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Introduction: Phages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation and accurate prediction of the host specificity of phages as well as in the identification of newly replicated virions in response to environmental challenges. Methods: A new workflow using biorthogonal non-canonical amino acid tagging (BONCAT) and click chemistry (CC) allowed the combined analysis of phages and their hosts, the identification of newly replicated virions, and the specific tagging of phages with biotin for affinity chromatography. Results: Replication of phage λ in Escherichia coli was selected as a model for workflow development. Specific labeling of phage λ proteins with the non-canonical amino acid 4-azido-L-homoalanine (AHA) during phage development in E. coli was confirmed by LC-MS/MS. Subsequent tagging of AHA with fluorescent dyes via CC allowed the visualization of phages adsorbed to the cell surface by fluorescence microscopy. Flow cytometry enabled the automated detection of these fluorescent phage-host complexes. Alternatively, AHA-labeled phages were tagged with biotin for purification by affinity chromatography. Despite biotinylation the tagged phages could be purified and were infectious after purification. Discussion: Applying this approach to environmental samples would enable host screening without cultivation. A flexible and powerful workflow for the detection and enrichment of phages and their hosts in pure cultures has been established. The developed method lays the groundwork for future workflows that could enable the isolation of phage-host complexes from diverse complex microbial communities using fluorescence-activated cell sorting or biotin purification. The ability to expand and customize the workflow through the growing range of compounds for CC offers the potential to develop a versatile toolbox in phage research. This work provides a starting point for these further studies by providing a comprehensive standard operating procedure. [ABSTRACT FROM AUTHOR]

Phosphonates such as ethylenediaminetetra (methylenephosphonic acid) (EDTMP) and aminotris (methylenephosphonic acid) (ATMP) are used every day in water treatment processes or in household products. Their consumption is still increasing, regardless of the debates on their environmental impact. Here, the microbial characterisation and determination of the biodegradation potential of selected industrially relevant phosphonates for the isolate Delftia sp. UMB14 is reported. The opportunistic strain was isolated from a biofilm that was derived from a conventional washing machine using conventional detergents containing phosphonates. In antimicrobial susceptibility testing, the strain was only susceptible to sulfonamide, tetracycline, and chloramphenicol. Physiological and biochemical characteristics were determined using the BIOLOG EcoPlate assay. Most importantly, the strain was shown to convert D-malic acid and D-mannitol, as confirmed for strains of Delftia lacustris, and thus the new isolate could be closely related. Biodegradation tests with different phosphonates showed that the strain preferentially degrades ATMP and EDTMP but does not degrade glyphosate (GS) and amino (methylphosphonic acid) (AMPA). A specific gene amplification confirmed the presence of phnX (phosphonoacetaldehyde hydrolase) and the absence of PhnJ (the gene for the core component of C–P lyase). The presence of PhnCDE is strongly suggested for the strain, as it is common in Delftia lacustris species. [ABSTRACT FROM AUTHOR]

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding betweenmicrobiologists andmodelers/bioinformaticians, stemming froma lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored formicrobiologists, researchers newtomicrobiomemodeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling. [ABSTRACT FROM AUTHOR]