Clinical Mass Spectrometry最新文献

Understanding levels of in utero drug exposure is important to properly customize the immediate, as well as ongoing, medical and social management needs of affected newborns. Here, we present the development of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the detection and quantification of 4 cannabinoid analytes in two neonatal matrices. The analytes targeted were Δ⁹-tetrahydrocannabinal (THC), 11-nor-9-carboxy-THC (THCA), 11-hydroxy-THC (11-OH-THC), and cannabinol (CBN). The matrices analyzed were umbilical cord tissue and meconium. A fifth analyte, cannabidiol (CBD), was also detected uniquely in meconium. Extracts were analyzed by LC-MS/MS in negative electrospray ionization mode.

Paired meconium and umbilical cord samples (i.e., one specimen from each matrix collected from each single birth, n = 46 pairs) were tested to evaluate concentration and metabolite profiles. THCA was detected in all positive (containing one or more analytes) meconium samples (n = 32). CBN, THC, 11-OH-THC, and CBD were present in 57% (n = 26), 39% (n = 18), 24% (n = 11), and 20% (n = 9), respectively. Concentrations were lower in the umbilical cord samples for all analytes (i.e., 0.27–537 ng/g for meconium and 0.1–9 ng/g for umbilical cord). In umbilical cord THCA was also detected in all positive samples (n = 19) while THC, CBN, and 11-OH-THC were present in 24% (n = 11), 17% (n = 8), and 11% (n = 5), respectively. Testing neonatal matrices for cannabinoids could be used to support studies designed to detect newborns exposed to cannabis in utero, as well as provide data that could be examined for correlations with clinical and social outcomes.

Background

Among Amish communities of North America, biallelic mutations of ST3GAL5 (c.694C > T) eliminate synthesis of GM3 and its derivative downstream a- and b-series gangliosides. Systemic ganglioside deficiency is associated with infantile onset psychomotor retardation, slow brain growth, intractable epilepsy, deafness, and cortical visual impairment. We developed a robust quantitative assay to simultaneously characterize glycan and ceramide moieties of plasma glycosphingolipids (GSLs) among ST3GAL5 c.694C > T homozygotes (n = 8), their heterozygous siblings (n = 24), and wild type control (n = 19) individuals.

Methods

Following extraction and saponification of total plasma lipids, GSLs were purified on a tC18 cartridge column, permethylated, and subjected to nanospray ionization mass spectrometry utilizing neutral loss scanning and data-dependent acquisition. Plasma GSLs were quantified against appropriate synthetic standards.

Results

Our method demonstrated linearity from 5 to 250 μl of plasma. Recovery of synthetic GSLs spiked into plasma was 99–104% with no matrix interference. Quantitative plasma GSL profiles discriminated among ST3GAL5 genotypes: GM3 and GD3 were undetectable in ST3GAL5 c.694C > T homozygotes, who had markedly elevated lactosylceramide (19.17 ± 4.20 nmol/ml) relative to heterozygous siblings (9.62 ± 2.46 nmol/ml) and wild type controls (6.55 ± 2.16 nmol/ml). Children with systemic ganglioside deficiency had a distinctive shift in ceramide composition toward higher mass species.

Conclusions

Our quantitative glycolipidomics method discriminates among ST3GAL5 c.694C > T genotypes, can reveal subtle structural heterogeneity, and represents a useful new strategy to diagnose and monitor GSL disorders in humans.

A method for analysis of 8 phenylcarboxylic acids in blood serum was developed based on the coupling of microextraction by packed sorbent, derivatization and GC–MS detection. These compounds are low molecular weight aromatic microbial metabolites that are proven and prospective indicators of sepsis in critically ill patients. Recoveries of the phenylcarboxylic acids from serum samples using microextraction by packed sorbent were 30–70%. The present method was linear (R² ≥ 0.9981) over a clinically significant range of concentrations (94–2250 µg L⁻¹/0.5–18 µM). The limits of quantification for the optimized method were 60–100 µg L⁻¹/0.4–0.7 µM for phenylpropionic, phenyllactic, 4-hydroxybenzoic and 4-hydroxyphenylacetic acids, and 160 µg L⁻¹/0.9–1.3 µM for benzoic, 4-hydroxyphenyllactic, homovanillic and 4-hydroxyphenylpropionic acids. The developed conditions were used to determine concentrations of the phenylcarboxylic acids in the most complicated matrix – serum samples of critically ill patients. Results were compared with liquid-liquid extraction and revealed a reduction in the time for sample preparation (45 min vs. 6 min) and serum (200 µL vs. 80 µL) volume. The combination of microextraction by packed sorbent and GC–MS methods, especially when fully automated could be a powerful tool for the clinical diagnosis of sepsis.

The spread of bacterial resistance has been continuously increasing in the recent decade. Multi-drug resistant (MDR) bacteria now represent one of the most worrisome public health issues, as they seriously complicate the treatment of infections, often leaving few therapeutic options.

Enterobacteria and Staphylococcus aureus are among the most common bacterial pathogens, while Bacteroides fragilis is the most frequent anaerobic pathogen. All of these species can cause severe and life-threatening infections, and represent the most frequent causes of antibiotic-resistant healthcare-associated infections worldwide, as they frequently exhibit resistance to various classes of antibiotics. Resistance to carbapenems, the last resort beta-lactam agent, is a particularly threatening problem. Achieved by different mechanisms, leads to total inefficacy of any beta-lactam agent.

During the recent years, MALDI-TOF mass spectrometry has become established as the reference method for bacterial identification in routine practice. It has proven to be a reliable and robust method to detect specific peaks in bacterial mass spectra, corresponding to specific resistance markers, enabling the instant detection of resistant isolates in real time during the standard routine identification process. Here, we investigated the performance of the subtyping module of the MALDI Biotyper system (Bruker Daltonik, GmbH) for the instant identification of KPC-producing Klebsiella pneumoniae, methicillin-resistant Staphylococcus aureus, and carbapenemase-producing Bacteroides fragilis during the identification workflow. We evaluated accuracy and potential impact on turnaround time. Furthermore, we investigated the possibility to extend the subtyping for detection of the KPC-specific marker to bacterial species other than K. pneumoniae.

For the rapid and reliable differentiation of clinically-relevant bacterial species, mass spectrometry-based methods have emerged in recent years as valid alternatives to existing techniques. Mass profiles generated by whole-cell Matrix-Assisted Laser Desorption Ionization-Time of Flight mass spectrometry have revolutionized microorganism identification and proven their potential for proteotyping at the species level. Indeed, the methodology has been widely deployed in clinical settings. However, the low resolution and dynamic range of the methodology has limited its capacity to distinguish between subspecies. This discrimination capacity is pivotal in cases where certain strains display virulence or antibiotic resistance, and for epidemiologic analyses. Moreover, sensitivity and specificity are both key parameters when attempting to discriminate between microorganisms present in complex multi-pathogenic samples. These two parameters are also essential to meet the growing interest in the characterization of microorganisms contained within even more complex samples, such as the human microbiome. Tandem mass spectrometry, with its high resolution, holds great potential for use in the real-time direct analysis of pathogens at the most relevant taxonomic rank in routine clinical practice. This review explores the numerous benefits and challenges of implementing advanced proteotyping methods, based on tandem mass spectrometry, in clinical laboratories. We provide an overview of the current applications and methodologies, while also discussing recent improvements and potential new approaches for typing, as well as their future applications.

Therapeutic drug monitoring (TDM) uses drug concentrations, primarily from plasma, to optimize drug dosing. Optimisation of drug dosing may improve treatment outcomes, reduce toxicity and reduce the risk of acquired drug resistance. The aim of this narrative review is to outline and discuss the challenges of developing multi-analyte assays for anti-tuberculosis (TB) drugs using liquid chromatography-tandem mass spectrometry (LC-MS/MS) by reviewing the existing literature in the field. Compared to other analytical methods, LC-MS/MS offers higher sensitivity and selectivity while requiring relatively low sample volumes. Additionally, multi-analyte assays are easier to perform since adequate separation and short run times are possible even when non-selective sample preparation techniques are used. However, challenges still exist, especially when optimizing LC separation techniques for assays that include analytes with differing chemical properties. Here, we have identified seven multi-analyte assays for first-line anti-TB drugs that use various solvents for sample preparation and mobile phase separation. Only two multi-analyte assays for second-line anti-TB drugs were identified (including either nine or 20 analytes), with each using different protein precipitation methods, mobile phases and columns. The 20 analyte assay did not include bedaquiline, delamanid, meropenem or imipenem. For these drugs, other assays with similar methodologies were identified that could be incorporated in the development of a future comprehensive multi-analyte assay.

TDM is a powerful methodology for monitoring patient’s individual treatments in TB programmes, but its implementation will require different approaches depending on available resources. Since TB is most-prevalent in low- and middle-income countries where resources are scarce, a patient-centred approach using sampling methods other than large volume blood draws, such as dried blood spots or saliva collection, could facilitate its adoption and use. Regardless of the methodology of collection and analysis, it will be critical that laboratory proficiency programmes are in place to ensure adequate quality control.

It is our intent that the information contained in this review will contribute to the process of assembling comprehensive multiplexed assays for the dynamic monitoring of anti-TB drug treatment in affected individuals.

Our digestive tract hosts more than a billion microorganisms comprising non-pathogenic bacteria, viruses, fungi and parasites. Understanding and characterizing the human gut microbiota has become a fundamental common theme to establish a link between its dysbiosis and certain pathologies, especially autoimmune and inflammatory diseases. Meta-Omics studies have, so far, provided great progress in this field. Genomics is conventionally used to determine the composition of the microbiota and, subsequently, metatranscriptomics lists the transcribed genes. However, to better understand the relationship between microbiota and health, protein-based studies are being applied. Proteomics enables the functional study of proteins as they are expressed by microbial communities. Metaproteomics exploits the power of mass spectrometry to identify broad protein profiles in complex samples, such as gut microbiota. The lastest technological advances in the field of mass spectrometry have opened the field of large-scale characterization of microbial proteins. Despite these hardware improvements, bioinformatics analysis remains a primary challenge. Herein, we describe the state-of-the-art concerning specific sample preparation and powerful shotgun analysis techniques. We also review several scientific studies of the human gut microbiota. Moreover, we discuss the advantages and limitations encountered in this research area, concerning new methods of sample preparation and innovative bioinformatic tools. Finally, prospects are addressed regarding the application of metaproteomic in the field of clinical microbiology and its integration with other meta-Omics.

It has been shown that bacteria in periodontally diseased patients can be recognized by the detection of volatile metabolites in the headspace of saliva by real-time ambient mass spectrometry. The aim of this study was to use this detection method to analyze the oral metabolome in diseased periodontitis patients before and after therapy to monitor disease evolution and healing events.

Twelve patients with advanced chronic periodontal disease and 12 periodontally healthy controls served as test and control groups, respectively. Clinical data, subgingival plaque samples and saliva samples were collected at baseline (BL) and 3 months after treatment. The test group received non-surgical scaling and root planing using systemic antibiotics and the control group received one session of supragingival cleaning. Saliva samples from all subjects were analyzed with ambient mass spectrometry.

Significant metabolic alterations were found in the headspace of saliva of periodontitis patients 3 months after the non-surgical periodontal treatment. Furthermore, the diseased group showed metabolic features after the treatment that were similar to the healthy control group. In addition, 29 metabolic features correlated with A. actinomycetemcomitans, 17 features correlated with P. gingivalis and one feature correlated with T. denticola.

It was shown that headspace secondary electrospray ionization – mass spectrometry allows the detection of different volatile metabolites in healthy and diseased patients. It can be concluded that this rapid and minimally invasive method could have the potential to routinely diagnose and monitor periodontal diseases in the headspace of saliva samples and, eventually, in exhaled breath.