resistance.

Extensive use of antibiotics is significantly associated with development of antibiotic-resistant (AR) bacteria. However, their causal relationships have not been adequately investigated, especially in human population and hospitals. Our aims were to understand clinical AR through revealing co-occurrence patterns between antibiotic-resistant bacteria and genes (ARB and ARGs), and their association with antibiotic use, and to consider impact of ARB and ARGs on environmental and human health. Antibiotic usage was calculated based on the actual consumption in our target hospital. ARB was identified by culture. In isolates collected from hospital sewage, bacterial-specific DNA sequences and ARGs were determined using metagenomics. Our data revealed that the use of culture-based single-indicator-strain approaches only captured ARB in 16.17% of the infectious samples. On the other hand, 1573 bacterial species and 885 types of ARGs were detected in the sewage. Furthermore, hospital use of antibiotics influenced the resistance profiles, but the strength varied among bacteria. From our metagenomics analyses, ARGs for aminoglycosides were the most common, followed by sulfonamide, tetracycline, phenicol, macrolides, and quinolones, comprising 82.6% of all ARGs. Association analyses indicated that 519 pairs of ARGs were significantly correlated with ARB species (r > 0.8). The co-occurrence patterns of bacteria-ARGs mirrored the AR in the clinic. In conclusion, our systematic investigation further emphasized that antibiotic usage in hospital significantly influenced the abundance and types of ARB and ARGs in dose- and time-dependent manners which, in turn, mirrored clinical AR. In addition, our data provide novel information on development of certain ARB with multiple antibiotic resistance. These ARB and ARGs from sewage can also be disseminated into the environment and communities to create health problems. Therefore, it would be helpful to use such data to develop improved predictive risk model of AR, to enhance effective use of antibiotics, and to reduce environmental pollution.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer.

BACKGROUND: Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers. METHODS: A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies. RESULTS: Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71. CONCLUSION: MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

Gene Expression Analysis of Human Papillomavirus-Associated Colorectal Carcinoma.

PURPOSE: Human papillomavirus (HPV) antigens had been found in colorectal cancer (CRC) tissue, but little evidence demonstrates the association of HPV with oncogene mutations in CRC. We aim to elucidate the mutated genes that link HPV infection and CRC carcinogenesis. METHODS: Cancerous and adjacent noncancerous tissues were obtained from CRC patients. HPV antigen was measured by using the immunohistochemical (IHC) technique. The differentially expressed genes (DEGs) in HPV-positive and HPV-negative tumor tissues were measured by using TaqMan Array Plates. The target genes were validated with the qPCR method. RESULTS: 15 (31.9%) cases of CRC patients were observed to be HPV positive, in which HPV antigen was expressed in most tumor tissues rather than in adjacent noncancerous tissues. With TaqMan Array Plates analyses, we found that 39 differentially expressed genes (DEGs) were upregulated, while 17 DEGs were downregulated in HPV-positive CRC tissues compared with HPV-negative tissues. Four DEGs (MMP-7, MYC, WNT-5A, and AXIN2) were upregulated in tumor vs. normal tissues, or adenoma vs. normal tissue in TCGA, which was overlapped with our data. In the confirmation test, MMP-7, MYC, WNT-5A, and AXIN2 were upregulated in cancerous tissue compared with adjacent noncancerous tissue. MYC, WNT-5A, and AXIN2 were shown to be upregulated in HPV-positive CRC tissues when compared to HPV-negative tissues. CONCLUSION: HPV-encoding genome may integrate into the tumor genomes that involved in multiple signaling pathways. Further genomic and proteomic investigation is necessary for obtaining a more comprehensive knowledge of signaling pathways associated with the CRC carcinogenesis.