6 research outputs found
Evaluation of a Novel Tc-99m Labelled Vitamin B12 Derivative for Targeting Escherichia coli and Staphylococcus aureus In Vitro and in an Experimental Foreign-Body Infection Model
A major 170 kDa protein associated with bovine adrenal medulla microtubules: a member of the centrosomin family?
Antibiotic-induced modifications of the stiffness of bacterial membranes.
In the latest years the importance of high resolution analysis of the microbial cell surface has been increasingly recognized. Indeed, in order to better understand bacterial physiology and achieve rapid diagnostic and treatment techniques, a thorough investigation of the surface modifications induced on bacteria by different environmental conditions or drugs is essential. Several instruments are nowadays available to observe at high resolution specific properties of microscopic samples. Among these, AFM can routinely study single cells in physiological conditions, measuring the mechanical properties of their membrane at a nanometric scale (force volume). Such analyses, coupled with high resolution investigation of their morphological properties, are increasingly used to characterize the state of single cells. In this work we exploit such technique to characterize bacterial systems. We have performed an analysis of the mechanical properties of bacteria (Escherichia coli) exposed to different conditions. Such measurements were performed on living bacteria, by changing in real-time the liquid environment: standard phosphate buffered saline, antibiotic (ampicillin) in PBS and growth medium. In particular we have focused on the determination of the membrane stiffness modifications induced by these solutions, in particular between stationary and replicating phases and what is the effect of the antibiotic on the bacterial structure
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Prediction of enzymatic pathways by integrative pathway mapping.
The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology