Monitoring of system conditioning after blank injections in untargeted UPLC-MS metabolomic analysis

Abstract

Ultra-performance liquid chromatography – mass spectrometry (UPLC-MS) is widely used for untargeted metabolomics in biomedical research. To optimize the quality and precision of UPLC-MS metabolomic analysis, evaluation of blank samples for the elimination of background features is required. Although blanks are usually run either at the beginning or at the end of a sequence of samples, a systematic analysis of their effect of the instrument performance has not been properly documented. Using the analysis of two common bio-fluids (plasma and urine), we describe how the injection of blank samples within a sequence of samples may affect both the chromatographic and MS detection performance depending on several factors, including the sample matrix and the physicochemical properties of the metabolites of interest. The analysis of blanks and post-blank conditioning samples using t-tests, PCA and guided-PCA provides useful information for the elimination of background UPLC-MS features, the identification of column carry over and the selection of the number of samples required to achieve a stable performance.

Differences in milk metabolites in Malnad Gidda (Bos indicus) cows reared under pasture-based feeding system

“…In the present study, differentially expressed milk metabolites were identified in cows reared under pasturebased and stall-fed feeding systems based on two different methods (acetonitrile precipitation and methanol: chloroform) along with their associated pathways. The data acquisition standards and recommendations for untargeted metabolomics have evolved, from times of simple way of blank profile comparison based quality control (QC) strategies [20][21][22] to including multiple injections of the pooled-QC samples along with the sample acquisition batches 19 . We acquired data before the arrival of pooled-QC strategies and therefore, used blank runs as a means to prevent sample-carryover and to differentiate the sample run profiles from the blanks.…”

“…The blank run raw files from each data acquisition batches were used to assess the quality of the sample data acquisition. XCMS analysis of the blank runs along with the actual samples was carried out and the aligned peak intensity table was used in the Metaboanalyst platform to assess the clustering of the samples and the blank runs from different batches, as demonstrated by Martinez-Sena et al 19 .…”

Effect of donor human milk on host-gut microbiota and metabolic interactions in preterm infants

“…Data acquired during the analysis of those samples were discarded. The blank extract was injected twice, once during system conditioning and at the end of the measurement sequence to identify signals from other than biological origin and data clean-up [32]. The injection order of sample extracts was randomized.…”

Comparing Targeted vs. Untargeted MS2 Data-Dependent Acquisition for Peak Annotation in LC–MS Metabolomics

“…Then, the sample batch including 42 milk samples, 13 QCs (1 QC every 6 samples) and 3 blanks were analyzed ( Figure 6A). QCs were used to monitor the instrument performance, correct within-batch effects, and identify unreliable, background, and carry-over features as described elsewhere [8][9][10]. Untargeted metabolomic analysis was carried out employing a 1290 Infinity HPLC system from Agilent Technologies (CA, USA) equipped with a UPLC BEH C18 column (50 × 2.1 mm, 1.7 µm) from Waters (Wexford, Ireland).…”