Identification of medically relevant microorganisms by vibrational spectroscopy

Spectroscopic characterization of microorganisms by Fourier transform infrared microspectroscopy

“…Carbohydrates, DNA/RNA backbone, and proteins all contribute to these bands, given the fact that amide I and II bands are relatively weaker here; this band may represent significant contributions from carbohydrates and DNA/RNA, which are abundant in the cytoplasm. It should be noticed that some authors 6,11 assigned this band to the CAO stretching in COO Ϫ -it would thus be hard to explain why this peak was so prominent in the cytoplasmic extract.…”

“…Since Naumann and coworkers published their pioneering work in this field, 1 various research groups around the world have shown the validity of FTIR spectroscopic techniques beyond reasonable doubt. [2][3][4][5][6][7] Results obtained have consistently proved that the spectral information is sufficient to distinguish between various microorganisms both at species and strain level. In particular, IR microspectrometry can be used to provide spatially resolved structural and compositional information at the molecular level, accounting for the heterogeneities of the microbial colonies at the microscopic level for enhanced discrimination.…”

“…As shown in Figure 1, only regions between 800 -1800 cm Ϫ1 and 2700 an 3100 cm Ϫ1 , which are the "fingerprints" region for microorganism differentiation, were used for analysis. 6,7 …”

“…10 Although considerable advances have been made in applying FTIR microspectroscopy for microorganism identification and differentiation following this approach, few have focused on examining the chemical and structural differences that are the real basis of these different patterns. Several efforts have been made to assign specific bands to functional groups that are biologically important, 6,11 but they are incomplete and some of the assignments proposed are still debatable. Most of these efforts are based on the first or second derivatives of the original (zero-order) spectrum.…”

Automatic identification of novel bacteria using Raman spectroscopy and Gaussian processes

“…contained in the training database). Particularly for applications such as pathogen identification [17,18,19,20] or general bacteria classification [11,12,21], this constraint can usually not be guaranteed a priori. Thus, additional data treatment is needed which justifies the assignment to one of a few known classes.…”