BacSp222 is a multifunctional bacteriocin produced by Staphylococcus pseudintermedius strain 222, an opportunistic pathogen of domestic animals. At micromolar concentrations, BacSp222 kills Gram-positive bacteria and is cytotoxic toward mammalian cells, while at nanomolar doses, it acts as an immunomodulatory factor, enhancing nitric oxide release in macrophage-like cell lines. The bacteriocin is a cationic, N-terminally formylated, 50-amino-acid-long linear peptide that is rich in tryptophan residues. In this study, the solution structure of BacSp222 was determined and compared to the currently known structures of similar bacteriocins. BacSp222 was isolated from a liquid culture medium in a uniformly ¹³C- and ¹⁵N-labeled form, and NMR data were collected. The structure was calculated based on NMR-derived constraints and consists of a rigid and tightly packed globular bundle of four alpha-helices separated by three short turns. Although the amino acid sequence of BacSp222 has no significant similarity to any known peptide or protein, a 3D structure similarity search indicates a close relation to other four-helix bundle-motif bacteriocins, such as aureocin A53, lacticin Q and enterocins 7A/7B. Assuming similar functions, biology, structure and physicochemical properties, we propose to distinguish the four-helix bundle bacteriocins as a new Type A in subclass IId of bacteriocins, containing linear, non-pediocin-like peptides.

The biological toolbox is full of techniques developed originally for analytical chemistry. Among them, spectroscopic experiments are very important source of atomic-level structural information. Nuclear magnetic resonance (NMR) spectroscopy, although very advanced in chemical and biophysical applications, has been used in microbiology only in a limited manner. So far, mostly one-dimensional ¹H experiments have been reported in studies of bacterial metabolism monitored in situ. However, low spectral resolution and limited information on molecular topology limits the usability of these methods. These problems are particularly evident in the case of complex mixtures, where spectral peaks originating from many compounds overlap and make the interpretation of changes in a spectrum difficult or even impossible. Often a suite of two-dimensional (2D) NMR experiments is used to improve resolution and extract structural information from internuclear correlations. However, for dynamically changing sample, like bacterial culture, the time-consuming sampling of so-called indirect time dimensions in 2D experiments is inefficient. Here, we propose the technique known from analytical chemistry and structural biology of proteins, i.e., time-resolved non-uniform sampling. The method allows application of 2D (and multi-D) experiments in the case of quickly varying samples. The indirect dimension here is sparsely sampled resulting in significant reduction of experimental time. Compared to conventional approach based on a series of 1D measurements, this method provides extraordinary resolution and is a real-time approach to process monitoring. In this study, we demonstrate the usability of the method on a sample of Escherichia coli culture affected by ampicillin and on a sample of Propionibacterium acnes, an acne causing bacterium, mixed with a dose of face tonic, which is a complicated, multi-component mixture providing complex NMR spectrum. Through our experiments we determine the exact concentration and time at which the anti-bacterial agents affect the bacterial metabolism. We show, that it is worth to extend the NMR toolbox for microbiology by including techniques of 2D z-TOCSY, for total “fingerprinting” of a sample and 2D ¹³C-edited HSQC to monitor changes in concentration of metabolites in selected metabolic pathways.

A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH..