Traditional microbe indicators including total bacteria, total coliforms, fecal coliforms, Escherichia coli, enterococci, and F+ coliphage are all frequently used to characterize the microbial contamination state of water bodies for their correlation with pathogenic bacteria. However, these indicators have a poor relationship with viruses, which pose serious threat to economic and human health. Alternative indicators such as bacteroidales may be suitable complementary alternatives to traditional microbe indicators and are being increasingly reported. In the present study, water was analyzed for selected sites along Haihe River in Tianjin for traditional indicators, an alternative indicator (bacteroidales), pathogenic bacteria (Salmonella, Escherichia coli (E. coli) O157:H7, and Vibrio parahaemolyticus), viruses (enteric adenovirus, norovirus, enterovirus, poliovirus and rotavirus), and physicochemical parameters. Results indicated that traditional microbe indicators detected in this study showed good correlation with pathogenic bacteria, and the alternative indicator (bacteroidales) had a surprisingly good relationship with viral presence. We propose that bacteroidales might be a suitable complementary indicator for viral contamination in water bodies.
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http://dx.doi.org/10.1007/s11356-019-04217-y | DOI Listing |
Microb Biotechnol
January 2025
Laboratory of Microbiology, Institute of Biology, University of Neuchatel, Neuchatel, Switzerland.
The inadequate removal of pharmaceuticals and personal care products (PPCPs) by traditional wastewater treatment plants (WWTPs) poses a significant environmental and public health challenge. Residual PPCPs find their way into aquatic ecosystems, leading to bioaccumulation in aquatic biota, the dissemination of antibiotic resistance genes (ARGs), and contamination of both water sources and vegetables. These persistent pollutants can have negative effects on human health, ranging from antibiotic resistance development to endocrine disruption.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, and Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, 200240, China.
Light-driven CO biovalorization offers a promising route for coupling carbon mitigation with petrochemical replacement. Synthetic phototrophic communities that mimic lichens can reduce the metabolic burden with improved CO utilization. However, inefficient channeling of carbon and energy between species seriously hinders the collaborative CO-to-molecule route.
View Article and Find Full Text PDFFront Immunol
January 2025
The School of Clinical Medicine, Fujian Medical University, Fuzhou, China.
Background: The combination of local therapy with lenvatinib and programmed cell death protein-1 (PD-1) inhibitors represents an emerging treatment paradigm for unresectable hepatocellular carcinoma (uHCC). Our study sought to investigate the interrelationship between gut microbiota and intratumoral microbiota in the context of triple therapy, with a view to identifying potential biological markers.
Methods: The gut microbial community profiles of patients with primary untreated hepatocellular carcinoma (HCC) and those treated with local therapy combined with lenvatinib and PD-1 inhibitors were analyzed by 16S rRNA gene amplicon sequencing.
Methods
January 2025
School of Computer Science and Engineering, Central South University, Changsha 410083, China; Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China.
Exploring the associations between microbes and drugs offers valuable insights into their underlying mechanisms. Traditional wet lab experiments, while reliable, are often time-consuming and labor-intensive, making computational approaches an attractive alternative. Existing similarity-based machine learning models for predicting microbe-drug associations typically rely on integrated similarities as input, neglecting the unique contributions of individual similarities, which can compromise predictive accuracy.
View Article and Find Full Text PDFBiomolecules
December 2024
Laboratory of Molecular Plant Biology and KU Leuven Plant Institute, Kasteelpark Arenberg 31, 3001 Leuven, Belgium.
Distinguishing between endo- and exo-type enzymes within the glycoside hydrolase (GH) classification presents significant challenges. Traditional methods, often based on endpoint activity measurements, do not capture the full range of products generated, leading to inconsistencies in classification. Not all exo-acting fructanases and glucanases produce monosaccharides (like fructose or glucose), while endo-acting enzymes do not solely produce higher-degree polymerization oligosaccharides.
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