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We present a chemical approach to profile fatty acid uptake in single cells. We use azide-modified analogues to probe the fatty acid influx and surface-immobilized dendrimers with dibenzocyclooctyne (DBCO) groups for detection. A competition between the fatty acid probes and BHQ2-azide quencher molecules generates fluorescence signals in a concentration-dependent manner. By integrating this method onto a microfluidics-based multiplex protein analysis platform, we resolved the relationships between fatty acid influx, oncogenic signaling activities, and cell proliferation in single glioblastoma cells. We found that p70S6K and 4EBP1 differentially correlated with fatty acid uptake. We validated that cotargeting p70S6K and fatty acid metabolism synergistically inhibited cell proliferation. Our work provided the first example of studying fatty acid metabolism in the context of protein signaling at single-cell resolution and generated new insights into cancer biology.

Additional file 2: Figure S1. Flood-phase wise variations in species richness (a), Shannon-Wiener diversity index (b), Simpson dominance index (c), Buzas and Gibson’s evenness index (d), and Taxonomic distinctness (e) of the wetland vegetation; Figure S2. Flood phase wise dominance–diversity curve of wetland vegetation in different sampling stations; a- Early flood phase, b- Mid-flood phase, c- Late flood phase; Station 1- inlet point 1; Station 2- middle point 1; Station 3- inlet point 2; Station 4- middle point 2 and Station 5- outlet point; Figure S3. Flood-phase wise variations in micro-topography and water flow regime of the wetland; depth (a), width (b), cross-sectional area (c), water velocity (d), and water discharge (e); Figure S4. Flood-phase wise variations in carbon stock in wetland vegetation

Additional file 1: Table S1. Distribution and density (no. of individuals ha-1) of vegetation across various sampling stations of the wetland and Kruskal-Wallis test with habitat conditions under different sampling stations as the main effect variable; Table S2. One-way analyses of variance for micro-topography, water flow regime and vegetation attributes in the wetland with flood phases as the main effect variable; Table S3. Importance Value Index (IVI) of vegetation across various sampling stations of the wetland and Kruskal-Wallis test with habitat conditions under different sampling stations as the main effect variable; Table S4. Carbon stock (Mg ha-1) of vegetation in different sampling stations of the wetland and Kruskal-Wallis test with habitat conditions under different sampling stations as the main effect variable; Table S5. Detailed results of multiple regression analysis (using backward method) for carbon stock in wetland vegetation against the micro-topographic parameters and water flow regime of the wetland; Table S6. Excluded variables in the multiple regression analysis (using backward method) for carbon stock in wetland vegetation against the micro-topographic and water flow regime of the wetland.