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INTRODUCTION: Bacterial cell characteristics change significantly during differentiation between planktonic and biofilm states. While established methods exist to detect and identify transcriptional and proteomic changes, metabolic fluctuations that distinguish these developmental stages have been less amenable to investigation. OBJECTIVES: The objectives of the study were to develop a robust reproducible sample preparation methodology for high throughput biofilm analysis and to determine differences between Staphylococcus aureus in planktonic and biofilm states. METHODS: The method uses bead beating in a chloroform/methanol/water extraction solvent to both disrupt cells and quench metabolism. Verification of the method was performed using liquid-chromatography-mass spectrometry. Raw mass-spectrometry data was analysed using an in-house bioinformatics pipe-line incorporating XCMS, MzMatch and in-house R-scripts, with identifications matched to internal standards and metabolite data-base entries. RESULTS: We have demonstrated a novel mechanical bead beating method that has been optimised for the extraction of the metabolome from cells of a clinical Staphylococcus aureus strain existing in a planktonic or biofilm state. This high-throughput method is fast and reproducible, allowing for direct comparison between different bacterial growth states. Significant changes in arginine biosynthesis were identified between the two cell populations. CONCLUSIONS: The method described herein represents a valuable tool in studying microbial biochemistry at a molecular level. While the methodology is generally applicable to the lysis and extraction of metabolites from Gram positive bacteria, it is particularly applicable to biofilms. Bacteria that exist as a biofilm are shown to be highly distinct metabolically from their 'free living' counterparts, thus highlighting the need to study microbes in different growth states. Metabolomics can successfully distinguish between a planktonic and biofilm growth state. Importantly, this study design, incorporating metabolomics, could be optimised for studying the effects of antimicrobials and drug modes of action, potentially providing explanations and mechanisms of antibiotic resistance and to help devise new antimicrobials.
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We report here the genome sequence of a clinical isolate of Staphylococcus aureus from an orthopedic infection. Phenotypically diverse Staphylococcus aureus strains are associated with orthopedic infections and subsequent implant failure, and some are highly resistant to antibiotics. This genome sequence will support further analyses of strains causing orthopedic infections.
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Proteins in milk have wide range of functions, they are carriers of minerals or chemically vulnerable and insoluble vitamins and other compounds, stabilisers of large aggregates or micelles of lipids, and components of both innate and acquired immune defence systems. Together with other components of milk, proteins may also contribute to the selection and establishment of appropriate microbiome in the gut of the infant. The proteome of mammalian milk is now known to be dynamic and changes radically with time after birth from colostrum to mature lactation. Significantly, immune and innate defence proteins appear in milk during infection of the mammary gland and possibly also during systemic infections. The understanding of the human milk proteome and how it changes with time during lactation and in disease is developing rapidly, and is to a large extent informed by proteomics of the milks of non-human mammals, domestic animals in particular. We review general methods now being applied for proteomic analysis of human milk. Moreover we place emphasis on how the milk proteome may change in different ways in response to disease, mastitis in particular, how such changes may be specific to pathogen types, and we give some insights about evolution.