The ATP-dependent chaperones are comprised of the 5 HSP90s, 17 HSP70s, 14 HSP60s, 6 ER-specific, and 8 MITO-specific Hsp100/AAA+ ATPases, respectively.
TPR proteins tend to be induced, whereas HSP40s are repressed (Figure 1B).
Ranked by decreasing median aging correlation, the induction of sHSPs and TPR genes consistently ranked high and the HSP60s, HSP40s, and HSP70s were consistently repressed.
Among the genes that are induced in brain aging and disease are sHSPs and TPR-containing chaperone genes (Figures S3A–S3D).
Among the genes that are repressed in both aging and AD, the HSP70- HSP40 system corresponds to 36% of the 58 genes (Table S3D).
Among repressed genes, the HSP40s exhibited significant change (p = 0.04875), with 62% of 48 HSP40 genes repressed in aging (p < 0.05) and 51% repressed in AD.
For example, concordantly aggravated expression pat- terns for the aging-induced genes HSPA2 (HSP70) and DNAJB2 (HSP40) and the aging-repressed HSPA12A (HSP70) and TOMM70A (TPR) were observed in brain biopsies from AD, HD, and PD patients (Figure 2C).
Four genes that are significantly repressed both in AD and HD (HSP90AB1, HSPA8, HSPA14, and TCP1) are also repressed in aging (Figure 6B).
This functional screen identified 18 genes (Figure 3D), corresponding to ten ATP-dependent chaperones, HSC70 (hsp-1), HSP90 (daf-21), and eight subunits of the CCT/TRiC chaperonin complex; the co-chaperones, HSP40 (dnj-12) and CDC37 (cdc-37); and the TPR-domain pro- tein STI1 that upon knockdown significantly enhanced A b 42 pro- teotoxicity (Figure 3D).
These included all subunits of the CCT/TRiC complex (except CCT5); HSP40 and HSP70 family members DNAJA1 (HDJ-2), DNAJA4, HSPA8 (HSC70), and HSPA14 (Figures 5B and 5C); and the TPR-domain APC/C subunits CDC23 and CDC27 that, upon knockdown, led to significantly elevated aggregation (Figure S5B).
Knockdown of daf-21 (HSP90) or hsp-1 (HSC70) led to increased paralysis in 45% and 44% of day 6 animals, respectively, and knockdown of TPR co-chaper- ones tpr-1 and dnj-12 resulted in 70% impairment (Figure S4D).
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If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.