Fig. 1

Schematic representation of LC-MS based lamprey spatial metabolomics workflow. (a) Fourteen different lamprey tissues were carefully dissected, and metabolites were extracted from each sample tissue. Twenty microliters of 2-chloro-L-phenylalanine (0.3 mg/mL) was added to each extract as an internal standard to monitor the data quality. (b) Block randomization was used in the experimental design to reduce the prevalence of unanticipated confounders. Pooled quality control (QC) samples were dispersed every 10 samples across the multiple batches to evaluate and correct inter-batch variations. The extracts were analyzed at both positive and negative ion modes. (c) The data quality was initially assessed using the R package RawHummus. Data preprocessing steps, including peak picking, retention time (RT) alignment, peak matching, and peak filling, were then conducted to generate a data matrix containing RT, mass-to-charge ratio (m/z) values, and peak intensity. The data matrix was used for univariate and multivariate statistical analyses. Next, mass features were identified using database searches, comparisons to authentic standards, and MS/MS. Identified mass features were used to construct the lamprey spatial metabolomics database. Abbreviation: E: eye; B: brain; M: muscle; S: supraneural body; N: notochord; X: blood; Bu: buccal gland; G: gill; H: heart; L: liver; O: ovary; I: intestine; K: kidney; and T: testis. These abbreviations are in accordance with the metadata.