The turnover of brain proteins is critical for organism survival, and its perturbations are linked to pathology. Nevertheless, protein lifetimes have been difficult to obtain in vivo. They are readily measured in vitro by feeding cells with isotopically labeled amino acids, followed by mass spectrometry analyses. In vivo proteins are generated from at least two sources: labeled amino acids from the diet, and non-labeled amino acids from the degradation of pre-existing proteins. This renders measurements difficult. Here we solved this problem rigorously with a workflow that combines mouse in vivo isotopic labeling, mass spectrometry, and mathematical modeling. We also established several independent approaches to test and validate the results. This enabled us to measure the accurate lifetimes of ~3500 brain proteins. The high precision of our data provided a large set of biologically significant observations, including pathway-, organelle-, organ-, or cell-specific effects, along with a comprehensive catalog of extremely long-lived proteins (ELLPs).

BCAS1 expression identifies newly formed and actively myelinating oligodendrocytes in development, adulthood, and disease.

Highlights d A screen in Drosophila identifies glial molecules with vital functions for neurons d Depletion of glial ferritin heavy chain results in iron-mediated axonal damage d Ferritin heavy chain is secreted by oligodendrocytes in mice

Aim We aimed to investigate the impact of microglial activity and microglial FDG uptake on metabolic connectivity, since microglial activation states determine FDG–PET alterations. Metabolic connectivity refers to a concept of interacting metabolic brain regions and receives growing interest in approaching complex cerebral metabolic networks in neurodegenerative diseases. However, underlying sources of metabolic connectivity remain to be elucidated. Materials and methods We analyzed metabolic networks measured by interregional correlation coefficients (ICCs) of FDG–PET scans in WT mice and in mice with mutations in progranulin (Grn) or triggering receptor expressed on myeloid cells 2 (Trem2) knockouts (−/−) as well as in double mutant Grn−/−/Trem2−/− mice. We selected those rodent models as they represent opposite microglial signatures with disease associated microglia in Grn−/− mice and microglia locked in a homeostatic state in Trem2−/− mice; however, both resulting in lower glucose uptake of the brain. The direct influence of microglia on metabolic networks was further determined by microglia depletion using a CSF1R inhibitor in WT mice at two different ages. Within maps of global mean scaled regional FDG uptake, 24 pre-established volumes of interest were applied and assigned to either cortical or subcortical networks. ICCs of all region pairs were calculated and z-transformed prior to group comparisons. FDG uptake of neurons, microglia, and astrocytes was determined in Grn−/− and WT mice via assessment of single cell tracer uptake (scRadiotracing). Results Microglia depletion by CSF1R inhibition resulted in a strong decrease of metabolic connectivity defined by decrease of mean cortical ICCs in WT mice at both ages studied (6–7 m; p = 0.0148, 9–10 m; p = 0.0191), when compared to vehicle-treated age-matched WT mice. Grn−/−, Trem2−/− and Grn−/−/Trem2−/− mice all displayed reduced FDG–PET signals when compared to WT mice. However, when analyzing metabolic networks, a distinct increase of ICCs was observed in Grn−/− mice when compared to WT mice in cortical (p < 0.0001) and hippocampal (p < 0.0001) networks. In contrast, Trem2−/− mice did not show significant alterations in metabolic connectivity when compared to WT. Furthermore, the increased metabolic connectivity in Grn−/− mice was completely suppressed in Grn−/−/Trem2−/− mice. Grn−/− mice exhibited a severe loss of neuronal FDG uptake (− 61%, p < 0.0001) which shifted allocation of cellular brain FDG uptake to microglia (42% in Grn−/− vs. 22% in WT). Conclusions Presence, absence, and activation of microglia have a strong impact on metabolic connectivity of the mouse brain. Enhanced metabolic connectivity is associated with increased microglial FDG allocation.

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