SSNOMBACTER: A collection of scattering-type scanning near-field optical microscopy and atomic force microscopy images of bacterial cells
M. Lucidi, D. E Tranca, L. Nichele, D. Ünay, G. A Stanciu, P. Visca, A. Maria Holban, R. Hristu, G. Cincotti, S. G Stanciu
GigaScience 9, giaa129 (2020)
Background
In recent years, a variety of imaging techniques operating at nanoscale resolution have been reported. These techniques have the potential to enrich our understanding of bacterial species relevant to human health, such as antibiotic-resistant pathogens. However, owing to the novelty of these techniques, their use is still confined to addressing very particular applications, and their availability is limited owing to associated costs and required expertise. Among these, scattering-type scanning near field optical microscopy (s-SNOM) has been demonstrated as a powerful tool for exploring important optical properties at nanoscale resolution, depending only on the size of a sharp tip. Despite its huge potential to resolve aspects that cannot be tackled otherwise, the penetration of s-SNOM into the life sciences is still proceeding at a slow pace for the aforementioned reasons.
Results
In this work we introduce SSNOMBACTER, a set of s-SNOM images collected on 15 bacterial species. These come accompanied by registered Atomic Force Microscopy images, which are useful for placing nanoscale optical information in a relevant topographic context.
Conclusions
The proposed dataset aims to augment the popularity of s-SNOM and for accelerating its penetration in life sciences. Furthermore, we consider this dataset to be useful for the development and benchmarking of image analysis tools dedicated to s-SNOM imaging, which are scarce, despite the high need. In this latter context we discuss a series of image processing and analysis applications where SSNOMBACTER could be of help.
In recent years, a variety of imaging techniques operating at nanoscale resolution have been reported. These techniques have the potential to enrich our understanding of bacterial species relevant to human health, such as antibiotic-resistant pathogens. However, owing to the novelty of these techniques, their use is still confined to addressing very particular applications, and their availability is limited owing to associated costs and required expertise. Among these, scattering-type scanning near field optical microscopy (s-SNOM) has been demonstrated as a powerful tool for exploring important optical properties at nanoscale resolution, depending only on the size of a sharp tip. Despite its huge potential to resolve aspects that cannot be tackled otherwise, the penetration of s-SNOM into the life sciences is still proceeding at a slow pace for the aforementioned reasons.
Results
In this work we introduce SSNOMBACTER, a set of s-SNOM images collected on 15 bacterial species. These come accompanied by registered Atomic Force Microscopy images, which are useful for placing nanoscale optical information in a relevant topographic context.
Conclusions
The proposed dataset aims to augment the popularity of s-SNOM and for accelerating its penetration in life sciences. Furthermore, we consider this dataset to be useful for the development and benchmarking of image analysis tools dedicated to s-SNOM imaging, which are scarce, despite the high need. In this latter context we discuss a series of image processing and analysis applications where SSNOMBACTER could be of help.