  We report here on the ability of elastic light scattering in discriminating
Gram+, Gram-and yeasts at an early stage of growth (6h). Our technique is
non-invasive, low cost and does require neither skilled operators nor reagents.
Therefore it is compatible with automation. It is based on the analysis of the
scattering pattern (scatterogram) generated by a bacterial microcolony growing
on agar, when placed in the path of a laser beam. Measurements are directly
performed on closed Petri dishes. The characteristic features of a given
scatterogram are first computed by projecting the pattern onto the Zernike
orthogonal basis. Then the obtained data are compared to a database so that
machine learning can yield identification result. A 10-fold cross-validation
was performed on a database over 8 species (15 strains, 1906 scatterograms), at
6h of incubation. It yielded a 94% correct classification rate between Gram+,
Gram-and yeasts. Results can be improved by using a more relevant function
basis for projections, such as Fourier-Bessel functions. A fully integrated
instrument has been installed at the Grenoble hospital's laboratory of
bacteriology and a validation campaign has been started for the early screening
of SA and MRSA (Staphylococcus aureus, methicillin-resistant S. aureus)
carriers. Up to now, all the published studies about elastic scattering were
performed in a forward mode, which is restricted to transparent media. However,
in clinical diagnostics, most of media are opaque, such as blood-supplemented
agar. That is why we propose a novel scheme capable of collecting
back-scattered light which provides comparable results.
