Development and validation of a UHPLC-HRMS-QTOF method for the detection of 132 New Psychoactive Substances and synthetic opioids, including fentanyl, in Dried Blood Spots.

Dried Blood Spots (DBS) represents a promising micro-sampling technique in the field of forensic toxicology to carry out minimally invasive blood sample collection. In DBS, cheap, fast and easy sampling is combined with effortless store and transport. These properties aimed us to develop and validate a quick and easy procedure for the detection of a large and diverse range of emerging and alarming New Psychoactive Substances (NPS). A drop of whole blood sample was collected on a DBS card and dried for 3 h, from which a total of 132 analytes (including NPS, synthetic opioids NSO and metabolites) plus 13 deuterated internal standards could be extracted using 500 µL of a methanol/acetonitrile mixture (3:1, v/v) and subsequently separated and identified by means of ultra-high-performance liquid-chromatography (UHPLC) coupled to high resolution mass spectrometry (HRMS). The extraction efficiency proved to be reproducible with yields ranging from 30% to 100% depending on the different classes of drugs. Trueness, repeatability, and intermediate precision fulfilled acceptance criteria for almost all synthetic opioids, cathinones and hallucinogens (bias and CV% below ±20%); in particular, the aggregate inter-day trueness data showed extremely limited deviation from the expected concentrations (-10% < bias% < +10%) for 114 target analytes out of 132. The calculated limits of detection ranged from 1.3 to 6.3 ng/mL, consistently exceeding the values experimentally tested. Moderate ion suppression was observed for most analytes, partly caused by blood fortification itself. Good stability of the target analytes at -20 °C, 4 °C, and 35 °C on DBS cards after drying was observed, even for long periods of time. Optimal storage condition appeared to be at 4 °C resulting in virtually no drugs degradation for up to 40 days. The novel analytical method based on DBS sampling, verified on venous whole blood real samples previously tested positive with our routine procedure, conveys remarkable potential in analytical toxicology, clinical analysis, and doping control.

Untargeted Metabolomics in Forensic Toxicology: A New Approach for the Detection of Fentanyl Intake in Urine Samples.

The misuse of fentanyl, and novel synthetic opioids (NSO) in general, has become a public health emergency, especially in the United States. The detection of NSO is often challenged by the limited diagnostic time frame allowed by urine sampling and the wide range of chemically modified analogues, continuously introduced to the recreational drug market. In this study, an untargeted metabolomics approach was developed to obtain a comprehensive "fingerprint" of any anomalous and specific metabolic pattern potentially related to fentanyl exposure. In recent years, in vitro models of drug metabolism have emerged as important tools to overcome the limited access to positive urine samples and uncertainties related to the substances actually taken, the possible combined drug intake, and the ingested dose. In this study, an in vivo experiment was designed by incubating HepG2 cell lines with either fentanyl or common drugs of abuse, creating a cohort of 96 samples. These samples, together with 81 urine samples including negative controls and positive samples obtained from recent users of either fentanyl or "traditional" drugs, were subjected to untargeted analysis using both UHPLC reverse phase and HILIC chromatography combined with QTOF mass spectrometry. Data independent acquisition was performed by SWATH in order to obtain a comprehensive profile of the urinary metabolome. After extensive processing, the resulting datasets were initially subjected to unsupervised exploration by principal component analysis (PCA), yielding clear separation of the fentanyl positive samples with respect to both controls and samples positive to other drugs. The urine datasets were then systematically investigated by supervised classification models based on soft independent modeling by class analogy (SIMCA) algorithms, with the end goal of identifying fentanyl users. A final single-class SIMCA model based on an RP dataset and five PCs yielded 96% sensitivity and 74% specificity. The distinguishable metabolic patterns produced by fentanyl in comparison to other opioids opens up new perspectives in the interpretation of the biological activity of fentanyl.

Targeted and untargeted detection of fentanyl analogues and their metabolites in hair by means of UHPLC-QTOF-HRMS.

Detection of new psychoactive substances and synthetic opioids is generally performed by means of targeted methods in mass spectrometry, as they generally provide adequate sensitivity and specificity. Unfortunately, new and unexpected compounds are continuously introduced in the illegal market of abused drugs, preventing timely updating of the analytical procedures. Moreover, the investigation of biological matrices is influenced by metabolism and excretion, in turn affecting the chance of past intake detectability. In this scenario, new opportunities are offered by both the non-targeted approaches allowed by modern UHPLC-HRMS instrumentation and the investigation of hair as the matrix of choice to detect long-term exposure to toxicologically relevant substances. In this study, we present a comprehensive and validated workflow that combines the use of UHPLC-QTOF-HRMS instrumentation with a simple hair sample extraction procedure for the detection of a variety of fentanyl analogues and metabolites. A simultaneous targeted and untargeted analysis was applied to 100 real samples taken from opiates users. MS and MS/MS data were collected for each sample. Data acquisition included a TOF-MS high-resolution scan combined with TOF-MS/MS acquisition demonstrating considerable capability to detect expected and unexpected substances even at low concentration levels. The predominant diffusion of fentanyl was confirmed by its detection in 68 hair samples. Other prevalent analogues were furanylfentanyl (28 positive samples) and acetylfentanyl (14 positive samples). Carfentanil, methylfentanyl, and ocfentanil were not found in any of the analyzed samples. Furthermore, the retrospective data analysis based on untargeted acquisition allowed the identification of two fentanyl analogues, namely ß-hydroxyfentanyl and methoxyacetylfentanyl, which were not originally included in the panel of targeted analytes.

Sheath flow SERS for chemical profiling in urine.

The molecular specificity and sensitivity of surface enhanced Raman scattering (SERS) makes it an attractive method for biomedical diagnostics. Here we present results demonstrating the utility and complications for SERS characterization in urine. The chemical fingerprint characteristics of Raman spectra suggest its use as a label free diagnostic; however, the complex composition of biological fluids presents a tremendous challenge. In particular, the limited number of surface sites and competing absorption tend to mask the presence of analytes in solution, particularly when the solution contains multiple analytes. To address these problems and characterize biological fluids we have demonstrated a sheath-flow interface for SERS detection. This sheath-flow SERS interface uses hydrodynamic focusing to confine analyte molecules eluting out of a column onto a planar SERS substrate where the molecules are detected by their intrinsic SERS signal. In this report we compare the direct detection of benzoylecgonine in urine using DSERS with chemical profiling by capillary zone electrophoresis and sheath-flow SERS detection. The SERS spectrum from the observed migration peaks can identify benzoylecgonine and other distinct spectra are also observed, suggesting improved chemical diagnostics in urine. With over 2000 reported compounds in urine, identification of each of the detected species is an enormous task. Nonetheless, these samples provide a benchmark to establish the potential clinical utility of sheath-flow SERS detection.

Online SERS detection and characterization of eight biologically-active peptides separated by capillary zone electrophoresis.

There is a need for low cost, sensitive and chemical specific detectors for routine characterization of biomolecules. In this study, we utilize sheath-flow surface-enhanced Raman scattering (SERS) to analyze a mixture of eight biologically-active peptides separated by capillary zone electrophoresis (CZE). Analysis of the SERS electropherogram resulting from online detection resolves the characteristic Raman bands attributed to the amino acid constituents of each peptide, which enables identification. The detection limit by SERS was found to be 10(-8) M. Our results suggest that the structural information obtained from the detected vibrational modes provides complementary characterization to other chemically specific detectors like mass spectrometry and improved chemical identification over other commonly used optical-based post-chromatographic detection methods. In addition, the sheath-flow SERS detection results in band narrowing in the observed electropherogram that enables distinction of closely migrating species. The results presented here indicate that this platform can provide fast, robust, reproducible, and chemical specific detection to facilitate the characterization of peptides.

Online SERS detection of the 20 proteinogenic L-amino acids separated by capillary zone electrophoresis.

A sheath-flow surface-enhanced Raman scattering (SERS) detector is demonstrated to provide chemical information enabling identification of the 20 proteinogenic L-amino acids separated by capillary zone electrophoresis (CZE). Amino acids were used to illustrate the chemical specificity of SERS detection from structurally related molecules. Analysis of the SERS electropherograms obtained from the separation and sequential online detection of six groups of structurally related amino acids shows that our sheath-flow SERS detector is able to resolve the characteristic Raman bands attributed to the amine, carboxyl, and side chain constituents. The results demonstrate the chemical information available from our detector and also provide insight into the nature of the analyte interaction with the silver SERS substrate. The spectra extracted from the SERS electropherogram of a mixture containing the 20 proteinogenic L-amino acids show unique signatures characteristic to each amino acid, thus enabling identification. The results presented here demonstrate the potential of this sheath-flow SERS detector as a general purpose method for high throughput characterization and identification following separations of complex biomolecular mixtures.

Identification of virulence determinants in influenza viruses.

To date there is no rapid method to screen for highly pathogenic avian influenza strains that may be indicators of future pandemics. We report here the first development of an oligonucleotide-based spectroscopic assay to rapidly and sensitively detect a N66S mutation in the gene coding for the PB1-F2 protein associated with increased virulence in highly pathogenic pandemic influenza viruses. 5'-Thiolated ssDNA oligonucleotides were employed as probes to capture RNA isolated from six influenza viruses, three having N66S mutations, two without the N66S mutation, and one deletion mutant not encoding the PB1-F2 protein. Hybridization was detected without amplification or labeling using the intrinsic surfaced-enhanced Raman spectrum of the DNA-RNA complex. Multivariate analysis identified target RNA binding from noncomplementary sequences with 100% sensitivity, 100% selectivity, and 100% correct classification in the test data set. These results establish that optical-based diagnostic methods are able to directly identify diagnostic indicators of virulence linked to highly pathogenic pandemic influenza viruses without amplification or labeling.

Ultrasensitive online SERS detection of structural isomers separated by capillary zone electrophoresis.

A mixture of structural isomers was separated and identified at nanomolar concentrations (∼100,000 molecules) by incorporating capillary zone electrophoresis (CZE) with a sheath flow surface-enhanced Raman scattering (SERS) detector. Baseline resolution was obtained from three structural isomers of rhodamine using a planar silver SERS substrate, demonstrating the utility of this approach for trace chemical analysis.

Ultrasensitive surface-enhanced Raman scattering flow detector using hydrodynamic focusing.

Label-free, chemical specific detection in flow is important for high throughput characterization of analytes in applications such as flow injection analysis, electrophoresis, and chromatography. We have developed a surface-enhanced Raman scattering (SERS) flow detector capable of ultrasensitive optical detection on the millisecond time scale. The device employs hydrodynamic focusing to improve SERS detection in a flow channel where a sheath flow confines analyte molecules eluted from a fused silica capillary over a planar SERS-active substrate. Increased analyte interactions with the SERS substrate significantly improve detection sensitivity. The performance of this flow detector was investigated using a combination of finite element simulations, fluorescence imaging, and Raman experiments. Computational fluid dynamics based on finite element analysis was used to optimize the flow conditions. The modeling indicates that a number of factors, such as the capillary dimensions and the ratio of the sheath flow to analyte flow rates, are critical for obtaining optimal results. Sample confinement resulting from the flow dynamics was confirmed using wide-field fluorescence imaging of rhodamine 6G (R6G). Raman experiments at different sheath flow rates showed increased sensitivity compared with the modeling predictions, suggesting increased adsorption. Using a 50 ms acquisition, a sheath flow rate of 180 µL/min, and a sample flow rate of 5 µL/min, a linear dynamic range from nanomolar to micromolar concentrations of R6G with a limit of detection (LOD) of 1 nM is observed. At low analyte concentrations, rapid analyte desorption is observed, enabling repeated and high-throughput SERS detection. The flow detector offers substantial advantages over conventional SERS-based assays such as minimal sample volumes and high detection efficiency.

Detection of genetic markers related to high pathogenicity in influenza by SERS.

We have developed a method for the detection of genetic markers associated with high pathogenicity in influenza. The assay consists of an array of 5'-thiolated ssDNA oligonucleotides immobilized on the surface of a Ag nanorod substrate that serve as capture probes for the detection of synthetic RNA sequences coding for a genetic mutation in the influenza PB1-F2 protein. Hybridization of the DNA probes to their complementary RNA sequences was detected using surface-enhanced Raman spectroscopy (SERS). Multivariate statistical analysis was used to differentiate the spectra of the complementary DNA probe-RNA target hybrids from those of the non-complementary DNA probes containing a single base pair polymorphism. Hierarchical cluster analysis (HCA) was able to distinguish with 100% accuracy the spectra of the complementary DNA probe-RNA target from the spectra of the immobilized DNA probes alone, or the DNA probes incubated with non-complementary RNA sequences. Linearity of response and limits of sensitivity of the SERS-based assays were determined using a partial least squares (PLS) regression model; detection limits computed by PLS was determined to be ~10 nM. The binding affinity of the DNA probes to their complementary RNA sequences was confirmed using enzyme-linked immunosorbent assay (ELISA); however, the detection limits observed using ELISA were approximately 10× higher (~100 nM) than those determined by PLS analysis of the SERS spectra.

Ag nanorod based surface-enhanced Raman spectroscopy applied to bioanalytical sensing.

Recent progress in substrate nanofabrication has led to the development of Ag nanorod arrays as uniform, reproducible, large area SERS-active substrates with high signal enhancement. These novel nanostructures fabricated by oblique angle vapor deposition (OAD) offer a robust platform for the rapid detection of biological agents and open new perspectives for the development and integration of biomedical diagnostic for clinical and therapeutic applications. Ag nanorod arrays have been investigated as SERS-active substrates for the detection and identification of pathogens, including bacteria and viruses, as well as to evaluate the potential of this biosensing platform for bio-recognition of high affinity events using oligonucleotide-modified substrates. This review summarizes the various nanostructured substrates designed for SERS-based applications, highlights the nanofabrication methodology used to produce Ag nanorod arrays, outlines their morphological and physical properties, and provides a summary of the most recent uses of these substrates for clinical diagnostic and biomedical applications.

Direct optical detection of viral nucleoprotein binding to an anti-influenza aptamer.

We have demonstrated label-free optical detection of viral nucleoprotein binding to a polyvalent anti-influenza aptamer by monitoring the surface-enhanced Raman (SERS) spectra of the aptamer-nucleoprotein complex. The SERS spectra demonstrated that selective binding of the aptamer-nucleoprotein complex could be differentiated from that of the aptamer alone based solely on the direct spectral signature for the aptamer-nucleoprotein complex. Multivariate statistical methods, including principal components analysis, hierarchical clustering, and partial least squares, were used to confirm statistically significant differences between the spectra of the aptamer-nucleoprotein complex and the spectra of the unbound aptamer. Two separate negative controls were used to evaluate the specificity of binding of the viral nucleoproteins to this aptamer. In both cases, no spectral changes were observed that showed protein binding to the control surfaces, indicating a high degree of specificity for the binding of influenza viral nucleoproteins only to the influenza-specific aptamer. Statistical analysis of the spectra supports this interpretation. AFM images demonstrate morphological changes consistent with formation of the influenza aptamer-nucleoprotein complex. These results provide the first evidence for the use of aptamer-modified SERS substrates as diagnostic tools for influenza virus detection in a complex biological matrix.

Detection of viral nucleoprotein binding to anti-influenza aptamers via SERS.

A highly sensitive surface-enhanced Raman (SERS)-based method for detection of influenza viral nucleoproteins is described. The intrinsic SERS spectrum of the aptamer-nucleoprotein complex provides direct evidence of binding between a polyvalent anti-influenza aptamer and the nucleoproteins of three influenza strains.

Removal of surface contamination and self-assembled monolayers (SAMs) from silver (Ag) nanorod substrates by plasma cleaning with argon.

Surface contamination of surface-enhanced Raman (SERS)-active metallic substrates has been a limitation to the utility of SERS as an analytical technique, potentially affecting surface coverage, spectral reproducibility, and analytical limits of detection. We have developed a simple and versatile cleaning method for SERS-active Ag nanorod arrays that consists of a short (4 min) exposure of the substrate to an Ar(+) plasma in a low-pressure environment. The findings presented here demonstrate that this cleaning procedure essentially eliminates organic background contamination. This procedure works equally well for self-assembled monolayers of thiolates that strongly adsorb onto Au and Ag surfaces. For SERS-active surfaces composed of arrays of Ag nanorods prepared by oblique-angle vapor deposition, we investigated the (1) Raman band intensities, (2) nanorod morphology via scanning electron microscopy, and (3) surface hydrophobicity via static contact angle measurements, as a function of exposure time of the Ag nanorods to the Ar(+) plasma. Short (4 min) exposure to Ar(+) plasma eliminated background contamination but decreased the observed SERS intensity for re-adsorbed analytes by approximately a factor of 2 while leaving the nanorod morphology essentially unchanged. Prolonged exposure to Ar(+) plasma (>10 min) resulted in substantial morphological changes of the Ag nanorod lattice and led to a decrease in the observed SERS intensities by a factor of 10. The results presented here suggest that Ar(+) plasma cleaning is an efficient process for removing carbonaceous and organic contamination as well as thiolate monolayers from SERS-active Ag surfaces, as long as the plasma conditions and exposure times are carefully monitored.