Abstract
Glial immune activity is a key feature of Alzheimer's disease (AD). Given that the blood factors heme and hemoglobin (Hb) are both elevated in AD tissues and have immunomodulatory roles, here we sought to interrogate their roles in modulating β-amyloid (Aβ)-mediated inflammatory activation of astrocytes. We discovered that heme and Hb suppress immune activity of primary mouse astrocytes by reducing expression of several proinflammatory cytokines (e.g. RANTES (regulated on activation normal T cell expressed and secreted)) and the scavenger receptor CD36 and reducing internalization of Aβ(1–42) by astrocytes. Moreover, we found that certain soluble (>75-kDa) Aβ(1–42) oligomers are primarily responsible for astrocyte activation and that heme or Hb association with these oligomers reverses inflammation. We further found that heme up-regulates phosphoprotein signaling in the phosphoinositide 3-kinase (PI3K)/Akt pathway, which regulates a number of immune functions, including cytokine expression and phagocytosis. The findings in this work suggest that dysregulation of Hb and heme levels in AD brains may contribute to impaired amyloid clearance and that targeting heme homeostasis may reduce amyloid pathogenesis. Altogether, we propose heme as a critical molecular link between amyloid pathology and AD risk factors, such as aging, brain injury, and stroke, which increase Hb and heme levels in the brain.
Keywords: amyloid-beta (AB), astrocyte, heme, hemoglobin, Alzheimer disease
Introduction
Alzheimer's disease (AD)5 affects more than 40 million people worldwide (1). Despite decades of research, we still lack an effective therapy for AD and have much left to learn about the mechanisms involved in AD pathogenesis. Neuroinflammation, in particular, is increasingly recognized as an important aspect of AD pathology (2), but whether glial activity promotes pathogenesis (3) or is neuroprotective (4, 5) remains an open question. Glial activity plays an important role in neuroprotection and maintaining tissue homeostasis by regulating metabolism (6), pruning neurites and synapses (7), and clearing pathogens such as the hallmark AD protein, β-amyloid (Aβ) (8). However, glial inflammatory activity can also promote a neurotoxic microenvironment via overexpression of neurotoxic cytokines (9–11) and reactive oxygen species (12), among other factors. Moreover, there is increasing evidence that glia efficiently clear Aβ early in AD but that they become dysfunctional with time (13–15), perhaps due to changes in environmental factors and immunomodulatory signaling during AD progression (11, 13). Whereas the role of microglia in AD has long been acknowledged, astrocytes are increasingly emerging as important modulators of AD pathology. Specifically, astrocytes have been reported to migrate toward Aβ plaques and uptake and degrade Aβ (14, 16–18), suggesting that deficits in astrocyte immune function may contribute to AD pathogenesis.
Increased brain tissue levels of the immunomodulatory blood factors heme and hemoglobin (Hb) are characteristic of AD (19–22) and are associated with a number of AD risk factors, including age, brain injury, and stroke (23, 24). Notably, analysis of post-mortem human AD tissue has shown increased heme in the temporal lobe (21) and increased Hb mRNA and protein in the inferior temporal gyrus and parietal gray and white matter (22), respectively. In fact, heme has been shown to colocalize with Aβ deposits in AD tissue (25), and Hb has been found within senile plaques and cerebral amyloid angiopathy (22). Furthermore, both heme and Hb have been reported to bind Aβ and alter aggregation state (19, 21). Studies in macrophages and endothelial cells indicate that heme stimulates the immune response via Toll-like receptor 4 (TLR4) signaling (26). Moreover, Hb can promote inflammation independently of heme (27). Despite these prior observations pointing to potential roles for heme and Hb in modulating AD pathogenesis, the effects of heme and Hb on Aβ-mediated inflammatory response and the physiologic consequences of heme and Hb interactions with Aβ remain unknown.
Herein, we sought to elucidate the effects of heme and Hb on astrocyte immune function and delineate how heme and Hb specifically affect astrocyte inflammatory response to Aβ. Surprisingly, our data reveal that heme and Hb, which are pro-inflammatory in macrophages (26, 28, 29), largely suppress the Aβ-mediated astrocyte expression of a broad collection of pro-inflammatory cytokines. Moreover, we determined that heme and Hb reduced expression of the scavenger receptor CD36 and internalization of Aβ(1–42) and other substrates. Our results further demonstrate that heme or Hb alters Aβ(1–42)-mediated inflammatory activation via dual mechanisms that involve both modulation of immune signaling and physical association with Aβ(1–42). With respect to signaling, heme and Hb modulate the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)/Akt pathway. With respect to heme/Hb interactions with Aβ(1–42), we find that a high-molecular weight (HMW) oligomeric soluble Aβ species is primarily responsible for inflammatory activation of astrocytes, and this species is no longer inflammatory when associated with heme or Hb. In total, our data reveal that heme and Hb are able to reduce astrocyte activation and phagocytic capacity by direct cell signaling and through interactions with Aβ(1–42). Given that Hb and heme levels are increased in AD brains (19, 20), our findings represent a new paradigm for understanding astrocyte dysfunction and neuroinflammation in AD. They specifically suggest that targeting heme/Hb homeostatic machinery could represent a viable therapeutic strategy for AD. Last, the suite of cell biological and biophysical methods that we employed can be easily adapted to probe the effects of a multitude of molecules found to be dysregulated in the AD brain for their effects on neuroinflammation.
Results
Heme and hemoglobin modulate Aβ(1–42)-induced astrocyte inflammatory cytokine expression
We used primary mouse astrocytes generated from CD-1 pups as a model system to delineate the effects of heme and Hb on Aβ(1–42)-induced inflammatory response. Although neonatal-derived astrocyte cultures are widely used, microglial contamination is a concern in assessing inflammatory response (30). We did not, however, detect expression of the microglia-specific marker, Iba-1, in Aβ(1–42)-stimulated cultures (Fig. S1), suggesting that our cultures were not significantly contaminated with microglia. Because physiologic concentrations of Aβ(1–42) are reported to be in the pico- to nanomolar range (31–34), we used 50 nm Aβ(1–42) for all culture conditions. The concentrations of heme and Hb have not been defined in Alzheimer's disease, although they are thought to be on the order of 10–100 μm in hemolytic disorders (29, 35). Thus, we tested our primary conditions at equimolar 50 nm heme or Hb and verified using high 25 μm concentrations. Heme or Hb was added to astrocyte culture medium containing fetal bovine serum, which has ∼60 nm heme and <10 nm Hb (Fig. S2). The heme present in serum is not bioavailable to Aβ(1–42), because it is almost all exclusively associated with high-affinity hemoproteins, Hb or hemopexin, which exhibit tight dissociation constants (KD) for heme, KD < 100 fm (36).
Canonical markers of astrocyte activation, such as glial fibrillary acidic protein (GFAP), are not reliable activation markers in culture due to high baseline expression (37, 38). Therefore, we used a multiplexed immunoassay to robustly quantify astrocyte activation in terms of protein expression of 32 cytokines into the culture medium (EMD Millipore, Billerica, MA). As expected, astrocytes conditioned for 24 h with Aβ(1–42) increased expression of numerous pro-inflammatory cytokines, including IL-1β (39), RANTES (40), and GM-CSF (41) (Fig. 1a). Because we measured a total of 32 cytokines, we aimed to create a cytokine profile that could be used to discern differences between groups. To do so, we utilized a discriminant partial least squares regression (D-PLSR) analysis (42). We have previously used this approach to identify a cytokine profile distinguishing post-mortem human control and AD brain tissues (9). Applying this analysis here identified an axis called a latent variable (LV1) that distinguished Aβ(1–42) conditioned wells from all other conditions (Fig. 1b). The LV1 axis consisted of a profile of cytokines that were most different between groups (Fig. 1c), whereas LV2 defined a second axis of cytokines that were most different in the heme + Aβ(1–42) condition (Fig. 1d). By plotting each sample in terms of its score on LV1 (representing a composite indicator of cytokine expression), we found that Aβ(1–42)-induced cytokine expression was significantly increased compared with controls or Aβ(1–42) wells that were co-treated with heme or Hb (Fig. 1e). Plotting of selected individual cytokines revealed a trend where certain pro-inflammatory cytokines, such as RANTES and GM-CSF (43), were down-regulated by heme and Hb, whereas others, such as KC (44) and MCP-1 (45), were not substantially modulated (Fig. 1f), reflecting our multivariate analysis (Fig. 1, b–e).
Figure 1.
Heme and Hb modulate cytokine protein expression. a, quantification of 32 cytokines expressed into the medium of primary mouse astrocyte cultures via Luminex analysis. Each column is z-scored. Compared with vehicle control (0.001% NH4OH), cytokine expression is increased in response to 50 nm Aβ(1–42). Moreover, co-conditioning of Aβ(1–42) with either 50 nm heme or 50 nm Hb suppressed cytokine expression (n = 3 wells). b, a D-PLSR analysis, generated from the cytokine expression data set, identified a latent variable (LV1), based on cytokine expression, which separates Aβ(1–42)-only–treated astrocytes from all other conditions along the horizontal axis. c, LV1 depicts a linear combination of cytokines that correlate with the Aβ(1–42)-only condition and identifies RANTES as the top correlate with Aβ(1–42)-treated astrocytes in the panel of 32 cytokines. d, LV2 depicts a linear combination of cytokines that correlate with the heme + Aβ(1–42) condition. e, plotting LV1 scores for each group shows that the LV1 profile segregates Aβ(1–42)-treated astrocytes from all other conditions (n = 3, p = 0.0087; vehicle versus Aβ(1–42)). f, plotting cytokine expression for six consistently measured cytokines, RANTES, M-CSF, IL-1β, IP-10, KC, and MCP-1, reveals that heme and Hb suppress expression of some, but not all, cytokines. Data are presented as mean ± S.E. (error bars). **, p < 0.01; ordinary one-way ANOVA with Dunnett's post hoc test. a.u., arbitrary units.
We additionally conditioned astrocytes with a high concentration (25 μm) of heme associated with hemolytic disorders (29, 35), which promotes cytokine expression in the RAW264.7 macrophage cell line (Fig. S3a). Analysis of the same panel of 32 cytokines in astrocytes demonstrated that 25 μm heme produced no change in cytokine expression compared with vehicle (Fig. S3b). Moreover, when applied together with Aβ(1–42), 25 μm heme further reduced cytokine expression compared with treatment with 50 nm heme + Aβ(1–42) (Fig. S3b). Applying the same concentrations of heme to the SIM-A9 cell line (46), we found that neither low nor high concentrations of heme alone were highly pro-inflammatory (Fig. S3c). Moreover, 50 nm heme or Hb suppressed cytokine expression compared with treatment with Aβ(1–42) alone. In contrast, 25 μm heme applied together with Aβ(1–42) amplified cytokine expression compared with treatment with Aβ(1–42) alone (Fig. S3c).
Together, these data demonstrate that heme and Hb reduce astrocyte inflammatory response as quantified by cytokine expression. Moreover, in contrast to microglia and macrophages, this anti-inflammatory effect is exerted on astrocytes by both low and high concentrations of heme.
Heme and hemoglobin reduce astrocyte uptake of Aβ(1–42) and phagocytic capacity
Because heme and Hb reduced Aβ(1–42)-induced expression of multiple inflammatory cytokines (Fig. 1), we next investigated their effects on astrocytic capacity to scavenge Aβ(1–42) and other substrates. First, we conditioned astrocytes with 50 nm Aβ(1–42), either alone or together with heme or Hb. We then used immunocytochemistry to stain for Aβ(1–42) using the 6E10 antibody (BioLegend, San Diego, CA). Astrocytes treated with Aβ(1–42) alone showed Aβ(1–42) aggregates within the plane of the cell (Fig. 2a, arrows). In contrast, astrocytes co-conditioned with heme, and to a lesser extent Hb, showed little Aβ(1–42) within the plane of the cell and substantial labeling on the cell surface, suggesting that heme and Hb suppress Aβ(1–42) internalization (Fig. 2a, arrows).
Figure 2.
Heme and Hb modulate astrocyte internalization of Aβ(1–42) and phagocytic capacity. a, confocal imaging of primary astrocytes incubated with 50 nm Aβ(1–42) (left) stained with DAPI (blue), Alexa Fluor 555 phalloidin (red), and anti-Aβ 6E10 (green) reveals Aβ(1–42) within the plane of the cell. Co-incubation with 50 nm heme (center) or 50 nm Hb (right) reduced Aβ(1–42) internalization. Arrows indicate Aβ(1–42) localization inside the cell (left) or on the cell surface (center, right). b, primary astrocytes, preincubated with 50 nm heme or 50 nm Hb, were incubated with trypan-quenched, fluorescein-labeled, killed E. coli particles. Particle internalization, measured by fluorescence intensity using a microplate reader, significantly decreased upon incubation with 50 nm Hb (n = 28 wells, p = 0.0129; vehicle versus Hb). c, primary astrocytes, preincubated with 50 nm heme or 50 nm Hb, were incubated with pH-sensitive pHrodo beads to assess phagocytic capacity. The percentage of total cells uptaking beads, quantified by fluorescence microscopy (Fig. S4), was significantly reduced upon treatment with Hb (n = 30 images; vehicle and Hb, n = 33 images; heme, p = 0.000025; vehicle versus Hb). d, primary astrocytes conditioned with vehicle control, 50 nm heme, and 50 nm Hb were lysed and analyzed via Western blotting for CD36 expression. Quantification, normalized by α-tubulin, reveals that both heme and Hb down-regulate expression of CD36 (n = 4 wells; p = 0.0076; vehicle versus heme, p = 0.0269; vehicle versus Hb). e, Western blotting depicting CD36 expression. Data are presented as mean ± S.E. (error bars). *, p < 0.05; **, p < 0.01; ordinary one-way ANOVA with Dunnett's post hoc test. ****, p < 0.0001; Kruskal-Wallis ANOVA with Dunn's post hoc test. Scale bars, 50 μm. a.u., arbitrary units.
To determine whether heme or Hb affected scavenger activity for other substrates, we next interrogated their effects on astrocyte internalization of killed Escherichia coli particles. We treated astrocyte cultures with killed E. coli microparticles that were labeled with a trypan-quenched fluorescein (Thermo Fisher Scientific). Fluorescence intensity (λex = 480 nm; λem = 520 nm) was quantified on a microplate reader and revealed that Hb and, to a lesser extent, heme reduced microparticle internalization compared with control (Fig. 2b). To determine whether these effects also modulated phagocytosis, we incubated astrocytes with pH-sensitive pHrodo® Zymosan particles, which fluoresce in phagosomes. Quantification of phagocytic cells using fluorescence microscopy (Fig. S4) demonstrated a significant reduction of phagocytosis in Hb-treated astrocytes and a nonsignificant reduction by heme (Fig. 2c), mirroring our observations with killed E. coli particles.
Because heme and Hb appeared to have similar effects, although to differing degrees, we next wanted to determine whether these effects were associated with changes in astrocyte phagocytic receptor expression. Aβ is highly promiscuous (47), although key astrocyte scavenger receptors include CD36, RAGE, and CD47 (48). Of these, we chose to quantify CD36 expression because it mediates both phagocytosis and inflammatory signaling in astrocytes (49). Indeed, Western blot analysis revealed decreased CD36 expression in the presence of heme or Hb (Fig. 2, d and e). This finding is consistent with heme- and Hb-mediated modulation of Aβ-induced inflammation (Fig. 1), because CD36 is required for astrocyte activation (49) and mediates Aβ-induced inflammatory signaling (50).
Heme and hemoglobin modulate Aβ(1–42) aggregation state and morphology
The ability of heme and Hb to interact with and alter the aggregation state of Aβ(1–42) (21, 22) may be responsible for attenuating Aβ(1–42)-mediated inflammatory activation of astrocytes and clearance of Aβ(1–42). To better understand heme and Hb interactions with Aβ(1–42) and the effects of these interactions on Aβ secondary structure, aggregation state, and morphology, we used a combination of UV-visible spectroscopy, CD spectroscopy, thioflavin T (ThT) fluorescence assays, size-exclusion chromatography (SEC), and transmission EM (TEM). First, using UV-visible spectroscopy, we found that titration of Aβ(1–42) into aqueous solutions of heme and Hb resulted in changes in heme absorbance spectra consistent with high-affinity interactions. In the case of heme, we found that Aβ(1–42) interacts with heme in a 2:1 stoichiometry, with apparent dissociation constants of KD1 ≤ 100 nm and KD2 = 3 μm (Fig. 3, a–c), consistent with prior studies (51, 52). In the case of Hb, we found that each monomer of Aβ(1–42) interacts with each monomer of tetrameric Hb (Fig. 3, e and f). Second, using CD spectroscopy, we found that the β-sheet secondary structure of Aβ(1–42) remains intact upon heme binding (Fig. 3d). Further, CD spectroscopy revealed that a mixture of Hb and Aβ(1–42) yields a CD-derived secondary structure that is distinct from the sum of the individual Hb and Aβ(1–42) spectra (Fig. 3g), confirming biophysical association between Hb and Aβ(1–42). Third, using ThT fluorescence (λex = 450 nm; λem = 482 nm) as a probe for Aβ(1–42) fibrillization (53), we found that heme and Hb could prevent the formation of ThT-positive Aβ(1–42) aggregates (Fig. S5a), and heme de-aggregated preformed ThT-positive Aβ(1–42) fibrils (Fig. S5b), consistent with prior studies demonstrating that heme and Hb suppress Aβ(1–42) fibrillization (19, 54).
Figure 3.

Heme and Hb bind to Aβ(1–42). a, the change in UV-visible spectrum of 500 nm heme in PBS upon the titration of 0–2 eq of Aβ(1–42) indicates the formation of a 1:1 Aβ(1–42)–heme complex. b, the change in UV-visible spectrum of 500 nm heme in PBS upon the titration of 2–10 equivalents of Aβ(1–42) indicates the formation of a 2:1 Aβ(1–42)–heme complex. c, the change in absorbance at 395 nm from the data in a and b is plotted as a function of the ratio of monomeric total [Aβ] to total [heme] and fit to the two-site binding model described in the supplemental material, revealing a KD1 < 100 nm and a KD2 = 3 μm. d, CD spectra of 20 μm Aβ (orange) and a 1:1 Aβ + heme mixture (green) after 3 h of incubation at 37 °C demonstrates that the β-sheet secondary structure of Aβ(1–42) remains intact in the presence of heme. e, the change in UV-visible spectrum of 500 nm Hb in PBS upon the titration of Aβ(1–42) indicates that one molecule of monomeric Aβ(1–42) interacts with each monomer of tetrameric Hb. f, the change in absorbance at 412 nm from the data in E is plotted as a function of the ratio of monomeric [Aβ] to [Hb] monomer and fit to a one-site binding model described in the supplemental material, revealing a KD = 380 nm. g, CD spectra of 20 μm Aβ(1–42) (orange), 5 μm Hb (red), a 1:1 mixture of Aβ and Hb (green), and the sum of the individual Aβ(1–42) and Hb spectra (black).
We next analyzed the effects of heme and Hb on the morphology and size of insoluble and soluble Aβ(1–42) species using SEC and TEM. TEM analysis of insoluble Aβ(1–42) revealed the presence of four morphologically distinct species that shift in distribution upon the presence of heme or Hb: extended long fibrils (Type I), tangled fibrils (Type II), amorphous aggregates (Type III), and short fibrils (Type IV) (Fig. 4a). This analysis was conducted by incubating 25 or 100 μm Aβ(1–42) alone or with 2× heme or 100 μm Aβ(1–42) with 25 μm Hb at 37 °C for 16 h and pelleting out insoluble Aβ(1–42). The predominant species in the Aβ(1–42)-only samples are the Type I extended fibrils (Fig. 4b), which are >1 μm in length and <10 nm in diameter, consistent with previous analysis of Aβ(1–42) fibrils (55). The Type IV short fibrils, which are ∼30 nm in length and ∼8 nm in diameter, are associated only with the presence of Type I and Type II fibrils. We therefore do not consider Type IV species in our analysis of heme and Hb effects on Aβ(1–42) aggregation and fibrillization. Incubation with heme results in the conversion of the Type I species to the amorphous Type III species in the insoluble fraction, with little effect on the Type II species. In the case of Hb, whereas there is greater variation between two independent trials, it is clear that Hb also has a profound effect on fibril morphology, shifting the species distribution from Type I extended fibrils to Type II tangled fibrils (Fig. 4b). Further, it is worth noting that the insoluble species generated from the application of heme and Hb are not enriched with heme (Fig. S6), suggesting that heme remains largely associated with soluble Aβ(1–42) species. Altogether, our studies with heme and Hb are consistent with prior work demonstrating that it reverses and/or suppresses Aβ(1–42) fibril growth (19, 21). However, our work shows that heme and Hb also have the capacity to increase the formation of certain HMW soluble oligomers of Aβ(1–42) and, with respect to Hb, can alter fibril morphology from extended (Type I) to tangled fibrils (Type II).
Figure 4.

Effects of heme and Hb on Aβ(1–42) oligomerization and morphology. a, representative TEM images of the Aβ(1–42) species found in soluble and insoluble Aβ(1–42) fractions. The particular images displayed are from the Aβ(1–42) pelleted fraction (left) and Aβ(1–42) + Hb pelleted fraction (right). The distinct fibril and aggregate types observed are indicated by the arrows and classified as follows: Type I (black), Type II (blue), Type III (red), and Type IV (green). Scale bars, 100 nm (left) and 200 nm (right). b, distribution of the Aβ(1–42) species in two independent trials of the pelleted fractions of 25 μm Aβ(1–42) (trial 1, left) or 100 μm Aβ(1–42) (trial 2, left), 100 μm Aβ(1–42) with 200 μm heme (trial 1, middle) or 25 μm Aβ(1–42) with 50 μm heme (trial 2, middle), and 100 μm Aβ(1–42) with 25 μm Hb (both trials, right). c, overlays of size-exclusion chromatograms of 100 μm Aβ(1–42) (black) or 100 μm Aβ(1–42) with 200 μm heme (red) after incubation for ∼16 h at 37 °C and centrifugation to remove insoluble material. Elution was monitored at 220 nm (top) and 400 nm (bottom) for Aβ peptide and heme, respectively. Black asterisk, 8-ml fraction that associates with heme. d, overlays of size exclusion chromatograms of 100 μm Aβ(1–42) (black) or 100 μm Aβ(1–42) with 25 μm Hb (red) after incubation for ∼16 h at 37 °C and centrifugation to remove insoluble material. Elution was monitored at 220 nm (top) and 400 nm (bottom) for Aβ peptide and heme, respectively. Black asterisk, 8-ml fraction that associated with heme. Red asterisk, free Hb peak (Fig. S7). e, distribution of Aβ(1–42) species in two independent trials of the SEC 8-ml fraction (denoted by black asterisks in c and d) of 25 μm Aβ(1–42) (trial 1, left) or 100 μm Aβ(1–42) (trial 2, left), 25 μm Aβ(1–42) with 50 μm heme (trial 1, middle) or 100 μm Aβ(1–42) with 200 μm heme (trial 2, middle), and 100 μm Aβ(1–42) with 25 μm Hb (both trials, right).
To analyze the effects of heme and Hb on soluble Aβ(1–42) aggregation state, size, and morphology, we subjected the soluble Aβ(1–42) fraction, after pelleting out insoluble Aβ(1–42), to SEC analysis. SEC analysis of soluble Aβ(1–42) revealed the presence of HMW aggregates, >75 kDa, that elute in the void volume, 8 ml, as well as low-molecular weight (LMW) species, <6.5 kDa, that elute at ∼19 ml (Fig. 4c). Both heme and Hb resulted in the loss of the LMW species eluting at 19 ml in favor of the HMW species eluting at 8 ml. Further, UV-visible spectroscopy indicates that the 8-ml species is associated with heme (Fig. 4, c and d), and immunoblot analysis of the 8-ml peak with Hb further demonstrated the co-elution of both Hb and Aβ(1–42) (Fig. S7a). By comparison, free Hb eluted at 12 ml (Fig. S7b). The HMW oligomers that elute in the 8-ml fraction are exclusively Type III amorphous Aβ(1–42) aggregates both in the absence and presence of heme or Hb, as indicated by TEM analysis (Fig. 4e). The LMW Aβ(1–42) species eluting at 19 ml appears by TEM to be a smaller amorphous aggregate than the Type III HMW species that elutes at 8 ml (Fig. S8).
To determine whether the Type III species are on-pathway to form amyloid fibrils, we incubated a 1 μm concentration of the SEC isolated Type III species, with or without heme/Hb, as well as the unseparated stock mixture of 2 μm Aβ(1–42) for 48 h at 37 °C and analyzed them by TEM. Interestingly, unlike the unseparated stock mixture of Aβ(1–42), which readily forms fibrils, the Type III species did not readily form fibrils (Fig. S9).
Altogether, these data demonstrate that heme and Hb do not simply de-aggregate or prevent fibril formation, but also act to promote the formation of distinct heme- and Hb-associated soluble HMW oligomers. The isolated Aβ(1–42) species and their inflammatory response are summarized in Table 1.
Table 1.
Aβ species isolated and assayed for immunomodulation of astrocytes
Shown is a summary of Aβ(1–42) species isolated from centrifugation and SEC. Indicated are the isolation method and immunomodulatory effects of each isolated species on astrocytes as determined by Luminex-based cytokine profiling in Fig. 5 and Fig. S10. NA, not applicable.
| Species | Method of isolation | Inflammatory response | Cytokine panel figure |
|---|---|---|---|
| Insoluble Aβ | Pelleted at 21,000 × g | Moderately inflammatory | Fig. S10a |
| HMW Aβ oligomers | SEC peak at 8 ml | Highly inflammatory | Fig. 5a |
| LMW Aβ oligomers | SEC peak at 19 ml | Not inflammatory | Fig. S10a |
| Insoluble Aβ + heme | Pelleted at 21,000 × g | Not tested | NA |
| Insoluble Aβ + Hb | Pelleted at 21,000 × g | Moderately inflammatory | Fig. S10b |
| HMW Aβ with heme or Hb | SEC peak at 8 ml | Not inflammatory | Fig. 5a/5c |
Inflammatory activation of astrocytes by soluble Aβ(1–42) aggregates is reversed by association with heme or hemoglobin
A combination of centrifugation and SEC identified a number of soluble and insoluble Aβ(1–42) species (Table 1), including ones that associate with and/or are produced as a consequence of heme and Hb. Recent studies of isolated Aβ from post-mortem human tissues have revealed that different species have distinct cytotoxicities and ligand affinities (56, 57). We therefore sought to identify which Aβ(1–42) species were pro-inflammatory and assess the effect that heme or Hb association with these species had on inflammatory activation of astrocytes. Toward this end, we conditioned astrocytes with 50 nm preparations of each soluble and insoluble Aβ(1–42) species for 24 h and assayed their ability to stimulate the expression of inflammatory cytokines relative to a 50 nm concentration of the unseparated Aβ(1–42) stock mixture and vehicle control. Most interestingly, we found that application of the soluble >75-kDa HMW Type III oligomer is highly inflammatory and comparable with that of the application of the unseparated Aβ(1–42) stock mixture (Fig. 5a). In marked contrast, preparations of the Aβ(1–42) pellet, which primarily consists of the Type I extended fibrils, or the soluble LMW species yielded minimal cytokine expression in astrocytes compared with the unseparated Aβ(1–42) stock mixture (Fig. S10a).
Figure 5.
Heme- and Hb-mediated immunomodulation of astrocytes is Aβ(1–42) species–dependent. a, heat map of z-scored cytokine expression show up-regulation of expression of 32 cytokines by primary mouse astrocytes upon incubation with HMW >75-kDa Aβ(1–42) aggregates, isolated via SEC, which is suppressed upon binding with heme (n = 3). b, plotting cytokine expression of RANTES, GM-CSF, IL-1β, IP-10, KC, and MCP-1 shows reduction in relative expression of all six cytokines when SEC-isolated Aβ(1–42) species are bound with heme. c, heat map of z-scored cytokine expression shows a broad suppression of cytokine expression by primary mouse astrocytes upon incubation with Hb-bound SEC isolated HMW Aβ(1–42) aggregates. d, plotting cytokine expression of RANTES, GM-CSF, IL-1β, IP-10, KC, and MCP-1 shows reduction in relative expression of all six cytokines when SEC-isolated Aβ(1–42) species are bound with Hb. Error bars, S.E. a.u., arbitrary units.
We next determined what role heme and Hb association play in mediating Aβ(1–42) inflammatory activation. Strikingly, heme or Hb association with the highly inflammatory soluble >75-kDa HMW Type III oligomer completely reverses its inflammatory activation of astrocytes (Fig. 5). On the other hand, the Hb-associated insoluble pellet, which has a greater fraction of Type II “tangled fibrils” relative to the noninflammatory Aβ(1–42)-only pellet that is primarily composed of Type I “extended fibrils” (Table 1), produced a high inflammatory response in astrocytes (Fig. S10b). It is worth noting that the heme-associated insoluble Aβ(1–42) pellet could not be tested for inflammatory activation of astrocytes due to the very low amount of Aβ(1–42) in the insoluble fraction. This is probably because the insoluble fraction does not contain fibrils and only consists of the Type III amorphous aggregate, which is present in both soluble and insoluble fractions (Fig. 4). However, given that the heme-associated soluble Type III Aβ(1–42) species are noninflammatory (Fig. 5a), we would predict that the insoluble Type III Aβ(1–42) species is likewise noninflammatory.
Overall, these data paint a complex and nuanced picture of the roles of heme and Hb in modulating the inflammatory activity of Aβ(1–42) on astrocytes. 1) Aβ(1–42) alone forms a soluble HMW >75-kDa species that is highly inflammatory. It also forms insoluble extended fibrils (Type I) and smaller oligomeric species that have minimal inflammatory properties. 2) Direct association of heme or Hb with the soluble HMW >75-kDa Aβ(1–42) species reduces astrocyte cytokine expression. 3) The presence of heme and Hb changes the Aβ(1–42) species found in the insoluble fraction. 4) The Type II “tangled fibrils” in the insoluble fraction produced by Hb are highly inflammatory.
Heme and hemoglobin modulate the PI3K/Akt pathway
We have established that heme and Hb exert their modulatory effects on astrocyte immune activity both by physically associating with Aβ(1–42) (Figs. 3 and 4) and by a second mechanism independent of Aβ(1–42) (Fig. 2). The latter suggests that heme and Hb have the capacity to impact Aβ(1–42) clearance through its effects on immune signaling. To gain insight into how heme or Hb modulates immune signaling, we quantified phosphorylation of 11 phosphoproteins in the PI3K/Akt signaling pathway. The PI3K/Akt pathway is of particular interest because of its known role in modulating autophagic clearance of Aβ in neurons (58) and because of its known ability to inhibit M1 macrophage polarization (59), which is linked to expression of scavengers receptors, including CD36 (60). Further, this pathway is important to astrocyte immune function, as it is involved in regulating astrocyte viability, migration, autophagy, and production of cytokines and inflammatory mediators (61–65).
Because phosphoprotein signaling occurs on a much faster time scale (on the order of minutes) than other phenotypic responses (66), we analyzed phosphoproteins from astrocytes conditioned with combinations of Aβ(1–42), 50 nm heme, and 50 nm Hb at 5- and 15-min time points (Fig. S11, a and b). To simultaneously account for data from both time points, we concatenated the time point data and used D-PLSR analysis to identify signaling differences between conditions. Analyzing the effects of heme alone identified two axes of interest with respect to heme and Aβ(1–42) (Fig. 6a). First, LV1 separated heme + Aβ(1–42) to the right with all other conditions to the left. Among other signals in the pathway, LV1 consisted of phospho-Akt, phospho-PTEN, and phospho-TCS2 at the 5-min time point as top correlates with the heme + Aβ(1–42) condition (Fig. 6b). The D-PLSR analysis also determined that both heme and heme + Aβ(1–42) were increased along LV2 (Fig. 6a), which consisted of phospho-mTOR at 15 min, and phospho-IRS1 at both 5- and 15-min time points as top correlates with heme or heme + Aβ(1–42) (Fig. 6c). Plotting all condition groups along LV1 revealed that heme + Aβ(1–42) was significantly different from heme alone (Fig. 6d), whereas plotting along LV2 revealed that treatment either with heme alone or with heme + Aβ(1–42) was significantly different from vehicle controls (Fig. 6e). Thus, these data indicate that heme can significantly shift signaling within the PI3K/Akt signaling pathway, which is modulated by Aβ(1–42). Applying the same analysis to Hb revealed that Hb did not significantly modulate signaling within the pathway compared with either control or Aβ(1–42) alone (Fig. S11, c–e).
Figure 6.
PI3K/AKT pathway signaling is modulated by heme. a, D-PLSR analysis of astrocyte PI3K/Akt phosphoprotein signaling identifies a latent variable (LV1) that separates the heme + Aβ(1–42) condition from the heme-only condition along the horizontal axis and, second, a latent variable (LV2) that separates all heme conditions from the vehicle condition along the vertical axis. b, LV1 depicts a linear combination of phosphoproteins at the 5- and 15-min time points that correlate with the heme + Aβ(1–42) or heme-only conditions. LV1 identifies upstream elements of the pathway, including p-PTEN, p-Akt, and p-TSC2, at 5 min as top correlates with the heme + Aβ(1–42) condition. c, LV2 depicts a linear combination of phosphoproteins at the 5- and 15-min time points that correlate with the heme and heme + Aβ(1–42) conditions or the vehicle control. LV2 identifies p-mTOR at 15 min and p-IRS at 15 and 5 min as top correlates with both heme conditions. d, plotting LV1 scores for each group shows that the LV1 profile significantly segregates the heme + Aβ(1–42) signaling effects from heme-only signaling effects (n = 3, p = 0.0022; heme versus heme + Aβ(1–42)). e, plotting LV2 scores for each group shows that the LV2 profile significantly segregates all heme conditions from the vehicle control (n = 3, p = 0.0125; vehicle versus heme, p = 0.0275; vehicle versus heme + Aβ(1–42)). f, CD36 expression in the presence of Aβ(1–42) and heme, quantified by Western blotting (Fig. S12), is recovered by treatment with rapamycin (n = 4; heme + Aβ(1–42), n = 3, heme + rapamycin + Aβ(1–42), p = 0.0022). g, illustration of the PI3K/Akt signaling network, depicting nodes involved in mediating immunomodulatory and phagocytic functions. Data are represented as mean ± S.E. (error bars). For d, **, p < 0.01; ordinary one-way ANOVA with Dunnett's post-hoc test. For e, *, p < 0.05; Kruskal-Wallis ANOVA with Dunn's post hoc test. For f, **, p < 0.01; Student's t test. n.s., not significant.
Because heme more substantially modulated PI3K/Akt signaling (Fig. 6) and CD36 expression (Fig. 2, d and e) than Hb, we next hypothesized that inhibition of the pathway would restore astrocyte scavenger activity. To test this, we used rapamycin, which inhibits signaling through mTOR, a central node within the PI3K/Akt pathway (Fig. 6g). Indeed, co-treatment of heme + Aβ(1–42) with 10 nm rapamycin yielded partial recovery of CD36 expression (Fig. 6f and Fig. S12). Importantly, these signaling data reveal that 1) the PI3K/Akt pathway is stimulated by heme and 2) the PI3K/Akt pathway regulates astrocyte scavenger activity.
Discussion
Neuroinflammation is recognized as a key component of AD pathology (2). However, it is unclear whether glial activity promotes neurotoxicity (3) or is neuroprotective (4, 5). In reality, the consequences of neuroinflammation occupy a continuum between neuroprotective (3) and neurodegenerative (4, 5). In terms of protection against AD, glial activation is essential for clearance of cytotoxic Aβ species. In terms of aggravating AD pathogenesis, excessive neuroinflammation contributes to a number of detrimental effects, including “fatigued” glia that are unable to clear Aβ, generation of toxic reactive oxygen species, and hyperactivated microglia that indiscriminately phagocytize neurons (11–15). Further complicating matters is the reality that different species of Aβ may affect neuroinflammation in very different ways. Moreover, the effects of each species may be modulated by other aspects of tissue pathology. Herein, we have identified heme and Hb as key AD-relevant immunomodulators and have probed mechanisms that mediate the inflammatory activation of astrocytes. Moreover, we have identified key Aβ(1–42) species that are responsible for astrocyte activation and the effects of heme and Hb on the inflammatory potential of these species. Overall, our data indicate that heme and Hb suppress the Aβ(1–42)-mediated inflammatory activation of astrocytes, suggesting that these factors contribute to AD pathogenesis by impairing Aβ clearance mechanisms.
A pathological hallmark of AD is a weakened blood–brain barrier (BBB) and a concomitant increase in blood and serum factors in the brain, including infiltrating red blood cells, heme, Hb, and haptoglobin (19, 20, 67). Because both heme and Hb have previously been shown to alter Aβ oligomerization (21, 22) and macrophage immune activity (28, 68), they have the potential to modulate AD pathogenesis. Although heme is known to have neurotoxic properties at high concentrations associated with hemorrhage (69), ours is the first study to evaluate the effects of heme and Hb on astrocyte immune activity at concentrations that are physiologically relevant outside of hemorrhage. Astrocytes are one of three glial cell types that take on varying immune and neuronal support functions (70). In addition to being essential regulators of neuronal metabolism, astrocytes possess vital immune functions and play essential roles in clearance of Aβ and regulation of microglial activity during AD pathogenesis (71, 72). Our integrated analysis of cytokines, signaling, scavenger activity, and biophysical analysis of heme/Hb association with Aβ(1–42) reveals for the first time that Hb and heme strongly modulate astrocyte immune activity. Moreover, heme/Hb effects are imparted both by directly modulating astrocyte function and by physically binding to Aβ(1–42).
Simultaneous analysis of the relative expression of 32 cytokines provided us with a detailed view of astrocyte inflammatory response to Aβ(1–42), heme, Hb, and heme/Hb-bound species of Aβ(1–42). We began our study by applying Aβ(1–42) and either heme or Hb to astrocyte cultures (Fig. 1a). Our multivariate analysis (Fig. 1, b and c) identified a composite cytokine variable that integrated all readings from each condition applied. Scoring each sample on this composite variable demonstrated that both heme and Hb reduced cytokine expression (Fig. 1e). From this analysis, Aβ(1–42) conditioning strongly correlates with RANTES, GM-CSF, and IL-1β, which were all down-regulated in cultures co-treated with heme or Hb (Fig. 1f). Of these, RANTES is a pro-inflammatory chemokine and involved in microglial recruitment (73, 74), GM-CSF promotes microglial proliferation (75), and IL-1β is a highly pro-inflammatory cytokine up-regulated early in AD (76) that has been shown to promote Aβ clearance in a mouse model (77). Interestingly, application of heme or Hb at low concentration (50 nm) did not strongly suppress expression of other cytokines, including IP-10, KC, and MCP-1, which are all involved in immune cell recruitment (44, 45, 78). However, application of a high dose of heme (25 μm) reduced these cytokines as well (Fig. S3, a and b), suggesting that multiple mechanisms are associated with heme/Hb suppression of inflammatory response. We note that whereas all of the cytokines modulated by heme and Hb are well-established to modulate immune activity, they have not generally been found to be neurotoxic.
Dual mechanisms of heme and Hb immunomodulatory activity (effects on astrocyte immune signaling and effects produced by binding to Aβ(1–42)) represent one possible explanation for why low doses of heme/Hb suppress certain cytokines and not others, whereas high doses of heme suppress cytokines globally. Evidence for heme and Hb down-regulating astrocyte inflammatory activity through physically modifying Aβ(1–42) stems from our finding that heme and Hb bind to a particularly inflammatory species of Aβ(1–42). Indeed, our SEC analysis revealed that a soluble HMW oligomeric species of Aβ(1–42) (>75 kDa) produced the principal inflammatory response compared with other fractions (Figs. 4 and 5 and Fig. S10). Moreover, the Aβ(1–42) HMW soluble oligomer was the only species that was verified to be associated with heme or Hb and strongly suppressed cytokine expression compared with the unbound oligomer. Further, this result is particularly important because it provides a physiological context to previously described Aβ–heme and Aβ–Hb interactions, as soluble Aβ oligomers are abundant in human AD brain tissue and have high binding affinities and neurotoxic properties (57, 79).
On the other hand, whereas fibrillar Aβ(1–42) is noninflammatory, the effect of Hb on altering Aβ(1–42) fibril morphology contributes to the formation of a highly inflammatory “tangled” fibrillar species (Fig. 4a and Fig. S10). Thus, whereas Hb renders a soluble oligomer noninflammatory, it acts to increase the inflammatory potential of an insoluble fibril. Altogether, the isolation of distinct Aβ(1–42) species and the effect of heme or Hb on their distribution and inflammatory activation of astrocytes highlight the complex and nuanced nature of Aβ-mediated immune signaling. Indeed, the observation of changes in neuroinflammation over the course of AD may reflect the competing effects of multiple Aβ, Aβ–heme, and/or Aβ–Hb species that have differing immunomodulatory activities. Additionally, the peroxidase activity of heme–Aβ complexes may further act to modulate the inflammatory response (54).
A second mechanism of heme/Hb control of inflammatory activity is via direct action on astrocyte signaling, which is supported by our observations that heme and Hb suppressed microparticle internalization, phagocytosis, and CD36 expression (Fig. 2) in experiments free of Aβ(1–42). Our results in astrocytes generally point toward heme as having anti-inflammatory effects at both low and high heme concentrations. Moreover, we found that scavenger activity of astrocytes was inhibited by low (50 nm) heme concentrations and that both low and high (25 μm) heme concentrations inhibited scavenger activity of SIM-A9 microglia (Fig. 2 and Fig. S13). Nevertheless, the canonical role of heme in immune signaling, primarily delineated in macrophages and endothelial cells, is that it stimulates inflammation via TLR4 (26). In contrast, our astrocyte data indicate that heme or Hb reduce the inflammatory response and stimulate phosphorylation of multiple signaling molecules in the PI3K/Akt pathway. In addition to regulating metabolism, this pathway regulates autophagy and is a known modulator of inflammation and phagocytosis (60, 80, 81). Additionally, the mTOR inhibitor rapamycin partially recovered expression of CD36 (Fig. 6f and Fig. S12), defining a novel and causal role for the PI3K/Akt pathway in heme signaling and suggesting that inhibition of this pathway has potential therapeutic efficacy for promoting Aβ clearance.
How are heme signals integrated to control immune activity? Extracellular “free” heme can be internalized by heme transporter HRG-1, and Hb may be internalized by the Hb receptor CD163, although the latter is primarily expressed in the brain by microglia (82–84). Once in the cell, free heme or Hb-derived heme can be catabolized into CO, biliverdin, and bilirubin, which all possess anti-inflammatory properties (85–88). Importantly, CO is known to activate the Akt pathway, providing a plausible explanation for heme-mediated immune signaling (89). An alternative mode of heme signaling may involve heme binding to a number of heme-regulated transcription factors, including p53, Bach1, and Rev-erb-α/β, which control genes important for immune function (90–92). Given that it is increasingly recognized that heme is a dynamic and mobile molecule important for a number of signaling pathways (36, 93–95), future work will involve elucidating the targets of heme signaling during inflammation.
What is the physiologically relevant concentration range and source of bioavailable heme and Hb in human control and AD brains? These unresolved questions would dictate the extent to which heme or Hb association with Aβ or heme-mediated immune signaling would occur in vivo. In the extreme case of hemolysis and hemorrhage, heme and Hb have been estimated to be in the 10–100 μm regime (35). Given that estimates of brain [Aβ] span the pico- to nanomolar range (96, 97) and the relatively tight heme–Aβ and heme–Hb interactions, KD < 100 nm and KD = 350 nm (Fig. 3c), it is likely that a significant fraction of Aβ is associated with heme and Hb in the AD microenvironment. An obvious source of heme and Hb during AD pathogenesis is from the vasculature because a weakened BBB is associated with AD. However, given the recent discovery of heme exporters (98, 99), an intriguing alternative possibility is that astrocytes and/or other brain cells modulate neuroinflammation via control of extracellular heme export. The recent development of fluorescence-based (36, 100, 101) and activity-based (95) heme sensors will be critical for elucidating brain heme homeostasis and the absolute concentrations of heme within cells and in the extracellular space in Alzheimer's disease.
We close by noting that changes in heme and Hb represent only one aspect of a complex mosaic of factors in brain pathophysiology that affects Aβ aggregation and brain immune activity during Alzheimer's disease. Indeed, many factors with the potential to modulate both Aβ aggregation and glial immune activity have been identified within Aβ plaques, including proteoglycans, cytokines, metals, apolipoprotein E, and proteases, among others (102). Nevertheless, there has been limited characterization of the effects of these molecules on Aβ speciation and on astrocyte and microglial immune activity. In this work, we have established an integrated methodology to elucidate the individual effects of particular AD-relevant molecules on astrocyte immune activity via 1) direct effects on astrocyte immune signaling and 2) effects due to physical association with Aβ or modulation of Aβ speciation. Our approach is readily generalizable and may yield broad new insights into the mechanisms promoting immune dysfunction in AD.
Altogether, our data indicate that Hb and heme are potent modulators of astrocyte immune activity by dual mechanisms. The first is by direct signaling to astrocytes, mediated at least in part by the PI3K/Akt pathway. The second is by physical association with a highly inflammatory Aβ(1–42) oligomer, whereby heme or Hb suppresses this inflammatory behavior. Given reports of increased Hb in late-stage AD and in transgenic mouse models, Hb and heme signaling and physical activity represent possible mechanisms responsible for astrocyte fatigue in AD tissues, thereby permitting amyloid pathogenesis. Additionally, recent findings of BBB leakage early in AD suggest that Hb concentration may be locally increased at the vascular wall (103). By extension, Hb and heme activity may be responsible for a high prevalence (∼90%) of cerebral amyloid angiopathy in AD patients (103). The recent report of heme-specific single-domain antibodies may represent a new therapeutic strategy to limit heme availability to Aβ (35). Further, our observation that rapamycin was able to partially restore astrocyte immune activity suggests that intervening in Hb/heme signaling represents a promising therapeutic strategy for AD. More broadly, our approach establishes a rigorous methodology to interrogate the immunomodulatory effects of diverse proteins and other molecules that co-localize or associate with Aβ.
Experimental procedures
Recombinant Aβ(1–42) preparation
For all experiments, hexafluoroisopropyl alcohol (HFIP)-pretreated Aβ(1–42) (rPeptide, Watkinsville, GA) was diluted from stocks of 50 or 500 μm Aβ in 1% NH4OH that were stored at −80 °C. Before reconstitution, Aβ(1–42) was retreated with 500 μl HFIP per milligram of Aβ(1–42) overnight to prevent pre-aggregation. HFIP was evaporated before dilution in 1% NH4OH.
Primary mouse astrocyte cultures
Astrocyte cultures were derived from postnatal day 0–1 CD1 mice (Charles River Laboratories) under a protocol approved by the Georgia Institute of Technology Institutional Animal Care and Use Committee. Cortices were isolated following an existing protocol (104) and triturated in plating medium with a 1-ml sterile pipette tip. Plating medium consisted of minimum essential medium (Thermo Fisher Scientific) with 10% horse serum (Sigma), 1% antibiotic/antimycotic solution (Sigma), and 0.3% glucose solution (Sigma). Cells were left to attach overnight to T-75 flasks coated in 0.1 mg/ml poly-d-lysine (Sigma). After 24 h, flasks were knocked to remove debris and rinsed with PBS, and plating medium was replaced with astrocyte medium (ScienCell) with 2% fetal bovine serum (ScienCell), 1% penicillin/streptomycin solution (ScienCell), and 1% astrocyte growth serum (ScienCell), in which cultures were maintained for up to four passages for conditioning. Cultures were maintained in a 37 °C, 5% CO2 humidified incubator.
SIM-A9 microglial cultures
SIM-A9 cells (American Type Culture Collection (ATCC), Manassas, VA) were cultured in Dulbecco's modified Eagle's medium/F-12 (ATCC) supplemented with 10% heat-inactivated bovine serum (Thermo Fisher Scientific) and 5% heat-inactivated horse serum (Thermo Fisher Scientific). Cultures were maintained in a 37 °C, 5% CO2 humidified incubator.
RAW 264.7 macrophage cultures
RAW 264.7 cells (ATCC) were cultured in Dulbecco's modified Eagle's medium (Lonza, Walkersville, MD) supplemented with 10% fetal bovine serum (Thermo Fisher Scientific) and 1% antibiotic/antimycotic solution (Sigma). Cultures were maintained in a 37 °C, 5% CO2 humidified incubator.
Cell conditioning and lysis
For cytokine expression, phosphoprotein signaling, and Western blot analyses, primary astrocytes were plated in 6-well plates and conditioned with combinations of hemin chloride (50 nm; EMD Millipore), human hemoglobin (50 nm; Sigma), rapamycin (10 nm; Selleck Chemicals, Houston, TX), and Aβ(1–42) (50 nm; rPeptide) in 1% (w/v) NH4OH. For CD36 analysis, cells co-conditioned with rapamycin were first preconditioned with rapamycin for 1 h. Conditions were applied at 75% confluence for 24 h, after which conditioning medium was collected for cytokine analysis, and cell lysates were collected for phosphoprotein signaling and Western blotting analyses using the Bio-Plex cell lysis kit (Bio-Rad), with the addition of one cOmplete mini protease inhibitor tablet (Roche, Basel, Switzerland) and 20 μl of phenylmethylsulfonyl fluoride (Sigma) per 5 ml of lysis buffer. Lysates were placed in microcentrifuge tubes and inverted at 4 °C for 10 min. Lysates and medium were centrifuged at 4 °C for 10 min at 13,200 rpm, and supernatant was collected and stored at −80 °C until analysis.
Multiplexed phosphoprotein and cytokine signaling analysis
For phosphoprotein signaling analysis, cell lysates were thawed on ice and centrifuged at 4 °C for 10 min at 13,200 rpm. Protein concentrations were determined using a Pierce BCA protein assay (Thermo Fisher Scientific) and normalized with Milliplex® MAP assay buffer (EMD Millipore) to 2 μg of protein/25 μl for Akt/mTor pathway analysis or 1 μg of protein/25 μl for mitogen-activated protein kinase pathway analysis. These protein concentrations were selected because they fell within the linear range of bead fluorescence intensity versus protein concentration for detectable analytes. Multiplexed phosphoprotein analysis was conducted for the Akt/mTOR pathway by adapting the protocols provided for the Milliplex® MAP Akt/mTOR 11-Plex (p-Akt, p-GSK3α/β, p-IGF1R, p-IR, p-IRS1, p-mTOR, p-p70S6K, p-PTEN, p-RPS6, and p-TSC2) and phosphoprotein magnetic bead kits (EMD Millipore).
For cytokine signaling analysis, conditioned medium was thawed on ice and centrifuged at 4 °C for 10 min at 13,200 rpm. All samples were diluted 2:3 (conditioned medium/assay buffer), because this dilution fell within the linear range of bead fluorescence intensity versus protein concentration for detectable analytes. Multiplex cytokine analysis was conducted by adapting the protocol provided for the Milliplex® MAP mouse cytokine/chemokine 32-Plex kit, with beads for eotaxin, G-CSF, GM-CSF, interferon-γ, IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-12p40, IL-12p70, IL-13, IL-15, IL-17, IP-10, KC, LIF, LIX, MCP-1, M-CSF, MIG, MIP-1α, MIP-1β, MIP-2, RANTES, tumor necrosis factor-α, and vascular endothelial growth factor. Cytokine and phosphoprotein signaling kits were read on a MAGPIX® system (Luminex, Austin, TX).
Western blot analysis
Cell lysates, obtained as described above, were thawed on ice and then centrifuged for 10 min at 10,000,000 rpm and 4 °C. Protein concentration was determined using a Pierce BCA protein assay and equal amounts of protein were dissolved in reducing sample buffer, boiled, and loaded onto SDS-polyacrylamide gels. Following separation by electrophoresis, proteins were transferred to a Hybond P 0.45-μm polyvinylidene fluoride membrane (GE Healthcare). Membranes were blocked at room temperature (RT) for 1 h with 5% milk in TBS containing 0.01% Tween 20. Membranes were probed at 4 °C overnight with rabbit anti-CD36 (1:500; Novus Biologicals, Littleton, CO) and mouse anti-α-tubulin (1:2000; Sigma). Membranes were then incubated with Alexa Fluor–conjugated secondary antibodies (1:2000; Thermo Fisher Scientific) for 2 h at RT. Imaging of blots was performed using an Odyssey CLx imager (LI-COR Biosciences, Lincoln, NE). Protein quantification was performed using Image Studio Lite version 5.2 (LI-COR Biosciences).
Aβ(1–42) internalization assay
Primary astrocytes were plated in 0.1 mg/ml poly-d-lysine–treated half-area 96-well, glass-bottom plates at a density of 10,000 cells/well and maintained in a 37 °C, 5% CO2 humidified incubator. At 75% confluence, cells were conditioned with either 50 nm Aβ(1–42), 50 nm Aβ(1–42) plus 50 nm hemin chloride, or 50 nm Aβ(1–42) plus 50 nm human hemoglobin in astrocyte medium for 24 h. Cells were fixed with 4% paraformaldehyde, permeabilized for 10 min at RT with 0.1% Triton X-100, and blocked with a 5% BSA, 3% goat serum (Sigma) solution for 1 h. Primary antibody incubation was performed overnight at 4 °C, using the 6E10 antibody (1:200; BioLegend) in 0.5% BSA wash buffer. After washing with wash buffer, fixed cells were incubated with Alexa Fluor 488 goat anti-mouse secondary antibody (1:200; Thermo Fisher Scientific) for 2 h at RT. Cells were co-stained with DAPI (100 ng/ml; Thermo Fisher Scientific) for nuclei and Alexa Fluor 555 phalloidin (1:40; Thermo Fisher Scientific) for actin.
Confocal microscopy was performed on a Zeiss LSM 700 laser-scanning inverted microscope to obtain 15–30 optical sections with 1-μm interval thickness. Orthogonal projections were rendered using Zen version 2.3 software (Zeiss, Oberkochen, Germany).
E. coli particle internalization assay
Primary astrocytes or SIM-A9 microglia were plated on 96-well plates at a density of 10,000 cells/well and left to adhere overnight in a 37 °C, 5% CO2 humidified incubator. Cells were treated with either control, 50 nm hemin chloride, or 50 nm human hemoglobin conditions for 4 h. Conditioning medium was aspirated, and cells were incubated with the E. coli fluorescent BioParticle suspension from the VybrantTM phagocytosis assay kit (Thermo Fisher Scientific) for 1 h. Extracellular fluorescence was quenched with trypan blue. Fluorescence was read on a SpectraMax M3 microplate reader (λex = 480 nm; λem = 520 nm) (Molecular Devices, Sunnyvale, CA).
Phagocytosis assay
Primary astrocytes or SIM-A9 microglia were plated in 0.1 mg/ml poly-d-lysine–treated half-area 96-well, glass-bottom plates at a density of 10,000 cells/well and left to adhere overnight in a 37 °C, 5% CO2 humidified incubator. Cells were treated with either control, 50 nm hemin chloride, or 50 nm human hemoglobin conditions for 24 h. Conditioning medium was aspirated, and cells were incubated with a fluorescent pHrodoTM Red Zymosan BioParticle suspension (Thermo Fisher Scientific) diluted in astrocyte medium for 2 h. After removing BioParticle suspension, cells were fixed with 4% paraformaldehyde, permeabilized for 10 min at RT with 0.1% Triton X-100, and blocked with a 5% BSA, 3% goat serum (Sigma) solution for 1 h. Primary antibody incubation was performed overnight at 4 °C, with rabbit anti-GFAP (1:1000; Novus Biologicals). After washing with wash buffer, fixed cells were incubated with Alexa Fluor 488 goat anti-mouse secondary antibody (1:200; Thermo Fisher Scientific) for 2 h at RT. Cells were co-stained with DAPI (1 ng/ml; Thermo Fisher Scientific) for nuclei. Fluorescence microscopy was performed on a Zeiss Axio Observer Z.1 inverted microscope and quantified using ImageJ.
Fluorescence assay for heme quantification
Heme concentration in pellet fractions was determined by a fluorescence-based assay (105). Briefly, samples were boiled in the presence of 1 m oxalic acid to remove iron from the protoporphyrin ring of heme. Fluorescence of protoporphyrin IX was measured with excitation at 400 nm and emission at 662 nm on a Tecan Infinite 200 Pro plate reader. Heme concentration was determined by comparison with serial dilutions of heme standards quantified by UV-visible spectroscopy using the extinction coefficient of aqueous heme at 612 nm of 4431 cm−1 m−1 (36) on a Cary 60 UV-visible spectrophotometer.
UV-visible spectroscopy
For heme–Aβ(1–42) binding, freshly dissolved Aβ(1–42) was diluted to 100 μm in PBS and titrated into 500 nm heme in PBS. The UV-visible spectral changes were monitored on a Cary 60 UV-visible spectrophotometer. The heme Soret band at 395 nm was plotted versus Aβ(1–42) concentration and fit with the two-site binding model described in the supporting material to determine the apparent dissociation constant. For Hb-Aβ(1–42) binding, freshly dissolved Aβ(1–42) was diluted to 200 μm in PBS and titrated into 500 nm Hb. The heme Soret band of Hb at 412 nm was plotted versus Aβ(1–42) concentration and fit with the one-site binding model described in the supporting material to determine apparent dissociation constant. Before each scan, the samples were allowed to equilibrate for 5 min, consistent with other reports indicating that heme binding to Aβ(1–42) occurs within 300 s (52, 54).
CD spectroscopy
Aβ(1–42) was freshly dissolved from frozen stocks at 20 μm in the presence or absence of 20 μm heme or 5 μm Hb in 1× PBS. Spectra were measured on a Jasco J-815 CD spectropolarimeter. Spectra were prepared from an average of 70 scans from 300 to 190 nm with 1-nm steps at 200 nm/min.
Size-exclusion chromatography
For SEC analysis, Aβ was diluted to 100 μm in 1× PBS with or without 200 μm heme or 25 μm Hb. The Aβ solutions were incubated at 37 °C for 16–18 h without agitation. To separate soluble and insoluble species, Aβ samples were pelleted at 21,100 × g for 5 min to remove insoluble fibrillar material. The pellet was resuspended in 100 μl of 1× PBS for subsequent TEM analysis. The supernatant was collected and chromatographed over a Superdex 10/300 GL size-exclusion column on an Agilent 1260 Infinity HPLC with an in-line photodiode array detector. Elution of Aβ was monitored by reading the absorbance at 220 and 280 nm, whereas elution of heme associated species was monitored by reading absorbance at 400 nm. The ratio of heme to Aβ in SEC fractions was determined by a fluorescence-based assay for heme detection (105). Quantification of Aβ in SEC or pellet fractions was accomplished by UV-visible spectroscopy using the peptide aromatic absorbance at 220 nm relative to serial dilutions of an Aβ stock solution. The ratio of Aβ and Hb in mixed Aβ/Hb SEC fractions was determined by immunoblotting for Aβ or Hb using 6E10 (1:5000; BioLegend) and H4890 (1:5000; Sigma) antibodies, respectively. Absorbance at 220 and 408 nm was then used to determine Aβ and Hb concentrations, respectively.
Transmission electron microscopy
TEM images were taken on a Jeol 100 CXII transmission electron microscope operating at 100 kV. Aβ SEC and pellet samples of 25 or 100 μm Aβ(1–42) alone or with 2× heme and 100 μm Aβ(1–42) with 25 μm Hb were stained using 1% uranyl acetate on 400-mesh continuous Formvar-coated grids (Ted Pella, Redding, CA). Briefly, 2 μl of sample was placed on the grid for 1 min, and excess liquid was blotted away with filter paper. Next, uranyl acetate was added for 45 s, and excess liquid was again removed by blotting with filter paper before the grid was allowed to air-dry. Grids were then stored in a desiccator. Images were collected from across each grid. The distribution in morphology of various Aβ species was scored by counting species types in ∼150–200-μm2 areas for the pellet and ∼100 μm2 for the SEC fractions in two independent experimental trials.
Thioflavin T assays
Aβ was freshly dissolved from frozen 1 mg/ml 1% NH4OH-treated aliquots to 110 μm stock solution in 1× PBS for ThT assays. A final concentration of 20 μm ThT and 6 μm Aβ was used to test for aggregation in the presence of heme or Hb. ThT fluorescence was monitored for 24 h at 37 °C on a Tecan Infinite 200 Pro plate reader with excitation at 450 nm and 9-nm bandwidth and emission at 482 nm with a 20-nm bandwidth. For the fibril de-aggregation assay, Aβ at 110 μm in 1× PBS was allowed to aggregate into fibrils overnight at room temperature without agitation. At each time point, fibrils were then diluted to 6 μm in the presence or absence of heme and placed at 37 °C. 10 μl of each sample was added to 200 μl of 20 μm ThT. ThT fluorescence was monitored at various time points on a Biotek Synergy Mx with 5-s shaking before measuring fluorescence at 435-nm excitation and 9-nm bandwidth and 486-nm emission with 9-nm bandwidth, as was reported previously for an Aβ and heme ThT assay (54).
Partial least-squares regression
D-PLSR analysis was performed in MATLAB using the partial least squares algorithm by Cleiton Nunes available on the Mathworks File Exchange. All data were z-scored before inputting into the algorithm. For all analyses, an orthogonal rotation in the LV1-LV2 plane was performed to identify LVs that best separated conditions.
Statistics
All statistical analyses were performed using GraphPad Prism version 7 (GraphPad Software, La Jolla, CA). Values are presented as mean ± S.E. Statistical significance was determined, as appropriate, using Student's t test, ordinary one-way analysis of variance (ANOVA) followed by Dunnett's or Sidak's post hoc test, or Kruskal–Wallis ANOVA followed by Dunn's post hoc test. Normality of data was tested using the Shapiro–Wilk test of normality. Levels of significance were set as follows: *, p < 0.05; **, p < 0.01; ****, p < 0.0001.
Author contributions
L. B. W., A. R. R., S. B. S., and R. K. D. conceived and designed the experiments and wrote the paper. S. B. S. conducted all astrocyte cell culture work, all Luminex analysis, and all D-PLSR analysis. R. K. D. conducted all biophysical analysis of the interactions between Aβ(1–42) and heme or Hb. K. J. S. conducted microglial phagocytosis experiments.
Supplementary Material
Acknowledgments
We are grateful to Prof. Ingeborg Schmidt-Krey for advice and technical assistance with TEM imaging. We acknowledge the core facilities at the Parker H. Petit Institute for Bioengineering and Bioscience at the Georgia Institute of Technology and the IEN/IMAT Materials Characterization Facility for use of their shared equipment, services, and expertise.
This work was supported by the Parker H. Petit Institute for Bioengineering and Bioscience (to A. R. R. and L. B. W.), start-up support from the George W. Woodruff School of Mechanical Engineering (to L. B. W.), start-up support from the School of Chemistry and Biochemistry (to A. R. R.), a Blanchard faculty fellowship (to A. R. R.), National Science Foundation Grant MCB 1552791 (to A. R. R.), and National Institutes of Health Grant ES025661 (to A. R. R.). The authors declare that they have no conflicts of interest with the contents of this article. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
This article contains Figs. S1–S13.
- AD
- Alzheimer's disease
- Aβ
- β-amyloid
- PI3K
- phosphatidylinositol-4,5-bisphosphate 3-kinase
- BBB
- blood–brain barrier
- HFIP
- hexafluoroisopropyl alcohol
- Hb
- hemoglobin
- HMW
- high-molecular weight
- LMW
- low-molecular weight
- GFAP
- glial fibrillary acidic protein
- IL
- interleukin
- RANTES
- regulated on activation normal T cell expressed and secreted
- GM-CSF
- granulocyte/macrophage colony-stimulating factor
- G-CSF
- granulocyte colony-stimulating factor
- M-CSF
- macrophage colony-stimulating factor
- D-PLSR
- discriminant partial least squares regression
- LV
- latent variable
- SEC
- size-exclusion chromatography
- TEM
- transmission electron microscopy
- MAP
- mitogen-activated protein
- p-
- phosphorylated
- RT
- room temperature
- DAPI
- 4′,6-diamidino-2-phenylindole
- ThT
- thioflavin T
- ANOVA
- analysis of variance
- KC
- keratinocyte chemoattractant.
References
- 1. Prince M., Comas-Herrera A., Knapp M., Guerchet M., and Karagiannidou M. (2016) World Alzheimer Report 2016, Alzheimer's Disease International, London [Google Scholar]
- 2. Heneka M. T., Carson M. J., El Khoury J., Landreth G. E., Brosseron F., Feinstein D. L., Jacobs A. H., Wyss-Coray T., Vitorica J., Ransohoff R. M., Herrup K., Frautschy S. A., Finsen B., Brown G. C., Verkhratsky A., et al. (2015) Neuroinflammation in Alzheimer's disease. Lancet Neurol. 14, 388–405 10.1016/S1474-4422(15)70016-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Meda L., Baron P., and Scarlato G. (2001) Glial activation in Alzheimer's disease: the role of Aβ and its associated proteins. Neurobiol. Aging 22, 885–893 10.1016/S0197-4580(01)00307-4 [DOI] [PubMed] [Google Scholar]
- 4. Hampton D. W., Webber D. J., Bilican B., Goedert M., Spillantini M. G., and Chandran S. (2010) Cell-mediated neuroprotection in a mouse model of human tauopathy. J. Neurosci. 30, 9973–9983 10.1523/JNEUROSCI.0834-10.2010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Sofroniew M. V. (2005) Reactive astrocytes in neural repair and protection. Neuroscientist 11, 400–407 10.1177/1073858405278321 [DOI] [PubMed] [Google Scholar]
- 6. Pellerin L., Bouzier-Sore A. K., Aubert A., Serres S., Merle M., Costalat R., and Magistretti P. J. (2007) Activity-dependent regulation of energy metabolism by astrocytes: an update. Glia 55, 1251–1262 10.1002/glia.20528 [DOI] [PubMed] [Google Scholar]
- 7. Eroglu C., and Barres B. A. (2010) Regulation of synaptic connectivity by glia. Nature 468, 223–231 10.1038/nature09612 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Lee C. Y., and Landreth G. E. (2010) The role of microglia in amyloid clearance from the AD brain. J. Neural Transm. 117, 949–960 10.1007/s00702-010-0433-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Wood L. B., Winslow A. R., Proctor E. A., McGuone D., Mordes D. A., Frosch M. P., Hyman B. T., Lauffenburger D. A., and Haigis K. M. (2015) Identification of neurotoxic cytokines by profiling Alzheimer's disease tissues and neuron culture viability screening. Sci. Rep. 5, 16622 10.1038/srep16622 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Wang W. Y., Tan M. S., Yu J. T., and Tan L. (2015) Role of pro-inflammatory cytokines released from microglia in Alzheimer's disease. Ann. Transl. Med. 3, 136 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Liddelow S. A., Guttenplan K. A., Clarke L. E., Bennett F. C., Bohlen C. J., Schirmer L., Bennett M. L., Münch A. E., Chung W. S., Peterson T. C., Wilton D. K., Frouin A., Napier B. A., Panicker N., Kumar M., et al. (2017) Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541, 481–487 10.1038/nature21029 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Perry G., Castellani R. J., Hirai K., and Smith M. A. (1998) Reactive oxygen species mediate cellular damage in Alzheimer disease. J. Alzheimers Dis. 1, 45–55 10.3233/JAD-1998-1103 [DOI] [PubMed] [Google Scholar]
- 13. Hickman S. E., Allison E. K., and El Khoury J. (2008) Microglial dysfunction and defective β-amyloid clearance pathways in aging Alzheimer's disease mice. J. Neurosci. 28, 8354–8360 10.1523/JNEUROSCI.0616-08.2008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Wyss-Coray T., Loike J. D., Brionne T. C., Lu E., Anankov R., Yan F., Silverstein S. C., and Husemann J. (2003) Adult mouse astrocytes degrade amyloid-β in vitro and in situ. Nat. Med. 9, 453–457 10.1038/nm838 [DOI] [PubMed] [Google Scholar]
- 15. Krabbe G., Halle A., Matyash V., Rinnenthal J. L., Eom G. D., Bernhardt U., Miller K. R., Prokop S., Kettenmann H., and Heppner F. L. (2013) Functional impairment of microglia coincides with β-amyloid deposition in mice with Alzheimer-like pathology. PLoS One 8, e60921 10.1371/journal.pone.0060921 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Basak J. M., Verghese P. B., Yoon H., Kim J., and Holtzman D. M. (2012) Low-density lipoprotein receptor represents an apolipoprotein E-independent pathway of Aβ uptake and degradation by astrocytes. J. Biol. Chem. 287, 13959–13971 10.1074/jbc.M111.288746 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Koistinaho M., Lin S., Wu X., Esterman M., Koger D., Hanson J., Higgs R., Liu F., Malkani S., Bales K. R., and Paul S. M. (2004) Apolipoprotein E promotes astrocyte colocalization and degradation of deposited amyloid-β peptides. Nat. Med. 10, 719–726 10.1038/nm1058 [DOI] [PubMed] [Google Scholar]
- 18. Xiao Q., Yan P., Ma X., Liu H., Perez R., Zhu A., Gonzales E., Burchett J. M., Schuler D. R., Cirrito J. R., Diwan A., and Lee J. M. (2014) Enhancing astrocytic lysosome biogenesis facilitates Aβ clearance and attenuates amyloid plaque pathogenesis. J. Neurosci. 34, 9607–9620 10.1523/JNEUROSCI.3788-13.2014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Chuang J. Y., Lee C. W., Shih Y. H., Yang T., Yu L., and Kuo Y. M. (2012) Interactions between amyloid-β and hemoglobin: implications for amyloid plaque formation in Alzheimer's disease. PLoS One 7, e33120 10.1371/journal.pone.0033120 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Seyfried N. T., Dammer E. B., Swarup V., Nandakumar D., Duong D. M., Yin L., Deng Q., Nguyen T., Hales C. M., Wingo T., Glass J., Gearing M., Thambisetty M., Troncoso J. C., Geschwind D. H., Lah J. J., and Levey A. I. (2017) A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 4, 60–72.e4 10.1016/j.cels.2016.11.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Atamna H., and Frey W. H. 2nd. (2004) A role for heme in Alzheimer's disease: heme binds amyloid beta and has altered metabolism. Proc. Natl. Acad. Sci. U.S.A. 101, 11153–11158 10.1073/pnas.0404349101 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Wu C.-W., Liao P.-C., Yu L., Wang S.-T., Chen S.-T., Wu C.-M., and Kuo Y.-M. (2004) Hemoglobin promotes Aβ oligomer formation and localizes in neurons and amyloid deposits. Neurobiol. Dis. 17, 367–377 10.1016/j.nbd.2004.08.014 [DOI] [PubMed] [Google Scholar]
- 23. Chodobski A., Zink B. J., and Szmydynger-Chodobska J. (2011) Blood-brain barrier pathophysiology in traumatic brain injury. Transl. Stroke Res. 2, 492–516 10.1007/s12975-011-0125-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Iadecola C. (2015) Dangerous leaks: blood-brain barrier woes in the aging hippocampus. Neuron 85, 231–233 10.1016/j.neuron.2014.12.056 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Cullen K. M., Kócsi Z., and Stone J. (2006) Microvascular pathology in the aging human brain: evidence that senile plaques are sites of microhaemorrhages. Neurobiol. Aging 27, 1786–1796 10.1016/j.neurobiolaging.2005.10.016 [DOI] [PubMed] [Google Scholar]
- 26. Figueiredo R. T., Fernandez P. L., Mourao-Sa D. S., Porto B. N., Dutra F. F., Alves L. S., Oliveira M. F., Oliveira P. L., Graça-Souza A. V., and Bozza M. T. (2007) Characterization of heme as activator of Toll-like receptor 4. J. Biol. Chem. 282, 20221–20229 10.1074/jbc.M610737200 [DOI] [PubMed] [Google Scholar]
- 27. Silva G., Jeney V., Chora A., Larsen R., Balla J., and Soares M. P. (2009) Oxidized hemoglobin is an endogenous proinflammatory agonist that targets vascular endothelial cells. J. Biol. Chem. 284, 29582–29595 10.1074/jbc.M109.045344 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Fernandez P. L., Dutra F. F., Alves L., Figueiredo R. T., Mourão-Sa D., Fortes G. B., Bergstrand S., Lönn D., Cevallos R. R., Pereira R. M., Lopes U. G., Travassos L. H., Paiva C. N., and Bozza M. T. (2010) Heme amplifies the innate immune response to microbial molecules through spleen tyrosine kinase (Syk)-dependent reactive oxygen species generation. J. Biol. Chem. 285, 32844–32851 10.1074/jbc.M110.146076 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Simões R. L., Arruda M. A., Canetti C., Serezani C. H., Fierro I. M., and Barja-Fidalgo C. (2013) Proinflammatory responses of heme in alveolar macrophages: repercussion in lung hemorrhagic episodes. Mediators Inflamm. 2013, 946878 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Saura J. (2007) Microglial cells in astroglial cultures: a cautionary note. J. Neuroinflammation 4, 26 10.1186/1742-2094-4-26 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Näslund J., Haroutunian V., Mohs R., Davis K. L., Davies P., Greengard P., and Buxbaum J. D. (2000) Correlation between elevated levels of amyloid beta-peptide in the brain and cognitive decline. JAMA 283, 1571–1577 10.1001/jama.283.12.1571 [DOI] [PubMed] [Google Scholar]
- 32. Collins-Praino L. E., Francis Y. I., Griffith E. Y., Wiegman A. F., Urbach J., Lawton A., Honig L. S., Cortes E., Vonsattel J. P., Canoll P. D., Goldman J. E., and Brickman A. M. (2014) Soluble amyloid β levels are elevated in the white matter of Alzheimer's patients, independent of cortical plaque severity. Acta Neuropathol. Commun. 2, 83 10.1186/PREACCEPT-3091772881321882,10.1186/s40478-014-0083-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Snider B. J., Fagan A. M., Roe C., Shah A. R., Grant E. A., Xiong C., Morris J. C., and Holtzman D. M. (2009) Cerebrospinal fluid biomarkers and rate of cognitive decline in very mild dementia of the Alzheimer type. Arch. Neurol. 66, 638–645 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Seubert P., Vigo-Pelfrey C., Esch F., Lee M., Dovey H., Davis D., Sinha S., Schlossmacher M., Whaley J., and Swindlehurst C., (1992) Isolation and quantification of soluble Alzheimer's β-peptide from biological fluids. Nature 359, 325–327 10.1038/359325a0 [DOI] [PubMed] [Google Scholar]
- 35. Gouveia Z., Carlos A. R., Yuan X., Aires-da-Silva F., Stocker R., Maghzal G. J., Leal S. S., Gomes C. M., Todorovic S., Iranzo O., Ramos S., Santos A. C., Hamza I., Gonçalves J., and Soares M. P. (2017) Characterization of plasma labile heme in hemolytic conditions. FEBS J. 284, 3278–3301 10.1111/febs.14192 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Hanna D. A., Harvey R. M., Martinez-Guzman O., Yuan X., Chandrasekharan B., Raju G., Outten F. W., Hamza I., and Reddi A. R. (2016) Heme dynamics and trafficking factors revealed by genetically encoded fluorescent heme sensors. Proc. Natl. Acad. Sci. U.S.A. 113, 7539–7544 10.1073/pnas.1523802113 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Puschmann T. B., Zandén C., De Pablo Y., Kirchhoff F., Pekna M., Liu J., and Pekny M. (2013) Bioactive 3D cell culture system minimizes cellular stress and maintains the in vivo-like morphological complexity of astroglial cells. Glia 61, 432–440 10.1002/glia.22446 [DOI] [PubMed] [Google Scholar]
- 38. Lange S. C., Bak L. K., Waagepetersen H. S., Schousboe A., and Norenberg M. D. (2012) Primary cultures of astrocytes: their value in understanding astrocytes in health and disease. Neurochem. Res. 37, 2569–2588 10.1007/s11064-012-0868-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Sutton E. T., Thomas T., Bryant M. W., Landon C. S., Newton C. A., and Rhodin J. A. (1999) Amyloid-β peptide induced inflammatory reaction is mediated by the cytokines tumor necrosis factor and interleukin-1. J. Submicrosc. Cytol. Pathol. 31, 313–323 [PubMed] [Google Scholar]
- 40. Johnstone M., Gearing A. J., and Miller K. M. (1999) A central role for astrocytes in the inflammatory response to β-amyloid: chemokines, cytokines and reactive oxygen species are produced. J. Neuroimmunol. 93, 182–193 10.1016/S0165-5728(98)00226-4 [DOI] [PubMed] [Google Scholar]
- 41. Patel N. S., Paris D., Mathura V., Quadros A. N., Crawford F. C., and Mullan M. J. (2005) Inflammatory cytokine levels correlate with amyloid load in transgenic mouse models of Alzheimer's disease. J. Neuroinflammation 2, 9 10.1186/1742-2094-2-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Eriksson L., Johansson E., Kettaneh-Wold N., and Wold S. (2006) Multi- and Megavariate Data Analysis: Principles and Applications, pp. 63–101, Umetrics, Umeå, Sweden [Google Scholar]
- 43. Parajuli B., Sonobe Y., Kawanokuchi J., Doi Y., Noda M., Takeuchi H., Mizuno T., and Suzumura A. (2012) GM-CSF increases LPS-induced production of proinflammatory mediators via upregulation of TLR4 and CD14 in murine microglia. J. Neuroinflammation 9, 268 10.1186/1742-2094-9-268 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Zhang K., Tian L., Liu L., Feng Y., Dong Y.-B., Li B., Shang D.-S., Fang W.-G., Cao Y.-P., and Chen Y.-H. (2013) CXCL1 contributes to β-amyloid-induced transendothelial migration of monocytes in Alzheimer's disease. PLoS One 8, e72744 10.1371/journal.pone.0072744 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Sokolova A., Hill M. D., Rahimi F., Warden L. A., Halliday G. M., and Shepherd C. E. (2009) Monocyte chemoattractant protein-1 plays a dominant role in the chronic inflammation observed in Alzheimer's disease. Brain Pathol. 19, 392–398 10.1111/j.1750-3639.2008.00188.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Nagamoto-Combs K., Kulas J., and Combs C. K. (2014) A novel cell line from spontaneously immortalized murine microglia. J. Neurosci. Methods 233, 187–198 10.1016/j.jneumeth.2014.05.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Jarosz-Griffiths H. H., Noble E., Rushworth J. V., and Hooper N. M. (2016) Amyloid-β receptors: the good, the bad, and the prion protein. J. Biol. Chem. 291, 3174–3183 10.1074/jbc.R115.702704 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Jones R. S., Minogue A. M., Connor T. J., and Lynch M. A. (2013) Amyloid-β-induced astrocytic phagocytosis is mediated by CD36, CD47 and RAGE. J. Neuroimmune Pharmacol. 8, 301–311 10.1007/s11481-012-9427-3 [DOI] [PubMed] [Google Scholar]
- 49. Bao Y., Qin L., Kim E., Bhosle S., Guo H., Febbraio M., Haskew-Layton R. E., Ratan R., and Cho S. (2012) CD36 is involved in astrocyte activation and astroglial scar formation. J. Cereb. Blood Flow Metab. 32, 1567–1577 10.1038/jcbfm.2012.52 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Moore K. J., El Khoury J., Medeiros L. A., Terada K., Geula C., Luster A. D., and Freeman M. W. (2002) A CD36-initiated signaling cascade mediates inflammatory effects of β-amyloid. J. Biol. Chem. 277, 47373–47379 10.1074/jbc.M208788200 [DOI] [PubMed] [Google Scholar]
- 51. Ghosh C., Mukherjee S., Seal M., and Dey S. G. (2016) Peroxidase to cytochrome b type transition in the active site of heme-bound amyloid β-peptides relevant to Alzheimer's disease. Inorg. Chem. 55, 1748–1757 10.1021/acs.inorgchem.5b02683 [DOI] [PubMed] [Google Scholar]
- 52. Atamna H., Frey W. H. 2nd, and Ko N. (2009) Human and rodent amyloid-β peptides differentially bind heme: relevance to the human susceptibility to Alzheimer's disease. Arch. Biochem. Biophys. 487, 59–65 10.1016/j.abb.2009.05.003 [DOI] [PubMed] [Google Scholar]
- 53. Jan A., Hartley D. M., and Lashuel H. A. (2010) Preparation and characterization of toxic Aβ aggregates for structural and functional studies in Alzheimer's disease research. Nat. Protoc. 5, 1186–1209 10.1038/nprot.2010.72 [DOI] [PubMed] [Google Scholar]
- 54. Atamna H., and Boyle K. (2006) Amyloid-β peptide binds with heme to form a peroxidase: relationship to the cytopathologies of Alzheimer's disease. Proc. Natl. Acad. Sci. U.S.A. 103, 3381–3386 10.1073/pnas.0600134103 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55. Sunde M., Serpell L. C., Bartlam M., Fraser P. E., Pepys M. B., and Blake C. C. (1997) Common core structure of amyloid fibrils by synchrotron X-ray diffraction. J. Mol. Biol. 273, 729–739 10.1006/jmbi.1997.1348 [DOI] [PubMed] [Google Scholar]
- 56. Shankar G. M., Li S., Mehta T. H., Garcia-Munoz A., Shepardson N. E., Smith I., Brett F. M., Farrell M. A., Rowan M. J., Lemere C. A., Regan C. M., Walsh D. M., Sabatini B. L., and Selkoe D. J. (2008) Amyloid-β protein dimers isolated directly from Alzheimer's brains impair synaptic plasticity and memory. Nat. Med. 14, 837–842 10.1038/nm1782 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Gong Y., Chang L., Viola K. L., Lacor P. N., Lambert M. P., Finch C. E., Krafft G. A., and Klein W. L. (2003) Alzheimer's disease-affected brain: presence of oligomeric Aβ ligands (ADDLs) suggests a molecular basis for reversible memory loss. Proc. Natl. Acad. Sci. U.S.A. 100, 10417–10422 10.1073/pnas.1834302100 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58. Xue Z., Guo Y., Zhang S., Huang L., He Y., Fang R., and Fang Y. (2014) β-Asarone attenuates amyloid β-induced autophagy via Akt/mTOR pathway in PC12 cells. Eur. J. Pharmacol. 741, 195–204 10.1016/j.ejphar.2014.08.006 [DOI] [PubMed] [Google Scholar]
- 59. Canton J., Neculai D., and Grinstein S. (2013) Scavenger receptors in homeostasis and immunity. Nat. Rev. Immunol. 13, 621–634 10.1038/nri3515 [DOI] [PubMed] [Google Scholar]
- 60. Covarrubias A. J., Aksoylar H. I., and Horng T. (2015) Control of macrophage metabolism and activation by mTOR and Akt signaling. Semin. Immunol. 27, 286–296 10.1016/j.smim.2015.08.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61. Li C. Y., Li X., Liu S. F., Qu W. S., Wang W., and Tian D. S. (2015) Inhibition of mTOR pathway restrains astrocyte proliferation, migration and production of inflammatory mediators after oxygen-glucose deprivation and reoxygenation. Neurochem. Int. 83, 9–18 [DOI] [PubMed] [Google Scholar]
- 62. Cao L., Walker M. P., Vaidya N. K., Fu M., Kumar S., and Kumar A. (2016) Cocaine-mediated autophagy in astrocytes involves sigma 1 receptor, PI3K, mTOR, Atg5/7, Beclin-1, and induces type II programed cell death. Mol. Neurobiol. 53, 4417–4430 10.1007/s12035-015-9377-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63. Codeluppi S., Fernandez-Zafra T., Sandor K., Kjell J., Liu Q., Abrams M., Olson L., Gray N. S., Svensson C. I., and Uhlén P. (2014) Interleukin-6 secretion by astrocytes is dynamically regulated by PI3K-mTOR-calcium signaling. PLoS One 9, e92649 10.1371/journal.pone.0092649 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64. Lisi L., Navarra P., Feinstein D. L., and Dello Russo C. (2011) The mTOR kinase inhibitor rapamycin decreases iNOS mRNA stability in astrocytes. J. Neuroinflammation 8, 1 10.1186/1742-2094-8-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65. Jiang J. H., Ge G., Gao K., Pang Y., Chai R. C., Jia X. H., Kong J. G., and Yu A. C. H. (2015) Calcium signaling involvement in cadmium-induced astrocyte cytotoxicity and cell death through activation of MAPK and PI3K/Akt signaling pathways. Neurochem. Res. 40, 1929–1944 10.1007/s11064-015-1686-y [DOI] [PubMed] [Google Scholar]
- 66. Janes K. A., and Lauffenburger D. A. (2006) A biological approach to computational models of proteomic networks. Curr. Opin. Chem. Biol. 10, 73–80 10.1016/j.cbpa.2005.12.016 [DOI] [PubMed] [Google Scholar]
- 67. Maresca B., Spagnuolo M. S., and Cigliano L. (2015) Haptoglobin modulates β-amyloid uptake by U-87 MG astrocyte cell line. J. Mol. Neurosci. 56, 35–47 10.1007/s12031-014-0465-6 [DOI] [PubMed] [Google Scholar]
- 68. Abraham N. G., and Drummond G. (2006) CD163-Mediated hemoglobin-heme uptake activates macrophage HO-1, providing an antiinflammatory function. Circ. Res. 99, 911–914 10.1161/01.RES.0000249616.10603.d6 [DOI] [PubMed] [Google Scholar]
- 69. Robinson S. R., Dang T. N., Dringen R., and Bishop G. M. (2009) Hemin toxicity: a preventable source of brain damage following hemorrhagic stroke. Redox Rep. 14, 228–235 10.1179/135100009X12525712409931 [DOI] [PubMed] [Google Scholar]
- 70. Rodríguez-Arellano J. J., Parpura V., Zorec R., and Verkhratsky A. (2016) Astrocytes in physiological aging and Alzheimer's disease. Neuroscience 323, 170–182 10.1016/j.neuroscience.2015.01.007 [DOI] [PubMed] [Google Scholar]
- 71. Liu C.-C., Hu J., Zhao N., Wang J., Wang N., Cirrito J. R., Kanekiyo T., Holtzman D. M., and Bu G. (2017) Astrocytic LRP1 mediates brain Aβ clearance and impacts amyloid deposition. J. Neurosci. 37, 4023–4031 10.1523/JNEUROSCI.3442-16.2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72. Lian H., Litvinchuk A., Chiang A. C.-A., Aithmitti N., Jankowsky J. L., and Zheng H. (2016) Astrocyte-microglia cross talk through complement activation modulates amyloid pathology in mouse models of Alzheimer's disease. J. Neurosci. 36, 577–589 10.1523/JNEUROSCI.2117-15.2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73. Mantovani A., Sica A., Sozzani S., Allavena P., Vecchi A., and Locati M. (2004) The chemokine system in diverse forms of macrophage activation and polarization. Trends Immunol. 25, 677–686 10.1016/j.it.2004.09.015 [DOI] [PubMed] [Google Scholar]
- 74. Huang W.-C., Yen F.-C., Shie F.-S., Pan C.-M., Shiao Y.-J., Yang C.-N., Huang F.-L., Sung Y.-J., and Tsay H.-J. (2010) TGF-β1 blockade of microglial chemotaxis toward Aβ aggregates involves SMAD signaling and down-regulation of CCL5. J. Neuroinflammation 7, 28 10.1186/1742-2094-7-28 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75. Lee S. C., Liu W., Brosnan C. F., and Dickson D. W. (1994) GM-CSF promotes proliferation of human fetal and adult microglia in primary cultures. Glia 12, 309–318 10.1002/glia.440120407 [DOI] [PubMed] [Google Scholar]
- 76. Griffin W. S. (2011) Alzheimer's: looking beyond plaques. F1000 Med. Rep. 3, 24 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77. Shaftel S. S., Kyrkanides S., Olschowka J. A., Miller J. N., Johnson R. E., and O'Banion M. K. (2007) Sustained hippocampal IL-1β overexpression mediates chronic neuroinflammation and ameliorates Alzheimer plaque pathology. J. Clin. Invest. 117, 1595–1604 10.1172/JCI31450 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78. Mills Ko E., Ma J. H., Guo F., Miers L., Lee E., Bannerman P., Burns T., Ko D., Sohn J., Soulika A. M., and Pleasure D. (2014) Deletion of astroglial CXCL10 delays clinical onset but does not affect progressive axon loss in a murine autoimmune multiple sclerosis model. J. Neuroinflammation 11, 105 10.1186/1742-2094-11-105 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79. Lambert M. P., Barlow A. K., Chromy B. A., Edwards C., Freed R., Liosatos M., Morgan T. E., Rozovsky I., Trommer B., Viola K. L., Wals P., Zhang C., Finch C. E., Krafft G. A., and Klein W. L. (1998) Diffusible, nonfibrillar ligands derived from Aβ1–42 are potent central nervous system neurotoxins. Proc. Natl. Acad. Sci. U.S.A. 95, 6448–6453 10.1073/pnas.95.11.6448 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80. Heras-Sandoval D., Pérez-Rojas J. M., Hernández-Damián J., and Pedraza-Chaverri J. (2014) The role of PI3K/AKT/mTOR pathway in the modulation of autophagy and the clearance of protein aggregates in neurodegeneration. Cell. Signal. 26, 2694–2701 10.1016/j.cellsig.2014.08.019 [DOI] [PubMed] [Google Scholar]
- 81. Krajcovic M., Krishna S., Akkari L., Joyce J. A., and Overholtzer M. (2013) mTOR regulates phagosome and entotic vacuole fission. Mol. Biol. Cell 24, 3736–3745 10.1091/mbc.e13-07-0408 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82. Borda J. T., Alvarez X., Mohan M., Hasegawa A., Bernardino A., Jean S., Aye P., and Lackner A. A. (2008) CD163, a marker of perivascular macrophages, is up-regulated by microglia in simian immunodeficiency virus encephalitis after haptoglobin-hemoglobin complex stimulation and is suggestive of breakdown of the blood-brain barrier. Am. J. Pathol. 172, 725–737 10.2353/ajpath.2008.070848 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83. Rajagopal A., Rao A. U., Amigo J., Tian M., Upadhyay S. K., Hall C., Uhm S., Mathew M. K., Fleming M. D., Paw B. H., Krause M., and Hamza I. (2008) Haem homeostasis is regulated by the conserved and concerted functions of HRG-1 proteins. Nature 453, 1127–1131 10.1038/nature06934 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84. Schaer C. A., Schoedon G., Imhof A., Kurrer M. O., and Schaer D. J. (2006) Constitutive endocytosis of CD163 mediates hemoglobin-heme uptake and determines the noninflammatory and protective transcriptional response of macrophages to hemoglobin. Circ. Res. 99, 943–950 10.1161/01.RES.0000247067.34173.1b [DOI] [PubMed] [Google Scholar]
- 85. Otterbein L. E., Bach F. H., Alam J., Soares M., Tao Lu H., Wysk M., Davis R. J., Flavell R. A., and Choi A. M. (2000) Carbon monoxide has anti-inflammatory effects involving the mitogen-activated protein kinase pathway. Nat. Med. 6, 422–428 10.1038/74680 [DOI] [PubMed] [Google Scholar]
- 86. Motterlini R., and Otterbein L. E. (2010) The therapeutic potential of carbon monoxide. Nat. Rev. Drug Discov. 9, 728–743 10.1038/nrd3228 [DOI] [PubMed] [Google Scholar]
- 87. Wegiel B., and Otterbein L. E. (2012) Go green: the anti-inflammatory effects of biliverdin reductase. Front. Pharmacol. 3, 47 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88. Nakagami T., Toyomura K., Kinoshita T., and Morisawa S. (1993) A beneficial role of bile pigments as an endogenous tissue protector: anti-complement effects of biliverdin and conjugated bilirubin. Biochim. Biophys. Acta 1158, 189–193 10.1016/0304-4165(93)90013-X [DOI] [PubMed] [Google Scholar]
- 89. Kim H. S., Loughran P. A., Rao J., Billiar T. R., and Zuckerbraun B. S. (2008) Carbon monoxide activates NF-kappaB via ROS generation and Akt pathways to protect against cell death of hepatocytes. Am. J. Physiol. Gastrointest. Liver Physiol. 295, G146–G152 10.1152/ajpgi.00105.2007 [DOI] [PubMed] [Google Scholar]
- 90. Yin L., Wu N., Curtin J. C., Qatanani M., Szwergold N. R., Reid R. A., Waitt G. M., Parks D. J., Pearce K. H., Wisely G. B., and Lazar M. A. (2007) Rev-erbα, a heme sensor that coordinates metabolic and circadian pathways. Science 318, 1786–1789 10.1126/science.1150179 [DOI] [PubMed] [Google Scholar]
- 91. Shen J., Sheng X., Chang Z., Wu Q., Wang S., Xuan Z., Li D., Wu Y., Shang Y., Kong X., Yu L., Li L., Ruan K., Hu H., Huang Y., Hui L., Xie D., Wang F., and Hu R. (2014) Iron metabolism regulates p53 signaling through direct heme-p53 interaction and modulation of p53 localization, stability, and function. Cell Rep. 7, 180–193 10.1016/j.celrep.2014.02.042 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92. Ogawa K., Sun J., Taketani S., Nakajima O., Nishitani C., Sassa S., Hayashi N., Yamamoto M., Shibahara S., Fujita H., and Igarashi K. (2001) Heme mediates derepression of Maf recognition element through direct binding to transcription repressor Bach1. EMBO J. 20, 2835–2843 10.1093/emboj/20.11.2835 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93. Hanna D. A., Martinez-Guzman O., and Reddi A. R. (2017) Heme gazing: illuminating eukaryotic heme trafficking, dynamics, and signaling with fluorescent heme sensors. Biochemistry 56, 1815–1823 10.1021/acs.biochem.7b00007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94. Reddi A. R., and Hamza I. (2016) Heme mobilization in animals: a metallolipid's journey. Acc. Chem. Res. 49, 1104–1110 10.1021/acs.accounts.5b00553 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95. Yuan X., Rietzschel N., Kwon H., Walter Nuno A. B., Hanna D. A., Phillips J. D., Raven E. L., Reddi A. R., and Hamza I. (2016) Regulation of intracellular heme trafficking revealed by subcellular reporters. Proc. Natl. Acad. Sci. U.S.A. 113, E5144–E5152 10.1073/pnas.1609865113 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96. Wu B., Kitagawa K., Zhang N. Y., Liu B., and Inagaki C. (2004) Pathophysiological concentrations of amyloid β proteins directly inhibit rat brain and recombinant human type II phosphatidylinositol 4-kinase activity. J. Neurochem. 91, 1164–1170 10.1111/j.1471-4159.2004.02805.x [DOI] [PubMed] [Google Scholar]
- 97. Lue L. F., Kuo Y. M., Roher A. E., Brachova L., Shen Y., Sue L., Beach T., Kurth J. H., Rydel R. E., and Rogers J. (1999) Soluble amyloid β peptide concentration as a predictor of synaptic change in Alzheimer's disease. Am. J. Pathol. 155, 853–862 10.1016/S0002-9440(10)65184-X [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98. Keel S. B., Doty R. T., Yang Z., Quigley J. G., Chen J., Knoblaugh S., Kingsley P. D., De Domenico I., Vaughn M. B., Kaplan J., Palis J., and Abkowitz J. L. (2008) A heme export protein is required for red blood cell differentiation and iron homeostasis. Science 319, 825–828 10.1126/science.1151133 [DOI] [PubMed] [Google Scholar]
- 99. Quigley J. G., Yang Z., Worthington M. T., Phillips J. D., Sabo K. M., Sabath D. E., Berg C. L., Sassa S., Wood B. L., and Abkowitz J. L. (2004) Identification of a human heme exporter that is essential for erythropoiesis. Cell 118, 757–766 10.1016/j.cell.2004.08.014 [DOI] [PubMed] [Google Scholar]
- 100. Song Y., Yang M., Wegner S. V., Zhao J., Zhu R., Wu Y., He C., and Chen P. R. (2015) A genetically encoded FRET sensor for intracellular heme. ACS Chem. Biol. 10, 1610–1615 10.1021/cb5009734 [DOI] [PubMed] [Google Scholar]
- 101. Abshire J. R., Rowlands C. J., Ganesan S. M., So P. T., and Niles J. C. (2017) Quantification of labile heme in live malaria parasites using a genetically encoded biosensor. Proc. Natl. Acad. Sci. U.S.A. 114, E2068–E2076 10.1073/pnas.1615195114 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102. Atwood C. S., Martins R. N., Smith M. A., and Perry G. (2002) Senile plaque composition and posttranslational modification of amyloid-β peptide and associated proteins. Peptides 23, 1343–1350 10.1016/S0196-9781(02)00070-0 [DOI] [PubMed] [Google Scholar]
- 103. Biron K. E., Dickstein D. L., Gopaul R., and Jefferies W. A. (2011) Amyloid triggers extensive cerebral angiogenesis causing blood brain barrier permeability and hypervascularity in Alzheimer's disease. PLoS One 6, e23789 10.1371/journal.pone.0023789 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104. Schildge S., Bohrer C., Beck K., and Schachtrup C. (2013) Isolation and culture of mouse cortical astrocytes. J. Vis. Exp. 10.3791/50079 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105. Michener J. K., Nielsen J., and Smolke C. D. (2012) Identification and treatment of heme depletion attributed to overexpression of a lineage of evolved P450 monooxygenases. Proc. Natl. Acad. Sci. U.S.A. 109, 19504–19509 10.1073/pnas.1212287109 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.




