Mass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders. The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results. The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.

Yaks (Bos mutus) live in the Qinghai-Tibet plateau. The quality of yak meat is unique due to its genetic and physiological characteristics. Identification of the proteome of yak muscle could help to reveal its meat-quality properties. The common proteome, phosphoproteome, and N-glycoproteome of yak longissimus thoracis (YLT) were analyzed by liquid chromatography-tandem mass spectrometry-based shotgun analysis. A total of 1812 common proteins, 1303 phosphoproteins (3918 phosphorylation sites), and 204 N-glycoproteins (285 N-glycosylation sites) were identified in YLT. The common proteins in YLT were involved mainly in myofibril structure and energy metabolism; phosphoproteins were associated primarily with myofibril organization, regulation of energy metabolism, and signaling; N-glycoproteins were engaged mainly in extracellular-matrix organization, cellular immunity, and organismal homeostasis. We reported, for the first time, the \"panorama\" of the YLT proteome, specifically the N-glycoproteome of YLT. Our results provide essential information for understanding post mortem physiology (rigor mortis and aging) and the quality of yak meat.

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.

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

UNASSIGNED: Quantitation of the isomeric branched-chain amino acids (BCAA; valine, alloisoleucine, isoleucine, leucine) is a challenging task that typically requires derivatization steps or long runtimes if a traditional chromatographic method involving a ninhydrin ion pairing reagent is used.
UNASSIGNED: To develop and perform clinical validation of a rapid, LC-MS/MS-based targeted metabolomics assay for detection and monitoring of underivatized BCAA in human plasma.
UNASSIGNED: Various columns and modes of chromatography were tested. The final optimized method utilized mixed mode chromatography with an Intrada column under isocratic condition. Sample preparation utilized the 96-well format. Briefly, extraction solvent containing the internal standard is added to 20 uL of sample, followed by shaking and positive pressure filtering, and the resulting extracted sample is analyzed. The assay was validated based on accepted quality standards (e.g., CLIA and CLSI) for clinical assays.
UNASSIGNED: The method is linear over a wide range of concentrations, 2.0-1500 µM, with LOD of 0.60 µM and LOQ of 2.0 µM. The precision of the assay was 4-10% across analytes. The method was also validated against reference laboratories via blinded split-sample analysis and demonstrated good agreement with accuracy: 89-95% relative to the external group mean.
UNASSIGNED: We have developed a method that is accurate, rapid, and reliable for routine clinical testing of patient sample BCAA, which is used in the diagnosis and management of maple syrup urine disease (MSUD). The assay also has desirable characteristics, such as short run time, small sample volume requirement, simple sample preparation without the need for derivatization, and high throughput.

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.

BACKGROUND: A distinct serum metabonomic pattern has been previously revealed to be associated with various forms of liver disease. Here, we aimed to apply mass spectrometry to obtain serum metabolomic profiles from individuals with cholangiocarcinoma and benign hepatobiliary diseases to gain an insight into pathogenesis and search for potential early-disease biomarkers.
METHODS: Serum samples were profiled using a hydrophilic interaction liquid chromatography platform, coupled to a mass spectrometer. A total of 47 serum specimens from 8 cholangiocarcinoma cases, 20 healthy controls, 8 benign disease controls (bile duct strictures) and 11 patients with hepatocellular carcinoma (as malignant disease controls) were included. Data analysis was performed using univariate and multivariate statistics.
RESULTS: The serum metabolome disparities between the metabolite profiles from healthy controls and patients with hepatobiliary disease were predominantly related to changes in lipid and lipid-derived compounds (phospholipids, bile acids and steroids) and amino acid metabolites (phenylalanine). A metabolic pattern indicative of inflammatory response due to cirrhosis and cholestasis was associated with the disease groups. The abundance of phospholipid metabolites was altered in individuals with liver disease, particularly cholangiocarcinoma, but no significant difference was seen between profiles from patients with benign biliary strictures and cholangiocarcinoma.
CONCLUSIONS: The serum metabolome in cholangiocarcinoma exhibited changes in metabolites related to inflammation, altered energy production and phospholipid metabolism. This study serves to highlight future avenues for biomarker research in large-scale studies.

Metabolic profiling, metabonomics and metabolomics are terms coined in the late 1990s as they emerged as the newest \'omics\' technology at the time. This line of research enquiry uses spectroscopic analytical platforms, which are mainly nuclear magnetic resonance spectroscopy and mass spectrometry (MS), to acquire a snapshot of metabolites, the end products of a complex biological system. Metabolic profiling enables the detection, quantification and characterisation of metabolites in biofluids, cells and tissues. The source of these compounds can be of endogenous, microbial or exogenous origin, such as dietary or xenobiotic. This results in generating extensive, multivariate spectroscopic data that require specific statistical manipulation, typically performed using chemometric and pattern recognition techniques to reduce its dimensions, facilitate its biological interpretation and allow sample classification and biomarker discovery. Consequently, it is possible to study the dynamic metabolic changes in response to disease, intervention or environmental conditions. In this review, we describe the fundamentals of MS so that clinicians can be literate in the field and are able to interrogate the right scientific questions.

Despite many recent advances in instrumentation, the sheer complexity of biological samples remains a major challenge in large-scale proteomics experiments, reflecting both the large number of protein isoforms and the wide dynamic range of their expression levels. However, while the dynamic range of expression levels for different components of the proteome is estimated to be ∼107-8, the equivalent dynamic range of LC-MS is currently limited to ∼106. Sample pre-fractionation has therefore become routinely used in large-scale proteomics to reduce sample complexity during MS analysis and thus alleviate the problem of ion suppression and undersampling. There is currently a wide range of chromatographic techniques that can be applied as a first dimension separation. Here, we systematically evaluated the use of hydrophilic interaction liquid chromatography (HILIC), in comparison with hSAX, as a first dimension for peptide fractionation in a bottom-up proteomics workflow. The data indicate that in addition to its role as a useful pre-enrichment method for PTM analysis, HILIC can provide a robust, orthogonal and high-resolution method for increasing the depth of proteome coverage in large-scale proteomics experiments. The data also indicate that the choice of using either HILIC, hSAX, or other methods, is best made taking into account the specific types of biological analyses being performed.

Accurate measurement and functional characterization of antibody Fc domain N-linked glycans is critical to successful biosimilar development. Here, we describe the application of methods to accurately quantify and characterize the N-linked glycans of 2 IgG1 biosimilars with effector function activity, and show the potential pitfalls of using assays with insufficient resolution. Accurate glycan assessment was combined with glycan enrichment using lectin chromatography or production with glycosylation inhibitors to produce enriched pools of key glycan species for subsequent assessment in cell-based antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity effector function assays. This work highlights the challenges of developing high-quality biosimilar candidates and the need for modern biotechnology capabilities. These results show that high-quality analytics, combined with sensitive cell-based assays to study in vivo mechanisms of action, is an essential part of biosimilar development.