Computational protocol: Toxicity of Food-Grade TiO2 to Commensal Intestinal and Transient Food-Borne Bacteria: New Insights Using Nano-SIMS and Synchrotron UV Fluorescence Imaging

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Protocol publication

[…] Deep ultraviolet fluorescence imaging of E. coli K12 MG1655 and L. lactis IBB477 cells after TiO2 exposure was carried out on a Zeiss Axio Observer Z-1 microscope at the DISCO beamline () of the SOLEIL synchrotron facility, as previously described for tryptophan-functionalized gold () and silver nanoparticles (). Bacterial cells were cultured in appropriate medium containing TiO2 at a concentration of 320 μg/mL (aggregated vs. dispersed forms, E171 vs. P25), collected at the stationary phase of growth and washed twice in phosphate buffered saline (5000 g, 5 min, room temperature). Thereafter, 2 μL of the washed cell suspension were placed on quartz coverslips (ESCO Optics, United States) and dried in ambient conditions for 30 min. Bacteria were first observed in bright field through a 100× Zeiss Ultrafluar objective with a 1.25 numerical aperture that requires glycerin immersion. Afterwards, the samples were illuminated by a 270-nm monochromatized synchrotron beam, which was used as the excitation source. The fluorescent signals were collected by a PIXIS 1024 BUV camera (Princeton, United States) in the spectral ranges 327–353 nm (Filter I, OMEGA Filters United States) and 420–480 nm (Filter II, OMEGA Filters, United States) during 90 s of integration time. In addition, to increase the signal to noise ratio, images were recorded with binning of the pixels (2 × 2) in μManager software (), used to control the whole setup. For each condition, two independent quartz coverslips with at least three different locations, covering a minimum of 200 bacterial cells, were investigated to validate the consistency of the observations. The images were analyzed using FIJI software (ImageJ, NIH) (). A set of specific FIJI macro scripts was developed to standardize the analysis (see Supplementary Material ). [...] Polymerized samples, obtained as described above, were sectioned in 300-nm thick slices (Ultracut Reichert) and mounted on silicon plots (Siltronix, Archamps, France). Elemental maps were obtained by Nano-SIMS using a NanoSIMS50 instrument (Cameca, Gennevilliers, France) (). The surface was scanned as a matrix of 256 × 256 pixels for an area of 10 μm2 by an energetic primary cesium ion beam with an acceleration of 8 kV and a primary current of 1.2 pA. The secondary negative ions emitted with 8 kV were filtered in mass, detected and counted simultaneously, allowing an elemental mapping of the original voxel sputtered (). In these conditions, the pixel size was about 40 nm for an estimated probe size of 100 nm. The ions recorded were 12C14N, 32S, 31P16O2, 46Ti16O, and 48Ti16O with a mass resolution M/ΔM higher than 5000. The Ti element was mapped (as TiO- cluster) on at least 100 individual cells of each sample. The distribution of the 12C14N- cluster, well known by the SIMS community, was simultaneously recorded as a “fingerprint” of bacterial cells. Due to the probability of ionization and the matrix effect, i.e., large variations in the ionization yields, SIMS is not a direct quantitative technique (). However, by normalization of the trace element by the matrix element signals, a quantitative analysis (coupled with a reference sample) or a semi-quantitative analysis can be performed with an excellent accuracy (). Unfortunately, for biological samples, it is very difficult to obtain standard samples. This explains why only the semi-quantitative approach was proposed here, based on the normalization of the signal of the titanium cluster (TiO) by the signal intensity of the main ion detected, the cluster (CN). The intensity ratio (TiO/CN) was then calculated for each cell and for all conditions (; ). A total number between 200 and 300 cells was considered (taking into account the aggregated and dispersed TiO2 forms). The signal intensities of the different elements were extracted from image acquisitions using OpenMIMS, a FIJI plugin developed at Harvard at the National Resource for Imaging Mass Spectrometry (). […]

Pipeline specifications

Software tools μManager, ImageJ, OpenMIMS
Applications Mass spectrometry imaging, Microscopic phenotype analysis
Organisms Escherichia coli, Bacteria, Lactobacillus rhamnosus, Lactococcus lactis subsp. lactis, Streptococcus thermophilus, Lactobacillus sakei, Lactobacillus delbrueckii subsp. lactis
Diseases Drug-Related Side Effects and Adverse Reactions