Reliable, robust, large-scale molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for monitoring the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a scalable analytical approach to detect viral proteins based on peptide immuno-affinity enrichment combined with liquid chromatography-mass spectrometry (LC-MS). This is a multiplexed strategy, based on targeted proteomics analysis and read-out by LC-MS, capable of precisely quantifying and confirming the presence of SARS-CoV-2 in phosphate-buffered saline (PBS) swab media from combined throat/nasopharynx/saliva samples. The results reveal that the levels of SARS-CoV-2 measured by LC-MS correlate well with their correspondingreal-time polymerase chain reaction (RT-PCR) read-out (r = 0.79). The analytical workflow shows similar turnaround times as regular RT-PCR instrumentation with a quantitative read-out of viral proteins corresponding to cycle thresholds (Ct) equivalents ranging from 21 to 34. Using RT-PCR as a reference, we demonstrate that the LC-MS-based method has 100% negative percent agreement (estimated specificity) and 95% positive percent agreement (estimated sensitivity) when analyzing clinical samples collected from asymptomatic individuals with a Ct within the limit of detection of the mass spectrometer (Ct ≤ 30). These results suggest that a scalable analytical method based on LC-MS has a place in future pandemic preparedness centers to complement current virus detection technologies.

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An ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS-MS) method for detection of 23 benzodiazepines and related compounds in whole blood was developed and validated. The method is used for screening and quantitation of benzodiazepines in whole blood received from autopsy cases and living persons. The detected compounds were alprazolam, bromazepam, brotizolam, chlordiazepoxide, demoxepam, clobazam, clonazepam, 7-aminoclonazepam, diazepam, nordiazepam, estazolam, flunitrazepam, 7-aminoflunitrazepam, lorazepam, lormetazepam, midazolam, nitrazepam, 7-aminonitrazepam, oxazepam, temazepam, triazolam, zaleplon, and zopiclone. Whole blood from drug-free volunteers was used for all experiments. Blood samples (0.200 g) were extracted with ethyl acetate at pH 9. Target drugs were quantified using a Waters ACQUITY UPLC system coupled to a Waters Quattro Premier XE triple quadrupole in positive electrospray ionization, multiple reaction monitoring mode. The use of deuterated internal standards for most compounds verified that the accuracy of the method was not influenced by matrix effects. Extraction recoveries were 73-108% for all analytes. Lower limits of quantification ranged from 0.002 to 0.005 mg/kg. Long-term imprecision (CV%) ranged from 6.0 to 18.7%. We present a fully validated UPLC-MS-MS method for 23 benzodiazepines in whole blood with a run-time of only 5 min and using only 0.200 g of whole blood.

Aim: Kynurenine metabolites are potential modulators of psychiatric disease. We aimed to develop a highly sensitive biochemical analysis of cerebrospinal fluid (CSF) tryptophan (TRP) metabolites, to investigate the stability of metabolites and to confirm our previous findings of aberrant CSF quinolinic acid (QUIN) and picolinic acid (PIC) in suicide attempters using this method. Methodology & results: Ten CSF TRP metabolites were analyzed with ultraperformance LC–MS/MS. The method showed small intra- and interassay variation. Metabolites were stable following freeze–thaw cycles. A decreased CSF PIC/QUIN ratio was found in suicide attempters. Conclusion: The feasibility of reliably determining CSF TRP metabolites were demonstrated, including separation of the two isomers PIC and nicotinic acid (NA) and the finding of a reduced PIC/QUIN ratio replicated in suicide attempters.

The kynurenine pathway of tryptophan degradation produces several neuroactive metabolites suggested to be involved in a wide variety of diseases and disorders, however, technical challenges in reliably detecting these metabolites hampers cross-comparisons. The main objective of this study was to develop an accurate, robust and precise bioanalytical method for simultaneous quantification of ten plasma kynurenine metabolites. As a secondary aim, we applied this method on blood samples taken from healthy subjects conducting 1 session of sprint interval exercise (SIE). It is well accepted that physical exercise is associated with health benefits and reduces risks of psychiatric illness, diabetes, cancer and cardiovascular disease, but also influences the peripheral and central concentrations of kynurenines. In line with this, we found that in healthy old adults ( n = 10; mean age 64 years), levels of kynurenine increased 1 hour ( P = .03) after SIE, while kynurenic acid (KYNA) concentrations were elevated after 24 hours ( P = .02). In contrast, no significant changes after exercise were seen in young adults ( n = 10; mean age 24 years). In conclusion, the described method performs well in reliably detecting all the analyzed metabolites in plasma samples. Furthermore, we also detected an age-dependent effect on the degree by which a single intense training session affects kynurenine metabolite levels.