NAD-PRECURSORS AND DIETARY RESTRICTION FOR TREATING AGE RELATED MEDICAL CONDITIONS
20230000888 · 2023-01-05
Assignee
Inventors
Cpc classification
A61K31/436
HUMAN NECESSITIES
A61K31/706
HUMAN NECESSITIES
A61K31/194
HUMAN NECESSITIES
A61K45/06
HUMAN NECESSITIES
A61K31/706
HUMAN NECESSITIES
A61K31/155
HUMAN NECESSITIES
A61K31/455
HUMAN NECESSITIES
A61K31/385
HUMAN NECESSITIES
A61P43/00
HUMAN NECESSITIES
A61K31/7004
HUMAN NECESSITIES
A61K2300/00
HUMAN NECESSITIES
A61K2300/00
HUMAN NECESSITIES
A61K31/454
HUMAN NECESSITIES
International classification
A61K31/706
HUMAN NECESSITIES
A61K31/155
HUMAN NECESSITIES
A61K31/194
HUMAN NECESSITIES
A61K31/385
HUMAN NECESSITIES
A61K31/436
HUMAN NECESSITIES
A61K31/454
HUMAN NECESSITIES
A61K31/7004
HUMAN NECESSITIES
Abstract
A nicotinamide adenine dinucleotide (NAD) precursor is provided for use in the treatment and/or prevention of an age-related medical condition in a subject. The NAD precursor is administered in combination with a calorie restriction diet (CRD) and/or a calorie restriction mimetic (CRM). Furthermore, a pharmaceutical combination is provided that includes a NAD precursor and a CRM.
Claims
1. A method of treating or reducing the risk of an age-related medical condition in a subject, having or at risk of an age-related medical condition, comprising: administrating a nicotinamide adenine dinucleotide (NAD) precursor to a subject, wherein said NAD precursor is administered in combination with a calorie restriction diet (CRD) and/or a calorie restriction mimetic (CRM).
2. The method according to claim 1, wherein the NAD precursor is nicotinamide riboside (NR).
3. The method according to claim 1, wherein the CRM is a fasting mimicking diet product.
4. The method according to claim 1, wherein the CRM is a chemical compound/drug, preferably selected from the group consisting of resveratrol, metformin, oxaloacetate, rimonabant, lipoic acid, 2-deoxy-D-glucose and rapamycin.
5. The method according to claim 1, wherein the age-related medical condition is associated with a decline in mitochondrial function.
6. The method according to claim 1, wherein the treatment and/or prevention of an age-related medical condition comprises slowing, reversing and/or inhibiting the ageing process.
7. The method according to claim 1, wherein the subject is human and is more than 40 years old.
8. The method according to claim 1, wherein the NAD precursor antagonizes an age-related decline of mitochondrial function.
9. The method according to claim 1, wherein the CRD and/or CRM promote metabolic plasticity, mitochondrial metabolism and/or metabolic stress responses.
10. A pharmaceutical combination, comprising a nicotinamide adenine dinucleotide (NAD) precursor, and a calorie restriction mimetic (CRM).
11. The pharmaceutical combination according to claim 10, wherein the NAD precursor is nicotinamide riboside (NR).
12. The pharmaceutical combination according to claim 10, wherein the CRM is selected from the group consisting of resveratrol, metformin, oxaloacetate, rimonabant, lipoic acid, 2-deoxy-D-glucose and rapamycin.
13. The pharmaceutical combination according to claim 10, wherein the NAD precursor is in a pharmaceutical composition in admixture with a pharmaceutically acceptable carrier, and the CRM compound is in a separate pharmaceutical composition in admixture with a pharmaceutically acceptable carrier, or the NAD precursor and the CRM compound are present in a kit, in spatial proximity but in separate containers and/or compositions, or the NAD precursor and the CRM compound are combined in a single pharmaceutical composition in admixture with a pharmaceutically acceptable carrier.
14. A method of treating or reducing the risk of an age-related medical condition in a subject having or at risk of an age-related medical condition, comprising administrating a pharmaceutical combination according to claim 10 to a subject.
15. The method according to claim 14, wherein the age-related medical condition is associated with a decline in mitochondrial function.
16. The method according to claim 8, wherein the NAD precursor enhances and/or restores a therapeutic response of a human subject to CRD and/or CRM administration.
17. The method according to claim 16, wherein the subject is over 40 years old.
18. The pharmaceutical combination according to claim 10, wherein the CRM is rapamycin and a fasting mimicking diet product.
Description
BRIEF DESCRIPTION OF THE FIGURES
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DETAILED DESCRIPTION OF THE FIGURES
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[0164] (C) Peripheral blood chimerism of young (2-3 months old) recipient mice that were transplanted with 200 HSCs from young (Y) or old (O) donor mice that were exposed to DR or AL diet (donors were from the experiment shown in
[0165] (D,E) Seahorse analysis on 80,000 CMPs of (D) young (3 months) and (E) old (23 months), female mice exposed to 2 weeks AL diet or DR (n=4 mice per group). The graph shows the oxygen consumption rate at basal level (b), after oligomycin injection (o), after FCCP injection (f), and after injection of rotenone/antimycin (r/a). The curves depict the average respiration at the indicated conditions. Data were normally distributed (Shapiro-Wilk test) and p-values were calculated on average data of 4 timepoints per mouse per condition using unpaired t-test with Welch's correction. Error bars depict SD.
[0166] (F,G) HSCs (CD150+CD34.sup.−Flt3.sup.−LSK) were freshly isolated from 2-weeks DR or AL diet exposed, young mice (2-3 months=Y.AL or Y.DR) and from 2-weeks DR or AL diet exposed, old mice (22-24 months=O.AL or O.DR). HSCs were analyzed for (F) Lactate and (G) Pyruvate. The histograms depict fold-changes scaled to young, AL-fed mice (Y.AL) set to 1. N=4 mice per group. Data are normally distributed (Shapiro-Wilk test). P-values were calculated by two-way ANOVA with Tukey's multiple comparison tests. Error bars depict SD.
[0167] (H) The heat map shows the protein expression of Ldha, Ldhb, Pdhb, and Pdha1 in freshly isolated CMPs from young and old mice, 2 weeks after exposure to DR or AL diet (n=5/group). Color code indicates log 2-fold up- or downregulation of significantly regulated proteins (q-value <0.05). Red is for upregulation, blue for down-regulation, and the X signs refer to non-significant regulation.
[0168] (I) ATP levels in freshly isolated HSCs from the same mice as in (F,G). The histogram shows fold-changes scaled to young, AL-fed mice (Y.AL) set to 1. N=4 mice per group. Data are normally distributed (Shapiro-Wilk test). P-values were calculated by two-way ANOVA with Tukey's multiple comparison tests. Error bars depict SD.
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[0170] (C,D) Seahorse analysis was done on 80,000 GMPs of (C) young (3 months) and (D) old mice (23 months) exposed to 2 weeks AL or DR (n=4 mice each). The data passed Shapiro-Wilk normality test. P-values in were calculated on average data of 4 timepoints per mouse per condition using unpaired t-test with Welch's correction. Error bars depict SD.
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[0172] (B) Total Bone marrows from young mice (2-3 months, n=14) and old mice (27-30 months, n=10) were stained with HSC markers, followed by CellROX green staining for ROS analysis. The staining intensity (geometric mean) was analyzed in HSCs (CD150+CD34-LSK) by FACS. Representative FACS profiles are shown on the right. Data did not show normal distribution (Shapiro-Wilk test). P-value was calculated by Mann Whitney test. Error bars depict SD.
[0173] (C,D) Seahorse analysis was carried out on 80,000 (C) MPPs (CD34*LSK) and (D) myeloid progenitors (MPs: lin-c-Kit*Sca1-, including CMP, GMP, and MEP). Cells were freshly isolated from young (4-5 months) and old mice (31 months). The graph shows the oxygen consumption rate at basal level (b), after oligomycin injection (o), FCCP injection (f), and after rotenone/antimycin injection (a/r). Data were normally distributed (Shapiro-Wilk test), p-values were calculated on average data of 4 timepoints per condition per mouse using unpaired t-test with Welch's correction. Error bars depict SD.
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[0175] (D-F) Levels of reactive oxygen species (ROS, same experiment as shown in
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[0177] (E) The heat map shows redox proteins that were detectable in LC-MS/MS-proteome analysis and showed a significant difference in expression levels (q-value <0.05) in freshly isolated MPPs (CD34.sup.+Flt3.sup.−LSK) from old mice (30-36 months) versus young mice (6-8 months). Color coding indicates log 2-fold of upregulated (red) and downregulated (blue) proteins.
[0178] (F-K) Freshly isolated HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) from young mice (4 months, n=4) and old mice (28-30 months, n=7) were analyzed for mRNA expression of target genes (relative to β-actin). For old mice HSCs were separated into CD41− and CD41+ HSCs. CD41+ HSCs were present at very low levels in young mice (<5%) and thus not isolated. (F,G) nuclear encoded, mitochondrial associated genes and (H-K) electron transport chain complex genes encoded by mitochondrial genome. Normality of data was assessed by Shapiro-Wilk test after Log 2 transformation. (F-1) Data are normally distributed and p-values were calculated by unpaired t-test with Welch's correction on Log 2-transformed data. (J,K) Data are not normally distributed and p-values were calculated by Mann Whitney test on Log 2-transformed data. Error bars depict SD.
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[0180] (C-E) One-thousand-five-hundred, freshly isolated HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) from young or old mice were cultured per well (96-well plate). (C) HSCs were exposed to 2-DG (3 mM), Oligomycin (=Oligo, 1.8 nM), or DMSO as control (=Con). Total cell numbers per well were determined by FACS after 5 days. Young mice (4 months, n=4) and old mice (24 months, n=6). Data are normally distributed (Shapiro-Wilk test). P-values were calculated by t-test with Welch's correction. Error bars depict SD. (D) HSCs were cultured with inhibitors that block the mitochondrial uptake of glutamate (BPTES, 9 μM), fatty acids (Etomoxir, 9 μM), or pyruvate (UK5099, 9 μM). Total cell numbers were counted by FACS after 5 days. Young mice (3-4 months, n=5) and old mice (26 months, n=4). Data are normally distributed (Shapiro-Wilk test). P-values were calculated by unpaired t-test with Welch's correction. (E) HSCs were exposed to a combination of 3 inhibitors (3 inhibitors=3I, same as in D) at a concentration of 6 μM (each) or to DMSO (Con). Young mice (2-3 months, n=5) and old mice (30-31 months, n=5). Data are normally distributed (Shapiro-Wilk test). P-values were calculated using 2-way ANOVA with Tukey's multiple comparisons test. Error bars depict SD.
[0181] (F,G) Young, 3-4 month old mice were treated within one week with two intraperitoneal injections of FCCP on day-1 and day-4 (high-dose: 4.8 mg/Kg or low-dose: 1.2 mg/Kg) or with vehicle control (10% DMSO) (n=4 mice per group). One week after the start of the treatment (day-7), total bone marrow cells were analyzed and used for culture experiments. (F) The histogram shows the frequency of HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) per million total bone marrow cells directly after isolation in the indicated groups of mice. (G) 2,500 freshly isolated HSCs from vehicle-treated of high-dose FCCP-treated animals were cultured and exposed to 3I-treatment (same concentration as in
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[0184] (C,D) Freshly isolated HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) from young mice (3-4 months, n=7) and old mice (24-25 months, n=7) were cultured overnight (7,000 HSCs per well of a 96-well plate). Eighteen hours later, HSCs were exposed to oligomycin-treatment (2.4 nM) or vehicle control (0.04% DMSO). After 20h treatment, 1,000 cells from the cultures were isolated by FACS to analyze the activity of (C) LDH and (D) PDH. The histograms depict the data scaled to the average of young, control-treated HSCs set to 1. Data are normally distributed (Shapiro-Wilk test). P-values were calculated by two-way ANOVA with Tukey's multiple comparison tests. Error bars depict SD.
[0185] (E,F) The same HSC cultures that were described in
[0186] (G) Freshly isolated CMPs (Lin.sup.−c-Kit.sup.+Sca1.sup.−CD34.sup.+FcγR.sup.−/low), from young (3 months, n=4) and old mice (24 months, n=4) were cultured and exposed for 12h to 3 inhibitors of mitochondrial nutrient uptake (3I=BPTES=6 uM, Etomoxir=6 uM, UK5099=6 uM) or DMSO control (Con). Afterwards the basal oxygen consumption rate (OCR) of the indicated groups was measured by Seahorse. Statistical analysis: The data were normally distributed (Shapiro-Wilk) and p-values were calculated by 2-way ANOVA with Tukey's multiple comparisons test. Error bars depict SD.
[0187] (H) Young, 3-4-month old mice were treated one week with two intraperitoneal injections of FCCP/week (high-dose: 4.8 mg/Kg or low-dose: 1.2 mg/Kg) or with vehicle control (10% DMSO) (n=4 mice per group). One week after the start of the treatment, CMPs were freshly isolated and exposed for 12h in culture to a combination of 3 inhibitors of mitochondrial nutrient uptake (31: 6 μM of each BPTES, Etomoxir, and UK5099) or DMSO control (Con). Statistical analysis: The data were normally distributed (Shapiro-Wilk) and p-values were calculated by 2-way ANOVA with Tukey's multiple comparisons test. Error bars depict SD.
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[0189] (A-D) Freshly isolated bone marrow cells were stained for HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) along with fluorescence conjugated, antibodies against (A,B) phosphorylated-mTOR (p-mTor) or (C,D) phosphorylated ribosomal protein S6 (p-S6). Cells were analyzed by FACS. The geometric means of fluorescence intensities (MFIs) in the HSC population of individual mice is shown in (A,B) for p-mTOR: (n=11 for Y.AL, n=12 for Y.DR, n=10 for O.AL, n=11 for O.DR) and in (C,D) for p-S6 (n=6 for Y.AL and O.AL, n=7 for Y.DR and O.DR). Statistical analysis: data are normally distributed (Shapiro-Wilk test) and p-values were calculated by unpaired t-test with Welch's correction. Error bars depict SD.
[0190] (E,F) The mRNA of freshly isolated MPPs was analysed by a customized NanoString platform detecting 52 genes that have a known role in metabolic stress responses. (E) The heatmap shows significantly regulated genes in MPPs from young, DR-exposed mice compared to MPPs from young, AL-fed mice (p-value <0.05 after Benjamini-Yekutieli adjustment using nSolver v.4 software from Nanostring Techn.). (F) shows the expression profile of the same set of genes in MPPs from old, DR-exposed mice in comparison to MPPs from old, AL-fed mice. Note that all stress response genes that significantly reacted to DR in MPPs from young mice showed increased expression levels compared to AL-fed young mice (red color code). In contrast, none of the stress response genes was significantly regulated in response to DR in MPPs from old mice.
[0191] (G,H) FACS analysis of freshly isolated bone marrow was used to determine the total HSC numbers (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) per million total bone marrow cells in (G) young and (H) old mice that were exposed to 2 weeks DR or AL diet. N=11 for Y.AL, n=12 for Y.DR, n=11 for O.AL, n=11 for O.DR. Statistical analysis: data are normally distributed (Shapiro-Wilk test) and p-values were calculated by the unpaired t-test with Welch's correction. Error bars depict SD.
[0192] (I) freshly isolated MPPs (CD34.sup.+Flt3.sup.−LSK) from young and old, AL-fed mice (n=4/group) were treated for two days in culture with a combination of 3 inhibitors of mitochondrial nutrient uptake (3I: 6 μM of each BPTES, Etomoxir, and UK5099) or DMSO (0.4%). Cells were then stained with a conjugated fluorescence-antibody against PINK1. The histogram shows the geometric means of the fluorescence intensity (MFIs) of PINK1 staining in the HSC population of individual mice. Statistical analysis: The data were not normally distributed (Shapiro-Wilk test) and the Mann-Whitney test was used for the calculation of p-values.
[0193] (J) Young mice (2-3 months) and old mice (22-24 months) were exposed for 1 week to DR or continuation of AL diet. Afterwards, freshly isolated MPPs (CD34.sup.+Flt3.sup.−LSK) were co-stained for the mitochondrial protein TOM20 and the autophagy-related protein LC3 and analyzed under the microscope. Quantification of mean fluorescence intensity (MFI) of LC3 protein expression was conducted by Image J. N=6 mice per group. The histograms depict data that were scaled to the average of staining intensity values in young AL-fed mice set to 1. Representative images of staining of TOM20 (red), LC3 (green) and DAPI (blue) are shown on the right. Data are normally distributed (Shapiro-Wilk test) and p-values were calculated by two-way ANOVA with Tukey's multiple comparison tests. Error bars depict SD.
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[0195] (C,D) The levels of phosphorylated AKT (p-AKT) in HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) were analyzed by FACS on the same mice as in
[0196] (E,F) FACS analysis of freshly isolated bone marrow cells on the total numbers of MPPs (CD34.sup.+Flt3.sup.−LSK) per million total bone marrow cells in (E) young and (F) old mice that were exposed to 2 weeks DR or AL diet. N=11 for Y.AL, n=12 for Y.DR, n=10 for O.AL, n=11 for O.DR. Statistical analysis: data are normally distributed (Shapiro-Wilk test) and p-values were calculated by the unpaired t-test with Welch's correction. Error bars depict SD.
[0197] (G) Freshly isolated MPPs (CD34.sup.+Flt3.sup.−LSK) from young mice (2-3 months, n=4) and old mice (27-30 months, n=6) were exposed to oligomycin (0.6 μM) or vehicle control (0.1% DMSO) for 3 hours in culture. Gene expression of Pink1 (relative to E-actin) was measured by qPCR. The transformed data are normally distributed (Shapiro-Wilk test) and p-values were calculated on transformed data by unpaired t-test with Welch's correction. Error bars depict SD.
[0198] (H,I) Colocalization of the autophagy protein LC3 and the mitochondrial protein TOM20 was analyzed by microscopy in freshly isolated MPPs (CD34.sup.+Flt3.sup.−LSK) from young and old mice that were exposed for 1 week to DR or continuation of AL diet (the same experiment as in
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[0200] (C,D) NanoString analysis on the expression of stress response genes was carried out on 10,000 MPPs (CD34.sup.+Flt3.sup.−LSK) from young (3-4 months, n=4) and old mice (22-24 months, n=4). MPPs were pre-treated in culture with 1 mM NR or DMSO (Con) for 12h followed by treatment with 31 or Vehicle (Veh: 0.4% DMSO) for 12h under continuation of NR or Veh treatment. (C,D) Volcano plots for the NanoString analysis. Horizontal, dashed line indicates threshold for genes that are significantly regulated in (C) MPPs from young mice and old mice that were exposed in culture to control treatments (Y.Con+Veh) versus (O.Con+Veh) and in (D) MPPs from young mice were exposed to control treatment versus MPPs from old mice that were exposed to NR followed by vehicle treatment (=Y.Con+Veh versus O.NR+Veh).
[0201] (E) The Venn-Diagram shows the overlap of significantly regulated genes (p-value below 0.05) from analysis in
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[0203] (B) Histogram of log 2 fold changes in O.DR vs. Y.DR (red) and O.AL vs. Y.AL (blue). Solid curves show probability density estimations. The change in differentially expressed proteins of both comparisons was calculated by Brown-Forsythe Test for difference of variance.
[0204] (C) Ingenuity Pathway Analysis (IPA) was carried out on proteome changes of GMPs from old (24 months, n=5) compared to young (3 months, n=5) mice exposed to 2 weeks DR (red histogram of log 2 fold changes in 7B). The graph shows the top-10 enriched pathways using a cut-off including all significantly, differently expressed proteins (q-value 0.05).
[0205] (D) The heat maps shows NADH-ubiquinone oxidoreductase subunits of mitochondrial membrane complex I (NDUFs) proteins that were included under the term “Sirtuin signaling” in the IPA analysis depicted in (C) and showed a significant difference in expression levels (q-value <0.05) in freshly isolated GMPs from old (24 months, n=5) and young (3 months, n=5) mice exposed to DR (O.DR vs. Y.DR).
[0206] (E) Freshly isolated HSCs from young mice (3-4 months) and old mice (22-24 months) were exposed to 1 mM Nicotine riboside (NR) or DMSO (con) for 2 days followed by treatment with a combination of 3 inhibitors of mitochondrial nutrient uptake (31: 6 μM of each BPTES, Etomoxir, and UK5099) or vehicle (0.4% DMSO=Veh) for another 2 days. The NR treatment was continued on das 3 and 4. The histogram shows the total number of the stem cell containing subpopulation (CD48−, Sca1+) of HSC-derived cultures from young (Y) and old (O) mice exposed to the indicated treatment regiment for 4 days: Y.Con+Veh, Y.Con+3I, O.Con+Veh, O.Con+3I, O.NR+Veh, O.NR+3I. N=3 HSC cultures derived from 3 individual mice per group. Data are normally distributed (Shapiro-Wilk test) and p-values were calculated by the paired t-test with Welch's correction. Error bars depict SD.
[0207] (F) Basal oxygen consumption rate in CMPs from young (3-5 months, n=4) and old mice (22-24 months, n=4). Cells were either pretreated with 1 mM Nicotine riboside (NR) or DMSO (Con) for 12 h. This was followed by treatment for 12h in vitro to combination of 3 inhibitors of mitochondrial nutrient uptake (by BPTES=6 uM, Etomoxir=6 uM, UK5099=6 uM) or DMSO as control. The data were not normally distributed (Shapiro-Wilk test) and the Mann-Whitney test was used for the calculation of p-values.
[0208] (G,H) NanoString analysis on the expression of stress response genes was carried out on 10,000 MPPs (CD34.sup.+Flt3.sup.−LSK) from young (3-4 months, n=4) and old mice (22-24 months, n=4). MPPs were pre-treated in vitro with 1 mM NR or DMSO (Con) for 12h followed by treatment with 31 or Vehicle (Veh: 0.4% DMSO) for 12h. The NR treatment was continued for the time window of 12-24h. (G, H) Volcano plots on the NanoString analysis of stress response genes. Horizontal, dashed line indicates threshold for genes that are significantly regulated in (G) 3I-exposed MPP from young mice (Y.Con+3I) versus 3I-exposed MPPs from old mice (O.Con+3I) and in (H) 3I-exposed MPPs from young mice (Y.Con+3I) versus 3I-exposed MPPs from old mice that were pre-treated for 12h with NR (O.NR+3I).
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[0210] (A-C) Respirometry analysis of the OCR of freshly-isolated CMPs in: (A) young and (B) old mice; (C) Quantification of OCR at basal level of the indicated groups as measured in (A,B, before oligomycin-application, marked by 0). N=4-6 mice per group. The Data were normally distributed (Shapiro-Wilk test) after log transformation. Error bars represent SD. P-values were calculated on average data of 4 time points using 2-way ANOVA with Tukey's multiple comparisons test on log-transformed data.
[0211] (D-F) OCRs were continuously measured for 12h in freshly isolated GMPs from (D) young and (E) old mice that were grown in glucose-restricted medium (1 mM=R), (F) Quantification of the last time point (635 min), p-values were calculated by unpaired t-test comparing the depicted OCR to the OCR under normal glucose. The Data were normally distributed (Shapiro-Wilk test) after log transformation. Error bars represent SD.
[0212] (G-K) NanoString mRNA analysis of stress response genes in freshly-isolated HSCs from young (Y) and old (O) mice that were exposed to ad libitum (AL) or dietary restriction (DR diet for 2 weeks) of NAD-precursor treatment (NR) or a combination of NR plus DR (=NR/DR). The dotted lines represent the q-value of 0.05. Genes above this line are significantly regulated in the indicated comparisons. Note that single treatments of DR-alone or NR-alone lead to an induction of health-promoting stress response genes in young mice, but not in old mice. In old mice, only the combination of NR/DR leads to an induction of health-promoting stress response genes.
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EXAMPLES
[0215] The invention is further described by the following examples. These are not intended to limit the scope of the invention, but represent preferred embodiments of aspects of the invention provided for greater illustration of the invention described herein.
[0216] Here we analyzed whether the time of intervention (young adult vs. late in life) would change the outcomes of DR on metabolic plasticity, stress responses, and functional improvements in hematopoietic stem and progenitor cells (HSPCs) of laboratory mice (C57Bl/6J). The focus on the hematopoietic system had the advantage that pure population of phenotypically defined stem cells (HSCs) and early progenitor cells (HPCs) could be employed for metabolic as well a functional tests such as the assessment of the repopulation capacity of HSCs in transplantation experiments in vivo. Moreover, this approach minimized the influence of aging-related changes in cell composition (that occur in many tissues) on the results. Our work reveals experimental evidence that aging-associated mitochondrial dysfunction abrogates the metabolic plasticity of HSPCs to respond to changes in nutrient availability. HSPCs from young mice adapt to DR-induced reduction in nutrient availability by activation of mitochondrial metabolism, metabolic stress responses, and mitophagy, resulting in improved stem cell function in transplantation assays in vivo. In contrast, HSPCs from old mice fail to enhance mitochondrial function or to activate stress response pathways in response to DR. Consequently, HSCs from old DR-exposed mice do not show an enhancement in functionality compared to HSCs from ad libitum (AL) fed mice. Of note, the supplementation of the NAD precursor, NR (Mouchiroud et al., 2013), rescues mitochondrial function, metabolic plasticity, nutrient sensing, and the regulation of stress response pathways in HSPCs from old mice, whereas chemical mitotoxins induce aging-like loss of metabolic plasticity in HSPCs from young mice. These results show that mitochondrial function itself represents an essential factor for DR-mediated induction of metabolic and functional enhancements of HSPCs. These responses to nutrient availability are disrupted by aging-associated mitochondrial dysfunction but reinstalled by NR supplementation.
[0217] Results of the Examples 1-8
Example 1: Body Weight Stabilization and Improvements in HSC Function in Response to DR are Abrogated in Aged Versus Young Mice
[0218] To analyze whether the age at intervention would impact on the outcome of DR, young mice (3-5 months) and old mice (20-22 months) were switched to dietary restriction (DR: 30% reduction of the individual food consumed under ad libitum—AL—conditions) or kept under AL feeding (see materials and methods). All mice were kept in single cage housing (on AL diet starting 2 weeks before the diet assignment) to accurately monitor individual food intake. The experimental cohorts of mice were followed for 4 months using the same single mouse housing regiment. During the first 9 days after switching the diet to DR, mice from both age groups lost ˜10-20% of the body weight compared to the pre-intervention body weights (
Example 2: Aging Abrogates Metabolic Plasticity of HSPCs to Respond to Changes in Nutrient Availability In Vivo
[0219] The above results showed that young mice may have the capacity to metabolically adapt to DR within 2 weeks, in order to stabilize body weight in response to reductions in nutrient availability, while old mice lose this capacity (
[0220] To directly analyze whether age-related changes in metabolic plasticity may influence the outcome of DR in mice, HSPCs were freshly isolated from young and old mice that were kept on AL diet or being switched to DR for 2 weeks. This time point was chosen since the body weight data indicated that young mice had adapted during this time window and managed to stabilize body weight despite the continuous exposure to DR (
[0221] The analysis of HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) from the same mice revealed a decrease in lactate levels and unchanged pyruvate levels in response to 2-weeks DR in young mice (
[0222] Together, the above experiments indicated that HSPCs from young mice adapt to changes in nutrient availability, resulting in increases in mitochondrial respiration and ATP production. However, HSPCs from old mice fail to adapt to changes in nutrient availability in a similar way.
Example 3: Aging Associates with Mitochondrial Dysfunction in Murine HSPCs
[0223] Decreases in mitochondrial function occur in various tissues during aging and in aging associated diseases (Sun et al., 2016). To determine if aging-associated metabolic compromise could represent a possible cause for the loss of metabolic adaptation in old HSPCs, the mitochondrial metabolism was analyzed in HSPCs from young and old mice that were kept on AL diet. FACS analysis revealed a reduction in the mitochondrial membrane potential (MtMP) in HSCs of old mice compared to young mice (
[0224] While DR-induced increases in OCR in combination with increases in ATP in HSPCs of young mice (
[0225] Mitochondria also influence the cellular pools of NAD/NADP (Xiao et al., 2017). Mitochondria oxidative metabolism needs NADH as electron donor for oxidative phosphorylation, which in turn leads to production of NAD+, an essential co-substrate to several enzymes, including the Sirtuins, PARPs, and others (Xiao et al., 2017). In addition, mitochondrial ROS clearance consumes NADPH, which functions as an important redox scavenger (Xiao et al., 2017). The cellular levels of NADPH (
[0226] As alterations in NAD/NADP pools can also lead to disturbed expression of nuclear/mitochondrial encoded genes (Cantó et al., 2015), we analyzed the mRNA expression of several key factors for mitochondrial biogenesis and function (
Example 4: HSPCs from Old Mice Exhibit Enhanced, Cell-Intrinsic Dependency on Glycolysis and Abrogated Responses to Mitochondria Inhibition
[0227] The above data suggested that chronic mitochondrial dysfunction could contribute to the failure of metabolic plasticity that was observed in HSPCs from old mice in response to DR in vivo. To determine whether aged HSCs carry cell intrinsic alterations in mitochondrial metabolism, the proteome of highly purified HSCs (CD150.sup.+CD34.sup.−LSK) from our recent publication (Chen et al., 2019) was analyzed for changes in proteins that regulate glycolysis or oxidative mitochondrial metabolism. This analysis revealed a significant upregulation of glycolytic enzymes in HSCs from old compared to young mice (
[0228] To test the functional relevance of these aging-associated changes in the proteome of HSCs, freshly isolated HSCs were exposed to treatment with oligomycin (an inhibitor of mitochondrial oxidative phosphorylation) or to treatment with 2-Deoxy-D-glucose (2-DG) in culture. 2-DG is an inhibitor of phosphoglucose isomerase and hexokinase, the first 2 enzymes initiating glycolysis (Ralser et al., 2008) In response to glycolysis inhibition, HSCs from old mice compared to HSCs from young mice were hypersensitive and exhibited a stronger reduction in cell numbers 5 days after initiation of the treatment (
[0229] To experimentally test whether mitochondrial dysfunction would cause an abrogation of adaptive responses of HSCs to reduction in nutrient availability, young mice were exposed the mitochondrial uncoupler FCCP or vehicle (two injections: day-1 and day-4). One week after the first injection, the mice were analyzed and freshly isolated HSCs of FCCP-treated vs. DMSO-treated mice were exposed in culture to the 3 above described inhibitors of mitochondrial nutrient uptake—a combination of BPTES, Etomoxir, and UK5099, referred to from here on as “3I”. Interestingly, 1-week of FCCP treatment resulted in a dose dependent increase in the number of phenotypic HSCs in bone marrow (
Example 5: Aging-Associated and Chemical-Induced Mitochondrial Dysfunction Abrogates Metabolic Plasticity in HSPCs
[0230] Our above data indicated that HSPCs from old mice exhibit mitochondrial dysfunction (
[0231] To further test this hypothesis, we analyzed the adaptability of mitochondrial metabolic pathways in freshly isolated HSPCs from young and old mice. First, we exposed freshly isolated HSCs to Oligomycin or to control treatment and we analyzed the RNA expression of Lactate dehydrogenase A (Ldha) and Pyruvate dehydrogenase A (Pdha) 3 hours after isolation and drug treatment. This experiment revealed a significant suppression of Ldha expression and a concomitant increase in Pdha expression in HSCs from young mice but HSCs from old mice were irresponsive (
[0232] Together, these results support a model indicating that mitochondrial dysfunction itself stalled HSPCs from old mice in metabolically compromised state, which resulted in a loss of metabolic plasticity to respond to changes in mitochondrial function/nutrient flow into mitochondria. Of note, this response was different from DR-induced responses as the latter were inducing increases in OCR in HSPCs from young mice (
Example 6: Aging Impairs Nutrient Sensing, Transcriptional Stress Responses, and the Induction of Clearance Pathways in HSPCs
[0233] Nutrient sensing pathways represent a prerequisite to activate stress response pathways that enhance cellular fitness in response to decreases in nutrient availability (Fontana et al., 2010). These responses are thought to increase metabolic fitness and to direct biomolecule and metabolic resources away from growth pathways toward an increased usage in repair and maintenance pathways (Geach, 2016). The mTOR signaling pathway controls major growth promoting signals and the pathway is suppressed in response to decreases in nutrient availability (Ochocki and Simon, 2013). FACS analysis revealed a suppression of phosphorylated (active) mTOR and phosphorylated ribosomal protein S6 (p-S6—a downstream target of mTOR) in HSCs of young mice that were exposed to 2-week DR treatment compared to AL-fed control mice (
[0234] The above data indicated that HSPCs from old mice compared to HSPCs from young mice exhibit defects in nutrient sensing and in the activation of stress response genes after short-term exposure (2 weeks) to DR. Nutrient sensing and induction of metabolic stress responses have been shown to lead to the activation of cellular and subcellular clearance mechanisms in response to DR that contribute to the beneficial effects of DR on disease prevention and lifespan extension. Examples include the induction of apoptosis (Dunn et al., 1997; Holt et al., 1998), autophagy/mitophagy (Hansen et al., 2008; Jia and Levine, 2007; Morselli et al., 2010), and unfolded protein responses (Mohrin et al., 2015). Interestingly, defects in clearance systems have been implicated to contribute to aging of HSCs (Ho et al., 2017; Mohrin et al., 2015). To test whether impairments in the induction of cellular or subcellular clearance mechanisms may contribute to the failure of HSPCs from old mice to adapt to DR to increase metabolic and cellular fitness, we followed the induction of autophagy/mitophagy and changes in HSPCs numbers in mice that were exposed to DR or AL control diet for 1-2 weeks.
[0235] In young mice, 2-week DR exposure induced a significant decline in HSC and MPP numbers compared to AL fed animals; however, this response was abrogated in aged mice (
Example 7: Short-Term DR has the Capacity to Ameliorate 80% of the Differences in the Proteome of HSPCs from Young and Old Mice, but Age-Related Alterations of NAD Dependent Biological Processes Remain
[0236] To determine aging-related changes in the proteome of HSPCs and to test whether DR would have the capacity to revert such changes, a proteome analysis was conducted on freshly isolated GMPs and CMPs from young and old mice that were on continuous AL diet or exposed to DR for 2 weeks. These cell types were chosen because they show similar defects in responding to changes in nutrient availability as HSC (see above results) and are available in high enough number per mouse (100,000) to conduct a deep proteomics analysis. In our analysis we detected >4,900 proteins per sample across the different groups. The below description focuses on GMPs because this population is purer and shows less aging-related changes in cell composition compared to CMPs. However, the data on CMPs are similar to those presented here on GMPs. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (Vizcaino et al., 2015) partner repository with the dataset identifier PXD015557 at: http://www.ebi.ac.uk/pride.
[0237] The analysis revealed that a high percentage of DR-induced changes in the proteome of GMPs (>80%) occurred in an age-dependent manner, e.g. only in young or old mice, but not overlapping in both age-groups (
[0238] To determine possible mechanisms that might be related to the failure of DR to re-induce metabolic plasticity in old mice, we analyzed proteins that remained differentially regulated in GMPs of old vs. young mice that were exposed for 2 weeks to DR (log 2 fold change in absolute number >0.25 as indicated by the dotted lines in the density plot of differentially expressed proteins in
[0239] To determine which biological processes were differentially regulated in the proteome of old vs young DR-exposed mice, “ingenuity pathway analysis—IPA” was conducted on all proteins that showed a significant difference (q-value <0.05) in expression in GMPs of DR-exposed, old vs. young mice. This analysis revealed the strongest enrichment for two biological processes (
Example 8: NR Supplementation Re-Installs Mitochondrial Function and Metabolic Plasticity in HSCs from Old Mice to Respond to Changes in Nutrient Availability
[0240] To test the hypothesis that NAD(P) availability limits the potential of HSPCs from old mice to respond to changes in nutrient availability, freshly isolated HSCs from young and old mice were exposed to inhibitors of mitochondrial nutrient uptake. Freshly isolated HSCs from young and old mice were pre-treated for 12 hours with NR—a potent progenitor of NAD synthesis, which has been shown to promote mitochondrial activity and lifespan extension in mice (Zhang et al., 2016)—or with a vehicle control. In line with our previous results (
[0241] Discussion of the Results of Examples 1-8
[0242] The present study provides direct experimental evidence that aging associated mitochondrial dysfunction abrogates metabolic plasticity of HSPCs to respond to reductions in nutrient availability. This leads to a failure of DR to induce metabolic and functional enhancements of HSCs in old compared to young mice. The study also demonstrates that the supplement of NAD precursors reinstalls mitochondrial function and the responsiveness of old HSCs to react to reductions in nutrient availability. Taken together these results determine mitochondrial function as an essential factor for metabolic and functional responsiveness of HSPCs to changes in nutrient availability. As aging related loss in mitochondrial abrogates metabolic plasticity, the study implies that the supplementation of NAD precursors would be required to reinstall DR-mediated improvements in HSC function and organism aging.
[0243] Mitochondrial Dysfunction Limits Metabolic Plasticity to Adapt to Changes in Nutrient Availability in Aging HSPCs.
[0244] Increases in mitochondrial nutrient flow and oxidative metabolism have previously been implicated to contribute to the extension of lifespan in response to DR in different model organisms including yeast (Lin et al., 2002), C. elegans (Bishop and Guarente, 2007; Weir et al., 2017), and mice (Nisoli et al., 2005). Studies on yeast have shown that cytochrome-c-dependent mitochondrial respiration is required for DR-mediated lifespan extension and that over-activation of mitochondrial biogenesis by itself leads to lifespan extension, which could not be enhanced any further by DR (Lin et al., 2002). These results suggested that increases in mitochondrial respiration represent an integral hub required for the lifespan extension in response to DR. This assumption was supported by studies on C. elegans showing that the induction of skn1-dependent signals in neurons is required for mitochondrial activation in somatic tissues and for DR-mediated lifespanextension (Bishop and Guarente, 2007). Importantly, aging-related limitations in mitochondria activation and its mechanistic consequences on cellular and organismal fitness in response to changes in nutrient availability have not been delineated.
[0245] The current study shows that the aging-associated failure to increase mitochondrial respiration represents a major cause for the loss of metabolic plasticity of aged HSPCs to adapt to changes in nutrient availability. The study reveals that the in vivo application of mitotoxins (FCCP) to young mice leads to mitochondrial dysfunction, which is sufficient to abrogate the metabolic responsiveness of HSPCs to adapt to changes in nutrient availability thus mimicking the aging phenotype. Furthermore, the supplementation of NAD precursors reinstalls mitochondrial activity with the subsequent responsiveness of aged HSCs to adapt (modify) proliferation rates, oxidative metabolism, and the expression of stress signaling pathways in response to changes in nutrient availability. These findings indicate that NAD dependent mitochondria dysfunction is a causative factor for the loss of metabolic and functional plasticity of HSPCs during aging. These results could have important implications for our understanding of stem cell and organism aging in general. Previous studies showed that transient inhibition of mitochondrial function in C. elegans only resulted in lifespan extension when applied during developmental stages but not when given to adult worms (Lin et al., 2002). It is conceivable that the decline in mitochondria function during the maturation and aging of C. elegans limits metabolic plasticity and the induction of lifespan extension. In agreement with this interpretation, DR-induced effects on reduction of mortality rates in mice are greatly impaired during aging, coinciding with a reduced capacity of white adipose fat tissue (WAT) to increase phospholipid-dependent mitochondrial biogenesis (Hahn et al., 2019)
[0246] Supplementation of NAD Precursors Reinstalls Metabolic Plasticity and the Responsiveness of Old HSCs to Changes in Nutrient Availability.
[0247] It has been proposed that the activation of mitochondrial metabolism leads to intra-mitochondrial and intracellular increases in NAD/NADP ratios, which in turn contribute to the activation of NAD-dependent stress responses that increase cellular fitness (Guarente, 2008). The current study shows that DR has the capacity to revert large proportions of aging-related alterations in the proteome of HSPCs. However, proteins involved in NAD dependent biological processes are not normalized but strongly dysregulated in old vs. young DR-exposed mice. These processes include a reduction in Sirtuin signaling and an increase in the expression of protein of complex I of the mitochondrial respiratory chain, which are required for initiation of oxidative phosphorylation (
[0248] Previous studies revealed that impairments in Sirtuin signaling (Brown et al., 2013; Mohrin et al., 2015) and autophagy (Ho et al., 2017) contribute to the aging-associated decline in HSC function. The current study indicates that aging-associated mitochondrial dysfunction abrogates nutrient sensing and the regulation of stress response pathways in old HPSCs. However, these deficiencies can be reversed by NR supplementation, which improves mitochondrial function and the regulation of stress signaling pathways in activated HSCs from old mice in culture. Studies on the in vivo application of NR to young mice also revealed evidence that NR reduces mitochondrial activity in HSCs by enhancing autophagy mediated clearance of mitochondria (Vannini et al., 2019). It is possible that NR dependent improvements in autophagy-mediated clearance of dysfunctional mitochondria also contribute to the here described potential of NR to rescue mitochondrial oxidative metabolism and consequently the responsiveness of old HSPCs to adapt to changes in nutrient availability.
[0249] Together, the current study provides experimental support that in old mice chronic mitochondrial dysfunction stalls HSPCs in a compromised metabolic state, leading to a loss of nutrient sensing and metabolic plasticity to respond to changes in nutrient availability. These defects limit the capacity of DR to induce mitochondrial metabolism, adaptive stress responses, and functional enhancement of HSPCs in old mice. It is conceivable that the aging-related failure in nutrient sensing and in induction of stress signaling pathways may also contribute to the functional decline of HSCs during aging, by for example abrogating circadian responses to changes in nutrient availability induced by pauses in nutrient uptake. The study identifies deficiencies in NADH as a key factor, which limits the induction of metabolic plasticity and adaptive responses in old HSCs. Importantly, the supplementation of NAD precursors reinstalls mitochondrial function, metabolic plasticity and adaptive responses of old HSCs to respond to reductions in mitochondrial nutrient flow. These findings imply that combining dietary interventions with the supplementation of NAD precursors have the potential to improve stem cell and organism function at old age.
Example 9: NAD Precursor Supplementation in Combination with CRD Rescues Mitochondria Function, the Induction of Stress Response in Hematopoietic Stem and Progenitor Cells of Old Mice—Results and Discussion
[0250] Based on our results, we reasoned that mitochondria enhancement could possibly re-install mitochondria plasticity to respond to changes in nutrient availability and, thereby, the capacity of DR (=CRD) to induce transcriptional responses and functional improvements of HSCs of old mice. However, the potential of mitochondria enhancement to reinstall mitochondrial responses to nutrient deprivation has never been explored.
[0251] To experimentally test whether mitochondrial enhancement could re-empower DR (=CRD) in old mice, young and old mice were exposed to NAD+ supplementation by feeding of nicotinamide riboside (NR). In addition, the mice were exposed for 2 weeks to DR (=CRD), starting 1 week after NR pre-feeding, or continuous AL feeding. Respirometry analysis of freshly isolated CMPs from young mice showed that either one of the single treatments (NR-alone or DR-alone) led to significant increases in mitochondrial respiration compared to HSCs from AL-fed, young mice, but there was no additive effect of NR/DR combination (
[0252] Similar results were obtained when freshly isolated GMPs from the mice of the 2-weeks dietary intervention cohorts were exposed to glucose deprivation in culture—it was only the combination of NR/DR treatment that reinstalled the cell-intrinsic capacity of GMPs from old to activate mitochondrial respiration in response to glucose depletion (
[0253] To analyze whether the NR/DR-mediated re-installment of mitochondrial metabolic plasticity in HSCs from old mice could rescue the induction of metabolic stress signals, freshly isolated HSCs from 2-week dietary cohorts were analyzed with the same NanoString assay as described above. In HSCs from young mice, supplementation of NR-alone induced metabolic stress signals (
[0254] Together, these results demonstrated that the capacity of dietary interventions to induce metabolic stress signaling depends strictly on the induction of mitochondrial activity, which in young mice can be achieved by either NR- or DR-treatment alone, whereas in old mice this can only be achieved by combining NAD precursor supplementation with DR-exposure.
Example 10: NAD Precursor Supplementation in Combination with CRD Improves Stem Cell Function and Lifespan of Old Mice—Results and Discussion
[0255] Transplantation of freshly isolated HSCs showed that all 3 dietary short-term interventions (2 weeks of DR-alone (=CRD), NR-alone (=NAD precursor supplementation) or NR/DR co-treatment) increased the repopulation capacity of HSCs from young mice (
[0256] To test effects of these dietary intervention on organism lifespan, 4 cohorts of 22-24 months old female mice (n=14-15 mice per group) were exposed to long-term treatments (until the end of life or the occurrence of humane endpoints). Single treatment with DR or NR led to slight increases in lifespan compared to AL-fed control mice (
[0257] Together, the data provide experimental evidence that aging-associated mitochondrial dysfunction abrogates the metabolic plasticity of HSPCs to respond to changes in nutrient availability by activating mitochondria respiration. These defects in turn impair DR-mediated induction of metabolic stress signals and health benefits of DR in old mice, such as HSC enhancement and lifespan elongation. The current work provides a mechanistic understanding for the failure of DR at old age and identifies a dietary intervention that reinstalls it. The study shows that mitochondria activation is a key mechanism, which fails to respond to DR in old vs. young mice. This failure can fully be rescued by NAD-precursor supplementation, which in turn enables DR (=CRD) to induce mitochondria activity, metabolic stress signaling, functional enhancement of HSPCs, and lifespan extension in old mice.
[0258] Importantly, the here described effect of late-life NR/DR treatment on overall lifespan appears to be very strong (>23% increase in median life expectancy compared to AL with currently 55% of the mice still being alive, p<0.0001) compared to the best, currently known dietary interventions that increase lifespan when applied to old mice, such as Spermidin or single NR treatment (6.9% in previous studies, 10% in this study with the effect not being significant) or single DR-treatment (no effect in previous studies, 10% in this study with the effect not being significant).
[0259] Given the global increases in size of the elderly population and in aging-associated diseases, a powerful, non-toxic, dietary intervention that increase health at old age would fulfill a huge unmet need. In humans, NAD precursor supplementation in combination with DR could represent a promising approach to achieve this goal.
Example 11: NAD-Precursor Supplementation Cooperates with Mitochondria-Inhibiting CRMs to Induce Mitochondria Activity—Results and Discussion
[0260] To test whether NAD precursor supplementation would cooperate with specific CRMs that mimic a certain sub-pathway induced by CRD, different classes of CRMs were employed. We tested the combined effects of NAD supplementation with [0261] (a) Metformin—a CRM, which induces mitochondrial stress [0262] (b) Pterostilbene—a CRM which induces Sirtuin-dependent stress responses including autophagy [0263] (c) Spermidine—a CRM, which induces autophagy (ad ownstream target of sirtuins (see above)
[0264] Old mice (22-24 months) were fed with CRMs (a-c) with or without combination with NAD-precursor supplementation for 2 weeks before analysis. Freshly isolated hematopoietic cells (CMPs) were tested for a rescue in responsiveness to activate mitochondria in response to glucose depletion—a marker of metabolic improvement induced by CRD in young mice or by a combination of NAD precursor supplementation plus CRD in old mice.
[0265] Of note NAD precursor supplementation showed synergistic effects on inducing mitochondria activity only when combine with metformin, which mimics the mitochondria stress induction of CRD. In contrast, NAD precursor supplementation showed no synergistic effects on inducing mitochondria activity when combined with pterostilbene mimicking the sirtuin/autophagy induction of CRD. Based on these results we anticipate that NAD precursor supplementation will also not show synergism with spermidine mimicking the induction of autophagy downstream of sirtuin activation in response to CRD.
[0266] Together these results show that NAD precursor supplementation has a great synergistic potential to induce mitochondria activity and health benefits in combination with the subclass of CRMs mimicking mitochondrial stress induced by CRD.
[0267] Methods Employed in the Examples
[0268] Mice:
[0269] All wild type mice used were C57BL/6 mice and obtained from Janvier. Mice were maintained in a specific pathogen-free animal facility in FLI with 12 hours of the light-dark cycle and fed with a standard mouse chow food. Experiments were conducted according to protocols approved by the state government of Thuringia (FLI17-006, FLI19-009, and O_KLR_18-20).
[0270] Dietary Restriction and Weight Curve
[0271] Prior to the start of dietary restriction (DR) experiment the daily food consumption of Young (2-3 months) and old (20-24 months) female WT C57BL/6 mice were measured for 2 weeks. Each mouse was placed in single cage. Mice that were exposed to DR were given 30% reduction of their daily food consumption. Mice in the control group (AL) were given unlimited access to ad libitum food (VRF1 from Sniff). The mice were always fed during the morning time. The weight of each mouse was measured before and during the experiment. The weight change for each mouse was calculated as follows: the weight of individual mouse at the indicated time point was divided by its initial weight one day before the start of DR experiment.
[0272] Dietary/Calorie Restriction Mimetics (CRM)
[0273] Old mice (22-24 month) were treated with CRMs: [0274] (a) Metformin-Hydrochlorid (0,1% weight proportion of chow)—metformin is a CRM that mimics mitochondrial stress induced by CRD, metformin does so by inhibiting complex-1 of the electron transport chain (ETC) of the mitochondria. [0275] (b) Perostilbene (120 mg/kg chow)—is a CRM, which leads to sirtuin activation. Sirtuin is also activated in response to CRD. Sirtuin activation induces stress responses including autophagy, which increases the quality of mitochondria by digesting dysfunctional mitochondria. [0276] (c) Spermidine (3 mM in the drinking water)—is a CRM, which induces autophagy, Autophagy is induced by Sirtuin activation. It is thus a downstream target of Sirtuins (see above).
[0277] (a-c) CRMs were given to mice for 2 weeks, (c) CRM was given to mice for 2 months to reach systemic increases in spermidine. Mice were treated with the CRM-alone or in combination with NAD-precursor feeding (NR) for 2 weeks prior to analysis.
[0278] Transplantation
[0279] Two hundred freshly isolated HSCs (CD150.sup.+CD34.sup.−Flt3.sup.−LSK) from each individual mouse were transplanted via intravenous injection into lethally gamma-irradiated (12 Gy) young recipients (2-3 months) recipients together with 1×10.sup.6 of competitor bone marrow cells. During the first week of transplantation the mice were provided with antibiotic water (0.01%, Baytril). The repopulation capacity in peripheral blood was measured by BD LSR Fortessa every 4 weeks for the whole period of transplantation. Four months after transplantation the mice euthanized and bone marrow was taken for chimerism analysis by BD LSR Fortessa or BD FACS ARIA Ill.
[0280] FCCP Injection
[0281] Young C57BL/6 wild type mice (3 months) male mice were weighed before the injection. The mice were then injected intraperitoneally with low dose (1.2 mg/Kg), high dose (4.82 mg/Kg) of FCCP, or 10% DMSO as control (all drugs were dissolved in 10% DMSO. The drug concentration was adjusted so that the final volume of injection of each injection is 150 pL/mouse. The mice were injected at day 1 and day 4 after weighing. Then they were analyzed at day 6.
[0282] FACS Sorting and Analysis
[0283] Bone marrow (BM) cells were obtained and isolated from fore limbs, hind limbs, pelvis and spine. After completely cleaning off the muscle and connective tissue, all the bones were crushed in sterile PBS containing 2% heat-inactivated FBS (staining media) using mortar and pestle. For isolating specific populations in BM cells, single-cell suspensions were enriched for c-Kit.sup.+cells by sequentially staining with c-Kit-APC (Biolegend) antibody and anti-APC microbeads (Miltenyi Biotec) on ice. The c-Kit.sup.+cells separated and harvested by MACS Separation LS Columns (Miltenyi Biotec) on magnetic stand (Miltenyi Biotec). The enriched cells were then stained with linage antibody cocktail containing biotinylated antibodies against CD4 (Biolegend, 100508), CD8 (Biolegend, 100704), TER-119 (Biolegend, 116204), CD11b (Biolegend, 101204), Gr-1 (Biolegend, 108404) and B220 (Biolegend, 103222) at 4° C. for 30 min. After washing, cells were incubated with a mix of antibodies against FcYR-FITC, Flt3-PE, Sca1-PE/Cy7, c-Kit-APC, Streptavidin-APC/Cy7, CD34-Alexa Fluor 700, and CD150-Brilliant Violet 605. After staining, the cells were washed and resuspended with 1 mL staining media containing 0.5 uL DAPI (1 mg/mL) to exclude dead cells. The desired cell populations according to the cell surface markers were subsequently sorted by BD Aria III flow cytometer.
[0284] For FACS analysis, freshly isolated total BM cells (1×10.sup.7) were stained with antibodies to detect the desired surface markers. After antibody staining, BM cells were incubated with Rhodamin123 (Thermo)—PBS (1.25 μg/mL) to detect mitochondrial membrane potential, or incubated with CellROX reagent (Thermo, 1:500 diluted) in 200 uL PBS at 37° C. for 30 mins to detect ROS. After staining, samples were washed with 1 mL staining media for twice, resuspended in 500 uL staining media with DAPI (1 μg/mL) and then were kept on ice for FACS analysis. For intracellular antigen detection: p-mTor, (pS2448), p-S.sup.6 (pS235/pS236), p-Akt (S473), and Pink1, BM cells were fixed with 100 ul Fixation/Permeabilization Solution (Fisher scientific, BD 554714) for 10 min and stained with p-mTor (BD Biosciences, 563489), p-S6 (BD Biosciences, 560434), p-Akt (R&D, IC7794G), or Pink1 (Abcam, ab186259) antibody overnight. After staining, samples were washed with 1 mL perm wash buffer (Fisher scientific, BD 554714) twice and FACS analysis was performed using BD LSR Fortessa.
[0285] Analysis of Transplanted Mice
[0286] For analysis of chimerism in peripheral blood (PB) of transplanted mice, 30 uL of EDTA-collected blood was stained with CD45.2-Percp-Cy5.5 (Biolegend, 109828) CD45.1-PE (Biolegend, 110708) conjugated anti-mouse antibodies for 30 min on ice. The cells were then lysed with 1×RBC lysis Buffer (BD Biosciences, 555899) for 5 min. The cells were then washed with 1×PBS and centrifuged for 5 min at 300 g on 4° C. The cells were then resuspended in 2% FBS in PBS and analyzed by BD LSR fortessa. For the analysis of hematopoietic stem and progenitor cells (HSPCs) from transplanted mice 10×10.sup.6 total bone marrow cells were incubated with a lineage cocktail containing biotinylated antibodies against CD4 (Biolegend, 100508), CD8 (Biolegend, 100704), TER-119 (Biolegend, 116204), CD11b (Biolegend, 101204), Gr-1 (Biolegend, 108404) and B220 (Biolegend, 103222) at 4° C. for 30 min. After washing, cells were incubated with a mix of antibodies against CD45.2-Percp-Cy5.5 (Biolegend, 109828) CD45.1-PE (Biolegend, 110708), CD150-Bv605 (Biolegend, 115927), CD34-AF700 (eBioscience, 56-0341-82), Flt3-PE (Biolegend, 135306), FcYR-FITC (Biolegend, 101306), Sca-1-PE-Cy7 (Biolegend, 108114), c-Kit-APC (Biolegend, 105812), and streptavidin-APC-Cy7 on ice. (Biolegend, 405208)
[0287] Cell Culture
[0288] HSCs and progenitors were cultured in SFEM medium (STEM CELL Technologies, 09650) supplemented with 50 ng/mL mSCF (Peprotech, 250-03), 50 ng/mL mTPO (Peprotech, 315-14), 100 units/mL penicillin, 100 μg/mL streptomycin (Gibco, 15140-122). For testing the response of HSPCs to the blocking of glycolysis or mitochondrial ATP synthesis, 2-DG (Sigma, D8375) or oligomycin A (Sigma, 75351) were used. For the inhibition of nutrient uptake into mitochondria, three inhibitors (3I) were used. BPTES (Sigma, SML0601) blocks glutamate uptake, Etomoxir (Sigma E1905) blocks Fatty acids uptake, and UK5099 (Sigma PZ0160) blocks pyruvate uptake. The final concentration of each inhibitor in the culture medium is 6 μM. Same amount of DMSO was used in the medium as control. For determination of cell number after NR treatment 500 HSCs from young (2-3 months) and old (22-24 months) were pre-incubated either with 1 mM NR (provided by Prof. Johan Auwerx Lab) or DMSO as control for 2 days followed by 2 days treatment with the inhibitors (BPTES, Etomoxir and UK5099, 6 μM each) or same amount of DMSO as control. The cells were then analyzed by BD LSR fortessa.
[0289] Seahorse Analysis
[0290] Measurement of metabolic activity was done using XF96e according to the guidelines of Agilent Seahorse XF Cell Mito Stress Test (Agilent technologies). In brief, XF base medium (Agilent technologies, 102353) was supplemented with final concentration of 1 mM pyruvate, 2 mM glutamine, 10 mM glucose, 50 ng/mL mTPO, and 50 ng/mL mSFC. The medium was adjusted to pH of 7.4 at 37° C. and filtered. Freshly isolated cells were seeded into 96-well seahorse cell culture plate pre-coated for 3 h with poly-lysine. The cells were then cultured with 180 μl of the adjusted medium and the plate was centrifuged at 300 g for 5 min. The cells were then cultured in 37° C. non-CO.sub.2 incubator for 1 h before the measurement. Mito-stress assay was performed according to the manufacturer protocol (Agilent technologies). The concentration of drugs used in the assay was 2 μM oligomycin, 4 μM FCCP, and 1 μM of rotenone/Antimycin A (sigma). For CMP and GMP 80,000 cells were used. For MPP 60,000 cells were used. For seahorse analysis of NR experiment (
[0291] NanoString Analysis
[0292] Measuring of RNA expression by NanoString was done according to our previous publication (Chen et al., 2019) and according to manufacturer protocol (NanoString technologies). In brief, 1×10.sup.4 cells were lysed in 2 μL of lysis/binding solution (Applied Biosystems, 8500G14). The cell lysate was then used for hybridization reaction as following: 2 μL of cell lysate was mixed with 5 μL of nCounter hybridization buffer (NanoString), 2 μL of Core Tagset, 2 μL of extension Tagset, 0.5 μL of 0.6 nm Probe A working pool, 0.5 μL of 0.6 nm probe A extension Pool, 0.5 μL of 3 nm Probe B working pool, and 0.5 μL of 3 nM Probe B extension pool (from IDT technologies). 2 μL of Nuclease-free water was added to each reaction to reach a final volume of 15 μL. The reaction mixture was prepared in Strip tubes (from NanoString technologies). Then it was incubated at 67° C. using thermal cycler (Masterycler from Eppendorf) for 16 h. Afterward, the Nanostring chemistry was processed automatically using nCounter prep-station 5s (NanoString technologies) according to manufacturer protocol. Directly after the run, the nCounter Cartridge was loaded into nCounter digital analyzer 5s (NanoString technologies). For NanoString analysis on young and old mice exposed to DR or AL food, freshly FACS-Sorted MPPs (CD34.sup.+Flt3.sup.− LSK) were used. For NR treatment, freshly FACS-Sorted MPPs (CD34.sup.+Flt3.sup.− LSK) from young and old mice were pretreated with 1 mM NR or the 31 (6 μM each) or DMSO for 12 h. Cells from NR treatment and DMSO were divided into 2 halves and further treated with 3I (6 μM each) or DMSO as control. The cells were harvested for NanoString analysis as described above. Data analysis was done after background correction using nSolver advanced analysis software (v.4) and (R software v 3.3.2.). The following housekeeping genes were used for normalization: ActB, B2M, Gapdh, Gusb, Hprt, PGK1, Polr1b, Polr2a, Ppia, Rpl19, Sdha, and Tbp. Heatmaps and volcano plots was done using GraphPad prism software version 8.
[0293] Proteomics of CMP and GMPs
[0294] 1×10.sup.5 PBS—washed cells (CMPs/GMPs) were FACS sorted directly into concentrated lysis buffer; the final composition was 1% SDS, 100 mM HEPES, 50 mM DTT, pH8.0). Samples were snap-frozen in dry ice before preparation for the proteomics data acquisition. After thawing on ice, samples were sonicated using a Bioruptor (60 sec ON/30 sec OFF, 10 cycles, high intensity at 20° C.) (Diagenode, Beligum), then heated to 95° C. for 10 min, before a repeat set of sonication cycles as before. Alklyation to block cysteines was carried out with iodoacetamide (15 mM final concentration, 30 min, dark, room temperature). Protein precipitation was carried out using 8× sample volume of ice-cold acetone and samples were left at −20° C. overnight. The following day, samples were centrifuged (20800× g, 30 min, 4° C.), supernatant carefully removed, and protein pellets washed twice with ice cold 80% acetone/20% water (300 μL), 10 min centrifugation (as above)). After removal of the second wash, pellets were air-dried before resuspension in the digestion buffer (1M Guanadine HCl in 0.1M HEPES, pH 8; LysC (1:100 enzyme:protein ratio), then incubated for 4 h at 37° C. The samples were diluted 1:1 with Milli-Q water (to reach 0.5 M GuaHCl) and incubated with trypsin (1:100 enzyme:protein) for 16 h at 37° C. The digests were then acidified with 10% trifluoroacetic acid and then desalted with Waters Oasis® HLB pElution Plate 30 μm (Waters Corporation, Milford, Mass., USA) in the presence of a slow vacuum. In this process, the columns were conditioned with 3×100 μL solvent B (80% acetonitrile; 0.05% formic acid) and equilibrated with 3×100 μL solvent A (0.05% formic acid in Milli-Q water). The samples were loaded, washed 3 times with 100 μL solvent A, and then eluted into PCR tubes with 50 μL solvent B. The eluates were dried down with the speed vacuum centrifuge prior to resuspension in 10 μL MS Buffer (5% acetonitrile, 95% Milli-Q water, with 0.1% formic acid) containing 0.25 μL of iRT kit (Biognosys AG) for the MS analyses.
[0295] LC-MS/MS (DDA for Library and DIA)
[0296] Data were acquired on a QE-HFX MS (Thermo), connected to an M-Class NanoAcquity (Waters).
[0297] The outlet of the analytical column was coupled directly to the mass spectrometer using the Proxeon nanospray source. Solvent A was water, 0.1% formic acid and solvent B was acetonitrile, 0.1% formic acid. Approximately 1 μg of each of the samples (reconstituted at estimated 1 μg/μL and spiked with iRT kit peptides (Biognosys AG, Switzerland)) were injected for LC-MS with a constant flow of solvent A, at 5 μL/min, in trapping mode. The trapping time was 6 min. Peptides were eluted via the analytical column with a constant flow of 0.3 μL/min. During the elution step, the percentage of solvent B increased in a non-linear fashion from 0% to 40% in 120 min. Total runtime was 145 min, including clean-up and column re-equilibration. The peptides were introduced into the mass spectrometer via a Pico-Tip Emitter 360 μm OD×20 μm ID; 10 μm tip (New Objective) and a spray voltage of 2.2 kV was applied. The capillary temperature was set at 300° C. The ion funnel RF was set to 40%. DDA data were acquired on pools of each condition, with the following settings: Full scan MS spectra with mass range 350-1650 m/z were acquired in profile mode in the Orbitrap with resolution of 120000. MS1 fill time was 20 ms, AGC target 3e6. Top N was used (=15) and the intensity threshold was 4e4. Normalized Collision Energy (NCE) with HCD was set to 27% and a 1.6 Da window was used for quadrupole isolation. MS2 data were acquired in profile mode from 200-2000 m/z. MS2 fill time was 25 ms or an AGC target of 2e5. Only 2-5+ charge states were selected for MS/MS. Dynamic exclusion was 20 s, and the peptide match “preferred” option was selected. For the DIA data, LC conditions remained unchanged. Full scan MS spectra with mass range 350-1650 m/z were acquired in profile mode in the Orbitrap with resolution of 120000. The default charge state was set to 3+. The filling time was set at maximum of 60 ms with limitation of 3e6 ions. DIA scans were acquired with 34 mass window segments of differing widths across the MS1 mass range. HCD fragmentation (stepped normalized collision energy; 25.5, 27, 30%) was applied and MS/MS spectra were acquired with a resolution of 30000 with a fixed first mass of 200 m/z after accumulation of 3e6 ions or after filling time of 40 ms (whichever occurred first). Data were acquired in profile mode. For data acquisition and processing of the raw data Xcalibur 4.0 (Thermo Scientific) was used in parallel with Tune version 2.9.
[0298] Data Analysis for DIA Data
[0299] For library creation, the DDA and DIA data were searched using the Pulsar search engine within Spectronaut (Spectronaut (version 13.1.190621.4365); Biognosys AG, Zurich, Switzerland). Data were searched against a species specific (Mus musculus) Swissprot database (01/2016, 16756 entries) alongside the database of common contaminants. The data were searched with trypsin/P specificity and the following modifications: Carbamidomethyl (C) (Fixed) and Oxidation (M)/Acetyl (Protein N-term) (Variable). A maximum of 2 missed cleavages was allowed. The identifications satisfied an FDR of 1% on both peptide and protein level. All other settings were the defaults from Biognosys (Bruderer et al., 2017; Rosenberger et al., 2017; Storey, 2002).
[0300] The resulting library contained 77363 precursors, corresponding to 4957 protein groups using Spectronaut protein inference. DIA data were then uploaded and searched against this spectral library in Spectronaut. Relative quantification was performed in the software for each pairwise comparison using the replicates from each condition. Quantification settings were modified from the defaults in the following way: Median and no Top N for the major and minor group quantities; data filtering on q-value percentile (0.5), no imputation, local cross-run normalization on q-value (sparse). The post-analysis settings were set to use the unpaired strategy. 7 samples were removed from the dataset due to poor quality recovery of material as seen in the MS chromatograms. The data (candidate table) and data reports were then exported as tables and further data analysis and visualization were performed with R-studio (version 1.0.153, employing R-version 3.6.1 (The R Foundation for Statistical Computing)) using in-house pipelines and scripts. Gene Set Enrichment Analysis (GSEA) on relevant pairwise comparisons was performed using Webgestalt ((Liao et al., 2019; Wang et al., 2013; Wang et al., 2017; Zhang et al., 2005).
[0301] Measurement of ATP, Lactate, and Pyruvate
[0302] The FACS purified HSC pellet (1000-1500 cells) lysed by 20 μL 1% NP40 on ice for 10 min and centrifuged at 8000 g for 5 min. The cell lysate was transferred into new clean tubes. The cellular ATP in low number of HSCs was measured by the ATP determination Kit (Thermo, A22066). Briefly, the ATP reaction solution and standard samples were prepared following the instruction manual with the reagents provided in the kit. The cell lysate (10 μL per sample) and standards were mixed with 100 μL ATP reaction solution and then added into the black 96-well flat bottom plate (Thermo). The plate was gently shaken, and the intensity of luminescence was measured for each well by microplate reader (Tecan). The relative cellular ATP level of each sample was calculated by subtracting the intensity value of empty control and divided by the initial cell number of the individual sample. For lactate or pyruvate measurement, the reagent was prepared according to the instruction manual of the Lactate Assay Kit (Sigma, MAK064) or Pyruvate Assay Kit (Sigma, MAK071). The cell lysate (3-5 μL per sample) was mixed with 50 μL Master Reaction Mix and added into the black 96-well flat bottom plate (Thermo). The plate was shaken briefly and incubated at room temperature for 10-30 min before the measurement. The cellular level of lactate or pyruvate was determined by measuring fluorescence intensity (λ.sub.ex=535 nm/λ.sub.em=587 nm) on microplate reader (Tecan).
[0303] Immunofluorescence Staining
[0304] FACS purified cells were dropped on poly-Lysine pre-coated slides and seated at 4° C. for 0.5-1 h to let the cells attached to the slides. Then the cells were fixed by 3.7% paraformaldehyde/PBS for 10 min at room temperature, followed by washing with PBS. Slides were permeabilized in 0.3% Triton X-100/2% BSA/PBS for 30 mins at room temperature and blocked in 2% BSA/PBS for 30 mins at room temperature. The cells were then incubated with LC3 (Biorbyt, orb97657) and Tom20 (Santa Cruz Biotechnology, sc-11415) antibodies for 1 h at room temperature. After washing with PBS 3 times, the cells were then incubated with secondary antibodies: AF594 conjugated donkey anti-rabbit (Life Technologies, A21207) and AF647 conjugated donkey anti-mouse (Life Technologies, A31571) for 30 min at room temperature. After staining, the slides were washed by PBS for 3 times and mounted by mounting medium (Vector Laboratories, H-1000) containing 1 μg/mL DAPI. The cells were imaged on Zeiss Axio Imager Microscope (100× objective), and the images were processed using ZEN Software (Zeiss). The fluorescence intensity per cell was measured by ImageJ on 19 cells per mouse to calculate the mean fluorescence intensity (MFI) of an individual mouse.
[0305] LC-MS (Metabolites)
[0306] Different populations of hematopoietic stem and progenitor cells (30000 cells per condition) were purified by FACS. The cell pellets were resuspended with ice cold 80% methanol and immediately stored in −80° C. for overnight. The samples were thawed at 4° C. on the next day, and centrifuged at the highest speed for 20 min at 4° C. The supernatant was transferred into new tubes and mixed with equal volume of acetonitrile and stored at −80° C. until analysis. Liquid Chromatography coupled to Mass Spectroscopy (LC-MS) analysis was conducted on a Q-Exactive—Orbitrap mass spectrometer interfaced with a Dionex UltiMate 3000 LC system (Thermo). LC separation was conducted using a ZIC-cHILIC column (10×2.1 mm, 3 μm, Merck, USA), using a gradient from buffer B (10 mM CH.sub.3COONH.sub.4 pH5.8, 90% acetonitrile) to buffer A (10 mM CH.sub.3COONH.sub.4 pH5.8, 10% acetonitrile). The column compartment was kept at 20° C. during analysis. The maximum injection volume was 10 μL. The following parameters for the HESI ions source were used: Sheath gas flow rate—48 units; Aux gas flow rate—11 units; Sweep gas flow rate—2 units; Spray voltage—3.5 kV; Capillary temperature—256° C.; S-lens RF level—90 units; Aux gas heater temperature—413° C. Mass spectra were recorded by tSIM at positive polarity and maximum resolution (140,000). Metabolites in the samples were quantified by peak integration in the XCalibur software using processing setup. A cell extract containing nucleotides with fully C13-saturate ribose was generated by growing 293 cells in presence of 6×C13-labeled glucose. Samples were spiked with this cell extract, and concentrations of the endogenous metabolites were determined by comparing the peak area of the endogenous metabolite to the internal standard. Fragmentation analysis was performed to confirm identification of the detected metabolites.
[0307] Statistical Analysis and Generation of Graphs
[0308] All data are presented as mean with standard deviation (S.D.), except where stated in the figure legends. The numbers of biological replicates are stated in the figure legends. No statistical method was used to predetermine sample size. All data were tested for the normal distribution using the Shapiro-Wilk normality test (p<0.05). For data that passed normality test, we used parametric tests. To compare the significance between 2 groups with single condition or treatment, we used a two-tailed, unpaired t-test with Welch's correction. To compare the statistical significance of differences between two treatments or conditions, two-way ANOVA with Tukey's multiple comparison tests were used. For data that are not normally distributed, the Mann-Whitney Test was used. The significance level was set at 0.05 (5%). Statistical tests and generation of graphs were done using GraphPad prism v.8. Analysis of FACS data was done using Flowjo version 10. Seahorse data were analyzed using Wave software.
TABLES OF THE EXAMPLES
[0309]
TABLE-US-00001 TABLE 1 List of proteins from Sirtuin-signaling from Ingenuity Pathway Analysis (IPA) that was carried out on proteome changes of GMPs from old (24 months, n = 5) compared to young (3 months, n = 5) mice exposed to 2 weeks DR (red histogram of log2 fold changes in FIG. 12C). The graph shows the top-10 enriched pathways using a cut-off including all significantly, differently expressed proteins (q-value ≤ 0.05). Expr False Discovery Rate Symbol Entrez Gene Name Expr Log Ratio (q-value) ACLY ATP citrate lyase 0.017 3.59E−02 ADAM 10 ADAM metallopeptidase domain 10 −0.007 3.87E−02 AKT1 AKT serinethreonine kinase 1 0.026 4.65E−02 APEX1 apurinicapyrimidinic −0.074 1.04E−02 endodeoxyribonuclease 1 ATG3 autophagy related 3 −0.072 2.01E−03 ATG5 autophagy related 5 −0.107 1.35E−02 ATG12 autophagy related 12 −1.868 4.06E−02 ATG16L1 autophagy related 16 like 1 −0.440 8.94E−03 ATP5F1C ATP synthase F1 subunit gamma 0.009 1.23E−02 ATP5PB ATP synthase peripheral stalk- 0.094 3.65E−03 membrane subunit b CPT1A carnitine palmitoyltransferase 1A 0.046 2.48E−10 CYC1 cytochrome c1 0.573 4.81E−04 FOXO3 forkhead box O3 −0.822 1.03E−03 G6PD glucose-6-phosphate −0.240 3.44E−02 dehydrogenase GABARAPL1 GABA type A receptor associated −0.733 7.19E−04 protein like 1 GABARAPL2 GABA type A receptor associated 0.255 3.75E−05 protein like 2 GABPA GA binding protein transcription −0.060 2.14E−02 factor subunit alpha GABPB1 GA binding protein transcription 0.301 7.31E−03 factor subunit beta 1 GOT2 glutamic-oxaloacetic transaminase 2 −0.008 3.18E−02 GSK3B glycogen synthase kinase 3 beta −0.140 2.96E−03 GTF3C2 general transcription factor IIIC −0.294 1.25E−02 subunit 2 H1F0 H1 histone family member 0 0.155 6.91E−03 HIST1H1C histone cluster 1 H1 family member c 0.114 1.99E−03 HIST1H1D histone cluster 1 H1 family member d 0.237 3.34E−02 LDHA lactate dehydrogenase A −0.251 8.43E−04 MAP1LC3B microtubule associated protein 1 0.307 1.95E−03 light chain 3 beta MYCN MYCN proto-oncogene, bHLH −0.309 1.03E−02 transcription factor NBN nibrin 0.060 3.50E−02 NDUFA2 NADH:ubiquinone oxidoreductase 0.207 3.86E−03 subunit A2 NDUFA4 NDUFA4 mitochondrial complex 0.000 3.51E−04 associated NDUFA5 NADH:ubiquinone oxidoreductase −0.172 2.60E−03 subunit A5 NDUFA9 NADH:ubiquinone oxidoreductase −0.070 7.38E−03 subunit A9 NDUFAF2 NADH:ubiquinone oxidoreductase 0.396 1.07E−02 complex assembly factor 2 NDUFB5 NADH:ubiquinone oxidoreductase 0.184 2.27E−03 subunit B5 NDUFB8 NADH:ubiquinone oxidoreductase 0.294 1.29E−02 subunit B8 NDUFB10 NADH:ubiquinone oxidoreductase 0.440 3.01E−05 subunit B10 NDUFS1 NADH:ubiquinone oxidoreductase 0.136 2.86E−02 core subunit S1 NDUFS3 NADH:ubiquinone oxidoreductase 0.074 3.61E−02 core subunit S3 NDUFS6 NADH:ubiquinone oxidoreductase 0.163 1.48E−02 subunit S6 NDUFS8 NADH:ubiquinone oxidoreductase 0.009 2.64E−02 core subunit S8 NDUFV1 NADH:ubiquinone oxidoreductase −0.082 4.04E−02 core subunit V1 NDUFV3 NADH:ubiquinone oxidoreductase 0.061 3.50E−02 subunit V3 NQO1 NAD(P)H quinone dehydrogenase 1 0.155 1.46E−03 PCK2 phosphoenolpyruvate −0.006 6.50E−03 carboxykinase 2, mitochondrial PGAM1 phosphoglycerate mutase 1 −0.075 1.17E−02 PGK1 phosphoglycerate kinase 1 −0.056 2.42E−04 POLR1C RNA polymerase I and III subunit C −0.132 3.66E−02 POLR1D RNA polymerase I and III subunit D 0.146 6.64E−04 POLR1E RNA polymerase I subunit E −0.040 4.73E−02 PPID peptidylprolyl isomerase D −0.046 1.02E−02 PPIF peptidylprolyl isomerase F −0.236 9.46E−03 RELA RELA proto-oncogene, NF-kB 0.148 3.51E−02 subunit SDHA succinate dehydrogenase complex −0.082 1.56E−03 flavoprotein subunit A SDHB succinate dehydrogenase complex 0.036 1.65E−02 iron sulfur subunit B SF3A1 splicing factor 3a subunit 1 0.029 8.98E−03 SIRT7 sirtuin 7 0.269 2.23E−02 SMARCA5 SWISNF related, matrix associated, 0.044 8.95E−03 actin dependent regulator of chromatin, subfamily a, member 5 SOD1 superoxide dismutase 1 0.041 2.82E−03 SOD2 superoxide dismutase 2 0.209 4.77E−03 STAT3 signal transducer and activator of 0.007 5.58E−03 transcription 3 TIMM9 translocase of inner mitochondrial 0.091 2.26E−05 membrane 9 TIMM44 translocase of inner mitochondrial −0.015 4.35E−02 membrane 44 TIMM50 translocase of inner mitochondrial 0.058 5.64E−03 membrane 50 TIMM17B translocase of inner mitochondrial 0.113 4.23E−02 membrane 17B TIMM8A translocase of inner mitochondrial 0.051 3.51E−03 membrane 8A TOMM22 translocase of outer mitochondrial 0.223 1.14E−02 membrane 22 TOMM70 translocase of outer mitochondrial 0.120 1.28E−02 membrane 70 TRIM28 tripartite motif containing 28 0.148 2.62E−02 TUBA1C tubulin alpha 1c −0.211 1.15E−03 UQCRC2 ubiquinol-cytochrome c reductase −0.040 1.36E−02 core protein 2 WRN Werner syndrome RecQ like −0.355 1.61E−02 helicase XPA XPA, DNA damage recognition and −0.180 5.84E−03 repair factor XPC XPC complex subunit, DNA 0.016 9.63E−03 damage recognition and repair factor XRCC5 X-ray repair cross complementing 5 0.387 2.69E−05
TABLE-US-00002 TABLE 2 List of differentially regulated genes from FIG. 12G: 3I-exposed MPP from young mice (Y.Con + 3I) versus 3I-exposed MPPs from old mice (O.Con + 3I) m.RNA Log2.FC P-Values Smc1-mRNA 5.49 0.000166 U2AF2-mRNA 5.04 0.000166 eIF4E-mRNA 5.45 0.000166 Eif3f-mRNA 6.98 0.000458 Eif4a1-mRNA 5.24 0.000458 U2AF1-mRNA 5.74 0.000916 SF3A2-mRNA 4.07 0.00198 Wapl-mRNA 4.16 0.00198 Nfatc1-mRNA −1.5 0.00198 Ldb1-mRNA −2.09 0.00198 SF3B2-mRNA 4.62 0.00198 Fli1-mRNA −1.97 0.00326 Erg-mRNA −2.35 0.00326 mfn2-mRNA −1.63 0.00326 Esco2-mRNA −2.5 0.00398 Eef2-mRNA 7.39 0.00398 Eif5a-mRNA 7.22 0.00398 SRSF9-mRNA 4.84 0.00531 SRSF3-mRNA 6.76 0.00562 Eif3h-mRNA 5.58 0.00602 Eif4a2-mRNA 1.63 0.00602 SRSF6-mRNA 5.51 0.00646 Lkb1-mRNA −1.18 0.00646 SF3B3-mRNA 3.84 0.0068 PP2A-mRNA 3.19 0.00705 TLR 3-mRNA −8.13 0.00756 4E-BP1-mRNA −2.12 0.00829 IGF-1r-mRNA −2.88 0.00875 SF3B1-mRNA 5.37 0.0107 TRAIL (aka Apo2 ligand)-mRNA −5.37 0.0107 hsp60-mRNA 3.34 0.0135 Runx1-mRNA −2.03 0.0141 SRSF2-mRNA 2.46 0.0143 NFAT-mRNA −3.01 0.0143 Ldh2-mRNA −3.57 0.0143 p57-mRNA −4.98 0.0143 Eif4h-mRNA 3.98 0.0143 cMyc-mRNA −1.2 0.0146 Pds5B-mRNA 3.97 0.0147 Total XBP1-mRNA −1.42 0.0154 Eef1d-mRNA 5.21 0.0154 Mecom(Evi1)-mRNA −3.39 0.0161 Eef1g-mRNA 2.87 0.0162 Eif2a-mRNA 3.53 0.0173 Gata2-mRNA −2.45 0.0185 mfn1-mRNA −1.33 0.0199 SRSF7-mRNA 2.36 0.0199 Nfatc3-mRNA −1.3 0.0212 Smc3-mRNA 3.76 0.022 Scl/tal1-mRNA −1.86 0.0225 ERDJ4-mRNA −2.96 0.0225 RORc-mRNA −4.98 0.0244 Rad21-mRNA 1.73 0.0301 Pds5A-mRNA −2.9 0.0307 NIPBL-mRNA 3.05 0.0308 SRSF5-mRNA 1.67 0.0308 Rab 22-mRNA −1.5 0.0308 Csf3r(G-CSFR)-mRNA −4.54 0.0329 Egr1-mRNA −3.15 0.0345 Eif3d-mRNA 1.53 0.0419 TGF-b-mRNA 1.13 0.0429 ATP2A3-mRNA −1.66 0.0429 naprt-mRNA −3.57 0.0429 Pbx1-mRNA −2.08 0.0429 IDH1-mRNA −1.72 0.0429 SRSF10-mRNA 2.41 0.0433 drp1-mRNA −1.14 0.0449 GRP94-mRNA 0.461 0.0455 Sgo2a-mRNA −2.49 0.0473
TABLE-US-00003 TABLE 3 List of differentially regulated genes from FIG. 12H: 3I-exposed MPPs from young mice (Y.Con + 3I) versus 3I-exposed MPPs from old mice that were pre-treated for 12 h with NR (O.NR + 3I). mRNA LogZFC P-Values atp5a1-mRNA 1.11 0.00456 Myh9-mRNA −2.45 0.0178 unspliced XBP1-mRNA 2.56 0.0178 IDH1-mRNA −2.62 0.0224 Pds5A-mRNA −3.08 0.0224 Ino1-mRNA −1.78 0.0283 Pkm-mRNA 1.73 0.0283 NRas-mRNA −2.16 0.0403
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