Untargeted LC-MS metabolomics of bronchoalveolar lavage fluid differentiates acute respiratory distress syndrome from health

Abstract

Acute respiratory distress syndrome (ARDS) remains a significant hazard to human health and is clinically challenging because there are no prognostic biomarkers and no effective pharmacotherapy. The lung compartment metabolome may detail the status of the local environment that could be useful in ARDS biomarker discovery and the identification of drug target opportunities. However, neither the utility of bronchoalveolar lavage fluid (BALF) as a biofluid for metabolomics nor the optimal analytical platform for metabolite identification is established. To address this, we undertook a study to compare metabolites in BALF samples from patients with ARDS and healthy controls using a newly developed liquid chromatography (LC)-mass spectroscopy (MS) platform for untargeted metabolomics. Following initial testing of three different high-performance liquid chromatography (HPLC) columns, we determined that reversed phase (RP)-LC and hydrophilic interaction chromatography (HILIC) were the most informative chromatographic methods because they yielded the most and highest quality data. Following confirmation of metabolite identification, statistical analysis resulted in 37 differentiating metabolites in the BALF of ARDS compared with health across both analytical platforms. Pathway analysis revealed networks associated with amino acid metabolism, glycolysis and gluconeogenesis, fatty acid biosynthesis, phospholipids, and purine metabolism in the ARDS BALF. The complementary analytical platforms of RPLC and HILIC-LC generated informative, insightful metabolomics data of the ARDS lung environment.

Figures

Figure 1

Gel electrophoresis (12.5%) of BALF proteins illustrates heterogeneity across samples. (A) The associated protein concentration of each sample. (B) Coomassie-stained gel of representative ARDS BALF samples (1–4). An equal amount of protein (30µg) was loaded for each sample. (C) Coomassie-stained gel of representative control and ARDS BALF samples loaded by volume. MWM = molecular weight marker; A = ARDS.

Figure 2

Guanosine network generated by Metscape 2 in which the abundant metabolites of ARDS BALF, xanthine and hypoxanthine, are components and urate (uric acid) is a product. Metabolites are depicted by octagons, with differentiating metabolites of ARDS BALF in dark red. Squares (grey) represent reactions with KEGG reaction identification (ID) numbers and round cornered squares (green) are the associated enzymes.

Scheme 1

Schematic of the data processing workflow. Following sample extraction (step 1) and either RP- or HILIC-MS (step 2), features were identified using an in-house metabolite library. An attempt to identify remaining unknown features was carried out by manual validation using the “Find by Feature” algorithm in Agilent Masshunter Qualitative Analysis Software (Santa Clara, CA), peak alignment between samples by mass and retention time and the “Find by Formula” feature in Masshunter (steps 3–5). To minimize gaps in the data, recursive feature identification was performed by searching the data a second time with the list of aligned features using the “Find by Formula” algorithm. The resulting features were statistically ranked (step 6) and the top 200 ranked features were utilized for additional analysis (step 7). At this point, unidentifiable features were not considered further and features with putative identifications were analytically validated using either reference standards or MS/MS (step 8). The resulting data sets were used to statistically compare ARDS BALF to healthy control BALF metabolites (step 9). BALF = bronchoalveolar lavage fluid; ARDS = acute respiratory distress syndrome; RP = reverse phase; HILIC = hydrophilic interaction chromatography.