Single-Cell Untargeted Lipidomics Using Liquid Chromatography and Data-Dependent Acquisition after Live Cell Selection.

We report the development and validation of an untargeted single-cell lipidomics method based on microflow chromatography coupled to a data-dependent mass spectrometry method for fragmentation-based identification of lipids. Given the absence of single-cell lipid standards, we show how the methodology should be optimized and validated using a dilute cell extract. The methodology is applied to dilute pancreatic cancer and macrophage cell extracts and standards to demonstrate the sensitivity requirements for confident assignment of lipids and classification of the cell type at the single-cell level. The method is then coupled to a system that can provide automated sampling of live, single cells into capillaries under microscope observation. This workflow retains the spatial information and morphology of cells during sampling and highlights the heterogeneity in lipid profiles observed at the single-cell level. The workflow is applied to show changes in single-cell lipid profiles as a response to oxidative stress, coinciding with expanded lipid droplets. This demonstrates that the workflow is sufficiently sensitive to observing changes in lipid profiles in response to a biological stimulus. Understanding how lipids vary in single cells will inform future research into a multitude of biological processes as lipids play important roles in structural, biophysical, energy storage, and signaling functions.

Inhibition of bradykinin in SARS-CoV-2 infection: a randomised, double-blind trial of icatibant compared with placebo (ICASARS).

SARS-CoV-2 binds to ACE2 receptors and enters cells. The symptoms are cough, breathlessness, loss of taste/smell and X-ray evidence of infiltrates on chest imaging initially caused by oedema, and subsequently by a lymphocytic pneumonitis. Coagulopathy, thrombosis and hypotension occur. Worse disease occurs with age, obesity, ischaemic heart disease, hypertension and diabetes.These features may be due to abnormal activation of the contact system. This triggers coagulation and the kallikrein-kinin system, leading to accumulation of bradykinin and its derivatives, which act on receptors B1R and B2R. Receptor activation causes cough, hypotension, oedema and release of the cytokine interleukin-6 (IL-6) which recruits lymphocytes. These effects are core features seen in early SARS CoV-2 infection. METHODS AND ANALYSIS: In this study, hypoxic patients with COVID-19 with symptom onset ≤7 days will be randomised to either a bradykinin inhibitor (icatibant) or placebo. Patients and investigators will be blinded. The primary outcome will be blood oxygenation, measured by arterial blood sampling. The secondary outcome will be cardiovascular status. Retinal imaging will be performed to assess vessel size. Blood samples will be taken for measurement of inflammatory analyses including IL-6. As a separate substudy, we will also take comparator blood inflammatory samples from a COVID-19-negative cohort. ETHICS AND DISSEMINATION: The study has received the following approvals: West Midlands-Edgbaston Research Ethics Committee. Medicines and Healthcare products Regulatory Agency has issued a clinical trial authorisation. Belfast Health and Social Care Trust is the study sponsor. Results will be made available to participants upon request and findings will be presented and published. TRIAL REGISTRATION NUMBER: NCT05407597.

Single-Cell Lipidomics Using Analytical Flow LC-MS Characterizes the Response to Chemotherapy in Cultured Pancreatic Cancer Cells.

In this work, we demonstrate the development and first application of nanocapillary sampling followed by analytical flow liquid chromatography-mass spectrometry for single-cell lipidomics. Around 260 lipids were tentatively identified in a single cell, demonstrating remarkable sensitivity. Human pancreatic ductal adenocarcinoma cells (PANC-1) treated with the chemotherapeutic drug gemcitabine can be distinguished from controls solely on the basis of their single-cell lipid profiles. Notably, the relative abundance of LPC(0:0/16:0) was significantly affected in gemcitabine-treated cells, in agreement with previous work in bulk. This work serves as a proof of concept that live cells can be sampled selectively and then characterized using automated and widely available analytical workflows, providing biologically relevant outputs.

Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers.

The global COVID-19 pandemic resulted in widespread harms but also rapid advances in vaccine development, diagnostic testing, and treatment. As the disease moves to endemic status, the need to identify characteristic biomarkers of the disease for diagnostics or therapeutics has lessened, but lessons can still be learned to inform biomarker research in dealing with future pathogens. In this work, we test five sets of research-derived biomarkers against an independent targeted and quantitative Liquid Chromatography-Mass Spectrometry metabolomics dataset to evaluate how robustly these proposed panels would distinguish between COVID-19-positive and negative patients in a hospital setting. We further evaluate a crowdsourced panel comprising the COVID-19 metabolomics biomarkers most commonly mentioned in the literature between 2020 and 2023. The best-performing panel in the independent dataset-measured by F1 score (0.76) and AUROC (0.77)-included nine biomarkers: lactic acid, glutamate, aspartate, phenylalanine, ß-alanine, ornithine, arachidonic acid, choline, and hypoxanthine. Panels comprising fewer metabolites performed less well, showing weaker statistical significance in the independent cohort than originally reported in their respective discovery studies. Whilst the studies reviewed here were small and may be subject to confounders, it is desirable that biomarker panels be resilient across cohorts if they are to find use in the clinic, highlighting the importance of assessing the robustness and reproducibility of metabolomics analyses in independent populations.

Expanding the Efficacy of Fingermark Enhancement Using ToF-SIMS.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been shown to enhance fingermark recovery compared to standard processes used by police forces, but there is no data to show how generally applicable the improvement is. Additionally, ToF-SIMS can be run in either positive or negative ion mode (or both), and there is no data on which mode of operation is most effective at revealing fingerprints. This study aims to fill these gaps by using ToF-SIMS to image fingerprints deposited on two common exhibit-type surfaces (polyethylene and stainless steel) using 10 donors and ageing fingerprints in either ambient, rainwater, or underground for 1 and 5 months. In all, 120 fingerprints were imaged using ToF-SIMS, and each was run in positive and negative modes. A fingerprint expert compared the fingerprint ridge detail produced by the standard process to the ToF-SIMS images. In over 50% of the samples, ToF-SIMS was shown to improve fingerprint ridge detail visualised by the respective standard process for all surfaces tested. In over 90% of the samples, the ridge detail produced by ToF-SIMS was equivalent to standard development across all different ageing and exposure conditions. The data shows that there is a benefit to running the ToF-SIMS in both positive and negative modes, even if no ridge detail was seen in one mode.

Vascular risk factors for COVID-19 ARDS: endothelium, contact-kinin system.

SARS-CoV-2 binds to ACE2 receptors, expressed within the lungs. Risk factors for hospitalization include hypertension, diabetes, ischaemic heart disease and obesity-conditions linked by the presence of endothelial pathology. Viral infection in this setting causes increased conversion of circulating Factor XII to its active form (FXIIa). This is the first step in the contact-kinin pathway, leading to synchronous activation of the intrinsic coagulation cascade and the plasma Kallikrein-Kinin system, resulting in clotting and inflammatory lung disease. Temporal trends are evident from blood results of hospitalized patients. In the first week of symptoms the activated partial thromboplastin time (APTT) is prolonged. This can occur when clotting factors are consumed as part of the contact (intrinsic) pathway. Platelet counts initially fall, reflecting their consumption in coagulation. Lymphopenia occurs after approximately 1 week, reflecting the emergence of a lymphocytic pneumonitis [COVID-19 acute respiratory distress syndrome (ARDS)]. Intrinsic coagulation also induces the contact-kinin pathway of inflammation. A major product of this pathway, bradykinin causes oedema with ground glass opacities (GGO) on imaging in early COVID-19. Bradykinin also causes release of the pleiotrophic cytokine IL-6, which causes lymphocyte recruitment. Thromobosis and lymphocytic pneumonitis are hallmark features of COVID-19 ARDS. In this review we examine the literature with particular reference to the contact-kinin pathway. Measurements of platelets, lymphocytes and APTT should be undertaken in severe infections to stratify for risk of developing ARDS.

Airway Epithelium Senescence as a Driving Mechanism in COPD Pathogenesis.

Cellular senescence is a state of permanent cell cycle arrest triggered by various intrinsic and extrinsic stressors. Cellular senescence results in impaired tissue repair and remodeling, loss of physiological integrity, organ dysfunction, and changes in the secretome. The systemic accumulation of senescence cells has been observed in many age-related diseases. Likewise, cellular senescence has been implicated as a risk factor and driving mechanism in chronic obstructive pulmonary disease (COPD) pathogenesis. Airway epithelium exhibits hallmark features of senescence in COPD including activation of the p53/p21WAF1/CIP1 and p16INK4A/RB pathways, leading to cell cycle arrest. Airway epithelial senescent cells secrete an array of inflammatory mediators, the so-called senescence-associated secretory phenotype (SASP), leading to a persistent low-grade chronic inflammation in COPD. SASP further promotes senescence in an autocrine and paracrine manner, potentially contributing to the onset and progression of COPD. In addition, cellular senescence in COPD airway epithelium is associated with telomere dysfunction, DNA damage, and oxidative stress. This review discusses the potential mechanisms of airway epithelial cell senescence in COPD, the impact of cellular senescence on the development and severity of the disease, and highlights potential targets for modulating cellular senescence in airway epithelium as a potential therapeutic approach in COPD.

Expanding the boundaries of atomic spectroscopy at the single-cell level: critical review of SP-ICP-MS, LIBS and LA-ICP-MS advances for the elemental analysis of tissues and single cells.

Metals have a fundamental role in microbiology, and accurate methods are needed for their identification and quantification. The inability to assess cellular heterogeneity is considered an impediment to the successful treatment of different diseases. Unlike bulk approaches, single-cell analysis allows elemental heterogeneity across genetically identical populations to be related to specific biological events and to the effectiveness of drugs. Single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) can analyse single cells in suspension and measure this heterogeneity. Here we explore advances in instrumental design, compare mass analysers and discuss key parameters requiring optimisation. This review has identified that the effect of pre-treatment of cell suspensions and cell fixation approaches require further study and novel validation methods are needed as using bulk measurements is unsatisfactory. SP-ICP-MS has the advantage that a large number of cells can be analysed; however, it does not provide spatial information. Techniques based on laser ablation (LA) enable elemental mapping at the single-cell level, such as laser-induced breakdown spectroscopy (LIBS) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). The sensitivity of commercial LIBS instruments restricts its use for sub-tissue applications; however, the capacity to analyse endogenous bulk components paired with developments in nano-LIBS technology shows great potential for cellular research. LA-ICP-MS offers high sensitivity for the direct analysis of single cells, but standardisation requires further development. The hyphenation of these trace elemental analysis techniques and their coupling with multi-omic technologies for single-cell analysis have enormous potential in answering fundamental biological questions.

Spatial single cell metabolomics: Current challenges and future developments.

Single cell metabolomics is a rapidly advancing field of bio-analytical chemistry which aims to observe cellular biology with the greatest detail possible. Mass spectrometry imaging and selective cell sampling (e.g. using nanocapillaries) are two common approaches within the field. Recent achievements such as observation of cell-cell interactions, lipids determining cell states and rapid phenotypic identification demonstrate the efficacy of these approaches and the momentum of the field. However, single cell metabolomics can only continue with the same impetus if the universal challenges to the field are met, such as the lack of strategies for standardisation and quantification, and lack of specificity/sensitivity. Mass spectrometry imaging and selective cell sampling come with unique advantages and challenges which, in many cases are complementary to each other. We propose here that the challenges specific to each approach could be ameliorated with collaboration between the two communities driving these approaches.

A Multimodal Desorption Electrospray Ionisation Workflow Enabling Visualisation of Lipids and Biologically Relevant Elements in a Single Tissue Section.

The colocation of elemental species with host biomolecules such as lipids and metabolites may shed new light on the dysregulation of metabolic pathways and how these affect disease pathogeneses. Alkali metals have been the subject of extensive research, are implicated in various neurodegenerative and infectious diseases and are known to disrupt lipid metabolism. Desorption electrospray ionisation (DESI) is a widely used approach for molecular imaging, but previous work has shown that DESI delocalises ions such as potassium (K) and chlorine (Cl), precluding the subsequent elemental analysis of the same section of tissue. The solvent typically used for the DESI electrospray is a combination of methanol and water. Here we show that a novel solvent system, (50:50 (%v/v) MeOH:EtOH) does not delocalise elemental species and thus enables elemental mapping to be performed on the same tissue section post-DESI. Benchmarking the MeOH:EtOH electrospray solvent against the widely used MeOH:H2O electrospray solvent revealed that the MeOH:EtOH solvent yielded increased signal-to-noise ratios for selected lipids. The developed multimodal imaging workflow was applied to a lung tissue section containing a tuberculosis granuloma, showcasing its applicability to elementally rich samples displaying defined structural information.

Nanocapillary sampling coupled to liquid chromatography mass spectrometry delivers single cell drug measurement and lipid fingerprints.

This work describes the development of a new approach to measure drug levels and lipid fingerprints in single living mammalian cells. Nanocapillary sampling is an approach that enables the selection and isolation of single living cells under microscope observation. Here, live single cell nanocapillary sampling is coupled to liquid chromatography for the first time. This allows molecular species to be separated prior to ionisation and improves measurement precision of drug analytes. The efficiency of transferring analytes from the sampling capillary into a vial was optimised in this work. The analysis was carried out using standard flow liquid chromatography coupled to widely available mass spectrometry instrumentation, highlighting opportunities for widespread adoption. The method was applied to 30 living cells, revealing cell-to-cell heterogeneity in the uptake of different drug molecules. Using this system, we detected 14-158 lipid features per single cell, revealing the association between bedaquiline uptake and lipid fingerprints.

Improving the technological readiness of time of Flight-Secondary Ion Mass Spectrometry for enhancing fingermark recovery - towards operational deployment.

The processes routinely used by police forces to visualise fingermarks in casework may not provide sufficient ridge pattern quality to aid an investigation. Time of Flight-Secondary Ion Mass Spectrometry (ToF-SIMS) has been proposed as a technique to enhance fingermark recovery. The technique is currently designated a Category C process in the Fingermark Visualisation Manual (FVM) as it shows potential for effective fingermark visualisation but has not yet been fully evaluated. Here the sensitivity of ToF-SIMS on three common exhibit-type surfaces - paper, polyethylene and stainless-steel was compared to standard processes. An adapted Home Office grading scale was used to evaluate the efficacy of fingerprint development by ToF-SIMS and to provide a framework for comparison with standard processes. ToF-SIMS was shown to visualise more fingerprints than the respective standard process, for all surfaces tested. In addition, ToF-SIMS was applied after the standard processes and successfully enhanced the fingerprint detail, even when the standard process failed to visualise ridge detail. This demonstrates the benefit for incorporating it into current operational fingermark development workflows. Multivariate analysis (MVA), using simsMVA, was additionally explored as a method to simplify the data analysis and image generation process.

One-shot 13 C15 N-metabolic flux analysis for simultaneous quantification of carbon and nitrogen flux.

Metabolic flux is the final output of cellular regulation and has been extensively studied for carbon but much less is known about nitrogen, which is another important building block for living organisms. For the tuberculosis pathogen, this is particularly important in informing the development of effective drugs targeting the pathogen's metabolism. Here we performed 13 C15 N dual isotopic labeling of Mycobacterium bovis BCG steady state cultures, quantified intracellular carbon and nitrogen fluxes and inferred reaction bidirectionalities. This was achieved by model scope extension and refinement, implemented in a multi-atom transition model, within the statistical framework of Bayesian model averaging (BMA). Using BMA-based 13 C15 N-metabolic flux analysis, we jointly resolve carbon and nitrogen fluxes quantitatively. We provide the first nitrogen flux distributions for amino acid and nucleotide biosynthesis in mycobacteria and establish glutamate as the central node for nitrogen metabolism. We improved resolution of the notoriously elusive anaplerotic node in central carbon metabolism and revealed possible operation modes. Our study provides a powerful and statistically rigorous platform to simultaneously infer carbon and nitrogen metabolism in any biological system.

Exploring New Methods to Study and Moderate Proton Beam Damage for Multimodal Imaging on a Single Tissue Section.

Characterizing proton beam damage in biological materials is of interest to enable the integration of proton microprobe elemental mapping techniques with other imaging modalities. It is also of relevance to obtain a deeper understanding of mechanical damage to lipids in tissues during proton beam cancer therapy. We have developed a novel strategy to characterize proton beam damage to lipids in biological tissues based on mass spectrometry imaging. This methodology is applied to characterize changes to lipids in tissues ex vivo, irradiated under different conditions designed to mitigate beam damage. This work shows that performing proton beam irradiation at ambient pressure, as well as including the application of an organic matrix prior to irradiation, can reduce damage to lipids in tissues. We also discovered that, irrespective of proton beam irradiation, placing a sample in a vacuum prior to desorption electrospray ionization imaging can enhance lipid signals, a conclusion that may be of future benefit to the mass spectrometry imaging community.

Multi-Omics Reveals Mechanisms of Partial Modulation of COVID-19 Dysregulation by Glucocorticoid Treatment.

Treatments for COVID-19 infections have improved dramatically since the beginning of the pandemic, and glucocorticoids have been a key tool in improving mortality rates. The UK's National Institute for Health and Care Excellence guidance is for treatment to be targeted only at those requiring oxygen supplementation, however, and the interactions between glucocorticoids and COVID-19 are not completely understood. In this work, a multi-omic analysis of 98 inpatient-recruited participants was performed by quantitative metabolomics (using targeted liquid chromatography-mass spectrometry) and data-independent acquisition proteomics. Both 'omics datasets were analysed for statistically significant features and pathways differentiating participants whose treatment regimens did or did not include glucocorticoids. Metabolomic differences in glucocorticoid-treated patients included the modulation of cortisol and bile acid concentrations in serum, but no alleviation of serum dyslipidemia or increased amino acid concentrations (including tyrosine and arginine) in the glucocorticoid-treated cohort relative to the untreated cohort. Proteomic pathway analysis indicated neutrophil and platelet degranulation as influenced by glucocorticoid treatment. These results are in keeping with the key role of platelet-associated pathways and neutrophils in COVID-19 pathogenesis and provide opportunity for further understanding of glucocorticoid action. The findings also, however, highlight that glucocorticoids are not fully effective across the wide range of 'omics dysregulation caused by COVID-19 infections.

Untargeted saliva metabolomics by liquid chromatography-Mass spectrometry reveals markers of COVID-19 severity.

BACKGROUND: The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. METHODS: Saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques. RESULTS: Positive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified. CONCLUSIONS: In this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.

Colocation of Lipids, Drugs, and Metal Biomarkers Using Spatially Resolved Lipidomics with Elemental Mapping.

Elemental imaging is widely used for imaging cells and tissues but rarely in combination with organic mass spectrometry, which can be used to profile lipids and measure drug concentrations. Here, we demonstrate how elemental imaging and a new method for spatially resolved lipidomics (DAPNe-LC-MS, based on capillary microsampling and liquid chromatography mass spectrometry) can be used in combination to probe the relationship between metals, drugs, and lipids in discrete areas of tissues. This new method for spatial lipidomics, reported here for the first time, has been applied to rabbit lung tissues containing a lesion (caseous granuloma) caused by tuberculosis infection. We demonstrate how elemental imaging with spatially resolved lipidomics can be used to probe the association between ion accumulation and lipid profiles and verify local drug distribution.

Metabolomics Markers of COVID-19 Are Dependent on Collection Wave.

The effect of COVID-19 infection on the human metabolome has been widely reported, but to date all such studies have focused on a single wave of infection. COVID-19 has generated numerous waves of disease with different clinical presentations, and therefore it is pertinent to explore whether metabolic disturbance changes accordingly, to gain a better understanding of its impact on host metabolism and enable better treatments. This work used a targeted metabolomics platform (Biocrates Life Sciences) to analyze the serum of 164 hospitalized patients, 123 with confirmed positive COVID-19 RT-PCR tests and 41 providing negative tests, across two waves of infection. Seven COVID-19-positive patients also provided longitudinal samples 2-7 months after infection. Changes to metabolites and lipids between positive and negative patients were found to be dependent on collection wave. A machine learning model identified six metabolites that were robust in diagnosing positive patients across both waves of infection: TG (22:1_32:5), TG (18:0_36:3), glutamic acid (Glu), glycolithocholic acid (GLCA), aspartic acid (Asp) and methionine sulfoxide (Met-SO), with an accuracy of 91%. Although some metabolites (TG (18:0_36:3) and Asp) returned to normal after infection, glutamic acid was still dysregulated in the longitudinal samples. This work demonstrates, for the first time, that metabolic dysregulation has partially changed over the course of the pandemic, reflecting changes in variants, clinical presentation and treatment regimes. It also shows that some metabolic changes are robust across waves, and these can differentiate COVID-19-positive individuals from controls in a hospital setting. This research also supports the hypothesis that some metabolic pathways are disrupted several months after COVID-19 infection.

An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics.

The majority of metabolomics studies to date have utilised blood serum or plasma, biofluids that do not necessarily address the full range of patient pathologies. Here, correlations between serum metabolites, salivary metabolites and sebum lipids are studied for the first time. 83 COVID-19 positive and negative hospitalised participants provided blood serum alongside saliva and sebum samples for analysis by liquid chromatography mass spectrometry. Widespread alterations to serum-sebum lipid relationships were observed in COVID-19 positive participants versus negative controls. There was also a marked correlation between sebum lipids and the immunostimulatory hormone dehydroepiandrosterone sulphate in the COVID-19 positive cohort. The biofluids analysed herein were also compared in terms of their ability to differentiate COVID-19 positive participants from controls; serum performed best by multivariate analysis (sensitivity and specificity of 0.97), with the dominant changes in triglyceride and bile acid levels, concordant with other studies identifying dyslipidemia as a hallmark of COVID-19 infection. Sebum performed well (sensitivity 0.92; specificity 0.84), with saliva performing worst (sensitivity 0.78; specificity 0.83). These findings show that alterations to skin lipid profiles coincide with dyslipidaemia in serum. The work also signposts the potential for integrated biofluid analyses to provide insight into the whole-body atlas of pathophysiological conditions.

Potential to Use Fingerprints for Monitoring Therapeutic Levels of Isoniazid and Treatment Adherence.

A fingerprint offers a convenient, noninvasive sampling matrix for monitoring therapeutic drug use. However, a barrier to widespread adoption of fingerprint sampling is the fact that the sample volume is uncontrolled. Fingerprint samples (n = 140) were collected from patients receiving the antibiotic isoniazid as part of their treatment, as well as from a drug-naive control group (n = 50). The fingerprint samples were analyzed for isoniazid (INH) and acetylisoniazid (AcINH), using liquid chromatography high-resolution mass spectrometry. The data set was analyzed retrospectively for metabolites known to be present in eccrine sweat. INH or AcINH was detected in 89% of the fingerprints collected from patients and in 0% of the fingerprints collected from the control group. Metabolites lysine, ornithine, pyroglutamic acid, and taurine were concurrently detected alongside INH/AcINH and were used to determine whether the fingerprint sample was sufficient for testing. Given a sufficient sample volume, the fingerprint test for INH use has sensitivity, specificity, and accuracy of 100%. Normalization to taurine was found to reduce intradonor variability. Fingerprints are a novel and noninvasive approach to monitor INH therapy. Metabolites can be used as internal markers to demonstrate a sufficient sample volume for testing and reduce intradonor variability.