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El pdf del artículo es la versión post-print. ; Macrophages play a relevant role ininnate and adaptive immunity depending on the balance of the stimuli received. From an analytical and functional point of view, macrophage stimulation can be segregated into three main modes, as follows: innate, classic, and alternative pathways. These differential activations result in the expression of specific sets of genes involved in the release of pro-or anti-inflammatory stimuli. In the present work, we have analyzed whether specific metabolic patterns depend on the signaling pathway activated. A[1,2-13C2]glucose tracer-based metabolomics approach has been used to characterize the metabolic flux distributions in macrophages stimulated through the classic, innate, and alternative pathways. Using this methodology combined with mass isotopomer distribution analysis of the new formed metabolites, the data show that activated macrophages are essentially glycolytic cells, and a clear cut off between the classic/innate activation and the alternative pathway exists. Interestingly, macrophage activation through LPS/IFN-γ or TLR-2, -3, -4, and -9 results in similar flux distribution patterns regardless of the pathway activated. However, stimulation through the alternative pathway has minor metabolic effects. Themolecular basis of the differences between these two types of behavior involves a switch in the expression of 6-phosphofructo-2-kinase/fructose-2,6- bisphosphatase (PFK2) from the liver type-PFK2 to the more active ubiquitous PFK2 isoenzyme, which responds to Hif-1α activation and increases fructose-2,6-bisphosphate concentration and the glycolytic flux. However, using macrophages targeted for Hif-1α, the switch of PFK2 isoenzymes still occurs in LPS/IFN-γ-activated macrophages, suggesting that this pathway regulates ubiquitous PFK2 expression through Hif-1a-independent mechanisms. Copyright © 2010 by The American Association of Immunologists, Inc. ; This work was supported by European Commission (FP7) Etherpath KBBE-Grant Agreement no. 222639, Grants SAF2005-01627, SAF2008-00164, and BFU2008- 02161 from Ministerio de Ciencia e Innovacio´n of the Spanish Government, 2005SGR00204 from the Generalitat de Catalunya, S-BIO-0283/2006 from Comunidad de Madrid, Red Temática de Investigación Sobre Cáncer (RETICC RD6/0020/ 0046) and Red Temática de Investigación Sobre Enfermedades Cardiovasculares (RECAVA RD6/0014/006), and FIS-RECAVA RD06/0014/0025. RECAVA and Ciberehd are funded by Instituto de Salud Carlos III. J.-C.R.-P. is supported by a fellowship from the University of Barcelona. ; Peer Reviewed