Defining Multiple Characteristic Raman Bands of α-Amino Acids as Biomarkers for Planetary Missions Using a Statistical Method

Abstract

Biomarker molecules, such as amino acids, are key to discovering whether life exists elsewhere in the Solar System. Raman spectroscopy, a technique capable of detecting biomarkers, will be on board future planetary missions including the ExoMars rover. Generally, the position of the strongest band in the spectra of amino acids is reported as the identifying band. However, for an unknown sample, it is desirable to define multiple characteristic bands for molecules to avoid any ambiguous identification. To date, there has been no definition of multiple characteristic bands for amino acids of interest to astrobiology. This study examined l-alanine, l-aspartic acid, l-cysteine, l-glutamine and glycine and defined several Raman bands per molecule for reference as characteristic identifiers. Per amino acid, 240 spectra were recorded and compared using established statistical tests including ANOVA. The number of characteristic bands defined were 10, 12, 12, 14 and 19 for l-alanine (strongest intensity band: 832 cm-1), l-aspartic acid (938 cm-1), l-cysteine (679 cm-1), l-glutamine (1090 cm−1) and glycine (875 cm-1), respectively. The intensity of bands differed by up to six times when several points on the crystal sample were rotated through 360 °; to reduce this effect when defining characteristic bands for other molecules, we find that spectra should be recorded at a statistically significant number of points per sample to remove the effect of sample rotation. It is crucial that sets of characteristic Raman bands are defined for biomarkers that are targets for future planetary missions to ensure a positive identification can be made.

Periodontitis detection using Raman spectroscopy, support vector machine, and salivary biomarkers

“…Table 4 shows that the reported Raman bands are comparable with those found in the literature. [ 43,50,55,56 ] Of all the biomolecules simulated (see Figure S5), ALT is associated with periodontal processes, a fact evidenced in clinical case reports. [ 54,57–60 ] Therefore, an intensity analysis was performed to differentiate healthy patients from those with periodontitis, as was done for albumin.…”

“…Using Raman spectroscopy, SVM, and the salivary biomarkers albumin and ALT, it is possible to discern the presence or absence of periodontal disease. Using SVM From literature [43,50] (cm À1 ) Percentage (%) Banda Raman (cm À1 ) Assignment [43,50] 769 ), based on the residual study of the active bands of periodontitis, which allowed an analysis based on the intensities associated with the concentrations for each biomarker identified; for patients with periodontitis, the intensities were higher (>10%) than in healthy individuals. Additionally, the saliva spectrum identified the presence of the biomarkers proline, hydroxyproline, tryptophan, glycine, and glutamine, using DFT with the B3LYP function simulated in ORCA and its Raman bands.…”

“…Figure S6 shows 21 bands, of which four prominent bands were identified in the literature. [43,50] These bands were located in the spectra of the saliva samples of the patients to perform an intensity analysis (see Figure 8).…”

“…In this section, we present computational simulations of the Raman spectrum using the B3LYP density functional theory (DFT) [39,40] with the free software ORCA [41] version 4.2.1 to identify other Raman bands not mentioned or not described in the previous sections. The simulated biomolecules together their Raman bands identified in the literature were glutamine (776, 1056.50, 1133, 1225.50, 1330, 1357, 1417, and 1732.20 cm À1 ), [42,43] glycine (875.00 and 1699 cm À1 ), [42][43][44][45] hydroxyproline (208, 320, 369, 964, 1083, 1226, 1272, 1302, 1372, and 1420 cm À1 ) [46,47] proline (438, 455, 580, 915, 986, 1171, 1191, and 1457 cm À1 ), [47,48] and tryptophan (432, 540, 579, 622, 706, 760, 1008, 1015, 1118, 1440, and 1614 cm À1 ), [49][50][51] which are of great importance because they interact with the tooth surface, modulating bacterial adhesion as well as the deposition of calcium and phosphate crystals in the enamel matrix. [52,53] The simulation of the biomarker ALT, which is considered a cytoplasmic enzyme typically found in human blood plasma, bile, cerebrospinal fluid, and saliva, was also carried out.…”

Mapping Bone Surface Composition Using Real-Time Surface Tracked Micro-Raman Spectroscopy

“…Cluster analysis reveals progressive increases in ν 1 PO 4 3and ν 1 CO 3 2peak intensities and the mineral-to-matrix ratio (from 0.07 to 0.33) simultaneously with a shift in the relative contributions of δ(N-H) and ν(C-N) vibrations to the Amide III band profile. Confined to poorly mineralized areas, cluster analysis reveals a broad feature at 945 cm -1 assigned to amorphous calcium phosphate [Crane et al, 2006] and another feature at 995 cm -1 that is likely attributable to amino acid alanine (Ala) [Rolfe et al, 2016]. Ala enters osteoblasts through a sodium-dependent transport mechanism and is involved in subsequent protein synthesis [Veldman and Schmid, 1998].…”