Lipidomic approach to identify Escherichia coli and Shigella spp. by matrix-assisted laser desorption/ionization mass spectrometry.

PURPOSE: Escherichia coli (E. coli) and Shigella species, being highly similar, present a challenge for differentiation using classical methods such as phenotyping, 16S rRNA sequencing, or protein profiling using matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). The paper proposes a method for identifying E. coli, S. flexneri, S. sonnei, and S. boydii by augmenting the Bruker Biotyper database with reference spectra of lipid profiles obtained using MALDI MS in the positive mode. MATERIALS/METHODS: Lipid extracts were made from cultured E. coli, S. flexneri, S. sonnei and S. boydii using the Bligh & Dyer protocol. MALDI MS spectra in positive ion mode were performed for the extracts. Reference spectra were created from 30 spectra for each bacterium and added to the Bruker Biotyper database. RESULTS: Identification of bacteria based on lipid profiles in the Biotyper database gave correct results with scores above 2.49. Statistical analysis of the results by Partial Least Squares-Discriminant Analysis (PLS-DA) showed that it is possible to correctly differentiate the microorganisms studied using the lipidomic approach. A panel of six m/z values was proposed for which the value of the area under the ROC curve is 1, thus enabling the identification of E. coli and S. flexneri with 100 â€‹% accuracy. CONCLUSIONS: Identification of bacteria from lipid fingerprints obtained by the MALDI MS technique is possible and may become a useful tool in the future, especially for microorganisms that are difficult to distinguish by other methods.

Matrix- and Surface-Assisted Laser Desorption/Ionization Mass Spectrometry Methods for Urological Cancer Biomarker Discovery-Metabolomics and Lipidomics Approaches.

Urinary tract cancers, including those of the bladder, the kidneys, and the prostate, represent over 12% of all cancers, with significant global incidence and mortality rates. The continuous challenge that these cancers present necessitates the development of innovative diagnostic and prognostic methods, such as identifying specific biomarkers indicative of cancer. Biomarkers, which can be genes, proteins, metabolites, or lipids, are vital for various clinical purposes including early detection and prognosis. Mass spectrometry (MS), particularly soft ionization techniques such as electrospray ionization (ESI) and laser desorption/ionization (LDI), has emerged as a key tool in metabolic profiling for biomarker discovery, due to its high resolution, sensitivity, and ability to analyze complex biological samples. Among the LDI techniques, matrix-assisted laser desorption/ionization (MALDI) and surface-assisted laser desorption/ionization (SALDI) should be mentioned. While MALDI methodology, which uses organic compounds as matrices, is effective for larger molecules, SALDI, based on the various types of nanoparticles and nanostructures, is preferred for smaller metabolites and lipids due to its reduced spectral interference. This study highlights the application of LDI techniques, along with mass spectrometry imaging (MSI), in identifying potential metabolic and lipid biomarkers for urological cancers, focusing on the most common bladder, kidney, and prostate cancers.

Study of sample preparation influence on bacterial lipids profile in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Lipids are one of the cell components therefore it is important to be able to accurately assess them. One of the analytical techniques used to study lipid profiles is matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS). The present study attempted to select optimal conditions for sample preparation and MALDI MS analysis of bacterial lipidome in both positive and negative ion modes using different extraction protocols-Folch, Matyash, and Bligh & Dyer, solvents used to apply samples, and matrices such as 9-aminoacridine (9-AA), α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), 2-mercaptobenzothiazole (MBT), and 2,4,6-trihydroxyacetophenone (THAP). The obtained results allowed concluding that DHB or CHCA matrices are suitable for lipid analysis in the positive mode, and in the negative mode THAP or 9-AA. The most appropriate protocol for extracting lipids from bacterial cells was the Bligh & Dyer method in both ionization modes. The use of the solvent TA30, which was a mixture of acetonitrile and 0.1% trifluoroacetic acid in water, provided on the spectra a significant number of signals from lipids in all groups analyzed, such as fatty acyls, glycerolipids, and glycerophospholipids.

Comparison of the Bruker Microflex LT and Zybio EXS2600 MALDI TOF MS systems for the identification of clinical microorganisms.

The emergence of Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI TOF MS) technology has expanded the capabilities for identifying microorganisms in clinical labs, replacing traditional biochemical testing with a proteomic approach. In the present study, we compared results between the two commercial MALDI TOF MS systems, Bruker Microflex LT Biotyper and Zybio EXS2600 Ex-Accuspec, for the identification of 1979 urinary isolates by direct extraction method. Current study found that both systems identified a high percentage of isolates to at least the genus level - Bruker 95.6 % of isolates, Zybio 92.4 %. In the case of 89.5 % of all analyzed spectra, the identification results were consistent between the used devices. The highest score values and the highest percentage of spectra identified to species were obtained for gram-negative bacteria. The results show that both systems are equally good choices in terms of analytical performance for routine microbiological diagnostic procedures.

Silver Nanoparticle Targets Fabricated Using Chemical Vapor Deposition Method for Differentiation of Bacteria Based on Lipidomic Profiles in Laser Desorption/Ionization Mass Spectrometry.

The global threat of numerous infectious diseases creates a great need to develop new diagnostic methods to facilitate the appropriate prescription of antimicrobial therapy. More recently, the possibility of using bacterial lipidome analysis via laser desorption/ionization mass spectrometry (LDI-MS) as useful diagnostic tool for microbial identification and rapid drug susceptibility has received particular attention because lipids are present in large quantities and can be easily extracted similar to ribosomal proteins. Therefore, the main goal of the study was to evaluate the efficacy of two different LDI techniques-matrix-assisted (MALDI) and surface-assisted (SALDI) approaches-in the classification of the closely related Escherichia coli strains under cefotaxime addition. Bacterial lipids profiles obtained by using the MALDI technique with different matrices as well as silver nanoparticle (AgNP) targets fabricated using the chemical vapor deposition method (CVD) of different AgNP sizes were analyzed by the means of different multivariate statistical methods such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), sparse partial least squares discriminant analysis (sPLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). The analysis showed that the MALDI classification of strains was hampered by interference from matrix-derived ions. In contrast, the lipid profiles generated by the SALDI technique had lower background noise and more signals associated with the sample, allowing E. coli to be successfully classified into cefotaxime-resistant and cefotaxime-sensitive strains, regardless of the size of the AgNPs. AgNP substrates obtained using the CVD method were used for the first time for distinguishing closely related bacterial strains based on their lipidomic profiles and demonstrate high potential as a future diagnostic tool for the detection of antibiotic susceptibility.

Advanced Mass Spectrometric Techniques for the Comprehensive Study of Synthesized Silicon-Based Silyl Organic Compounds: Identifying Fragmentation Pathways and Characterization.

The primary objective of this study was to synthesize and characterize novel silicon-based silyl organic compounds in order to gain a deeper understanding of their potential applications and interactions with other compounds. Four new artificial silyl organic compounds were successfully synthesized: 1-O-(Trimethylsilyl)-2,3,4,6-tetra-O-acetyl-ß-d-glucopyranose (compound 1), 1-[(1,1-dimethylehtyl)diphenylsilyl]-1H-indole (compound 2), O-tert-butyldiphenylsilyl-(3-hydroxypropyl)oleate (compound 3), and 1-O-tert-Butyldiphenylsilyl-myo-inositol (compound 4). To thoroughly characterize these synthesized compounds, a combination of advanced mass spectrometric techniques was employed, including nanoparticle-assisted laser desorption/ionization mass spectrometry (NALDI-MS), Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), and triple quadrupole electrospray tandem mass spectrometry (QqQ ESI-MS/MS). These analytical methods enabled the accurate identification and characterization of the synthesized silyl organic compounds, providing valuable insights into their properties and potential applications. Furthermore, the electrospray ionization-Fourier transform ion cyclotron resonance-tandem mass spectrometry (ESI-FT-ICR-MS/MS) technique facilitated the proposal of fragmentation pathways for the ionized silyl organic compounds, contributing to a more comprehensive understanding of their behavior during mass spectrometric analysis. These findings suggest that mass spectrometric techniques offer a highly effective means of investigating and characterizing naturally occurring silicon-based silyl organic compounds, with potential implications for advancing research in various fields and applications in different industries.

Monoisotopic silver nanoparticles-based mass spectrometry imaging of human bladder cancer tissue: Biomarker discovery.

PURPOSE: Bladder cancer (BC) is the 10th most common form of cancer worldwide and the 2nd most common cancer of the urinary tract after prostate cancer, taking into account both incidence and prevalence. MATERIALS/METHODS: Tissues from patients with BC and also tissue extracts were analyzed by laser desorption/ionization mass spectrometry imaging (LDI-MSI) with monoisotopic silver-109 nanoparticles-enhanced target (109AgNPET). RESULTS: Univariate and multivariate statistical analyses revealed 10 metabolites that differentiated between tumor and normal tissues from six patients with diagnosed BC. Selected metabolites are discussed in detail in relation to their mass spectrometry (MS) imaging results. The pathway analysis enabled us to link these compounds with 17 metabolic pathways. CONCLUSIONS: According to receiver operating characteristic (ROC) analysis of biomarkers, 10 known metabolites were identified as the new potential biomarkers with areas under the curve (AUC) higher than >0.99. In both univariate and multivariate analysis, it was predicted that these compounds could serve as useful discriminators of cancerous versus normal tissue in patients diagnosed with BC.

Isolation and Identification of Lactococcus lactis and Weissella cibaria Strains from Fermented Beetroot and an Investigation of Their Properties as Potential Starter Cultures and Probiotics.

The presence of certain microorganisms in dairy products or silage is highly desirable. Among them are probiotic strains of lactic acid bacteria (LAB), which show many beneficial features, including antimicrobial properties that support the development of beneficial microflora; in addition, owing to their biochemical activity, they influence the nutritional, dietary, and organoleptic properties of food products. Before being placed on the market, each strain requires separate testing to determine its probiotic properties and effectiveness. The aim of this study was to isolate LAB strains from a pickled beetroot sample that could be used in the dairy industry and with the potential to be considered as a probiotic in the future. Two strains identified using the MALDI technique were selected-Lactococcus lactis and Weissella cibaria. The optimal growth conditions of the strains were determined, and their proteolytic properties were assessed with the use of the o-PA reagent and spectrophotometry. The lipid profile was analyzed using the SALDI (surface-assisted laser desorption/ionization) technique and silver nanoparticles. High-performance liquid chromatography was used to assess the ability of the strains to synthesize beneficial metabolites, such as B vitamins (B2, B3, and B9) or lactic acid, and gas chromatography was used to analyze the substances responsible for organoleptic properties. Moreover, the ability to inhibit the growth of pathogenic strains was also tested in the selected strains. Both tested strains demonstrated the desired properties of starter cultures for future use in functional food production, showing that fermented plant products can serve as valuable potential probiotic sources.

Nanostructured Layer of Silver for Detection of Small Biomolecules in Surface-Assisted Laser Desorption Ionization Mass Spectrometry.

A facile approach for the synthesis of a silver nanostructured layer for application in surface-assisted laser desorption/ionization mass spectrometry of low-molecular-weight biomolecules was developed using electrochemical deposition. The deposition was carried out using the following silver salts: trifluoroacetate, acetate and nitrate, varying the voltage and time. The plate based on trifluoroacetate at 10 V for 15 min showed intense SALDI-MS responses for standards of various classes of compounds: fatty acids, cyclitols, saccharides and lipids at a concentration of 1 nmol/spot, with values of the signal-to-noise ratio ≥50. The values of the limit of detection were 0.71 µM for adonitol, 2.08 µM for glucose and 0.39 µM for palmitic acid per spot. SEM analysis of the plate showed anisotropic flower-like microstructures with nanostructures on their surface. The reduced chemical background in the low-mass region can probably be explained by the absence of stabilizers and reducing agents during the synthesis. The plate synthesized with the developed approach showed potential for future use in the analysis of low-molecular-weight compounds of biological relevance. The absence of the need for the utilization of sophisticated equipment and the synthesis time (10 min) may benefit large-scale applications of the layer for the detection of various types of small biomolecules.

Serum and urine analysis with gold nanoparticle-assisted laser desorption/ionization mass spectrometry for renal cell carcinoma metabolic biomarkers discovery.

PURPOSE: Renal cell carcinoma (RCC) is a very aggressive and often fatal heterogeneous disease that is usually asymptomatic until late in the disease. There is an urgent need for RCC specific biomarkers that may be exploited clinically for diagnostic and prognostic purposes. MATERIALS/METHODS: Serum and urine samples were collected from patients with diagnosed kidney cancer and assessed with gold nanoparticle enhanced target (AuNPET) surface assisted-laser desorption/ionization mass spectrometry (SALDI MS) based metabolomics and statistical analysis. RESULTS: A database search allowed providing assignment of signals for the most promising features with a satisfactory value of the area under the curve and accuracy. Four potential biomarkers were found in urine and serum samples to distinguish clear cell renal cell carcinoma (ccRCC) from controls, 4 for the ccRCC with and without metastases, and 6 metabolites to distinguish low and high stages or grades. CONCLUSIONS: This pilot study suggests that serum and urine metabolomics based on AuNPET-LDI MS may be useful in distinguishing types, grades and stages of human RCC.

Metabolomic and elemental profiling of human tissue in kidney cancer.

INTRODUCTION: Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite advances in treatment, no specific biomarker is currently in use to guide therapeutic interventions. OBJECTIVES: Major aim of this work was to perform metabolomic and elemental profiling of human kidney cancer and normal tissue and to evaluate cancer biomarkers. METHODS: Metabolic and elemental profiling of tumor and adjacent normal human kidney tissue from 50 patients with kidney cancer was undertaken using three different analytical methods. RESULTS: Five potential tissue biomarkers of kidney cancer were identified and quantified using with high-resolution nuclear magnetic resonance spectroscopy. The contents of selected chemical elements in tissues was analyzed using inductively coupled plasma optical emission spectrometry. Eleven mass spectral features differentiating between kidney cancer and normal tissues were detected using silver-109 nanoparticle enhanced steel target laser desorption/ionization mass spectrometry. CONCLUSIONS: Our results, derived from the combination of ICP-OES, LDI MS and 1H NMR methods, suggest that tissue biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer.

Nuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based metabolome profiling of urine samples from kidney cancer patients.

Kidney cancer is one of the most frequently diagnosed cancers of the urinary tract in the world. Despite significant advances in kidney cancer treatment, no urine specific biomarker is currently used to guide therapeutic interventions. In an effort to address this knowledge gap, metabolic profiling of urine samples from 50 patients with kidney cancer and 50 healthy volunteers was undertaken using high-resolution proton nuclear magnetic resonance spectroscopy (1H NMR) and silver-109 nanoparticle enhanced steel target laser desorption/ionization mass spectrometry (109AgNPET LDI MS). Twelve potential urine biomarkers of kidney cancer were identified and quantified using one-dimensional (1D) 1H NMR metabolomics. Seven mass spectral features which differed significantly in abundance (p < 0.05) between kidney cancer patients and healthy volunteers were also detected using 109AgNPET-based laser desorption/ionization mass spectrometry (LDI MS). This work provides a framework to expand biomarker discovery that could be used as useful diagnostic or prognostic of kidney cancer progression.

Screening of Urinary Renal Cancer Metabolic Biomarkers with Gold Nanoparticles-assisted Laser Desorption/Ionization Mass Spectrometry.

Renal cell carcinoma is a very aggressive and often fatal disease for which there are no specific biomarkers found to date. The purpose of this work was to find features that differentiate urine metabolic profiles of healthy people and cancer patients. Laser desorption/ionization mass spectrometry on gold nanostructures-based techniques were used for the metabolic analysis of urine of 50 patients with kidney cancer. Comparison with data from 50 healthy volunteers led to the discovery of several compounds that may be considered potential renal cell carcinoma (RCC) biomarkers. Statistical analysis of data allowed for the discovery of m/z values that had the greatest impact on group differentiation. A database search enabled the assignment of signals for the most promising 15 features among them: serine, heptanol, 3-methylene-indolenine, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, phosphodimethylethanolamine, 4-methoxyphenylacetic acid, N-acetylglutamine, 3,5-dihydroxyphenylvaleric acid, hydroxyhexanoylglycine, valyl-leucine, leucyl-histidine, oleamide, 9,12,13-trihydroxyoctadecenoic acid, stearidonyl carnitine and squalene. Differences of metabolite profiles of human urine could be identified by gold nanoparticle-enhanced target (AuNPET) LDI MS method and used for the detection of renal cancer.

Nuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based serum metabolomics of kidney cancer.

Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite all the efforts made, no serum-specific biomarker is currently used in the clinical management of patients with this tumor. In this study, comprehensive high-resolution proton nuclear magnetic resonance spectroscopy (1H NMR) and silver-109 nanoparticle-enhanced steel target laser desorption/ionization mass spectrometry (109AgNPET LDI MS) approaches were conducted, in conjunction with multivariate data analysis, to discriminate the global serum metabolic profiles of kidney cancer (n = 50) and healthy volunteers (n = 49). Eight potential biomarkers have been identified using 1H NMR metabolomics and nine mass spectral features which differed significantly (p < 0.05) between kidney cancer patients and healthy volunteers, as observed by LDI MS. A partial least squares discriminant analysis (OPLS-DA) model generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from cancerous samples (Q2 > 0.7), area under the receiver operative characteristic curve (ROC) AUC > 0.96. Compared with healthy human serum, kidney cancer serum had higher levels of glucose and lower levels of choline, glycerol, glycine, lactate, leucine, myo-inositol, and 1-methylhistidine. Analysis of differences between these metabolite levels in patients with different types and grades of kidney cancer was undertaken. Our results, derived from the combination of LDI MS and 1H NMR methods, suggest that serum biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer. Graphical abstract.

Metabolomic study of human tissue and urine in clear cell renal carcinoma by LC-HRMS and PLS-DA.

Renal cell carcinoma (RCC) is the most prevalent and lethal malignancy of the kidney. Despite all the efforts made, no tissue biomarker is currently used in the clinical management of patients with kidney cancer. A search for possible biomarkers in urine for clear cell renal cell carcinoma (ccRCC) has been conducted. Non-targeted metabolomic analyses were performed on paired samples of surgically removed renal cancer and normal tissue, as well as on urine samples. Extracts were analyzed by liquid chromatography/high-resolution mass spectrometry (LC-HRMS). Hydroxybutyrylcarnitine, decanoylcarnitine, propanoylcarnitine, carnitine, dodecanoylcarnitine, and norepinephrine sulfate were found in much higher concentrations in both cancer tissues (compared with the paired normal tissue) and in urine of cancer patients (compared with control urine). In contrast, riboflavin and acetylaspartylglutamate (NAAG) were present at significantly higher concentrations both in normal kidney tissue as well as in urine samples of healthy persons. This preliminary study resulted in the identification of several compounds that may be considered potential clear cell renal carcinoma biomarkers. Graphical abstract PLS-DA plot based on LC-MS data for normal and cancer human tissue samples. The aim of this work was the identification of up- and downregulated compounds that could potentially serve as renal cancer biomarkers.

Metabolic profiling of moulds with laser desorption/ionization mass spectrometry on gold nanoparticle enhanced target.

Surface-assisted laser desorption/ionization mass spectrometry on gold nanoparticle enhanced target (AuNPET) technique was used for metabolomic analysis and secondary metabolites detection of two mould strains - Aspergillus versicolor and Penicillium chrysogenum in model conditions on microbiological malt extract agar medium. Results obtained with the use of AuNPET-based mass spectrometry technique were compared with traditional matrix-assisted laser desorption/ionization (MALDI) method based on α-cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB) matrices. Gold nanoparticle enhanced target method enabled effective ionization of microbial cellular extract ingredients without interference from the matrix and also improved calibration of spectra resulting in the detection of much higher amount of characteristic metabolites for studied organisms than MALDI.

Silver-109-based laser desorption/ionization mass spectrometry method for detection and quantification of amino acids.

A new methodology applicable for both high-resolution laser desorption/ionization mass spectrometry and mass spectrometry imaging of amino acids is presented. The matrix-assisted laser desorption ionization-type target containing monoisotopic cationic 109 Ag nanoparticles (109 AgNPs) was used for rapid mass spectrometry measurements of 11 amino acids of different chemical properties. Amino acids were directly tested in 100,000-fold concentration change conditions ranging from 100 µg/mL to 1 ng/mL which equates to 50 ng to 500 fg of amino acid per measurement spot. Limit of detection values obtained suggest that presented method/target system is among the fastest and most sensitive ones in laser mass spectrometry. Mass spectrometry imaging of spots of human blood plasma spiked with amino acids showed their surface distribution allowing optimization of quantitative measurements.

Laser desorption/ionization MS imaging of cancer kidney tissue on silver nanoparticle-enhanced target.

AIM: Renal cell carcinoma is a very aggressive and often fatal disease for which there are no specific biomarkers found to date. The purpose of work was to find substances that differentiate the cancerous and healthy tissue by using laser desorption/ionization MS imaging combined with silver nanoparticle-enhanced target. RESULTS: Ion images and comparative analysis of spectra revealed differences in intensities for several metabolites, for which their biochemical properties were discussed. Statistical analysis allowed to distinguish healthy and cancer tissue without the involvement of a pathologist. CONCLUSION: Laser desorption/ionization MS imaging technology combined with silver nanoparticle-enhanced target enabled rapid visualization of the differences between the clear cell renal cell carcinoma and the healthy part of the kidney tissue.

Laser Desorption/Ionisation Mass Spectrometry Imaging of European Yew (Taxus baccata) on Gold Nanoparticle-enhanced Target.

INTRODUCTION: European yew (Taxus baccata) is a plant known to man for centuries as it produces many interesting and important metabolites. These chemical compounds were repeatedly analysed by various analytical techniques, but none of the methods used so far allowed the localisation of the chemical compounds within the tissue and also correlation between plant morphology and its biochemistry. OBJECTIVE: Visualisation of the spatial distribution of yew metabolites with nanoparticle-based mass spectrometry imaging. METHODOLOGY: Compounds occurring on cross-section of a one-year yew sprig has been transferred to gold nanoparticle-enhanced target (AuNPET) by imprinting. The imprint was then subjected to mass spectrometry imaging analysis. RESULTS: Nanoparticle-enhanced mass spectrometry imaging made it possible to study the distribution of selected compounds in the European yew tissue, including taxanes - terpene alkaloids characteristic for the Taxus genus. Results prove that aspartate, taxinine M, baccatin IV and taxine B are located mainly in the cortex. Taxuspine W was located in the vascular tissue. Maleate was found to be located mainly in the phloem tissue. In contrast, the proton adduct of chlorophyll b was found in the external layer of twigs. CONCLUSION: The results presented a high correlation between the location of compounds and the morphology of the plant, thus giving the opportunity to see the selected details of chemical structure of the analysed tissue for the first time. Copyright © 2017 John Wiley & Sons, Ltd.

Gold nanoparticle-enhanced target for MS analysis and imaging of harmful compounds in plant, animal tissue and on fingerprint.

Gold nanoparticle-enhanced target (AuNPET) was used for detailed investigation of various materials of biological origin - human fingerprint, onion bulb and chicken liver. Analysis of these objects was focused on toxic and harmful compounds - designer drug containing pentedrone, diphenylamine in onion and potentially cancerogenic metronidazole antibiotic in liver. Detection of large quantity of endogenous compounds from mentioned objects is also shown. Most of analyzed compounds were also localized with MS imaging and relationship between their function and location was discussed. Detected compounds belong to a very wide range of chemical compounds such as saccharides, ionic and non-ionic glycerides, amino acids, fatty acids, sulfides, sulfoxides, phenols etc. Fingerprint experiments demonstrate application of AuNPET for detection, structure confirmation and also co-localization of drug with ridge patterns proving person-drug contact.