Journal of Mass Spectrometry and Advances in the Clinical Lab最新文献

Background

Optimizing antimicrobial therapy to attain drug exposure that limits the emergence of resistance, effectively treats the infection, and reduces the risk of side effects is of a particular importance in critically ill patients, in whom normal functions are augmented or/and are infected with pathogens less sensitive to treatment. Achievement of these goals can be enhanced by therapeutic drug monitoring (TDM) for many antibiotics. A liquid chromatography tandem mass spectrometry (LC–MS/MS) method is presented here for simultaneous quantification of ten antimicrobials: cefazolin (CZO), cefepime (CEP), cefotaxime (CTA), ceftazidime (CTZ), ciprofloxacin (CIP), flucloxacillin (FLU), linezolid (LIN), meropenem (MER), piperacillin (PIP) and tazobactam (TAZ) in human plasma.

Methods

Plasma samples were precipitated with acetonitrile and injected into the LC–MS/MS. Chromatographic separation was on a Waters Acquity BEH C₁₈ column. Compounds were eluted with water and acetonitrile containing 0.1 % formic acid, using a gradient (0.5–65 % B), in 3.8 min. The flow rate was 0.4 mL/min, and the run time was 5.8 min.

Results

The calibration curves were linear across the tested concentration ranges (0.5–250, CZO, CEP, CTA, CTZ and FLU; 0.2–100, MER and TAZ; 0.1–50, CIP and LIN and 1–500 mg/L, PIP). The intra and inter-day imprecision was < 11 %. Accuracy ranged from 95 to 114 %. CTZ and MER showed ionization suppression while CIP showed ionization enhancement, which was normalized with the use of the internal standard.

Conclusion

An LC–MS/MS method for simultaneous quantification of ten antimicrobials in human plasma was developed for routine TDM.

Introduction

The use of illicitly manufactured synthetic opioids, specifically fentanyl and its analogs, has escalated exponentially in the United States over the last decade. Due to the targeted nature of drug detection methods in clinical laboratories and the ever-evolving list of synthetic opioids of concern, alternative analytical approaches are needed.

Methods

Using the fentanyl analog screening (FAS) kit produced by the Centers for Disease Control and Prevention (CDC), we developed a liquid chromatography-high resolution mass spectrometry (LC-HRMS) synthetic opioid spectral library and data acquisition method using information dependent acquisition of product ion spectra. Chromatographic retention times, limits of detection and matrix effects, in urine and serum, for the synthetic opioids in the FAS kit (n = 150) were established. All urine and serum specimens sent to a clinical toxicology laboratory for comprehensive drug testing in 2019 (n = 856) and 2021 (n = 878) were analyzed with the FAS LC-HRMS library to determine the prevalence of fentanyl analogs and other synthetic opioids, retrospectively (2019) and prospectively (2021).

Results

The limit of detection (LOD) of each opioid ranged from 1 to 10 ng/mL (median, 2.5 ng/mL) in urine and 0.25–2.5 ng/mL (median, 0.5 ng/mL) in serum. Matrix effects ranged from −79 % to 86 % (median, −37 %) for urine, following dilution and direct analysis, and −80 % to 400 % (median, 0 %) for serum, following protein precipitation. The prevalence of fentanyl/fentanyl analogs in serum samples increased slightly from 2019 to 2021 while it remained the same in urine. There were only 2 samples identified that contained a fentanyl analog without the co-occurrence of fentanyl or fentanyl metabolites. Analysis of the established MS/MS spectral library revealed characteristic fragmentation patterns in most fentanyl analogs, which can be used for structure elucidation and drug identification of future analogs.

Conclusions

The LC-HRMS method was capable of detecting fentanyl analogs in routine samples sent for comprehensive drug testing. The method can be adapted to accommodate testing needs for the evolving opioid epidemic.

Antimicrobial resistance is increasing in prevalence and there is a clear need for the development of rapid detection methods in clinical diagnostics. This review explores –omics studies utilising mass spectrometry to investigate the molecular phenotype associated with carbapenem resistance. Whilst the specific mechanisms of carbapenem resistance are well characterised, the resistant phenotype is poorly understood. Understanding how the acquisition of resistance affects cellular physiology and cell metabolism through molecular phenotyping is a necessary step towards detecting resistance by diagnostic means. In addition, this article examines the potential of mass spectrometry for the identification of resistance biomarkers through molecular profiling of bacteria. Developments in mass spectrometry platforms are expanding the biomarker-based diagnostic landscape. Targeted measures, such as high-resolution mass spectrometry coupled with chromatographic separation show considerable promise for the identification of molecular signatures and the development of a rapid diagnostic assay for the detection of carbapenem resistance.

Introduction

The measurement of insulin and C-peptide provides a valuable tool for the clinical evaluation of hypoglycemia. In research, these biomarkers are used together to better understand hyperinsulinemia, hepatic insulin clearance, and beta cell function. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an attractive approach for the analysis of insulin and C-peptide because the platform is specific, can avoid certain limitations of immunoassays, and can be multiplexed. Previously described LC-MS/MS methods for the simultaneous quantification of insulin and C-peptide measure the intact analytes and most have relied on immunoaffinity enrichment. These approaches can be limited in terms of sensitivity and interference from auto-antibodies, respectively. We have developed a novel method that does not require antibodies and uses proteolytic digestion to yield readily ionizable proteotypic peptides that enables the sensitive, specific, and simultaneous quantitation of insulin and C-peptide.

Methods

Serum samples were precipitated with acetonitrile. Analytes were enriched using solid phase extraction and then digested with endoproteinase Glu-C. Surrogate peptides for insulin and C-peptide were analyzed using targeted LC-MS/MS.

Results

Inter-day imprecision was below 20 %CV and linearity was observed down to the lower limit of quantitation for both analytes (insulin = 0.09 ng/mL, C-peptide = 0.06 ng/mL). Comparison to a commercially available insulin immunoassay (Beckman Coulter UniCel DxI 600 Access) revealed a 30% bias between methods.

Conclusion

A novel LC-MS/MS method for the simultaneous analysis of insulin and C-peptide using Glu-C digestion was developed and evaluated. A detailed standard operating procedure is provided to help facilitate implementation in other laboratories.

Introduction

Amino acids are critical biomarkers for many inborn errors of metabolism, but amino acid analysis is challenging due to the range of chemical properties inherent in these small molecules. Techniques are available for amino acid analysis, but they can suffer from long run times, laborious derivatization, and/or poor resolution of isobaric compounds.

Objective

To develop and validate a method for the quantitation of a non-derivatized free amino acid profile in both plasma and urine samples using mixed-mode chromatography and tandem mass spectrometry.

Methods

Chromatographic conditions were optimized to separate leucine, isoleucine, and allo-isoleucine and maintain analytical runtime at less than 15 min. Sample preparation included a quick protein precipitation followed by LC-MS/MS analysis. Matrix effects, interferences, linearity, carryover, acceptable dilution limits, precision, accuracy, and stability were evaluated in both plasma and urine specimen types.

Results

A total of 38 amino acids and related compounds were successfully quantitated with this method. In addition, argininosuccinic acid was qualitatively analyzed. A full clinical validation was performed that included method comparison to a reference laboratory for plasma and urine with Deming regression slopes ranging from 0.38 to 1.26.

Conclusion

This method represents an alternative to derivatization-based methods, especially in urine samples where interference from metabolites and medications is prevalent.