Lipid network and moiety analysis for revealing enzymatic dysregulation and mechanistic alterations from lipidomics data.

Lipidomics is of growing importance for clinical and biomedical research due to many associations between lipid metabolism and diseases. The discovery of these associations is facilitated by improved lipid identification and quantification. Sophisticated computational methods are advantageous for interpreting such large-scale data for understanding metabolic processes and their underlying (patho)mechanisms. To generate hypothesis about these mechanisms, the combination of metabolic networks and graph algorithms is a powerful option to pinpoint molecular disease drivers and their interactions. Here we present lipid network explorer (LINEX$^2$), a lipid network analysis framework that fuels biological interpretation of alterations in lipid compositions. By integrating lipid-metabolic reactions from public databases, we generate dataset-specific lipid interaction networks. To aid interpretation of these networks, we present an enrichment graph algorithm that infers changes in enzymatic activity in the context of their multispecificity from lipidomics data. Our inference method successfully recovered the MBOAT7 enzyme from knock-out data. Furthermore, we mechanistically interpret lipidomic alterations of adipocytes in obesity by leveraging network enrichment and lipid moieties. We address the general lack of lipidomics data mining options to elucidate potential disease mechanisms and make lipidomics more clinically relevant.

Figure-ground assignment in pigeons: evidence for a figural benefit.

Four pigeons discriminated whether a target spot appeared on a colored figural shape or on a differently colored background by first pecking the target and then reporting its location: on the figure or the background. We recorded three dependent variables: target detection time, choice response time, and choice accuracy. The birds were faster to detect the target, to report its location, and to learn the correct response on figure trials than on background trials. Later tests suggested that the pigeons might have attended to the figural region as a whole rather than using local properties in performing the figure-background discrimination. The location of the figural region did not affect figure-ground assignment. Finally, when 4 other pigeons had to detect and peck the target without making a choice report, no figural advantage emerged in target detection time, suggesting that the birds' attention may not have been automatically summoned to the figural region.