Integrative metagenomic dissection of last-resort antibiotic resistance genes and mobile genetic elements in hospital wastewaters.

Hospital wastewater is a critical source of antimicrobial resistance (AMR), which facilitates the proliferation and spread of clinically significant antimicrobial resistance genes (ARGs) and pathogenic bacteria. This study utilized metagenomic approaches, including advanced binning techniques, such as MetaBAT2, MaxBin2, and CONCOCT, which offer significant improvements in accuracy and completeness over traditional binning methods. These methods were used to comprehensively assess the dynamics and composition of resistomes and mobilomes in untreated wastewater samples taken from two general hospitals and one cancer hospital. This study revealed a diverse bacterial landscape, largely consisting of Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria, with notable variations in microbial composition among hospitals. Analysis of the top 15 genera showed unique microbial pattern distribution in each hospital: Aeromonas was predominant in 1stHWTS (49.39 %), Acidovorax in the CAHWTS at 16.85 %, and Escherichia and Bacteroides in the 2ndHWTS at 11.44 % and 11.33 %, respectively. A total of 114 pathogenic bacteria were identified, with drug-resistant Aeromonas caviae and Escherichia coli being the most prevalent. The study identified 34 types and 1660 subtypes of ARGs, including important last-resort antibiotic resistance genes (LARGs), such as blaNDM, mcr, and tet(X). Using metagenomic binning, this study uncovered distinct patterns of host-resistance associations, particularly with Proteobacteria and Firmicutes. Network analysis highlighted the complex interactions among ARGs, mobile genetic elements (MGEs), and bacterial species, all contributing to the dissemination of AMR. These findings emphasize the intricate nature of AMR in hospital wastewater and the influence of hospital-specific factors on microbial resistance patterns. This study provides support for implementing integrated management strategies, including robust surveillance, advanced wastewater treatment, and strict antibiotic stewardship, to control the dissemination of AMR. Understanding the interplay among bacterial communities, ARGs, and MGEs is important for developing effective public health measures against AMR.

Blue-Light Driven Iron-Catalyzed Oxy-phosphinylation of Activated Alkenes for ß-Ketophosphine Oxide Synthesis.

We have developed an original blue-light mediated iron-catalyzed oxy-phosphinylation of activated alkenes by secondary phosphine oxides under air at room temperature. Various ß-ketophosphine oxides were then obtained in 43-97 % isolated yields. Control experiments revealed that radical process is involved in the mechanism.

Characterization of antibiotic resistance genes and mobile elements in extended-spectrum ß-lactamase-producing Escherichia coli strains isolated from hospitalized patients in Guangdong, China.

AIM: This study aimed to investigate the high-resolution phenotypic and genotypic characterization of extended-spectrum ß-lactamase (ESBL)-producing Escherichia coli strains isolated from hospitalized patients to explore the resistance genes and mobile genetic elements (MGEs) involved in horizontal dissemination. METHODS: Between May and September 2021, a total of 216 ESBL-producing E. coli isolates were recovered from multiple departments. The identification of strains was performed using MALDI-TOF mass spectrometry and PCR, while antibiotic susceptibility testing was carried out using the Vitek 2 COMPACT system to determine resistance patterns, while PCR was used to detect different resistance genes and MGEs. In addition, a conjugation assay was performed to investigate the horizontal gene transfer of resistance genes. Selected isolates underwent whole-genome sequencing (WGS) using the Illumina MiSeq platform. RESULTS: A total of 216 out of 409 E. coli isolates recovered from a tertiary hospital were observed to be ESBL-producing, giving a carriage rate of 52.8%, as determined by phenotypic screening. The most frequent sources of ESBL-producing E. coli isolates were urine (129/216, 59.72%) and blood (50/216, 23.14%). The most prevalent ESBL genes identified were blaCTX-M (60.18%), blaTEM (40.27%), and blaSHV (18.05%). Three E. coli isolates were found to carry the genes blaNDM, mcr-1, and fosA3 genes. The most prevalent MGEs were IS26 (95.37%), Int (87.03%), and IncFIB (76.85%). WGS analysis of eight MDR E. coli strains revealed that these isolates belonged to eight different sequence types (STs) and serotypes and were found to harbor multiple plasmid replicons and virulence factors. CONCLUSION: This study highlights a high incidence of antibiotic resistance genes and MGEs associated with the dissemination of ESBLs and other resistance genes.

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.

Machine Learning Techniques for Antimicrobial Resistance Prediction of Pseudomonas Aeruginosa from Whole Genome Sequence Data.

Aim: Due to the growing availability of genomic datasets, machine learning models have shown impressive diagnostic potential in identifying emerging and reemerging pathogens. This study aims to use machine learning techniques to develop and compare a model for predicting bacterial resistance to a panel of 12 classes of antibiotics using whole genome sequence (WGS) data of Pseudomonas aeruginosa. Method: A machine learning technique called Random Forest (RF) and BioWeka was used for classification accuracy assessment and logistic regression (LR) for statistical analysis. Results: Our results show 44.66% of isolates were resistant to twelve antimicrobial agents and 55.33% were sensitive. The mean classification accuracy was obtained ≥98% for BioWeka and ≥96 for RF on these families of antimicrobials. Where ampicillin was 99.31% and 94.00%, amoxicillin was 99.02% and 95.21%, meropenem was 98.27% and 96.63%, cefepime was 99.73% and 98.34%, fosfomycin was 96.44% and 99.23%, ceftazidime was 98.63% and 94.31%, chloramphenicol was 98.71% and 96.00%, erythromycin was 95.76% and 97.63%, tetracycline was 99.27% and 98.25%, gentamycin was 98.00% and 97.30%, butirosin was 99.57% and 98.03%, and ciprofloxacin was 96.17% and 98.97% with 10-fold-cross validation. In addition, out of twelve, eight drugs have found no false-positive and false-negative bacterial strains. Conclusion: The ability to accurately detect antibiotic resistance could help clinicians make educated decisions about empiric therapy based on the local antibiotic resistance pattern. Moreover, infection prevention may have major consequences if such prescribing practices become widespread for human health.

Photodynamic therapy treats acne by altering the composition of the skin microbiota.

BACKGROUND: Acne is the eighth-most prevalent inflammatory skin disease with no optimal treatment. Photodynamic therapy (PDT) is an effective treatment for severe acne. AIMS: The effect of PDT on the composition and diversity of skin microflora in severe acne patients was studied. MATERIALS AND METHODS: A total of 18 patients with severe acne and 8 healthy individuals were selected for this study. Patients were treated with 5-aminolevulinic acid-mediated PDT once a week three times in total; the skin microbiome was measured by 16S ribosomal RNA gene sequencing before and after treatment (1 week after each PDT). RESULTS: The microflora composition was different between healthy controls and patients, and between patients before and after treatment. Alpha diversity indices were lower in patients than those in control. There were 15 bacterial genera with high relative abundance that had noticeable changes during treatment. At the genus level,particularly Cutibacterium acnes (C. acnes formerly Propionibacterium acnes), there was no statistically significant difference among different group. The abundances of Staphylococcus epidermidis and Staphylococcus aureus were low. DISCUSSION: The microbial composition is different between severe acne patients acne patients and healthy individuals. The therapeutic efficacy of severe acne treated with PDT is associated with the composition and diversity of skin microbiota. CONCLUSION: The skin microbial composition changes after PDT treatment. PDT is an effective method for the treatment of severe acne.

Exploring antibiotic resistance genes, mobile gene elements, and virulence gene factors in an urban freshwater samples using metagenomic analysis.

Antibiotic resistance genes (ARGs) and antimicrobial resistance elements (AMR) are novel environmental contaminants that pose a significant risk to human health globally. Freshwater contains a variety of microorganisms that might affect human health; its quality must be assessed before use. However, the dynamics of mobile genetic elements (MGEs) and ARG propagation in freshwater have rarely been studied in Singapore. Therefore, this study used metagenomics to compare diversity, virulence factor composition, and ARG and MGE co-occurrence with bacterial communities in paired (n = 8) environmental freshwater samples. KneadData, FMAP, and Kraken2 were used for bioinformatics analysis and R (v4.1.1) for statistical analysis. Sequence reads with a total of 9043 species were taxonomically classified into 66 phyla, 130 classes, 261 orders, 584 families, and 2477 genera. Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes were found the Phyla in all samples. Analysis of QIIME output by PICRUSt and ß-diversity showed unique clusters and functional microbial community structures. A total of 2961 ARGs were found that conferred resistance to multidrug, aminoglycosides, tetracyclines, elfamycins, and more. The classified ARG mechanism revealed significant distribution of virulence factors in bacterial cells. Transposes and transposon were highly correlated to ARG gene transfer. Co-occurrence network analysis showed several MGEs appear to use the same ARGs (intI and rho) and were dominant in all samples. Furthermore, ARGs are also highly correlated with bacteria like Campylobacter and Escherichia. This study enhances the understanding of antibiotic risk assessment and provides a new perspective on bacterial assembly contamination and the functional prevalence of ARGs and MGEs with antibiotic resistance bacteria. Moreover, it raises public awareness because these contaminants put people's lives at risk of acquiring bacterial infections. In addition, it can also help propose hybrid water treatment approaches.

Coexistence of bla NDM-5 and tet(X4) in international high-risk Escherichia coli clone ST648 of human origin in China.

The emergence of pathogens is conferring resistance to last-resort therapies such as tigecycline, colistin, and carbapenems, limiting the therapeutic options, and raising concerns about the emergence of new "superbugs." This study reports the first incident of a bla NDM-5 and tet(X4) co-harboring Escherichia coli with resistance to carbapenem and tigecycline recovered as the causative agent of a urinary tract infection in a 94-year-old patient. The E. coli strain ECCL209 carries multiple resistance genes [i.e., bla TEM-1B , bla NDM-5, bla CMY-2, aadA22, florR, erm(B), mph(A), erm(42), lnuG, qnrS1, and sul2] and exhibits resistance to almost all clinically used antibiotics. MLST analysis found that the strain belongs to ST648, considered a worldwide high-risk pandemic clone. Moreover, multiple plasmid incompatibility types were detected, i.e., IncHI1A, IncHI1B, IncFII, IncFIA, IncFIB, IncQ1, Col, and IncX4. Genetic analysis revealed that bla NDM-5 and tet(X4) genes were localized on two hybrid plasmids with multiple replicons. Continuous monitoring studies are suggested to quantify the antimicrobial resistance and assess the dissemination of such superbugs into a human healthcare setting.

Genomic diversity of resistant and virulent factors of Burkholderia pseudomallei clinical strains recovered from Guangdong using whole genome sequencing.

Background: Burkholderia pseudomallei (B. pseudomallei) is a highly infectious agent and causes melioidosis, in both humans and animals, which is endemic in Southeast Asia and Northern Australia. Objectives: This study aims to determine the molecular epidemiology, resistant determinants, and genomic diversity of the clinical isolates of B. pseudomallei to further elucidate the phylogenetic and evolutionary relationship of the strains with those in other endemic regions. Methods: In this study, we obtained eight clinical B. pseudomallei isolates from Guangdong province from 2018 to 2019. All the isolates were sequenced using the Illumina NovaSeq platform. The draft genomes of B. pseudomallei were further used to find antibiotic-resistant genes (ARGs), virulence factors, and gene mutations. Multilocus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis were performed to characterize the diversity and epidemiology of the strains. Results: All isolates were susceptible to antibiotics commonly used for melioidosis treatment. Class D beta-lactamases genes OXA-57 and OXA-59, as well as various mutation factors such as amrA, amrB, omp38, gyrA, and ceoB were identified. MLST analysis of the B. pseudomallei strains identified eight different sequence types (STs): ST1774, ST1775, ST271, ST562, ST46, ST830, ST1325, and ST10. Phylogenetic analysis found that the strains used in this study showed high genetic diversity. We also report 165 virulence factors among B. pseudomallei strains responsible for different neurological disorders, pneumonia, skin lesions, and abscesses. All strains recovered in this study were susceptible to commonly used antibiotics. However, high genetic diversity exists among the isolates. The surveillance, diagnosis, and clinical features of melioidosis varied in different geographical locations. These regional differences in the clinical manifestations have implications for the practical management of the disease. Conclusion: The present study reports the identification of different mutation and virulence factors among B. pseudomallei strains responsible for different neurological disorders, pneumonia, skin lesions, and abscesses.

Synergistic Activity of Tetrandrine and Colistin against mcr-1-Harboring Escherichia coli.

Before the emergence of plasmid-mediated colistin resistance, colistin was once considered the last drug of choice for infections caused by carbapenem-resistant bacteria. Currently, researchers are relentlessly exploring possible alternative therapies that could efficiently curb the spread of drug resistance. In this study, we aim to investigate the synergistic antibacterial activity of tetrandrine in combination with colistin against mcr-1-harboring Escherichia coli. We examined the antibacterial activity of tetrandrine in combination with colistin in vivo and in vitro and examined the bacterial cells by fluorescence, scanning, and transmission electron microscopy (TEM) to explore their underlying mechanism of action. We further performed a computational analysis of MCR-1 protein and tetrandrine to determine the interaction interface of these two molecules. We confirmed that neither colistin nor tetrandrine could, on their own, inhibit the growth of mcr-1-positive E. coli. However, in combination, tetrandrine synergistically enhanced colistin activity to inhibit the growth of E. coli both in vivo and in vitro. Similarly, molecular docking showed that tetrandrine interacted with the three crucial amino acids of the MCR-1 protein in the active site, which might inhibit MCR-1 from binding to its substrates, cause MCR-1 to lose its ability to confer resistance. This study confirmed that tetrandrine and colistin have the ability to synergistically overcome the issue of colistin resistance in mcr-1-harboring E. coli.

Clinical Significance of Fusobacterium nucleatum and Microsatellite Instability in Evaluating Colorectal Cancer Prognosis.

Objective: Both genetic and microbial factors play important roles in colorectal cancer (CRC) development. The effects of Fusobacterium nucleatum (F. nucleatum) and microsatellite instability (MSI) on CRC prognosis require more clinical evidence. We aimed to investigate the role of F. nucleatum and MSI as biomarkers in predicting the prognosis of CRC. Methods: CRC patients in various TNM stages were enrolled. MSI status and F. nucleatum were detected by immunohistochemical staining of formalin-fixed paraffin-embedded (FFPE) specimens. The associations between MSI status and F. nucleatum and clinical parameters were analyzed. Results: MSI tumors were more frequently observed in the colon than in the rectum. Cancerous tissues had higher levels of F. nucleatum than adjacent noncancerous tissues. There were no significant differences in F. nucleatum abundance in different age, sex, tumor stage, location, and tumor marker groups. MSI status was associated with tumor location and stage. Survival analyses revealed that disease-free survival (DFS) was significantly longer in the F. nucleatum-negative, younger age, and TNM stage I-II groups (p< 0.05), and age, advanced TNM stage (III and IV), and F. nucleatum status were independent factors for poor prognosis. Multivariate Cox regression and receiver operating characteristic (ROC) curve analyses showed that conventional tumor biomarkers of CRC had more prognostic value than F. nucleatum and MSI. Conclusion: Age, advanced TNM stage, and F. nucleatum positivity were independent factors of poor prognosis, suggesting that F. nucleatum and MSI may contribute to the identification of new strategies for the prevention and treatment of CRC.

Surveillance of SARS-CoV-2 antibodies of patients in the local affected area during Wuhan lockdown.

BACKGROUND: Serosurveillance is crucial in estimating the range of SARS-CoV-2 infections, predicting the possibility of another wave, and deciding on a vaccination strategy. To understand the herd immunity after the COVID-19 pandemic, the seroprevalence was measured in 3062 individuals with or without COVID-19 from the clinic. METHODS: The levels of SARS-CoV-2 antibody IgM and IgG were measured by the immuno-colloidal gold method. A fusion fragment of nucleocapsid and spike protein was detected by a qualitative test kit with sensitivity (89%) and specificity (98%). RESULTS: The seroprevalence rate for IgM and IgG in all outpatients was 2.81% and 7.51%, respectively. The sex-related prevalence rate of IgG was significantly higher (P < 0.05) in women than men. The highest positive rate of IgM was observed in individuals < 20 years of age (3.57%), while the highest seroprevalence for IgG was observed in persons > 60 years of age (8.61%). Positive rates of IgM and IgG in the convalescent patients were 31.82% and 77.27%, respectively, which was significantly higher than individuals with suspected syndromes or individuals without any clinical signs (P < 0.01). Seroprevalence for IgG in medical staff was markedly higher than those in residents. No significant difference of seroprevalence was found among patients with different comorbidities (P > 0.05). CONCLUSIONS: The low positive rate of the SARS-CoV-2 IgM and nucleic acid (NA) test indicated that the SARS-CoV-2 outbreak is subsiding after 3 months, and the possibility of reintroduction of the virus from an unidentified natural reservoir is low. Seroprevalence provides information for humoral immunity and vaccine in the future.

Incidence and molecular characterization of ESBL-producing and colistin-resistant Escherichia coli isolates recovered from healthy food-producing animals in Pakistan.

OBJECTIVES: To investigate the occurrence and molecular features of ESBL-producing and colistin-resistant Escherichia coli isolates recovered from healthy food-producing animals in Pakistan. METHODS: A total of 153 E. coli isolates were recovered from 250 faecal samples collected from livestock and poultry. The antibiotic susceptibility, resistant determinants and mobile genetic elements were determined for all the isolates. The clonal relatedness was analysed by MLST. Plasmids harbouring, localization and transferability of mcr-1 gene were carried out by Southern hybridization, S1-PFGE and transconjugation. RESULTS: Out of 153 E. coli strains, 49.01% isolates were ESBLs producers, whereas 18.95% were resistant to colistin and 84.31% of the isolates. Multidrug resistance was found in 84% of the isolates. The ESBL-producing E. coli in buffaloes, cattle, sheep, goat and broilers faecal samples were 60%, 74%, 54%, 50% and 68%, respectively. Among the ESBLs genes, blaCTX-M was the most prevalent group detected in 98.66%, while only mcr-1 of the colistin-resistant genes could be PCR amplified in 29 isolates. The common MGEs found were ISECP1 (35.13%), ISCR1 (33.78%), ISApl1 (20.27%) and Inti1 (58.10%). The most predominant Inc. types found were IncFIB 46.66%, followed by IncFIA 30.66%, IncFIC 26.66%, IncFrepB 26.66%, IncHI2 26.66%, IncP 22.66% and IncX4 21.33%. The most frequent sequence type detected was ST58. Southern blot and S1-PFGE confirmed the plasmid harbouring of mcr-1 gene. CONCLUSION: The co-occurrence of mcr-1 and ESBLs-encoding genes, along with MGEs in E. coli from healthy food animals in Pakistan, is a major concern. SIGNIFICANCE AND IMPACT OF STUDY: Antimicrobial resistance can be transferred from animals to humans by direct contact or via the food chain and environment. The prevalence and co-occurrence of ESBL and colistin resistance genes from food-producing animals is rare in Pakistan. To our knowledge, this is the first report to find ESBLs and mcr-1-harbouring E. coli from the faecal samples of the healthy food-producing animals in Pakistan. The presence of ARGs in association with MGEs, co-harbouring the virulence factors, as determined in the current study, is a severe threat to livestock and the human community as it has horizontally and food web transferability.

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.

Microbiomes and Resistomes in Biopsy Tissue and Intestinal Lavage Fluid of Colorectal Cancer.

Aim: The gut microbiome plays a crucial role in colorectal cancer (CRC) tumorigenesis, but compositions of microorganisms have been inconsistent in previous studies due to the different types of specimens. We investigated the microbiomes and resistomes of CRC patients with colonic biopsy tissue and intestinal lavage fluid (IVF). Methods: Paired samples (biopsy tissue and IVF) were collected from 20 patients with CRC, and their gut microbiomes and resistomes were measured by shotgun metagenomics. Clinical and laboratory data were recorded. Bioinformatics (KneadData, Kraken2, and FMAP) and statistical analysis were done using the R (v4.0.2) software. Results: Bacterial diversity in IVF was higher than in tissue samples, and bacterial operational taxonomic units (OTUs) were 2,757 in IVF vs. 197 in tissue. ß-diversity showed distinct clusters in paired samples. The predominant bacteria in IVF were phylum Proteobacteria, while the predominant bacteria of tissue were phylum Actinobacteria. Twenty-seven representative bacteria were selected to form six bacterial clusters, which showed only Firmicutes Cluster 1, and the Bacteroidetes Cluster 1 were significantly more abundant in the IVF group than those in the tissue group (p < 0.05). The Firmicutes Cluster 2, Bacteroidetes Cluster 2, Pathogen Cluster, and Prevotella Cluster were not significantly different between IVF and tissue (p > 0.05). Correlation analysis revealed that some bacteria could have effects on metabolic and inflammatory parameters of CRC patients. A total of 1,295 antibiotic resistance genes (ARGs) were detected in the gut microbiomes, which conferred multidrug resistance, as well as resistance to tetracycline, aminoglycoside, and more. Co-occurrence patterns revealed by the network showed mainly ARG-carrying bacteria to be similar between IVF and tissue, but leading bacteria located in the hub differed between IVF and tissue. Conclusion: Heterogeneity of microbiota is particularly evident when studied with IVF and tissue samples, but bacterial clusters that have close relationships with CRC carcinogenesis are not significantly different, using IVF as an alternative to tissue for gut microbiome, and resistome assessment may be a feasible method.

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.

Aberrant cytokine expression in COVID-19 patients: Associations between cytokines and disease severity.

Cytokines play pleiotropic, antagonistic, and collaborative in viral disease. The high morbidity and mortality of coronavirus disease 2019 (COVID-19) make it a significant threat to global public health. Elucidating its pathogenesis is essential to finding effective therapy. A retrospective study was conducted on 71 patients hospitalized with COVID-19. Data on cytokines, T lymphocytes, and other clinical and laboratory characteristics were collected from patients with variable disease severity. The effects of cytokines on the overall survival (OS) and event-free survival (EFS) of patients were analyzed. The critically severe and severe patients had higher infection indexes and significant multiple organ function abnormalities than the mild patients (P < 0.05). IL-6 and IL-10 were significantly higher in the critically severe patients than in the severe and mild patients (P < 0.05). IL-6 and IL-10 were closely associated with white blood cells, neutrophils, T lymphocyte subsets, D-D dimer, blood urea nitrogen, complement C1q, procalcitonin C-reactive protein. Moreover, the IL-6 and IL-10 levels were closely correlated to dyspnea and dizziness (P < 0.05). The patients with higher IL-10 levels had shorter OS than the group with lower levels (P < 0.05). The older patients with higher levels of single IL-6 or IL-10 tended to have shorter EFS (P < 0.05), while the patients who had more elevated IL-6 and IL-10 had shorter OS (P < 0.05). The Cox proportional hazard model revealed that IL-6 was the independent factor affecting EFS. IL-6 and IL-10 play crucial roles in COVID-19 prognosis.

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.

Microbiome in Intestinal Lavage Fluid May Be A Better Indicator in Evaluating The Risk of Developing Colorectal Cancer Compared with Fecal Samples.

OBJECTIVE: Intestinal microbiota plays a vital role in the pathogenesis of colorectal cancer (CRC), which is crucial for assessing the risk and prognosis of CRC. Most studies regarding human gut microbiota mainly based on the feces, but the exact composition of microbiota vary significantly due to fecal composition is easily affected by many factors. We aim to evaluate whether intestinal lavage fluid (IVF) is a better substitution mirroring the gut microbiota. METHODS: We performed 16S rRNA gene analysis on fecal and IVF samples from 30 CRC patients and 25 healthy individuals, comparison in luminal (feces) / mucosal (IVF) adherent bacterial community profiles were analyzed. RESULTS: The difference between feces and IVF were observed, including the diversity and abundance of pathogenic bacteria (either in single strain or in co-occurrence pattern). IVF group shared 605 OTUs with the fecal group, but there was 94 OTUs only observed in fecal samples, while 247 OTUs were mainly existing in the IVF group. Among them, 27 vital bacterial species detected in IVF, while 10 critical species detected in fecal samples. The co-occurrence bacteria Fusobacteria Cluster and Proteobacteria Cluster 2 significantly increased in IVF than in control (P < .01), while Firmicutes Cluster 1, Firmicutes Cluster 2 and Proteobacteria Cluster 1 were markedly lower in IVF than in control (P < .001). In CRC feces, Fusobacteria Cluster was higher than in control (P < .05), but Firmicutes Cluster 1 was of substantially less abundance than in control (P < .001). Proteobacteria Cluster 2 was increased dramatically in IVF than in feces (P < .05), Firmicutes Cluster 1 were of substantially less abundance than in feces (P < .05). CONCLUSION: Pathogenic microbiota is more abundant in IVF than in feces. Microbiota of IVF may closely be related to the mucosal-associated microbial communities, which benefit from elucidating the relationship of the intestinal microbiota and CRC carcinogenesis.