Multi-step preparation technique to recover multiple metabolite compound classes for in-depth and informative metabolomic analysis

The Effect of Dietary Carbohydrate and Fat Manipulation on the Metabolome and Markers of Glucose and Insulin Metabolism: A Randomised Parallel Trial

High carbohydrate, lower fat (HCLF) diets are recommended to reduce cardiometabolic disease (CMD) but low carbohydrate high fat (LCHF) diets can be just as effective. The effect of LCHF on novel insulin resistance biomarkers and the metabolome has not been fully explored. The aim of this study was to investigate the impact of an ad libitum 8-week LCHF diet compared with a HCLF diet on CMD markers, the metabolome, and insulin resistance markers. n = 16 adults were randomly assigned to either LCHF (n = 8, <50 g CHO p/day) or HCLF diet (n = 8) for 8 weeks. At weeks 0, 4 and 8, participants provided fasted blood samples, measures of body composition, blood pressure and dietary intake. Samples were analysed for markers of cardiometabolic disease and underwent non-targeted metabolomic profiling. Both a LCHF and HCLF diet significantly (p < 0.01) improved fasting insulin, HOMA IR, rQUICKI and leptin/adiponectin ratio (p < 0.05) levels. Metabolomic profiling detected 3489 metabolites with 78 metabolites being differentially regulated, for example, an upregulation in lipid metabolites following the LCHF diet may indicate an increase in lipid transport and oxidation, improving insulin sensitivity. In conclusion, both diets may reduce type 2 diabetes risk albeit, a LCHF diet may enhance insulin sensitivity by increasing lipid oxidation.

Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers

Mass spectrometry (MS) is one of the most widely used analytical techniques in many fields. Recent developments in chemical and biological researches have drawn much attention to the measurement of substances with low abundances in samples. Continuous efforts have been made consequently to further improve the sensitivity of MS. Modifications on the mass analyzers of mass spectrometers offer a direct, universal and practical way to obtain higher sensitivity. This review provides a comprehensive overview of the latest developments in mass analyzers for the improvement of mass spectrometers' sensitivity, including quadrupole, ion trap, time-of-flight (TOF) and Fourier transform ion cyclotron (FT-ICR), as well as different combinations of these mass analyzers. The advantages and limitations of different mass analyzers and their combinations are compared and discussed. This review provides guidance to the selection of suitable mass spectrometers in chemical and biological analytical applications. It is also beneficial to the development of novel mass spectrometers.

UPLC-ESI-MS/MS Based Characterization of Active Flavonoids from Apocynum spp. and Anti-Bacteria Assay

In the current study, the active flavonoids from Apocynum venetum and Apocynum hendersonii leaf were efficiently characterized using UPLC-ESI-MS/MS, and yielding the highest content of 15.35 mg/g (A. venetum) and 13.28 mg/g (A. hendersonii) respectively. The antioxidant assay in vitro showed that the isolated flavonoid ingredient groups exhibited free radical scavenging activities to DPPH, ABTS and linoleic acid. The antimicrobial assay revealed the isolated flavonoid ingredient from both A. venetum and A. hendorsonii have exerted anti-MRSA and anti-P. aeruginosa effect through disrupting cell integrity and declining ATP. In vivo assay demonstrated that these flavonoid ingredients effectively accelerated MRSA-infected and P. aeruginosa-infected Balb/c mice wound healing. In summary, these results showed that the characterized flavonoid ingredients exhibited great potential as natural antioxidant and antimicrobial agents, and shed light into future potential applications of Apocynum spp.

Comparing the effects of an exposure to a polycyclic aromatic hydrocarbon mixture versus individual polycyclic aromatic hydrocarbons during monocyte to macrophage differentiation: Mixture exposure results in altered immune metrics

Polycyclic aromatic hydrocarbons (PAHs) are generated by the incomplete combustion of carbon. Exposures correlate with systemic immune dysfunction and overall immune suppression. Real-world exposures to PAHs are almost always encountered as mixtures; however, research overwhelmingly centers on isolated exposures to a single PAH, benzo[a]pyrene (B[a]P). Here, a human monocyte line (U937) was exposed to B[a]P, benz[a]anthracene (B[a]A), or a mixture of six PAHs (6-MIX) to assess the differential toxicity on monocytes. Further, monocytes were exposed to PAHs with and without CYP1A1 inhibitors during macrophage differentiation to delineate PAH exposure and PAH metabolism-driven alterations to the immune response. U937 monocytes exposed to B[a]P, B[a]A, or 6-MIX had higher levels of cellular health and growth not observed following equimolar exposures to other individual PAHs. PAH exposures during differentiation did not alter monocyte-derived macrophage (MDM) numbers; however, B[a]A and 6-MIX exposures significantly altered M1/M2 polarization in a CYP1A1-dependent manner. U937-MDM adherence was differentially suppressed by all three PAH treatments with 6-MIX exposed U937-MDM having significantly more adhesion than U937-MDM exposed to either individual PAH. Finally, 6-MIX exposures during differentiation reduced U937-MDM endocytic function significantly less than B[a]A exposed cells. Exposure to a unique PAH mixture during U937-MDM differentiation resulted in mixture-specific alterations of pro-inflammatory markers compared to individual PAH exposures. While subtle, these differences highlight the probability that using a model PAH, B[a]P, may not accurately reflect the effects of PAH mixture exposures. Therefore, future studies should include various PAH mixtures that encompass probable real-world PAH exposures for the endpoints under investigation.

The acyl chains of phosphoinositide PIP3 alter the structure and function of nuclear receptor steroidogenic factor-1

Nuclear receptors are transcription factors that bind lipids, an event that induces a structural conformation of the receptor that favors interaction with transcriptional coactivators. The nuclear receptor steroidogenic factor-1 (SF-1, NR5A1) binds the signaling phosphoinositides PI(4,5)P2 (PIP2) and PI(3,4,5)P3 (PIP3), and our previous crystal structures showed how the phosphoinositide headgroups regulate SF-1 function. However, what role the acyl chains play in regulating SF-1 structure remains unaddressed. Here, we used X-ray crystallography with in vitro binding and functional assays to examine how the acyl chains of PIP3 regulate human SF-1 ligand-binding domain structure and function. Altering acyl chain length and unsaturation regulates apparent binding of all tested phosphoinositides to SF-1. Mass spectrometry-based lipidomics data suggest C16 and C18 phospholipids preferentially associate with SF-1 expressed ectopically in bacteria. We then solved the 2.5 Å crystal structure of SF-1 bound to dioleoyl PIP3(18:1/18:1) to compare it with a matched structure of SF-1 bound to dipalmitoyl PIP3(16:0/16:0). The dioleoyl-bound structure was severely disordered in a specific SF-1 region associated with pathogenic human polymorphisms and within the coactivator-binding region critical for SF-1 function while inducing increased sensitivity to protease digestion in solution. Validating these structural observations, in vitro functional studies showed dioleoyl PIP3 induced 6-fold poorer affinity of a peroxisome proliferator-activated receptor gamma coactivator 1-alpha coactivator peptide for SF-1 compared with dipalmitoyl PIP3. Together, these data suggest the chemical nature of the phosphoinositide acyl chains controls the ordered state of specific, clinically important structural regions in SF-1, regulating SF-1 function in vitro.

Lipidomics-Based Comparison of Molecular Compositions of Green, Yellow, and Red Bell Peppers

Identifying and annotating the molecular composition of individual foods will improve scientific understanding of how foods impact human health and how much variation exists in the molecular composition of foods of the same species. The complexity of this task includes distinct varieties and variations in natural occurring pigments of foods. Lipidomics, a sub-field of metabolomics, has emerged as an effective tool to help decipher the molecular composition of foods. For this proof-of-principle research, we determined the lipidomic profiles of green, yellow and red bell peppers (Capsicum annuum) using liquid chromatography mass spectrometry and a novel tool for automated annotation of compounds following database searches. Among 23 samples analyzed from 6 peppers (2 green, 1 yellow, and 3 red), over 8000 lipid compounds were detected with 315 compounds (106 annotated) found in all three colors. Assessments of relationships between these compounds and pepper color, using linear mixed effects regression and false discovery rate (<0.05) statistical adjustment, revealed 11 compounds differing by color. The compound most strongly associated with color was the carotenoid, β-cryptoxanthin (p-value = 7.4 × 10⁻⁵; FDR adjusted p-value = 0.0080). These results support lipidomics as a viable analytical technique to identify molecular compounds that can be used for unique characterization of foods.

Developing preliminary blood metabolomics-based biomarkers of insufficient sleep in humans

STUDY OBJECTIVE

Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep.

METHODS

We conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms.

RESULTS

The top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew's Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism.

CONCLUSION

We identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.

Recent advances in the application of metabolomics for food safety control and food quality analyses

As one of the omics fields, metabolomics has unique advantages in facilitating the understanding of physiological and pathological activities in biology, physiology, pathology, and food science. In this review, based on developments in analytical chemistry tools, cheminformatics, and bioinformatics methods, we highlight the current applications of metabolomics in food safety, food authenticity and quality, and food traceability. Additionally, the combined use of metabolomics with other omics techniques for "foodomics" is comprehensively described. Finally, the latest developments and advances, practical challenges and limitations, and requirements related to the application of metabolomics are critically discussed, providing new insight into the application of metabolomics in food analysis.

Early Mechanistic Events Induced by Low Molecular Weight Polycyclic Aromatic Hydrocarbons in Mouse Lung Epithelial Cells: A Role for Eicosanoid Signaling

Low molecular weight polycyclic aromatic hydrocarbons (LMW PAHs; < 206.3 g/mol) are under regulated environmental contaminants (eg, secondhand smoke) that lead to gap junction dysregulation, p38 MAPK activation, and increased mRNA production of inflammatory mediators, such as cytokines and cyclooxygenase (COX2), in lung epithelial cells. However, the early mechanisms involving lipid signaling through the arachidonic acid pathway and subsequent eicosanoid production leading to these downstream events are not known. Common human exposures are to mixtures of LMW PAHs, thus C10 cells (a mouse lung epithelial cell line) were exposed to a representative binary PAH mixture, 1-methylanthracene (1-MeA) and fluoranthene (Flthn), for 30 min-24 h with and without p38 and cytosolic phospholipase A2 (cPLA2) inhibitors. Cytosolic phospholipase A2 inhibition reversed PAH-induced phospho-p38 MAPK activation and gap junction dysregulation at 30 min. A significant biphasic increase in cPLA2 protein was observed at 30 min, 2, and 4 h, as well as COX2 protein at 2 and 8 h. Untargeted metabolomics demonstrated a similar trend with significantly changing metabolites at 30 min and 4 h of exposure relative to 1 h; a "cPLA2-like" subset of metabolites within the biphasic response were predominately phospholipids. Targeted metabolomics showed several eicosanoids (eg, prostaglandin D2 (PGD2), PGE2α) were significantly increased at 4, 8, and 12 h following exposure to the binary PAH mixture and this effect was p38-dependent. Finally, PAH metabolism was not observed until after 8 h. These results indicate an early lipid signaling mechanism of LMW PAH toxicity in lung epithelial cells due to parent PAH compounds.

Putative multiple reaction monitoring strategy for the comparative pharmacokinetics of postoral administration Renshen-Yuanzhi compatibility through liquid chromatography-tandem mass spectrometry

Background

Exploring the pharmacokinetic (PK) changes of various active components of single herbs and their combinations is necessary to elucidate the compatibility mechanism. However, the lack of chemical standards and low concentrations of multiple active ingredients in the biological matrix restrict PK studies.

Methods

A putative multiple reaction monitoring strategy based on liquid chromatography coupled with mass spectrometry (LC–MS) was developed to extend the PK scopes of quantification without resorting to the use of chemical standards. First, the compounds studied, including components with available reference standard (ARS) and components lacking reference standard (LRS), were preclassified to several groups according to their chemical structures. Herb decoctions were then subjected to ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry analysis with appropriate collision energy (CE) in MS² mode. Finally, multiple reaction monitoring transitions transformed from MS² of ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry were used for ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry to obtain the mass responses of LRS components. LRS components quantification was further performed by developing an assistive group-dependent semiquantitative method.

Results

The developed method was exemplified by the comparative PK process of single herbs Radix Ginseng (RG), Radix Polygala (RP), and their combinations (RG–RP). Significant changes in PK parameters were observed before and after combination.

Conclusion

Results indicated that Traditional Chinese Medicine combinations can produce synergistic effects and diminish possible toxic effects, thereby reflecting the advantages of compatibility. The proposed strategy can solve the quantitative problem of LRS and extend the scopes of PK studies.

Untargeted metabolite profiling on the water-soluble metabolites of edible bird's nest through liquid chromatography-mass spectrometry

Background and Aim

Edible bird's nest (EBN) is the nutrient-rich salivary bioproduct produced by swiftlets in Southeast Asia. Currently, researchers are exploring the therapeutic effects of EBN, such as cell growth promotion, antioxidant content, antiviral effects, bone strengthening, eyes care, and neuroprotection bioactivities. The therapeutic effects of EBN have been studied through different extraction methods but the metabolites profile of the EBN in each extract has not yet been elucidated. This study aimed to profile the water-soluble metabolites of EBN prepared in different extraction methods. Subsequently, an extraction method will be selected as an ideal extraction method for untargeted metabolite profiling on the water-soluble metabolites in EBN.

Materials and Methods

In this study, water-soluble metabolites of EBN extracted by the four extraction methods were subjected to metabolite profiling through liquid chromatography-mass spectrometry (LC-MS). The extraction methods were acid extraction(ABN), pancreatic extraction (EzBN), eHMG extraction, and spray drying of HMG extraction (pHMG). The metabolite profiles, such as the number of metabolites and their identities in each extraction method, were evaluated through LC-MS analysis.

Results

The identity of metabolites present in the four extraction methods is inconsistent. Based on LC-MS analysis, only one and six metabolites were extracted differently through EzBN and ABN, respectively, in the first pre-screening. Through the second LC-MS screening on pHMG and eHMG extraction methods, eHMG was selected as an ideal extraction method due to the highest numbers of water-soluble metabolites with an amount of 193 was detected. Besides, eHMG extraction method was able to extract sialic acid and a high percentage of secondary metabolites.

Conclusion

This study suggests that eHMG is the ideal extraction method for extracting higher number of water-soluble metabolites from EBN and could be further developed as an extraction method for industry application. In addition, this study also has identified the types of primary and secondary metabolites present in EBN.

Untargeted Differential Metabolomics Analysis Using Drift Tube Ion Mobility-Mass Spectrometry

Mass spectrometry-based metabolomics is being increasingly applied to a number of applications, including the fields of clinical, industrial, plant, and nutritional science. Several improvements have advanced the field considerably over the past decade, including ultra-high performance liquid chromatography (uHPLC), column chemistries, instruments, software, and molecular databases. However, challenges remain, including how to separate small molecules that are part of highly complex samples; this can be accomplished using chromatographic techniques or through improved resolution in the gas phase. Ion mobility-mass spectrometry (IM-MS) provides an extra dimension of gas phase separation that can result in improvements to both quantitation and compound identification. Here we describe a typical drift tube IM-MS metabolomics workflow, which includes the following steps: (1) Data acquisition, (2) Data preprocessing, (3) Molecular feature finding, and (4) Differential analysis and Molecular annotation. Overall, these methods can help investigators from a variety of scientific fields use IM-MS metabolomics as part of their own workflow.

Bronchoalveolar Lavage Fluid from COPD Patients Reveals More Compounds Associated with Disease than Matched Plasma

Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography-mass spectrometry (LC-MS) on BAL and matched plasma from 115 subjects from the SPIROMICS cohort. Regression was performed with COPD phenotypes as the outcome and metabolites as the predictor, adjusted for clinical covariates and false discovery rate. Weighted gene co-expression network analysis (WGCNA) grouped metabolites into modules which were then associated with phenotypes. K-means clustering grouped similar subjects. We detected 7939 and 10,561 compounds in BAL and paired plasma samples, respectively. FEV₁/FVC (Forced Expiratory Volume in One Second/Forced Vital Capacity) ratio, emphysema, FEV₁ % predicted, and COPD exacerbations associated with 1230, 792, eight, and one BAL compounds, respectively. Only two plasma compounds associated with a COPD phenotype (emphysema). Three BAL co-expression modules associated with FEV₁/FVC and emphysema. K-means BAL metabolomic signature clustering identified two groups, one with more airway obstruction (34% of subjects, median FEV₁/FVC 0.67), one with less (66% of subjects, median FEV₁/FVC 0.77; p < 2 × 10^-4). Associations between metabolites and COPD phenotypes are more robustly represented in BAL compared to plasma.

Impact of Blood Collection Tubes and Sample Handling Time on Serum and Plasma Metabolome and Lipidome

Background: Metabolomics is emerging as a valuable tool in clinical science. However, one major challenge in clinical metabolomics is the limited use of standardized guidelines for sample collection and handling. In this study, we conducted a pilot analysis of serum and plasma to determine the effects of processing time and collection tube on the metabolome. Methods: Blood was collected in 3 tubes: Vacutainer serum separator tube (SST, serum), EDTA (plasma) and P100 (plasma) and stored at 4 degrees for 0, 0.5, 1, 2, 4 and 24 h prior to centrifugation. Compounds were extracted using liquid-liquid extraction to obtain a hydrophilic and a hydrophobic fraction and analyzed using liquid chromatography mass spectrometry. Differences among the blood collection tubes and sample processing time were evaluated (ANOVA, Bonferroni FWER ≤ 0.05 and ANOVA, Benjamini Hochberg FDR ≤ 0.1, respectively). Results: Among the serum and plasma tubes 93.5% of compounds overlapped, 382 compounds were unique to serum and one compound was unique to plasma. There were 46, 50 and 86 compounds affected by processing time in SST, EDTA and P100 tubes, respectively, including many lipids. In contrast, 496 hydrophilic and 242 hydrophobic compounds differed by collection tube. Forty-five different chemical classes including alcohols, sugars, amino acids and prenol lipids were affected by the choice of blood collection tube. Conclusion: Our results suggest that the choice of blood collection tube has a significant effect on detected metabolites and their overall abundances. Perhaps surprisingly, variation in sample processing time has less of an effect compared to collection tube; however, a larger sample size is needed to confirm this.

Metabolomics and transcriptomics pathway approach reveals outcome-specific perturbations in COPD

Chronic obstructive pulmonary disease (COPD) comprises multiple phenotypes such as airflow obstruction, emphysema, and frequent episodes of acute worsening of respiratory symptoms, known as exacerbations. The goal of this pilot study was to test the usefulness of unbiased metabolomics and transcriptomics approaches to delineate biological pathways associated with COPD phenotypes and outcomes. Blood was collected from 149 current or former smokers with or without COPD and separated into peripheral blood mononuclear cells (PBMC) and plasma. PBMCs and plasma were analyzed using microarray and liquid chromatography mass spectrometry, respectively. Statistically significant transcripts and compounds were mapped to pathways using IMPaLA. Results showed that glycerophospholipid metabolism was associated with worse airflow obstruction and more COPD exacerbations. Sphingolipid metabolism was associated with worse lung function outcomes and exacerbation severity requiring hospitalizations. The strongest associations between a pathway and a certain COPD outcome were: fat digestion and absorption and T cell receptor signaling with lung function outcomes; antigen processing with exacerbation frequency; arginine and proline metabolism with exacerbation severity; and oxidative phosphorylation with emphysema. Overlaying transcriptomic and metabolomics datasets across pathways enabled outcome and phenotypic differences to be determined. Findings are relevant for identifying molecular targets for animal intervention studies and early intervention markers in human cohorts.

A prototypic small molecule database for bronchoalveolar lavage-based metabolomics

The analysis of bronchoalveolar lavage fluid (BALF) using mass spectrometry-based metabolomics can provide insight into lung diseases, such as asthma. However, the important step of compound identification is hindered by the lack of a small molecule database that is specific for BALF. Here we describe prototypic, small molecule databases derived from human BALF samples (n=117). Human BALF was extracted into lipid and aqueous fractions and analyzed using liquid chromatography mass spectrometry. Following filtering to reduce contaminants and artifacts, the resulting BALF databases (BALF-DBs) contain 11,736 lipid and 658 aqueous compounds. Over 10% of these were found in 100% of samples. Testing the BALF-DBs using nested test sets produced a 99% match rate for lipids and 47% match rate for aqueous molecules. Searching an independent dataset resulted in 45% matching to the lipid BALF-DB compared to<25% when general databases are searched. The BALF-DBs are available for download from MetaboLights. Overall, the BALF-DBs can reduce false positives and improve confidence in compound identification compared to when general databases are used.

High-Resolution Metabolomics Assessment of Military Personnel: Evaluating Analytical Strategies for Chemical Detection

OBJECTIVE

The aim of this study was to maximize detection of serum metabolites with high-resolution metabolomics (HRM).

METHODS

Department of Defense Serum Repository (DoDSR) samples were analyzed using ultrahigh resolution mass spectrometry with three complementary chromatographic phases and four ionization modes. Chemical coverage was evaluated by number of ions detected and accurate mass matches to a human metabolomics database.

RESULTS

Individual HRM platforms provided accurate mass matches for up to 58% of the KEGG metabolite database. Combining two analytical methods increased matches to 72% and included metabolites in most major human metabolic pathways and chemical classes. Detection and feature quality varied by analytical configuration.

CONCLUSIONS

Dual chromatography HRM with positive and negative electrospray ionization provides an effective generalized method for metabolic assessment of military personnel.

Determining Double Bond Position in Lipids Using Online Ozonolysis Coupled to Liquid Chromatography and Ion Mobility-Mass Spectrometry

The increasing focus on lipid metabolism has revealed a need for analytical techniques capable of structurally characterizing lipids with a high degree of specificity. Lipids can exist as any one of a large number of double bond positional isomers, which are indistinguishable by single-stage mass spectrometry alone. Ozonolysis reactions coupled to mass spectrometry have previously been demonstrated as a means for localizing double bonds in unsaturated lipids. Here we describe an online, solution-phase reactor using ozone produced via a low-pressure mercury lamp, which generates aldehyde products diagnostic of cleavage at a particular double bond position. This flow-cell device is utilized in conjunction with structurally selective ion mobility-mass spectrometry. The lamp-mediated reaction was found to be effective for multiple lipid species in both positive and negative ionization modes, and the conversion efficiency from precursor to product ions was tunable across a wide range (20-95%) by varying the flow rate through the ozonolysis device. Ion mobility separation of the ozonolysis products generated additional structural information and revealed the presence of saturated species in a complex mixture. The method presented here is simple, robust, and readily coupled to existing instrument platforms with minimal modifications necessary. For these reasons, application to standard lipidomic workflows is possible and aids in more comprehensive structural characterization of a myriad of lipid species.

Application of Metabolomics in Lung Research

Advancements in omics technologies have increased our potential to evaluate molecular changes in a rapid and comprehensive manner. This is especially true in mass spectrometry-based metabolomics where improvements, including ease of use, in high-performance liquid chromatography (HPLC), column chemistries, instruments, software, and molecular databases, have advanced the field considerably. Applications of this relatively new omics technology in clinical research include discovering disease biomarkers, finding new drug targets, and elucidating disease mechanisms. Here we describe a typical clinical metabolomics workflow, which includes the following steps: (1) extraction of metabolites from the lung, plasma, bronchoalveolar lavage, or cells; (2) sample analysis via liquid chromatography-mass spectrometry; and (3) data analysis using commercial and freely available software packages. Overall, the methods delineated here can help investigators use metabolomics to discovery novel biomarkers and to understand lung diseases.

Metabolomic similarities between bronchoalveolar lavage fluid and plasma in humans and mice

This observational study catalogues the overlap in metabolites between matched bronchoalveolar lavage fluid (BALF) and plasma, identifies the degree of congruence between these metabolomes in human and mouse, and determines how molecules may change in response to cigarette smoke (CS) exposure. Matched BALF and plasma was collected from mice (ambient air or CS-exposed) and humans (current or former smokers), and analyzed using mass spectrometry. There were 1155 compounds in common in all 4 sample types; fatty acyls and glycerophospholipids strongly overlapped between groups. In humans and mice, more than half of the metabolites present in BALF were also present in plasma. Mouse BALF and human BALF had a strong positive correlation with 2040 metabolites in common, suggesting that mouse models can be used to interrogate human lung metabolome changes. While power was affected by small sample size in the mouse study, the BALF metabolome appeared to be more affected by CS than plasma. CS-exposed mice showed increased plasma and BALF glycerolipids and glycerophospholipids. This is the first report cataloguing the metabolites present across mouse and human, BALF and plasma. Findings are relevant to translational studies where mouse models are used to examine human disease, and where plasma may be interrogated in lieu of BALF or lung tissue.