are natural inhabitants of building plumbing biofilms, where interactions with other microorganisms influence their survival, proliferation, and death. Here, we investigated the associations of with bacterial and eukaryotic microbiomes in biofilm samples extracted from 85 shower hoses of a multiunit residential building. spp. relative abundance in the biofilms ranged between 0-7.8%, of which only 0-0.46% was . Our data suggest that some microbiome members were associated with high (e.g. ) or low (e.g. ) relative abundance. The correlations of the different variants (30 Zero-Radius OTUs detected) showed distinct patterns, suggesting separate ecological niches occupied by different species. This study provides insights into the ecology of with respect to: (i) the colonization of a high number of real shower hoses biofilm samples; (ii) the ecological meaning of associations between and co-occurring bacterial/eukaryotic organisms; (iii) critical points and future directions of microbial-interaction-based-ecological-investigations.
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http://dx.doi.org/10.1093/femsmc/xtad016 | DOI Listing |
J Infect Dis
January 2025
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Background: Aging-related comorbidities are more common in people with human immunodeficiency virus (HIV) compared to people without HIV. The gut microbiome may play a role in healthy aging; however, this relationship remains unexplored in the context of HIV.
Methods: 16S rRNA gene sequencing was conducted on stool from 1409 women (69% with HIV; 2304 samples) and 990 men (54% with HIV; 1008 samples) in the MACS/WIHS Combined Cohort Study.
Proc Natl Acad Sci U S A
January 2025
Centre for Tuberculosis Research, Tuberculosis Research Laboratory, Translational Health Science and Technology Institute, National Capital Region Biotech Science Cluster 3rd Milestone, Faridabad, Haryana 121001, India.
Itaconate, an abundant metabolite produced by macrophages upon interferon-γ stimulation, possesses both antibacterial and immunomodulatory properties. Despite its crucial role in immunity and antimicrobial control, its mechanism of action and dissimilation are poorly understood. Here, we demonstrate that infection of mice with increases itaconate levels in lung tissues.
View Article and Find Full Text PDFInorg Chem
January 2025
School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, P. R. China.
N-heterocyclic carbene (NHC)-based phosphorescent iridium complexes have attracted extensive attention due to their good optical properties and high stability in recent years. However, currently reported NHC-based iridium complexes can easily achieve emission of blue, green, or even ultraviolet light, while emission of red or deep-red light is relatively rare. Here, we report a new family of NHC-based deep-red iridium complexes (Ir1, Ir2, Ir3, and Ir4) featuring three-charge (0, -1, -2) ligands.
View Article and Find Full Text PDFProtein Sci
February 2025
Department of Molecular Biology, University of Wyoming, Laramie, Wyoming, USA.
Organisms from all kingdoms of life depend on Late Embryogenesis Abundant (LEA) proteins to survive desiccation. LEA proteins are divided into broad families distinguished by the presence of family-specific motif sequences. The LEA_4 family, characterized by 11-residue motifs, plays a crucial role in the desiccation tolerance of numerous species.
View Article and Find Full Text PDFJ Oral Microbiol
January 2025
Integrative Microecology Clinical Center, Shenzhen Clinical Research Center for Digestive Disease, Shenzhen Technology Research Center of Gut Microbiota Transplantation, The Clinical Innovation & Research Center, Shenzhen Key Laboratory of Viral Oncology, Department of Clinical Nutrition, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Background: This study aims to develop an oral microbiota-based model for gastric cancer (GC) risk stratification and prognosis prediction.
Methods: Oral microbial markers for GC prognosis and risk stratification were identified from 99 GC patients, and their predictive potential was validated on an external dataset of 111 GC patients. The identified bacterial markers were used to construct a Deep Neural Network (DNN) model, a Random Forest (RF) model, and a Support Vector Machine (SVM) model for predicting GC prognosis.
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