Prostaglandin E2 Enhances Aged Hematopoietic Stem Cell Function

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Patterson, P. Artur Plett, Carol H. Sampson, Edward Simpson, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-224253/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Aging of hematopoiesis is associated with increased frequency and clonality of hematopoietic stem cells (HSCs), along with functional compromise and myeloid bias, with donor age being a significant variable in survival after HSC transplantation. No clinical methods currently exist to enhance aged HSC function, and little is known regarding how aging affects molecular responses of HSCs to biological stimuli. Exposure of HSCs from young fish, mice, nonhuman primates, and humans to 16,16-dimethyl prostaglandin E 2 (dmPGE 2 ) enhances transplantation, but the effect of dmPGE 2 on aged HSCs is unknown. Here we show that ex vivo pulse of bone marrow cells from young adult (3 mo) and aged (25 mo) mice with dmPGE 2 prior to serial competitive transplantation significantly enhanced long-term repopulation from aged grafts in primary and secondary transplantation (27% increase in chimerism) to a similar degree as young grafts (21% increase in chimerism; both p<0.05). RNA sequencing of phenotypically-isolated HSCs indicated that the molecular responses to dmPGE 2 are similar in young and old, including CREB1 activation and increased cell survival and homeostasis. Common genes within these pathways identified likely key mediators of HSC enhancement by dmPGE 2 and age-related signaling differences. HSC expression of the PGE 2 receptor EP4, implicated in HSC function, increased with age in both mRNA and surface protein. This work suggests that aging does not alter the major dmPGE 2 response pathways in HSCs which mediate enhancement of both young and old HSC function, with significant implications for expanding the therapeutic potential of elderly HSC transplantation. Stem Cell & Developmental Cell Biology hematopoietic stem cells (HSCs) hematopoiesis HSC transplantation cell survival Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Hematopoietic stem cells (HSCs) are responsible for continual replacement of all blood cell types, and HSC transplantation (HSCT) is a life-saving option for many patients with hematologic diseases. However, HSC function and engraftment capacity drastically decrease with age 1 – 7 . Loss of immune function, anemia, myeloid skewing, and increased incidence of myeloproliferative diseases and leukemia are observed in the elderly, and aged bone marrow (BM) cells are unfavorable for transplantation 4,8−11 . While many factors are thought to contribute to HSC aging, including cell-intrinsic and niche-mediated 2 , 12 , 13 , specific molecular pathways functionally linked to aged HSC defects are not well characterized, and no treatment exists to enhance aging hematopoiesis or augment the transplantation potential of these cells. The number of people > 65 years of age is projected to almost double between 2012 and 2050 14 , intensifying the problem of aged HSC dysfunction and the critical need for novel therapeutic approaches for those in need of HSC support. Prostaglandin E2 (PGE 2 ) is a bioactive lipid with hematopoietic roles described since the 1970s 15 – 17 . More recently, the stable derivative 16,16-dimethyl PGE 2 (dmPGE 2 ) was found to enhance HSC frequency and transplantation efficiency in both zebrafish and murine models 18 , 19 . We have previously shown that pulse exposure to dmPGE 2 enhances homing, survival, and proliferation for both young (2–3 mo) mouse BM and human cord blood derived CD34 + cells, which was associated with increased CXCR4 and Survivin expression, decreased apoptosis, and increased HSC proliferation 19 , 20 . Further, dmPGE 2 pulse exposure augmented competitiveness of human cord blood grafts in a Phase I clinical trial with double cord blood transplantation 21 , and has been used clinically to enhance engraftment of gene modified HSCs 22 . Thus, dmPGE 2 is known to enhance HSC function and has potential for clinical translation. The objective of the current work was to assess the effects of dmPGE 2 pulse exposure on aged HSCs at both the functional and molecular level in comparison to young HSCs. Functionally, dmPGE 2 pulse prior to competitive serial transplantation significantly enhanced the long-term repopulating capacity of aged HSCs similarly to young. A high-throughput genomic comparison of old and young HSC responses to dmPGE 2 highlighted common transcriptional pathways in old and young mediating HSC enhancement, and identified novel signaling alterations in HSCs with age. Materials And Methods Mice All studies were approved by the Indiana University School of Medicine Institutional Animal Care and Use Committee. Aged mice : C57BL/6J male mice were purchased at 10 weeks old from Jackson Laboratories (Bar Harbor, ME) and aged in our facility until used at 25 mo of age. Young mice : C57BL/6J male mice were purchased at 10 weeks old from the Indiana University In Vivo Therapeutics Core (IVTC) and used at 3 mo of age. Transplant recipient mice : B6.BoyJ congenic (CD45.1) male and female mice were purchased at 6–8 weeks of age from the IVTC and used as transplant recipients at 8–10 weeks of age. Transplants were randomized by recipient sex and age such that young and old donor samples were equally distributed between recipients that were male or female, and younger (closer to 8 weeks) or older (closer to 10 weeks). Mice were randomized within cages so that each cage contained recipients of both vehicle and dmPGE 2 -pulsed cells, but from the same donor when possible for rigor of comparison between matched samples. BM Collection Femurs, tibiae, pelvic bones, and humeri from young and old C57BL/6J mice were flushed with cell buffer (PBS containing 2% FBS and 2 mM EDTA). Cells were passed through a 40 µm filter, and total nucleated cells (TNC) enumerated using an Element HT5 Hematology Analyzer (Heska Corporation, Loveland, CO). In the transplantation experiment, an aliquot of cells from each mouse was removed for flow cytometric assessment of young vs. old BM prior to dmPGE 2 pulse. DmPGE 2 Pulse Exposure DmPGE 2 in methyl acetate from Cayman Chemicals (Ann Arbor, MI) was stored at -20 o C. Prior to use, dmPGE 2 was evaporated to dryness on ice under N 2 and reconstituted in 100% EtOH at a stock concentration of 10 mg/ml (26.28 mM). Whole BM (WBM) cells (transplantation experiments) or lineage-depleted WBM cells (RNA-seq experiments) from individual C57BL/6J (CD45.2) young or old mice were split in two portions. One portion was pulsed in a concentration of 10 µM dmPGE 2 in cell buffer, and the other in an equivalent volume of vehicle (100% EtOH) in cell buffer, at 2.5 x 10 6 TNC/mL for 1 h in a humidified CO 2 incubator at 37°C, with vortexing every 15 min. Cells were then centrifuged at 500 x g for 10 min to remove dmPGE 2 or vehicle and washed with cell buffer. Competitive Serial Transplantation Pulsed WBM cells from 4 young and 4 old donor C57BL/6J mice (CD45.2) were transplanted into 6 recipients per donor, where 3 received cells pulsed with dmPGE 2 and 3 received cells from the same donor pulsed with vehicle for matched analysis. To that end, 8–10 week-old congenic recipient mice (CD45.1) were exposed to 137 Cs irradiation (11 Gy split dose, 4 h apart) using a Mark 1 Irradiator (JL Shepherd, San Fernando, California), as previously described 23 . DmPGE 2 - or vehicle-pulsed donor WBM cells were resuspended in PBS and combined with competitor CD45.1 WBM cells not pulsed with dmPGE 2 or vehicle in a 3:2 ratio, for a final retro-orbital injection of 100 uL containing 3 x 10 5 donor and 2 x 10 5 competitor TNCs per recipient mouse. Recipients were given autoclaved acidified water (pH 2.0–3.0) and irradiated Uniprim diet (Envigo, Madison, WI) for 1 week prior to, and 4 weeks after irradiation/transplantation. Peripheral blood (PB) was analyzed monthly for donor chimerism and for multilineage reconstitution at month 6. After 7 mo, WBM was collected from all primary recipients. Cells from each set of 3 replicate primary recipients (or 2 in two cases where one recipient died in primary phase) were combined equally and 1.5 x 10 6 TNC transplanted into 3 secondary CD45.1 recipients conditioned with radiation as above. PB was analyzed monthly for donor chimerism, except for months 4–5 due to pandemic-related laboratory restrictions, and for multilineage reconstitution at month 6. Cell Staining and Flow Cytometry Analysis BM cells were stained with an amine-reactive live/dead dye (Invitrogen LIVE/DEAD Fixable Dead Cell Stain kit Yellow, Thermo Fisher, Waltham, MA) followed by blocking with TruStain FcX+ (Biolegend, San Diego, CA) and fluorophore-conjugated monoclonal antibodies to identify phenotypic HSCs (pHSCs) using a lineage cocktail in APC (CD3, GR-1, B220, Ter-119, CD11b, and CD5; R&D Systems, Minneapolis, MN), Sca1 in PerCP/Cy5.5, c-Kit in BV711, CD150 in PE/Cy7, and CD48 in APC/Cy7 (Biolegend). EP4 was stained with an unconjugated primary polyclonal antibody (Novus Biologicals, Littleton, CO) and a secondary anti-rabbit IgG antibody conjugated to BV421 (Biolegend). Cells were then analyzed immediately by flow cytometry. PB cells were RBC-lysed, blocked with TruStain FcX+ (Biolegend), and stained with fluorophore-conjugated antibodies to white blood cell markers including CD45.1 in PE, CD45.2 in FITC, B220 in Pacific Blue, CD3 in PerCP/Cy5.5, and CD11b in APC (Biolegend). Cells were fixed in 1% paraformaldehyde and stored at 4°C until flow cytometric analysis. Flow cytometric data were acquired using an LSRII flow cytometer (BD Biosciences, San Jose, CA) and analyzed using FlowJo software (BD Biosciences). WBM Processing, HSC Sorting, and RNA Extraction for Sequencing WBM cells from 8 young and 4 old mice were enriched for immature cells by magnetic lineage depletion (EasySep Mouse Hematopoietic Progenitor Cell Isolation kit, STEMCELL Technologies), then pairs of young samples were combined to increase the number of pHSCs available for sorting from 4 individual BM samples from young mice alongside 4 individual BM samples from old mice. Cells were then pulsed with dmPGE 2 or vehicle for 1 h as described above, immediately stained, and viable pHSCs isolated by fluorescence associated cell sorting (FACS) using a SORP Aria flow cytometer (BD Biosciences). Cells were sorted directly into lysis buffer for RNA extraction using the RNeasy Plus Micro Kit (Qiagen, Hilden, Germany). A 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) was used for quality control of all RNA preparations, giving a median RNA integrity of 9.6 RIN (range 6.2–10.0). RNA Sequencing and Statistics/Bioinformatics Library preparation was performed using the SMART-Seq v4 Ultra Low Input RNA Kit (Clontech, Mountain View, CA) and the Nextera XT DNA Lib Kit (Illumina, San Diego, CA). Two hundred picomolar pooled libraries were utilized per flow cell for clustering amplification on cBot using HiSeq 3000/4000 PE Cluster Kit and sequenced with 2×75bp paired-end configuration on HiSeq4000 (Illumina) using a HiSeq 3000/4000 PE SBS Kit. Sequencing data were assessed for quality using FastQC version 0.11.5 (Babraham Bioinformatics, Cambridge, UK). The sequence reads were mapped to the mouse genome (UCSC mm10) using STAR (Spliced Transcripts Alignment to a Reference) 24 version 2.5 using parameter "--outSAMmapqUnique 60". To evaluate the quality of the RNA-seq data, number of reads that fall into different annotated regions (exonic, intronic, splicing junction, intergenic, promoter, UTR, etc.) of the reference genes were determined with bamUtils 25 version 0.5.9. Uniquely mapped sequencing reads were assigned to mm10 refGene genes and quantified using featureCounts (from subread) 26 version 1.5.1 using parameters "-s 2 -p -Q 10". Low quality mapped reads (including reads mapped to multiple positions) were excluded. Differential expression (DE) analysis was performed with edgeR 27 . In this workflow, the statistical methodology applied uses negative binomial generalized linear models with likelihood ratio tests. A paired design was used to compare samples across conditions such that the relationships between samples from the same animals were retained ("blocking" in edgeR). False discovery rate (FDR) calculations therefore reflect the collective significance of the treatment on gene expression while accounting for baseline differences between the animals. DE data was analyzed for biological insights using Ingenuity Pathway Analysis (IPA, Qiagen, Hilden, Germany) 28 . Two IPA Core Analyses were run, one for the young and one for the old dmPGE 2 vs. vehicle comparisons, with cutoffs set to FDR |0.5| (FC, fold change). The young and old analyses were compared using the IPA Comparison Analysis function. Upstream Regulators were filtered on Genes, RNAs, and Proteins, z-score cutoff |2|, p-value cutoff 1.3 (log 10 ). Diseases and Functions were filtered on Cellular and Molecular Functions, with additional removal of cancer cell-specific functions, z-score cutoff |2|, p-value cutoff 1.3 (log 10 ). The set of 70 genes increased by dmPGE 2 in young (FDR 0.6) was submitted to the DAVID 6.8 Functional Annotation tool using default settings and output from the Functional Annotation Chart filtered on UP_KEYWORDS and cutoff at Benjamini-adjusted p-value < 0.01 (david.ncifcrf.gov) 29 . Heatmaps were generated in Microsoft Excel using conditional formatting for cell color based on FPKM values (fragments per kilobase per million mapped reads). Heatmaps depicting relative gene expression among all samples/groups (blue-red) used the following formula for each cell: (FPKM – average FPKM across all samples all groups)/standard deviation of FPKM across all samples all groups. Heatmaps depicting change in (Δ) gene expression between paired samples (gray-orange) used the formula: (FPKM dmPGE 2 – FPKM vehicle )/standard deviation of FPKM across all samples in age group, where superscripts denote different treatments of the same mouse BM sample. Statistics Other statistical analyses were performed using Microsoft Excel and GraphPad Prism 8. All data with error bars represent mean ± SEM. Paired t-tests were performed between matched vehicle- and dmPGE 2 -treated samples from the same donor in chimerism analyses, 1-tailed for expected increase with dmPGE 2 . Unpaired t-tests were performed between young and old flow cytometry data points (2-tailed). Results DmPGE 2 enhances long-term serial repopulation capacity of aged HSCs Since dmPGE 2 enhances homing, survival and proliferation of long-term repopulating HSCs in young mice 19 , 20 , we tested whether a similar effect could be demonstrated on HSCs from old mice, which are known to demonstrate reduced regenerative potential and myeloid skewed differentiation 1 , 30 . WBM aliquots from 3 mo (young) or 25 mo (old) mice were pulsed with either dmPGE 2 or vehicle prior to competitive serial transplantation, allowing for matched analysis of dmPGE 2 effects on long-term repopulating HSC potential (Fig. 1 A). PB chimerism in recipients was assessed monthly by flow cytometry for CD45.2 donor cell frequency and for trilineage distribution at 6 mo post-transplant (Fig. 1 B). In primary transplants, dmPGE 2 pulse increased long-term donor-derived chimerism for all 4 young donors and 3 of 4 old donors (Fig. 1 C). After secondary transplantation, long-term repopulation was increased by dmPGE 2 pulse for all donors of both age groups (Fig. 1 D). Chimerism of aged grafts at 6 mo post-secondary transplant was increased an average of 27%, similar to the average increase of 21% for young (Fig. 1 E), indicating enhanced HSC self-renewal capacity for both young and aged BM grafts by dmPGE 2 . Lineage reconstitution Analysis of PB lineage reconstitution showed that pulse with dmPGE 2 increased myeloid frequency in all four young grafts, observed in both primary and secondary transplantations (Fig. 1 C-D, dark green). However, this was not at the expense of lymphoid production; total lymphoid and myeloid production were both increased by dmPGE 2 pulse exposure in comparison to competitor cells as a frequency of total peripheral CD45 cells (CD45.1 + CD45.2) (Fig. 1 F). Transplantation of grafts from old mice resulted in myeloid-skewed PB reconstitution as expected, regardless of vehicle or dmPGE 2 treatment (Fig. 1 C-D, dark green). However, similar to young, both lymphoid and myeloid production were increased by dmPGE 2 in comparison to competitor cells (Fig. 1 F). One old graft lost long-term myeloid production after secondary transplantation, with poor overall chimerism for both dmPGE 2 and vehicle (Old 4, Fig. 1 D), but still showed increased lymphoid potential with dmPGE 2 (Fig. 1 F), which resulted in an apparent reversal of myeloid skew among donor cells in these recipients. Donor BM phenotypic HSC (pHSC) frequencies and EP4 expression pre-transplant Prior to pulse and transplantation, aliquots of WBM cells from young and old donors were analyzed for baseline pHSC frequency and dmPGE 2 receptor expression (Fig. 2 A). As expected, the pHSC population in old mice was greatly expanded compared to that in young mice, exhibiting 24-fold higher frequency (Fig. 2 B), similar to our previously published data 23 . EP4, the receptor primarily implicated in HSC functional responses to dmPGE 2 31–33 , was strongly expressed on the surface of aged HSCs and was higher compared to young (Fig. 2 C). BM chimerism and stem/progenitor frequencies post-transplant Donor-derived BM chimerism was assessed at the time of secondary transplantation (7 mo post-primary transplant). CD45.2 BM chimerism was significantly higher after dmPGE 2 pulse for all grafts from young donors, and was variably increased after dmPGE 2 pulse for 3 of 4 grafts from old donors (Fig. 2 D), mirroring the effect on primary PB chimerism. The single old donor without increased BM chimerism also did not show increased PB chimerism after primary transplantation (“Old 1”, Fig. 1 C). However, the subsequent superiority of the dmPGE 2 -treated graft in secondary transplantation (“Old 1”, Fig. 1 D) suggests it may retain a dmPGE 2 -mediated qualitative advantage in HSC self-renewal revealed by the stress of serial transplantation. While the aged grafts contained 24-fold higher pHSC frequency compared to young grafts prior to pulse and transplantation (Fig. 2 B), similar pHSC frequencies were found among long-term engrafted CD45.2 BM cells from young and old donors (Fig. 2 E), likely reflecting the functional compromise of the original pHSC population in the aged mice. Interestingly, dmPGE 2 increased the frequency of phenotypic myeloid-committed progenitors (pMP) (gating illustrated in Fig. 2 A) among engrafted donor cells for 4 of 4 young grafts and 3 of 4 old grafts (Fig. 2 F). Further, dmPGE 2 altered the distribution of stem versus progenitor cells within the primitive LSK compartment of the old grafts, partially reversing the age-associated predominance of pHSCs (Fig. 2 G) in favor of increased phenotypic hematopoietic progenitor cells (pHPCs, Fig. 2 H; gating illustrated in Fig. 2 A). This may suggest increased capacity for generation and/or maintenance of downstream progenitor populations when grafts are pulsed with dmPGE 2 . Shared and divergent transcriptional responses to dmPGE 2 in young and old HSCs To identify molecular correlates of enhanced long-term HSC function by dmPGE 2 in both young and aged HSCs, and to identify signaling differences in HSCs with age, pHSCs from pulsed BM samples were immediately isolated by FACS and analyzed using RNA-seq (Fig. 3 A). Differentially expressed genes were defined as FDR < 0.05 by pair-wise analysis between dmPGE 2 - and vehicle-pulsed samples from the same mouse, across 4 young samples or 4 old samples to determine age-specific transcriptional effects. The paired analyses allow for robust detection of dmPGE 2 effects despite baseline gene expression differences between individual mice, which can become particularly variable with advanced age. DmPGE 2 significantly affected 230 genes in young HSCs (184 increased, 46 decreased), and 112 genes in old HSCs (85 increased, 27 decreased). Of these, 53 common genes reached significance in both age groups (49 increased, 4 decreased; Fig. S1). Substantially fewer genes reached FDR < 0.05 in old HSCs, which may be due in part to greater variability in responsiveness among old mice, but may also reflect an overall decrease in HSC responses to dmPGE 2 with age. All differentially expressed genes reaching FDR < 0.05 in both age groups combined were clustered based on similar (age-independent) or unique (age-dependent) dmPGE 2 effects between young and old, and were visualized both for relative expression across all samples (Fig. 3 B) and for individually paired Δ gene expression induced by dmPGE 2 (Fig. 3 C). The top two clusters in Figs. 3 B and 3 C represent similar increase/decrease in both age groups (FDR < 0.05 for at least one age group and < 0.6 in the other), and comprised a majority of the genes. Since dmPGE 2 pulse effectively enhanced HSC function in serial transplantation for both age groups, we first focused analysis on shared gene effects to narrow the pathways likely involved in the mechanism of enhancement. The lower clusters represent genes affected differently by dmPGE 2 in old and young HSCs; these are not likely involved in the mechanism of enhancement but can shed light on changes in HSC signaling pathways with age. Shared dmPGE 2 signaling in young and old HSCs IPA was used to identify the most likely upstream regulators activated by dmPGE 2 in HSCs based on all downstream gene expression changes (FDR |0.5|) in young and old mice, and a comparison analysis of results from each age group revealed the same top regulators predicted in young and old (Fig. 4 A). The regulator with the highest activation z-score in both age groups was CREB1, a known mediator of PGE 2 signaling through receptors EP2 and EP4 34 , supporting similar HSC-intrinsic signaling in old and young. Among the CREB1-regulated genes contributing to each z-score, 16 were shared between young and old (Fig. 4 B). Cellular functions activated by dmPGE 2 were also predicted, with ‘Cell survival’ and ‘Cellular homeostasis’ reaching significant activation z-scores in both young and old HSCs (Fig. 4 C). Overlapping gene sets contributed to both functions, and 18 of these genes were shared between young and old (Fig. 4 D). Seven of these genes (bold) are also known to be regulated by CREB1 (Fig. 4 B). Thus, CREB1 activation by dmPGE 2 may be increasing HSC survival and homeostasis through Bhlhe40, Cdkn1a, Cebpb, Gadd45b, Nr4a2, Pim3 , and Vegfa , among others in these heatmaps potentially not yet functionally linked. Overall, these genes and predicted regulators (Fig. 4 A) shared in old and young HSC responses to dmPGE 2 provide strong candidates for further study as molecular mediators of enhancement of HSC potential. Since dmPGE 2 activates CREB1 through either EP2 or EP4, baseline mRNA expression of each receptor was compared (Fig. 4 E). EP2 was not detectable above background in young or old HSCs while EP4 was highly expressed and increased with age, confirming the flow cytometry findings for EP4 (Fig. 2 C). Also, dmPGE 2 pulse exposure decreased EP4 expression in each of the old HSC samples and 3 of 4 young samples (Fig. 4 F). Desensitization through EP4 has been noted 35 , and this negative feedback effect on EP4 expression has been reported in murine HSCs after in vivo dmPGE 2 treatment 36 . Together these findings further support EP4 as the relevant receptor for enhancement of both young and old HSC long-term function. Divergent dmPGE 2 signaling in young and old HSCs The third cluster in Fig. 3 B/C, and the second largest cluster overall, is comprised of 70 genes significantly increased by dmPGE 2 in young HSCs (FDR 0.6). Visualizing relative expression in Fig. 3 B, many of these genes appear already elevated at baseline in vehicle-treated old HSCs and are not further increased with dmPGE 2 . These genes were classified for functional annotation enrichments using DAVID bioinformatics analysis (Table 1). The top enrichment category was ‘Phosphoprotein’, comprising 44 of the 70 genes. These phosphoproteins also made up 23/29 genes from ‘Alternative splicing’, and 14/17 genes from ‘Transcription’, the next two most enriched categories. The category of ‘Alternative Splicing’ is defined by UniProt as “Protein for which at least two isoforms exist due to distinct pre-mRNA splicing events” (uniprot.org). Since alternative splicing has been implicated in the development of myeloproliferative disorders which increase in prevalence with age 37 , 38 , these genes are reported in Table 2 . Thus, a sizeable subset of dmPGE 2 -induced genes observed in young HSCs become less responsive with age and are enriched for phosphoproteins with alternative splice variants and those involved in transcriptional regulation. Table 1. Functional Annotation enrichments a among the 70 genes increased by dm PGE 2 in young but not in old HSCs # Term Count (/70) Fold Enrich. Benj. p-val 1 Phosphoprotein 44 1.9 3.7E-5 2 Alternative splicing 29 2.0 4.2E-3 3 Transcription 17 3.1 4.9E-3 4 Transcription regulation 16 3.0 6.1E-3 5 Transferase 15 3.0 7.1E-3 6 Coiled coil 21 2.3 8.4E-3 a DAVID Functional Annotation Chart, filtered on UP_KEYWORD and Benjamini-adjusted p < 0.01. Table 2 Genes annotated with ‘Alternative splicing’ # Gene DmPGE 2 Effect Avg Baseline (Veh) FPKM a FDR Yng FDR Old Yng Old FC with age 1 Adgrg2 0.0433 0.9989 1.06 6.16 5.81 2 Evc 0.0002 0.7657 1.23 6.14 5.00 3 Sytl5 0.0434 0.9956 1.09 2.82 2.58 4 Dmxl2 0.0244 0.9961 1.19 2.89 2.43 5 Ttc39a 0.0433 0.8046 1.57 3.46 2.21 6 Ubr4 0.0039 0.8811 6.44 10.40 1.61 7 Clk1 0.0475 0.8251 28.02 43.76 1.56 8 Dmd 0.0407 0.7699 0.73 1.12 1.53 9 Epc1 0.0076 0.9400 8.40 12.86 1.53 10 Mga 0.0407 0.9750 7.99 12.08 1.51 11 4932438a13rik 0.0096 0.3003 5.39 8.09 1.50 12 Kmt2c 0.0113 0.9757 5.67 8.43 1.49 13 Mycbp2 0.0080 0.1822 6.70 9.87 1.47 14 Adgrl2 0.0067 0.9859 11.57 17.01 1.47 15 Usp53 0.0286 1.0000 2.35 3.35 1.43 16 Suco 0.0052 0.6945 8.85 12.50 1.41 17 Madd 0.0235 0.8872 27.58 37.94 1.38 18 Dopey1 0.0363 0.7969 3.60 4.66 1.30 19 Slc12a7 0.0489 0.8411 12.54 15.98 1.27 20 Ankrd6 0.0249 0.8225 0.80 1.02 1.27 21 Ggt5 0.0313 1.0000 2.68 3.39 1.27 22 Gramd1a 0.0052 0.8862 38.00 47.70 1.26 23 Birc6 0.0216 0.9706 5.13 6.43 1.25 24 Syne2 0.0016 1.0000 1.58 1.93 1.22 25 Zfp292 0.0328 0.9640 8.55 10.19 1.19 26 Setdb1 0.0153 0.7388 14.53 16.61 1.14 27 Ipo8 0.0112 0.7760 14.05 15.78 1.12 28 Smcr8 0.0282 0.9233 5.19 5.40 1.04 29 Pcgf5 0.0433 0.7128 47.00 42.89 0.91 a Average FPKM (fragments per kilobase per million mapped reads) among vehicle-treated young (Yng) or old HSCs (n = 4 per sex); FDR, false discovery rate for dmPGE 2 vs. vehicle analyses; FC, fold change. An additional “difference of difference” FDR calculation was utilized to compare the treatment effect in old versus young HSCs and identify genes affected significantly differently by dmPGE 2 in each age group (Fig. 5 A). Each of these genes was affected in the opposite direction by dmPGE 2 in old and young HSCs (FDR < 0.05). Several had higher average expression with age in the vehicle-treated samples and were decreased by dmPGE 2 in old HSCs, as opposed to being increased by dmPGE 2 in young HSCs, including Ccbe1, Evc, Mlk2, Mycbp2, Rorb, and Ubr4 . Since Rorb was so strongly upregulated with age and differentially affected by dmPGE 2 , its close family members Rora and Rorc were also examined (Fig. 5 B). Rora was slightly increased with age and strongly upregulated by dmPGE 2 in both young and old HSC, while Rorc was strongly increased with age and slightly elevated by dmPGE 2 in old but not in young. In addition, two genes ( H2afx and Kcnj5 ) had lower average expression with age and were increased by dmPGE 2 in old HSCs, opposite to the dmPGE 2 effect in young, and four others had similar baseline expression in young and old HSCs but opposite treatment effects ( Elf2, Max, Psap, and Ncoa2 ; Fig. 5 A). These RNA-seq analyses identify potential molecular targets for age-related HSC dysfunction. Discussion After HLA matching, donor age is generally the most critical factor determining survival after HSCT 11 . Grafts from older donors have been associated with increased graft failure even when controlling for cell number 39 , 40 , which may relate to declining inherent stem cell quality 1 – 5 , 41 . Increased incidence of graft versus host disease (GVHD) in recipients of grafts from older donors has also been observed 10 , 42 , potentially related to an increase in antigen-experienced lymphocytes with age 43 , 44 or the general increase in low-level inflammation that characterizes aging 45 . However, neither of these associations show consistent relationships with HSCT outcome 10 , 46 , and a combination of several age-related factors likely contribute. For these reasons, transplant physicians tend to favor younger donors, but finding the appropriately matched donor can sometimes be difficult or impossible. The probability of finding an unrelated matched donor varies with ethnicity, and can be especially problematic for some ethnic groups, e.g. African-Americans 47 . Elderly family members would have strong motivation to donate if suitably matched, and strategies to enhance aged grafts could help increase the possibility of success. While hematopoietic malignancies treatable by autologous transplant increase in prevalence with age, elderly patients are often not eligible due to the rigors of the HSCT process as well as their own declining HSC quality. However, recent strategies employing reduced-intensity conditioning for elderly patients, as well as advances in transplant technique and supportive care, increasingly enable allogeneic and autologous HSCT in this population 48 – 50 . The ability to augment the function of aged grafts prior to infusion could facilitate successful, life-saving autologous transplants for older patients. Here we found that ex vivo pulse exposure to dmPGE 2 can enhance the transplantation capacity of murine HSCs of advanced age. Previous work in young grafts has shown this effect to translate from zebrafish and mice 18 , 19 to non-human primates 51 , 52 and ultimately to enhancement of human cord blood transplantation 21 . Thus, the current findings have a high likelihood of translation. PGE 2 is an eicosanoid synthesized within most body tissues by many different cell types, acting in autocrine or paracrine fashion 53 . Activities mediated by PGE 2 are highly pleiotropic, depending on the tissue/cell type and expression of its four G-protein coupled receptors EP1-4 35,54 . EP1 signals primarily through PKC and Ca 2+ mobilization, EP2 and EP4 induce cAMP production and subsequent cAMP response element-binding protein (CREB) activation as observed here, and EP3 inhibits cAMP production 35 , 54 . EP4 has been recognized as a key functional regulator for HSCs, including transplantation studies 32 , 33 . In the setting of radiation exposure, where dmPGE 2 protects and enhances HSC function 36 , only dmPGE 2 or EP4 agonism conferred survival from lethal irradiation 55 . In the current transcriptomic analysis, the predominance of CREB1-induced gene expression following dmPGE 2 pulse in both young and old HSCs, along with strong EP4 expression but undetectable EP2 mRNA levels as observed here and previously by RNA-seq of purified murine pHSCs 36 , strongly supports EP4 as the relevant receptor mediating HSC enhancement regardless of age. An interesting finding in this study was increased EP4 expression in HSCs with age. PGE 2 production is known to increase with age in macrophages 56 and decrease with age in gastrointestinal tissues 57 . In skeletal muscle, the capacity for PGE 2 synthesis increases with age while receptor levels are downregulated 58 . It remains unclear if basal PGE 2 levels change with age within the BM, and which factors would drive the increase in EP4 expression on HSCs. The intensity of CREB1-regulated genes was noticeably higher in old HSCs after dmPGE 2 pulse and may be related to the number of EP4 receptors, though higher basal expression of these genes was also seen in control HSCs in a variable manner between aged mice (Fig. 4 B). Thus, the change in CREB1-regulated genes was greater in some old mice but not in others, and the relevance of increased EP4 expression on aged HSCs remains uncertain. Ultimately, this investigation established that HSCs of advanced age do not lose expression or signaling through the pivotal EP4 receptor. While the primary objective of these studies was not to compare old versus young HSC function, but rather to evaluate the effect of dmPGE 2 on old grafts in parallel with young grafts, the transplantation experiments were performed simultaneously with the same cohorts of recipients and competitor cells. The studies indicated that the old and young grafts functioned similarly in regard to overall long-term and serial chimerism capacity. Since the old grafts contained approximately 24-fold higher pHSC frequency, and equivalent numbers of WBM cells were transplanted, these observations are in line with the reported substantial decrease in function of pHSCs with age 2 , 3 , 6 , 7 . We also observed myeloid-skewed reconstitution from aged HSCs as described 2 – 4 , 6 , 30 . Interestingly, dmPGE 2 pulse consistently increased the relative myeloid contribution of the young donor cells, bringing their lineage ratios closer to those of the aged. However, dmPGE 2 also increased the overall frequencies of donor lymphoid cells in comparison to competitors, suggesting dmPGE 2 has a positive effect on both major immune cell branches but augments myeloid reconstitution to a greater degree. DmPGE 2 also augmented both branches for old HSCs compared to competitors without further affecting the inherent myeloid skew with age. Of interest, we have previously reported an increase in the proportion of myeloid cells in PB of mice transplanted with young HSCs pulsed with dmPGE 2 following primary and secondary transplant, however this was not consistent across tertiary and quaternary transplants and was without overall effect on the enhancement of induced stem cell competitiveness 59 . Bioinformatic analysis of dmPGE 2 signaling in young versus old HSCs revealed that the core response pathways remained largely unchanged with age. Several age-independent genes were identified as both increased by CREB1 signaling and involved in the significantly predicted functions of ‘Cell survival’ and ‘Cellular homeostasis’ . Many of these genes additionally have described roles in hematopoiesis, supporting their involvement in HSC modulation by dmPGE 2 . Vegfa encodes for vascular endothelial growth factor A (VEGF-A) which, while first discovered for its primary role in angiogenesis 60 , enhances human HPC formation 61 , promotes hematopoietic cell generation from embryonic stem cells of both mouse 62 and human 63 , and regulates HSC survival 64 . Cebpb is the gene for CCAAT enhancer binding protein beta (C/EBPβ), a transcription factor that promotes lymphopoiesis 65 and emergency myelopoiesis 66 , 67 at the level of stem and progenitor cell regulation 68 , 69 . Gadd45b , encoding growth arrest and DNA-damage-inducible beta (GADD45β), appears essential for DNA damage protection and survival of HSCs/HPCs and induced pluripotent stem cells (iPSCs) under stress 70 . Cdkn1a encodes the cyclin-dependent kinase inhibitor P21, which preserves HSC quiescence under stress and promotes HSC self-renewal in serial transplantation 71 , while Nr4a2 encoding the transcription factor nuclear receptor subfamily 4 group A member 2, also known as NURR1, also attenuates HSC cycling 72 and may contribute to the maintenance of stem cell quiescence during the stress of transplantation. In addition to transplantation, steady-state hematopoiesis in older humans is subject to increased bone marrow failure and decreased hematologic tolerance of cytotoxic injury, as well as the increased propensity for myeloproliferative disorders and cancerous transformation 8 , 9 . A broader understanding of aged HSC function is essential to development of novel treatments for hematopoietic compromise in the elderly. The high-throughput genomic comparison of old and young HSC responses to dmPGE 2 provided a unique modality for investigating changes in HSC stimulation response pathways with age. Several signaling alterations identified here may have relevance for targeting in treatment of age-induced HSC defects. Genes differentially affected by dmPGE 2 in young and old HSCs included numerous phosphoproteins induced in young but not in old, many of which were already elevated with age. IPA did not return any significant predictions for a common upstream regulator controlling these genes (no more than 5 had shared association with any given regulator), but functional categories including ‘Alternative splicing’ exhibited significant enrichment (Table 1). Abnormalities in alternative splicing have been implicated in the development of myeloproliferative disorders that increase in prevalence with age, with over 50% of myelodysplastic syndromes harboring spliceosome factor mutations in the dominant clone 37 , 38 . The current analysis suggests dmPGE 2 -responsive genes that become less responsive with age tend to be those with alternative splice variants, and tend to have higher mRNA levels detectable in old HSCs pre-stimulation (Table 2 ). However, the current experimental design did not distinguish between splice variants, and further investigation is needed to determine whether these transcripts could be affected by dysregulated splicing in HSCs of advanced age. Several specific genes were identified as significantly oppositely affected by dmPGE 2 stimulation in old versus young HSCs, revealing divergent molecular responses potentially related to aging defects. Ccbe1 and Rorb were particularly elevated with age and strongly decreased by dmPGE 2 only in old HSCs. Ccbe1 , encoding for collagen and calcium binding EGF domains 1 (CCBE1), is a secreted protein thought to function in remodeling of extracellular matrix and cell migration, and is an important factor in lymphangiogenesis 73 – 75 . It is also an essential mediator of erythroblastic island formation for erythropoiesis in fetal liver, though it is not required for postnatal erythropoiesis 76 . This gene has otherwise not been associated with hematopoiesis, and gene expression levels found here in young HSCs were near-zero at baseline with a very slight elevation by dmPGE 2 . However, the Ccbe1 transcript was much more detectable in aged HSCs and was strongly and consistently downregulated by dmPGE 2 stimulation. Thus, transcription of Ccbe1 appears to be ‘turned on’ in HSCs by an unknown aging factor that may be sensitive to ‘turning back off’ by dmPGE 2 signaling. However, a potential role for this protein in aged HSCs remains to be explored. A more substantial target may be Rorb , which encodes for RAR related orphan receptor B (RORβ), a member of the highly conserved ROR family of receptor tyrosine kinases 77 . These kinases, including RORβ, are known to negatively regulate WNT/B-catenin signaling 78 , 79 , an important facilitator of HSC fate decisions 80 . In the context of dmPGE 2 stimulation, dmPGE 2 enhanced WNT signaling during zebrafish embryogenesis and was required for WNT-mediated regulation of HSC development 81 . In addition, RORβ is elevated with age in marrow-derived osteoprogenitor cells, contributing to development of osteoporosis 79 , 82 . Our study reveals that RORβ is elevated with age in HSCs, and decreased in response to dmPGE 2 in an age-dependent manner. Rora and Rorc also exhibited unique expression patterns affected by both age and dmPGE 2 treatment (Fig. 5 B). Together, these findings may indicate a novel mechanism of age-associated dysregulation of HSC fate decisions through increased ROR expression, and reveal an intriguing avenue for downregulation of RORβ in aged HSCs through the PGE 2 signaling pathway. In conclusion, this study has identified that aged HSCs primarily retain the molecular capacity to respond to dmPGE 2 pulse exposure and initiate transcriptional programs enhancing survival and long-term repopulating function, which has potential importance toward the goal of enhancing aged human grafts for transplantation. Moreover, age-related alterations in HSC signaling in response to PGE 2 were identified as potential targets for treatment of age-related defects. Declarations ACKNOWLEDGEMENTS This work was supported by the Indiana University Cooperative Center for Excellence in Hematology CCEH (U54 DK106846) through a Pilot and Feasibility award (AMP), the National Institute on Aging (AG046246) (LMP, CMO), and the National Institute of Allergy and Infectious Diseases (AI128894) (CMO). We thank the In Vivo Therapeutics Core at the Indiana University Melvin and Bren Simon Comprehensive Cancer Center for providing mice for these studies. Flow cytometry was performed at the Flow Cytometry Resource Facility of the IU Simon Comprehensive Cancer Center (National Cancer Institute [NCI] grant P30 CA082709). Flow cytometry was supported in part by a Center of Excellence Grant in Molecular Hematology (PO1 DK090948). Sequencing analysis was carried out in the Center for Medical Genomics at Indiana University School of Medicine, which is partially supported by the Indiana University Grand Challenges Precision Health Initiative. Funding: This work was supported by the Indiana University Cooperative Center for Excellence in Hematology CCEH (U54 DK106846), the National Institute on Aging (AG046246), and the National Institute of Allergy and Infectious Diseases (AI128894). Conflicts of interest: The authors have no conflicts of interest to declare that are relevant to the content of this article. Ethics approval: All murine studies were approved by the Indiana University School of Medicine Institutional Animal Care and Use Committee. Consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and material (data transparency): The accession number for the RNA-seq data reported in this paper is GEO: (TBD). Code availability: Not applicable. Author contributions: All authors made substantial contributions to this study. 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Supplementary Files GraphicalAbstract.pdf AgedPGEPulseFigS1.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Minor Revisions Needed 02 Mar, 2021 First submitted to journal 08 Feb, 2021 Editor assigned by journal 07 Feb, 2021 Reviewers invited by journal 07 Feb, 2021 Reviews received at journal 07 Feb, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Sampson","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Carol","middleName":"H.","lastName":"Sampson","suffix":""},{"id":11024543,"identity":"6b377a6b-59c7-4cf2-ad8f-aba69d51627b","order_by":3,"name":"Edward Simpson","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Edward","middleName":"","lastName":"Simpson","suffix":""},{"id":11024544,"identity":"fefc15b8-8a1c-4384-9346-dbc4adeaddb4","order_by":4,"name":"Yunlong Liu","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yunlong","middleName":"","lastName":"Liu","suffix":""},{"id":11024545,"identity":"5e00abb1-a0ab-43ae-8f88-6695124c8522","order_by":5,"name":"Louis M. Pelus","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Louis","middleName":"M.","lastName":"Pelus","suffix":""},{"id":11024546,"identity":"fb63e8f0-5e86-4a16-a206-cd5e35b385ab","order_by":6,"name":"Christie M. Orschell","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Christie","middleName":"M.","lastName":"Orschell","suffix":""}],"badges":[],"createdAt":"2021-02-08 19:35:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-224253/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-224253/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":5884515,"identity":"53e0377b-704f-4a45-82e4-6d2fe2889a48","added_by":"auto","created_at":"2021-02-11 23:51:25","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":101463,"visible":true,"origin":"","legend":"DmPGE2 pulse increases long-term chimerism in serial transplantation of old BM similar to young. \nA) WBM cells from 4 young (3 mo) and 4 old (25 mo) mice expressing CD45.2 were pulsed ex vivo for 1 h with dmPGE2 or vehicle, and 3 x 105 cells transplanted along with 2 x 105 untreated congenic (CD45.1) competitor WBM cells into irradiated CD45.1 primary (1°) recipients (3 recipients per treatment per donor = 12 recipients per group). After 7 mo, 1.5 x 106 WBM cells from 1° recipients were transplanted into irradiated secondary (2°) recipients; Tx, transplant. B) Recipient PB was analyzed monthly for CD45.2 chimerism and trilineage reconstitution at 6 mo by flow cytometry as shown. C) 1° and D) 2° donor-derived chimerism over time for 4 young (Young 1-4) and 4 old (Old 1-4) donors when pulsed with either vehicle or dmPGE2 (left), and trilineage ratios within the CD45.2 compartment (right) at 6 mo post-transplant; V, vehicle; P, dmPGE2. E-F) Summary of young and old 2° transplant donor chimerism at 6 mo, showing E) the change in CD45.2 chimerism of each graft after dmPGE2 pulse, and F) donor and competitor lymphoid and myeloid populations as a frequency of total CD45 cells (CD45.1 + CD45.2), normalized to 100%; V, vehicle; P, dmPGE2. P-values from paired t-tests are indicated in (E).\n","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/0cc9da05a1d6a7e4cd9889ae.jpg"},{"id":5884411,"identity":"c29cc2bf-9bfe-4b92-8b95-294c40068f38","added_by":"auto","created_at":"2021-02-11 23:45:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87711,"visible":true,"origin":"","legend":"BM population analysis pre- and post-transplantation. \nA) Flow cytometry gating strategy for phenotypic analysis of BM cells; representative pre-pulse young and old BM samples are shown. B) Frequency of phenotypic HSCs (pHSCs) among live BM cells, and C) EP4 surface expression, for each young and old donor sample prior to pulse and transplantation; p-values from paired t-tests (2-tailed) are indicated on graphs. D-H) Upon harvest for 2° transplant (7 mo following 1° transplant) recipient BM was analyzed by flow cytometry for D) donor CD45.2 BM chimerism, E) pHSC and F) phenotypic myeloid progenitor (pMP) frequency of donor cells, and G) pHSC and H) pHPC frequency of the donor LSK population; shown with paired vehicle and dmPGE2 values connected by the dotted line; p-values from paired t-tests (1-tailed) are indicated on graphs. pHSC, phenotypic hematopoietic stem cells; pMP, phenotypic myeloid progenitors; pHPC, phenotypic hematopoietic progenitor cells. *Primary recipients of vehicle-treated BM from donor mouse “Young 3” had too few CD45.2 LSK cells detected for pHSC/HPC frequencies, and were thus not included in graphs. \n","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/313776b7f66b5787468a6aa1.jpg"},{"id":5884563,"identity":"fafcfced-a112-49fd-92a3-0256efbfe9e8","added_by":"auto","created_at":"2021-02-11 23:54:25","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":132470,"visible":true,"origin":"","legend":"Transcriptional responses to dmPGE2 in young and old HSCs by RNA-seq. \nA) WBM cells from young (3 mo) and old (25 mo) mice were enriched for immature cells by magnetic lineage depletion then pulsed for 1 h with dmPGE2 or vehicle prior to staining and FACS sorting of pHSCs for RNA-seq. B) Relative expression heatmap and C) Paired Δ (change with dmPGE2 vs. vehicle) heatmap of all 289 genes with FDR\u003c0.05 for dmPGE2 vs. vehicle in young and/or old pHSCs combined. Genes are clustered by dmPGE2 effects that are age-independent (same Δ direction and FDR\u003c0.6 in other age group) or age-dependent (FDR\u003e0.6 in other age group).","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/0a1cf87b26c6acee1e971fc3.jpg"},{"id":5884517,"identity":"80059c69-c4a1-466e-9b1b-45e941c3b7d9","added_by":"auto","created_at":"2021-02-11 23:51:25","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":102453,"visible":true,"origin":"","legend":"Bioinformatic comparison indicates preserved dmPGE2 signaling pathways in old HSCs. \nA) Top 10 Upstream Regulators by z-score from an IPA Comparison Analysis between the young and old dmPGE2 vs. vehicle analyses (z-score cutoff \u003e |2|). B) Genes contributing to the CREB1 activation z-score in both young and old analyses. C) Cellular/Molecular Functions by z-score from the Comparison Analysis as in (A) (z-score cutoff \u003e |2|). D) Genes contributing to the ‘Cell survival’ and/or ‘Cellular homeostasis’ activation z-scores in both young and old analyses. Bold genes in (B) and (D) are common in both heatmaps. E-F) Relative mRNA levels detected for PGE2 receptors E) EP2 and EP4 from vehicle-treated groups (baseline), and F) EP4 with paired vehicle and dmPGE2 values connected; FPKM, fragments per kilobase per million mapped reads.","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/883757a23107ef2ba9ab1412.jpg"},{"id":5884428,"identity":"dcf82be8-d66d-4151-a6c4-2c62bfd02e44","added_by":"auto","created_at":"2021-02-11 23:48:25","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":86128,"visible":true,"origin":"","legend":"Genes oppositely affected by dmPGE2 stimulation in young and old HSCs. \nRelative mRNA levels are shown for each gene in young or old HSCs with paired vehicle and dmPGE2 values connected, for A) twelve genes identified as significantly differently affected by dmPGE2 based on “difference of difference” FDRs (all FDR\u003c0.05), and B) other Rorb family members for comparison; FPKM, fragments per kilobase per million mapped reads.\n","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/a16a4bf25c3bb7c0909ccaec.jpg"},{"id":13659157,"identity":"a2e66253-34c0-4393-a7cb-43d84c1c4612","added_by":"auto","created_at":"2021-09-17 10:18:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":979808,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/96a45f25-1fd9-4cd6-8d51-4f5d43ebbcf4.pdf"},{"id":5884413,"identity":"274e6cc2-5bc2-4f39-86bc-91d3dab81884","added_by":"auto","created_at":"2021-02-11 23:45:25","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":890313,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/2f79de49ab3ff965e93a0dbd.pdf"},{"id":5884426,"identity":"e11ef6d3-dc48-44cc-bf94-2d21fb41a03c","added_by":"auto","created_at":"2021-02-11 23:48:25","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1207148,"visible":true,"origin":"","legend":"","description":"","filename":"AgedPGEPulseFigS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-224253/v1/0d00d4287ba6f5d228183b14.pdf"}],"financialInterests":"","formattedTitle":"Prostaglandin E2 Enhances Aged Hematopoietic Stem Cell Function","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHematopoietic stem cells (HSCs) are responsible for continual replacement of all blood cell types, and HSC transplantation (HSCT) is a life-saving option for many patients with hematologic diseases. However, HSC function and engraftment capacity drastically decrease with age\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Loss of immune function, anemia, myeloid skewing, and increased incidence of myeloproliferative diseases and leukemia are observed in the elderly, and aged bone marrow (BM) cells are unfavorable for transplantation\u003csup\u003e4,8\u0026minus;11\u003c/sup\u003e. While many factors are thought to contribute to HSC aging, including cell-intrinsic and niche-mediated\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, specific molecular pathways functionally linked to aged HSC defects are not well characterized, and no treatment exists to enhance aging hematopoiesis or augment the transplantation potential of these cells. The number of people\u0026thinsp;\u0026gt;\u0026thinsp;65 years of age is projected to almost double between 2012 and 2050\u003csup\u003e14\u003c/sup\u003e, intensifying the problem of aged HSC dysfunction and the critical need for novel therapeutic approaches for those in need of HSC support.\u003c/p\u003e\u003cp\u003eProstaglandin E2 (PGE\u003csub\u003e2\u003c/sub\u003e) is a bioactive lipid with hematopoietic roles described since the 1970s\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. More recently, the stable derivative 16,16-dimethyl PGE\u003csub\u003e2\u003c/sub\u003e (dmPGE\u003csub\u003e2\u003c/sub\u003e) was found to enhance HSC frequency and transplantation efficiency in both zebrafish and murine models\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. We have previously shown that pulse exposure to dmPGE\u003csub\u003e2\u003c/sub\u003e enhances homing, survival, and proliferation for both young (2\u0026ndash;3 mo) mouse BM and human cord blood derived CD34\u0026thinsp;+\u0026thinsp;cells, which was associated with increased CXCR4 and Survivin expression, decreased apoptosis, and increased HSC proliferation\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Further, dmPGE\u003csub\u003e2\u003c/sub\u003e pulse exposure augmented competitiveness of human cord blood grafts in a Phase I clinical trial with double cord blood transplantation\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and has been used clinically to enhance engraftment of gene modified HSCs\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Thus, dmPGE\u003csub\u003e2\u003c/sub\u003e is known to enhance HSC function and has potential for clinical translation.\u003c/p\u003e\u003cp\u003eThe objective of the current work was to assess the effects of dmPGE\u003csub\u003e2\u003c/sub\u003e pulse exposure on aged HSCs at both the functional and molecular level in comparison to young HSCs. Functionally, dmPGE\u003csub\u003e2\u003c/sub\u003e pulse prior to competitive serial transplantation significantly enhanced the long-term repopulating capacity of aged HSCs similarly to young. A high-throughput genomic comparison of old and young HSC responses to dmPGE\u003csub\u003e2\u003c/sub\u003e highlighted common transcriptional pathways in old and young mediating HSC enhancement, and identified novel signaling alterations in HSCs with age.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMice\u003c/h2\u003e\u003cp\u003e All studies were approved by the Indiana University School of Medicine Institutional Animal Care and Use Committee. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAged mice\u003c/span\u003e: C57BL/6J male mice were purchased at 10 weeks old from Jackson Laboratories (Bar Harbor, ME) and aged in our facility until used at 25 mo of age. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eYoung mice\u003c/span\u003e: C57BL/6J male mice were purchased at 10 weeks old from the Indiana University In Vivo Therapeutics Core (IVTC) and used at 3 mo of age. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTransplant recipient mice\u003c/span\u003e: B6.BoyJ congenic (CD45.1) male and female mice were purchased at 6\u0026ndash;8 weeks of age from the IVTC and used as transplant recipients at 8\u0026ndash;10 weeks of age. Transplants were randomized by recipient sex and age such that young and old donor samples were equally distributed between recipients that were male or female, and younger (closer to 8 weeks) or older (closer to 10 weeks). Mice were randomized within cages so that each cage contained recipients of both vehicle and dmPGE\u003csub\u003e2\u003c/sub\u003e-pulsed cells, but from the same donor when possible for rigor of comparison between matched samples.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eBM Collection\u003c/h2\u003e\u003cp\u003eFemurs, tibiae, pelvic bones, and humeri from young and old C57BL/6J mice were flushed with cell buffer (PBS containing 2% FBS and 2 mM EDTA). Cells were passed through a 40 \u0026micro;m filter, and total nucleated cells (TNC) enumerated using an Element HT5 Hematology Analyzer (Heska Corporation, Loveland, CO). In the transplantation experiment, an aliquot of cells from each mouse was removed for flow cytometric assessment of young vs. old BM prior to dmPGE\u003csub\u003e2\u003c/sub\u003e pulse.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eDmPGE\u003csub\u003e2\u003c/sub\u003e Pulse Exposure\u003c/h2\u003e\u003cp\u003eDmPGE\u003csub\u003e2\u003c/sub\u003e in methyl acetate from Cayman Chemicals (Ann Arbor, MI) was stored at -20 \u003csup\u003eo\u003c/sup\u003eC. Prior to use, dmPGE\u003csub\u003e2\u003c/sub\u003e was evaporated to dryness on ice under N\u003csub\u003e2\u003c/sub\u003e and reconstituted in 100% EtOH at a stock concentration of 10 mg/ml (26.28 mM). Whole BM (WBM) cells (transplantation experiments) or lineage-depleted WBM cells (RNA-seq experiments) from individual C57BL/6J (CD45.2) young or old mice were split in two portions. One portion was pulsed in a concentration of 10 \u0026micro;M dmPGE\u003csub\u003e2\u003c/sub\u003e in cell buffer, and the other in an equivalent volume of vehicle (100% EtOH) in cell buffer, at 2.5 x 10\u003csup\u003e6\u003c/sup\u003e TNC/mL for 1 h in a humidified CO\u003csub\u003e2\u003c/sub\u003e incubator at 37\u0026deg;C, with vortexing every 15 min. Cells were then centrifuged at 500 x g for 10 min to remove dmPGE\u003csub\u003e2\u003c/sub\u003e or vehicle and washed with cell buffer.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eCompetitive Serial Transplantation\u003c/h2\u003e\u003cp\u003ePulsed WBM cells from 4 young and 4 old donor C57BL/6J mice (CD45.2) were transplanted into 6 recipients per donor, where 3 received cells pulsed with dmPGE\u003csub\u003e2\u003c/sub\u003e and 3 received cells from the same donor pulsed with vehicle for matched analysis. To that end, 8\u0026ndash;10 week-old congenic recipient mice (CD45.1) were exposed to \u003csup\u003e137\u003c/sup\u003eCs irradiation (11 Gy split dose, 4 h apart) using a Mark 1 Irradiator (JL Shepherd, San Fernando, California), as previously described\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. DmPGE\u003csub\u003e2\u003c/sub\u003e- or vehicle-pulsed donor WBM cells were resuspended in PBS and combined with competitor CD45.1 WBM cells not pulsed with dmPGE\u003csub\u003e2\u003c/sub\u003e or vehicle in a 3:2 ratio, for a final retro-orbital injection of 100 uL containing 3 x 10\u003csup\u003e5\u003c/sup\u003e donor and 2 x 10\u003csup\u003e5\u003c/sup\u003e competitor TNCs per recipient mouse. Recipients were given autoclaved acidified water (pH 2.0\u0026ndash;3.0) and irradiated Uniprim diet (Envigo, Madison, WI) for 1 week prior to, and 4 weeks after irradiation/transplantation. Peripheral blood (PB) was analyzed monthly for donor chimerism and for multilineage reconstitution at month 6.\u003c/p\u003e\u003cp\u003eAfter 7 mo, WBM was collected from all primary recipients. Cells from each set of 3 replicate primary recipients (or 2 in two cases where one recipient died in primary phase) were combined equally and 1.5 x 10\u003csup\u003e6\u003c/sup\u003e TNC transplanted into 3 secondary CD45.1 recipients conditioned with radiation as above. PB was analyzed monthly for donor chimerism, except for months 4\u0026ndash;5 due to pandemic-related laboratory restrictions, and for multilineage reconstitution at month 6.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eCell Staining and Flow Cytometry Analysis\u003c/h2\u003e\u003cp\u003eBM cells were stained with an amine-reactive live/dead dye (Invitrogen LIVE/DEAD Fixable Dead Cell Stain kit Yellow, Thermo Fisher, Waltham, MA) followed by blocking with TruStain FcX+ (Biolegend, San Diego, CA) and fluorophore-conjugated monoclonal antibodies to identify phenotypic HSCs (pHSCs) using a lineage cocktail in APC (CD3, GR-1, B220, Ter-119, CD11b, and CD5; R\u0026amp;D Systems, Minneapolis, MN), Sca1 in PerCP/Cy5.5, c-Kit in BV711, CD150 in PE/Cy7, and CD48 in APC/Cy7 (Biolegend). EP4 was stained with an unconjugated primary polyclonal antibody (Novus Biologicals, Littleton, CO) and a secondary anti-rabbit IgG antibody conjugated to BV421 (Biolegend). Cells were then analyzed immediately by flow cytometry.\u003c/p\u003e\u003cp\u003ePB cells were RBC-lysed, blocked with TruStain FcX+ (Biolegend), and stained with fluorophore-conjugated antibodies to white blood cell markers including CD45.1 in PE, CD45.2 in FITC, B220 in Pacific Blue, CD3 in PerCP/Cy5.5, and CD11b in APC (Biolegend). Cells were fixed in 1% paraformaldehyde and stored at 4\u0026deg;C until flow cytometric analysis. Flow cytometric data were acquired using an LSRII flow cytometer (BD Biosciences, San Jose, CA) and analyzed using FlowJo software (BD Biosciences).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eWBM Processing, HSC Sorting, and RNA Extraction for Sequencing\u003c/h2\u003e\u003cp\u003eWBM cells from 8 young and 4 old mice were enriched for immature cells by magnetic lineage depletion (EasySep Mouse Hematopoietic Progenitor Cell Isolation kit, STEMCELL Technologies), then pairs of young samples were combined to increase the number of pHSCs available for sorting from 4 individual BM samples from young mice alongside 4 individual BM samples from old mice. Cells were then pulsed with dmPGE\u003csub\u003e2\u003c/sub\u003e or vehicle for 1 h as described above, immediately stained, and viable pHSCs isolated by fluorescence associated cell sorting (FACS) using a SORP Aria flow cytometer (BD Biosciences). Cells were sorted directly into lysis buffer for RNA extraction using the RNeasy Plus Micro Kit (Qiagen, Hilden, Germany). A 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) was used for quality control of all RNA preparations, giving a median RNA integrity of 9.6 RIN (range 6.2\u0026ndash;10.0).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eRNA Sequencing and Statistics/Bioinformatics\u003c/h2\u003e\u003cp\u003eLibrary preparation was performed using the SMART-Seq v4 Ultra Low Input RNA Kit (Clontech, Mountain View, CA) and the Nextera XT DNA Lib Kit (Illumina, San Diego, CA). Two hundred picomolar pooled libraries were utilized per flow cell for clustering amplification on cBot using HiSeq 3000/4000 PE Cluster Kit and sequenced with 2\u0026times;75bp paired-end configuration on HiSeq4000 (Illumina) using a HiSeq 3000/4000 PE SBS Kit. Sequencing data were assessed for quality using FastQC version 0.11.5 (Babraham Bioinformatics, Cambridge, UK). The sequence reads were mapped to the mouse genome (UCSC mm10) using STAR (Spliced Transcripts Alignment to a Reference)\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e version 2.5 using parameter \"--outSAMmapqUnique 60\". To evaluate the quality of the RNA-seq data, number of reads that fall into different annotated regions (exonic, intronic, splicing junction, intergenic, promoter, UTR, etc.) of the reference genes were determined with bamUtils\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e version 0.5.9.\u003c/p\u003e\u003cp\u003eUniquely mapped sequencing reads were assigned to mm10 refGene genes and quantified using featureCounts (from subread)\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e version 1.5.1 using parameters \"-s 2 -p -Q 10\". Low quality mapped reads (including reads mapped to multiple positions) were excluded. Differential expression (DE) analysis was performed with edgeR\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. In this workflow, the statistical methodology applied uses negative binomial generalized linear models with likelihood ratio tests. A paired design was used to compare samples across conditions such that the relationships between samples from the same animals were retained (\"blocking\" in edgeR). False discovery rate (FDR) calculations therefore reflect the collective significance of the treatment on gene expression while accounting for baseline differences between the animals.\u003c/p\u003e\u003cp\u003eDE data was analyzed for biological insights using Ingenuity Pathway Analysis (IPA, Qiagen, Hilden, Germany)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Two IPA Core Analyses were run, one for the young and one for the old dmPGE\u003csub\u003e2\u003c/sub\u003e vs. vehicle comparisons, with cutoffs set to FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and log\u003csub\u003e2\u003c/sub\u003eFC\u0026gt;|0.5| (FC, fold change). The young and old analyses were compared using the IPA Comparison Analysis function. Upstream Regulators were filtered on Genes, RNAs, and Proteins, z-score cutoff |2|, p-value cutoff 1.3 (log\u003csub\u003e10\u003c/sub\u003e). Diseases and Functions were filtered on Cellular and Molecular Functions, with additional removal of cancer cell-specific functions, z-score cutoff |2|, p-value cutoff 1.3 (log\u003csub\u003e10\u003c/sub\u003e). The set of 70 genes increased by dmPGE\u003csub\u003e2\u003c/sub\u003e in young (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but not in old (FDR\u0026thinsp;\u0026gt;\u0026thinsp;0.6) was submitted to the DAVID 6.8 Functional Annotation tool using default settings and output from the Functional Annotation Chart filtered on UP_KEYWORDS and cutoff at Benjamini-adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01 (david.ncifcrf.gov)\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHeatmaps were generated in Microsoft Excel using conditional formatting for cell color based on FPKM values (fragments per kilobase per million mapped reads). Heatmaps depicting relative gene expression among all samples/groups (blue-red) used the following formula for each cell: (FPKM \u0026ndash; average FPKM across all samples all groups)/standard deviation of FPKM across all samples all groups. Heatmaps depicting change in (Δ) gene expression between paired samples (gray-orange) used the formula: (FPKM\u003csup\u003edmPGE\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e \u0026ndash; FPKM\u003csup\u003evehicle\u003c/sup\u003e)/standard deviation of FPKM across all samples in age group, where superscripts denote different treatments of the same mouse BM sample.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistics\u003c/h2\u003e\u003cp\u003eOther statistical analyses were performed using Microsoft Excel and GraphPad Prism 8. All data with error bars represent mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Paired t-tests were performed between matched vehicle- and dmPGE\u003csub\u003e2\u003c/sub\u003e-treated samples from the same donor in chimerism analyses, 1-tailed for expected increase with dmPGE\u003csub\u003e2\u003c/sub\u003e. Unpaired t-tests were performed between young and old flow cytometry data points (2-tailed).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDmPGE\u003csub\u003e2\u003c/sub\u003e enhances long-term serial repopulation capacity of aged HSCs\u003c/h2\u003e\u003cp\u003eSince dmPGE\u003csub\u003e2\u003c/sub\u003e enhances homing, survival and proliferation of long-term repopulating HSCs in young mice\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, we tested whether a similar effect could be demonstrated on HSCs from old mice, which are known to demonstrate reduced regenerative potential and myeloid skewed differentiation\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. WBM aliquots from 3 mo (young) or 25 mo (old) mice were pulsed with either dmPGE\u003csub\u003e2\u003c/sub\u003e or vehicle prior to competitive serial transplantation, allowing for matched analysis of dmPGE\u003csub\u003e2\u003c/sub\u003e effects on long-term repopulating HSC potential (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). PB chimerism in recipients was assessed monthly by flow cytometry for CD45.2 donor cell frequency and for trilineage distribution at 6 mo post-transplant (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In primary transplants, dmPGE\u003csub\u003e2\u003c/sub\u003e pulse increased long-term donor-derived chimerism for all 4 young donors and 3 of 4 old donors (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). After secondary transplantation, long-term repopulation was increased by dmPGE\u003csub\u003e2\u003c/sub\u003e pulse for all donors of both age groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Chimerism of aged grafts at 6 mo post-secondary transplant was increased an average of 27%, similar to the average increase of 21% for young (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), indicating enhanced HSC self-renewal capacity for both young and aged BM grafts by dmPGE\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003eLineage reconstitution\u003c/h2\u003e\u003cp\u003eAnalysis of PB lineage reconstitution showed that pulse with dmPGE\u003csub\u003e2\u003c/sub\u003e increased myeloid frequency in all four young grafts, observed in both primary and secondary transplantations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D, dark green). However, this was not at the expense of lymphoid production; total lymphoid and myeloid production were both increased by dmPGE\u003csub\u003e2\u003c/sub\u003e pulse exposure in comparison to competitor cells as a frequency of total peripheral CD45 cells (CD45.1\u0026thinsp;+\u0026thinsp;CD45.2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Transplantation of grafts from old mice resulted in myeloid-skewed PB reconstitution as expected, regardless of vehicle or dmPGE\u003csub\u003e2\u003c/sub\u003e treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D, dark green). However, similar to young, both lymphoid and myeloid production were increased by dmPGE\u003csub\u003e2\u003c/sub\u003e in comparison to competitor cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). One old graft lost long-term myeloid production after secondary transplantation, with poor overall chimerism for both dmPGE\u003csub\u003e2\u003c/sub\u003e and vehicle (Old 4, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), but still showed increased lymphoid potential with dmPGE\u003csub\u003e2\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), which resulted in an apparent reversal of myeloid skew among donor cells in these recipients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003eDonor BM phenotypic HSC (pHSC) frequencies and EP4 expression pre-transplant\u003c/h2\u003e\u003cp\u003ePrior to pulse and transplantation, aliquots of WBM cells from young and old donors were analyzed for baseline pHSC frequency and dmPGE\u003csub\u003e2\u003c/sub\u003e receptor expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). As expected, the pHSC population in old mice was greatly expanded compared to that in young mice, exhibiting 24-fold higher frequency (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), similar to our previously published data\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. EP4, the receptor primarily implicated in HSC functional responses to dmPGE\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e31\u0026ndash;33\u003c/sup\u003e, was strongly expressed on the surface of aged HSCs and was higher compared to young (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003eBM chimerism and stem/progenitor frequencies post-transplant\u003c/h2\u003e\u003cp\u003eDonor-derived BM chimerism was assessed at the time of secondary transplantation (7 mo post-primary transplant). CD45.2 BM chimerism was significantly higher after dmPGE\u003csub\u003e2\u003c/sub\u003e pulse for all grafts from young donors, and was variably increased after dmPGE\u003csub\u003e2\u003c/sub\u003e pulse for 3 of 4 grafts from old donors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), mirroring the effect on primary PB chimerism. The single old donor without increased BM chimerism also did not show increased PB chimerism after primary transplantation (\u0026ldquo;Old 1\u0026rdquo;, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). However, the subsequent superiority of the dmPGE\u003csub\u003e2\u003c/sub\u003e-treated graft in secondary transplantation (\u0026ldquo;Old 1\u0026rdquo;, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) suggests it may retain a dmPGE\u003csub\u003e2\u003c/sub\u003e-mediated qualitative advantage in HSC self-renewal revealed by the stress of serial transplantation.\u003c/p\u003e\u003cp\u003eWhile the aged grafts contained 24-fold higher pHSC frequency compared to young grafts prior to pulse and transplantation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), similar pHSC frequencies were found among long-term engrafted CD45.2 BM cells from young and old donors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE), likely reflecting the functional compromise of the original pHSC population in the aged mice. Interestingly, dmPGE\u003csub\u003e2\u003c/sub\u003e increased the frequency of phenotypic myeloid-committed progenitors (pMP) (gating illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) among engrafted donor cells for 4 of 4 young grafts and 3 of 4 old grafts (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Further, dmPGE\u003csub\u003e2\u003c/sub\u003e altered the distribution of stem versus progenitor cells within the primitive LSK compartment of the old grafts, partially reversing the age-associated predominance of pHSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG) in favor of increased phenotypic hematopoietic progenitor cells (pHPCs, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH; gating illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). This may suggest increased capacity for generation and/or maintenance of downstream progenitor populations when grafts are pulsed with dmPGE\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eShared and divergent transcriptional responses to dmPGE\u003csub\u003e2\u003c/sub\u003e in young and old HSCs\u003c/h2\u003e\u003cp\u003eTo identify molecular correlates of enhanced long-term HSC function by dmPGE\u003csub\u003e2\u003c/sub\u003e in both young and aged HSCs, and to identify signaling differences in HSCs with age, pHSCs from pulsed BM samples were immediately isolated by FACS and analyzed using RNA-seq (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Differentially expressed genes were defined as FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 by pair-wise analysis between dmPGE\u003csub\u003e2\u003c/sub\u003e- and vehicle-pulsed samples from the same mouse, across 4 young samples or 4 old samples to determine age-specific transcriptional effects. The paired analyses allow for robust detection of dmPGE\u003csub\u003e2\u003c/sub\u003e effects despite baseline gene expression differences between individual mice, which can become particularly variable with advanced age.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDmPGE\u003csub\u003e2\u003c/sub\u003e significantly affected 230 genes in young HSCs (184 increased, 46 decreased), and 112 genes in old HSCs (85 increased, 27 decreased). Of these, 53 common genes reached significance in both age groups (49 increased, 4 decreased; Fig. S1). Substantially fewer genes reached FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in old HSCs, which may be due in part to greater variability in responsiveness among old mice, but may also reflect an overall decrease in HSC responses to dmPGE\u003csub\u003e2\u003c/sub\u003e with age. All differentially expressed genes reaching FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in both age groups combined were clustered based on similar (age-independent) or unique (age-dependent) dmPGE\u003csub\u003e2\u003c/sub\u003e effects between young and old, and were visualized both for relative expression across all samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and for individually paired Δ gene expression induced by dmPGE\u003csub\u003e2\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The top two clusters in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC represent similar increase/decrease in both age groups (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for at least one age group and \u0026lt;\u0026thinsp;0.6 in the other), and comprised a majority of the genes. Since dmPGE\u003csub\u003e2\u003c/sub\u003e pulse effectively enhanced HSC function in serial transplantation for both age groups, we first focused analysis on shared gene effects to narrow the pathways likely involved in the mechanism of enhancement. The lower clusters represent genes affected differently by dmPGE\u003csub\u003e2\u003c/sub\u003e in old and young HSCs; these are not likely involved in the mechanism of enhancement but can shed light on changes in HSC signaling pathways with age.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003eShared dmPGE\u003csub\u003e2\u003c/sub\u003e signaling in young and old HSCs\u003c/h2\u003e\u003cp\u003eIPA was used to identify the most likely upstream regulators activated by dmPGE\u003csub\u003e2\u003c/sub\u003e in HSCs based on all downstream gene expression changes (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and log\u003csub\u003e2\u003c/sub\u003eFC\u0026gt;|0.5|) in young and old mice, and a comparison analysis of results from each age group revealed the same top regulators predicted in young and old (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The regulator with the highest activation z-score in both age groups was CREB1, a known mediator of PGE\u003csub\u003e2\u003c/sub\u003e signaling through receptors EP2 and EP4\u003csup\u003e34\u003c/sup\u003e, supporting similar HSC-intrinsic signaling in old and young. Among the CREB1-regulated genes contributing to each z-score, 16 were shared between young and old (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eCellular functions activated by dmPGE\u003csub\u003e2\u003c/sub\u003e were also predicted, with \u003cem\u003e\u0026lsquo;Cell survival\u0026rsquo;\u003c/em\u003e and \u003cem\u003e\u0026lsquo;Cellular homeostasis\u0026rsquo;\u003c/em\u003e reaching significant activation z-scores in both young and old HSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Overlapping gene sets contributed to both functions, and 18 of these genes were shared between young and old (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Seven of these genes (bold) are also known to be regulated by CREB1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Thus, CREB1 activation by dmPGE\u003csub\u003e2\u003c/sub\u003e may be increasing HSC survival and homeostasis through \u003cem\u003eBhlhe40, Cdkn1a, Cebpb, Gadd45b, Nr4a2, Pim3\u003c/em\u003e, and \u003cem\u003eVegfa\u003c/em\u003e, among others in these heatmaps potentially not yet functionally linked. Overall, these genes and predicted regulators (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) shared in old and young HSC responses to dmPGE\u003csub\u003e2\u003c/sub\u003e provide strong candidates for further study as molecular mediators of enhancement of HSC potential.\u003c/p\u003e\u003cp\u003eSince dmPGE\u003csub\u003e2\u003c/sub\u003e activates CREB1 through either EP2 or EP4, baseline mRNA expression of each receptor was compared (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). EP2 was not detectable above background in young or old HSCs while EP4 was highly expressed and increased with age, confirming the flow cytometry findings for EP4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Also, dmPGE\u003csub\u003e2\u003c/sub\u003e pulse exposure decreased EP4 expression in each of the old HSC samples and 3 of 4 young samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Desensitization through EP4 has been noted\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and this negative feedback effect on EP4 expression has been reported in murine HSCs after in vivo dmPGE\u003csub\u003e2\u003c/sub\u003e treatment\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Together these findings further support EP4 as the relevant receptor for enhancement of both young and old HSC long-term function.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003eDivergent dmPGE\u003csub\u003e2\u003c/sub\u003e signaling in young and old HSCs\u003c/h2\u003e\u003cp\u003eThe third cluster in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB/C, and the second largest cluster overall, is comprised of 70 genes significantly increased by dmPGE\u003csub\u003e2\u003c/sub\u003e in young HSCs (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but not affected at all in old HSCs (FDR\u0026thinsp;\u0026gt;\u0026thinsp;0.6). Visualizing relative expression in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, many of these genes appear already elevated at baseline in vehicle-treated old HSCs and are not further increased with dmPGE\u003csub\u003e2\u003c/sub\u003e. These genes were classified for functional annotation enrichments using DAVID bioinformatics analysis (Table\u0026nbsp;1). The top enrichment category was \u0026lsquo;Phosphoprotein\u0026rsquo;, comprising 44 of the 70 genes. These phosphoproteins also made up 23/29 genes from \u0026lsquo;Alternative splicing\u0026rsquo;, and 14/17 genes from \u0026lsquo;Transcription\u0026rsquo;, the next two most enriched categories. The category of \u0026lsquo;Alternative Splicing\u0026rsquo; is defined by UniProt as \u0026ldquo;Protein for which at least two isoforms exist due to distinct pre-mRNA splicing events\u0026rdquo; (uniprot.org). Since alternative splicing has been implicated in the development of myeloproliferative disorders which increase in prevalence with age\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, these genes are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Thus, a sizeable subset of dmPGE\u003csub\u003e2\u003c/sub\u003e-induced genes observed in young HSCs become less responsive with age and are enriched for phosphoproteins with alternative splice variants and those involved in transcriptional regulation.\u003c/p\u003e\n\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Functional Annotation enrichments\u003csup\u003ea\u003c/sup\u003e among the 70\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003egenes increased by dm\u003c/strong\u003e\u003cstrong\u003ePGE\u003csub\u003e2\u003c/sub\u003e\u003c/strong\u003e\u003cstrong\u003e in young but not in old HSCs\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e\u003cstrong\u003e#\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u003cstrong\u003eTerm \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003eCount (/70)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e\u003cstrong\u003eFold Enrich.\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u003cstrong\u003eBenj. p-val\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u0026nbsp;Phosphoprotein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e1.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e3.7E-5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u0026nbsp;Alternative splicing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e2.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e4.2E-3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u0026nbsp;Transcription\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e3.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e4.9E-3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u0026nbsp;Transcription regulation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e6.1E-3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u0026nbsp;Transferase\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e7.1E-3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"24\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"160\"\u003e\n\u003cp\u003e\u0026nbsp;Coiled coil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e2.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e8.4E-3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eDAVID Functional Annotation Chart, filtered on UP_KEYWORD\u003c/p\u003e\n\u003cp\u003eand Benjamini-adjusted p \u0026lt; 0.01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenes annotated with \u0026lsquo;Alternative splicing\u0026rsquo;\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e#\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eDmPGE\u003csub\u003e2\u003c/sub\u003e Effect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eAvg Baseline (Veh) FPKM\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eFDR Yng\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eFDR Old\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eYng\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eOld\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eFC with age\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eAdgrg2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eEvc\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSytl5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDmxl2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTtc39a\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eUbr4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eClk1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0475\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e28.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e43.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDmd\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7699\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eEpc1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eMga\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e4932438a13rik\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eKmt2c\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eMycbp2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.1822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eAdgrl2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e17.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eUsp53\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSuco\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.6945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eMadd\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8872\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e37.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDopey1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSlc12a7\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eAnkrd6\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eGgt5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0313\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eGramd1a\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e38.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e47.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eBirc6\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9706\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSyne2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eZfp292\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0328\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9640\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSetdb1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7388\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eIpo8\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSmcr8\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePcgf5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e47.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003eAverage FPKM (fragments per kilobase per million mapped reads) among\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003evehicle-treated young (Yng) or old HSCs (n\u0026thinsp;=\u0026thinsp;4 per sex); FDR, false discovery\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003erate for dmPGE\u003csub\u003e2\u003c/sub\u003e vs. vehicle analyses; FC, fold change.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAn additional \u0026ldquo;difference of difference\u0026rdquo; FDR calculation was utilized to compare the treatment effect in old versus young HSCs and identify genes affected significantly differently by dmPGE\u003csub\u003e2\u003c/sub\u003e in each age group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Each of these genes was affected in the opposite direction by dmPGE\u003csub\u003e2\u003c/sub\u003e in old and young HSCs (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Several had higher average expression with age in the vehicle-treated samples and were decreased by dmPGE\u003csub\u003e2\u003c/sub\u003e in old HSCs, as opposed to being increased by dmPGE\u003csub\u003e2\u003c/sub\u003e in young HSCs, including \u003cem\u003eCcbe1, Evc, Mlk2, Mycbp2, Rorb, and Ubr4\u003c/em\u003e. Since \u003cem\u003eRorb\u003c/em\u003e was so strongly upregulated with age and differentially affected by dmPGE\u003csub\u003e2\u003c/sub\u003e, its close family members \u003cem\u003eRora\u003c/em\u003e and \u003cem\u003eRorc\u003c/em\u003e were also examined (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). \u003cem\u003eRora\u003c/em\u003e was slightly increased with age and strongly upregulated by dmPGE\u003csub\u003e2\u003c/sub\u003e in both young and old HSC, while \u003cem\u003eRorc\u003c/em\u003e was strongly increased with age and slightly elevated by dmPGE\u003csub\u003e2\u003c/sub\u003e in old but not in young. In addition, two genes (\u003cem\u003eH2afx\u003c/em\u003e and \u003cem\u003eKcnj5\u003c/em\u003e) had lower average expression with age and were increased by dmPGE\u003csub\u003e2\u003c/sub\u003e in old HSCs, opposite to the dmPGE\u003csub\u003e2\u003c/sub\u003e effect in young, and four others had similar baseline expression in young and old HSCs but opposite treatment effects (\u003cem\u003eElf2, Max, Psap, and Ncoa2\u003c/em\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). These RNA-seq analyses identify potential molecular targets for age-related HSC dysfunction.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAfter HLA matching, donor age is generally the most critical factor determining survival after HSCT\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Grafts from older donors have been associated with increased graft failure even when controlling for cell number\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, which may relate to declining inherent stem cell quality\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Increased incidence of graft versus host disease (GVHD) in recipients of grafts from older donors has also been observed\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, potentially related to an increase in antigen-experienced lymphocytes with age\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e or the general increase in low-level inflammation that characterizes aging\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. However, neither of these associations show consistent relationships with HSCT outcome\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, and a combination of several age-related factors likely contribute. For these reasons, transplant physicians tend to favor younger donors, but finding the appropriately matched donor can sometimes be difficult or impossible. The probability of finding an unrelated matched donor varies with ethnicity, and can be especially problematic for some ethnic groups, e.g. African-Americans\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Elderly family members would have strong motivation to donate if suitably matched, and strategies to enhance aged grafts could help increase the possibility of success.\u003c/p\u003e\u003cp\u003eWhile hematopoietic malignancies treatable by autologous transplant increase in prevalence with age, elderly patients are often not eligible due to the rigors of the HSCT process as well as their own declining HSC quality. However, recent strategies employing reduced-intensity conditioning for elderly patients, as well as advances in transplant technique and supportive care, increasingly enable allogeneic and autologous HSCT in this population\u003csup\u003e\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. The ability to augment the function of aged grafts prior to infusion could facilitate successful, life-saving autologous transplants for older patients. Here we found that ex vivo pulse exposure to dmPGE\u003csub\u003e2\u003c/sub\u003e can enhance the transplantation capacity of murine HSCs of advanced age. Previous work in young grafts has shown this effect to translate from zebrafish and mice\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e to non-human primates\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e and ultimately to enhancement of human cord blood transplantation\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Thus, the current findings have a high likelihood of translation.\u003c/p\u003e\u003cp\u003ePGE\u003csub\u003e2\u003c/sub\u003e is an eicosanoid synthesized within most body tissues by many different cell types, acting in autocrine or paracrine fashion\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Activities mediated by PGE\u003csub\u003e2\u003c/sub\u003e are highly pleiotropic, depending on the tissue/cell type and expression of its four G-protein coupled receptors EP1-4\u003csup\u003e35,54\u003c/sup\u003e. EP1 signals primarily through PKC and Ca\u003csup\u003e2+\u003c/sup\u003e mobilization, EP2 and EP4 induce cAMP production and subsequent cAMP response element-binding protein (CREB) activation as observed here, and EP3 inhibits cAMP production\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. EP4 has been recognized as a key functional regulator for HSCs, including transplantation studies\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In the setting of radiation exposure, where dmPGE\u003csub\u003e2\u003c/sub\u003e protects and enhances HSC function\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, only dmPGE\u003csub\u003e2\u003c/sub\u003e or EP4 agonism conferred survival from lethal irradiation\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. In the current transcriptomic analysis, the predominance of CREB1-induced gene expression following dmPGE\u003csub\u003e2\u003c/sub\u003e pulse in both young and old HSCs, along with strong EP4 expression but undetectable EP2 mRNA levels as observed here and previously by RNA-seq of purified murine pHSCs\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, strongly supports EP4 as the relevant receptor mediating HSC enhancement regardless of age.\u003c/p\u003e\u003cp\u003eAn interesting finding in this study was increased EP4 expression in HSCs with age. PGE\u003csub\u003e2\u003c/sub\u003e production is known to increase with age in macrophages\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e and decrease with age in gastrointestinal tissues\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. In skeletal muscle, the capacity for PGE\u003csub\u003e2\u003c/sub\u003e synthesis increases with age while receptor levels are downregulated\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. It remains unclear if basal PGE\u003csub\u003e2\u003c/sub\u003e levels change with age within the BM, and which factors would drive the increase in EP4 expression on HSCs. The intensity of CREB1-regulated genes was noticeably higher in old HSCs after dmPGE\u003csub\u003e2\u003c/sub\u003e pulse and may be related to the number of EP4 receptors, though higher basal expression of these genes was also seen in control HSCs in a variable manner between aged mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Thus, the change in CREB1-regulated genes was greater in some old mice but not in others, and the relevance of increased EP4 expression on aged HSCs remains uncertain. Ultimately, this investigation established that HSCs of advanced age do not lose expression or signaling through the pivotal EP4 receptor.\u003c/p\u003e\u003cp\u003eWhile the primary objective of these studies was not to compare old versus young HSC function, but rather to evaluate the effect of dmPGE\u003csub\u003e2\u003c/sub\u003e on old grafts in parallel with young grafts, the transplantation experiments were performed simultaneously with the same cohorts of recipients and competitor cells. The studies indicated that the old and young grafts functioned similarly in regard to overall long-term and serial chimerism capacity. Since the old grafts contained approximately 24-fold higher pHSC frequency, and equivalent numbers of WBM cells were transplanted, these observations are in line with the reported substantial decrease in function of pHSCs with age\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. We also observed myeloid-skewed reconstitution from aged HSCs as described\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Interestingly, dmPGE\u003csub\u003e2\u003c/sub\u003e pulse consistently increased the relative myeloid contribution of the young donor cells, bringing their lineage ratios closer to those of the aged. However, dmPGE\u003csub\u003e2\u003c/sub\u003e also increased the overall frequencies of donor lymphoid cells in comparison to competitors, suggesting dmPGE\u003csub\u003e2\u003c/sub\u003e has a positive effect on both major immune cell branches but augments myeloid reconstitution to a greater degree. DmPGE\u003csub\u003e2\u003c/sub\u003e also augmented both branches for old HSCs compared to competitors without further affecting the inherent myeloid skew with age. Of interest, we have previously reported an increase in the proportion of myeloid cells in PB of mice transplanted with young HSCs pulsed with dmPGE\u003csub\u003e2\u003c/sub\u003e following primary and secondary transplant, however this was not consistent across tertiary and quaternary transplants and was without overall effect on the enhancement of induced stem cell competitiveness\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBioinformatic analysis of dmPGE\u003csub\u003e2\u003c/sub\u003e signaling in young versus old HSCs revealed that the core response pathways remained largely unchanged with age. Several age-independent genes were identified as both increased by CREB1 signaling and involved in the significantly predicted functions of \u003cem\u003e\u0026lsquo;Cell survival\u0026rsquo;\u003c/em\u003e and \u003cem\u003e\u0026lsquo;Cellular homeostasis\u0026rsquo;\u003c/em\u003e. Many of these genes additionally have described roles in hematopoiesis, supporting their involvement in HSC modulation by dmPGE\u003csub\u003e2\u003c/sub\u003e. \u003cem\u003eVegfa\u003c/em\u003e encodes for vascular endothelial growth factor A (VEGF-A) which, while first discovered for its primary role in angiogenesis\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, enhances human HPC formation\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e, promotes hematopoietic cell generation from embryonic stem cells of both mouse\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e and human\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e, and regulates HSC survival\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eCebpb\u003c/em\u003e is the gene for CCAAT enhancer binding protein beta (C/EBPβ), a transcription factor that promotes lymphopoiesis\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e and emergency myelopoiesis\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e at the level of stem and progenitor cell regulation\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eGadd45b\u003c/em\u003e, encoding growth arrest and DNA-damage-inducible beta (GADD45β), appears essential for DNA damage protection and survival of HSCs/HPCs and induced pluripotent stem cells (iPSCs) under stress\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eCdkn1a\u003c/em\u003e encodes the cyclin-dependent kinase inhibitor P21, which preserves HSC quiescence under stress and promotes HSC self-renewal in serial transplantation\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, while \u003cem\u003eNr4a2\u003c/em\u003e encoding the transcription factor nuclear receptor subfamily 4 group A member 2, also known as NURR1, also attenuates HSC cycling\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e and may contribute to the maintenance of stem cell quiescence during the stress of transplantation.\u003c/p\u003e\u003cp\u003eIn addition to transplantation, steady-state hematopoiesis in older humans is subject to increased bone marrow failure and decreased hematologic tolerance of cytotoxic injury, as well as the increased propensity for myeloproliferative disorders and cancerous transformation\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. A broader understanding of aged HSC function is essential to development of novel treatments for hematopoietic compromise in the elderly. The high-throughput genomic comparison of old and young HSC responses to dmPGE\u003csub\u003e2\u003c/sub\u003e provided a unique modality for investigating changes in HSC stimulation response pathways with age. Several signaling alterations identified here may have relevance for targeting in treatment of age-induced HSC defects.\u003c/p\u003e\u003cp\u003eGenes differentially affected by dmPGE\u003csub\u003e2\u003c/sub\u003e in young and old HSCs included numerous phosphoproteins induced in young but not in old, many of which were already elevated with age. IPA did not return any significant predictions for a common upstream regulator controlling these genes (no more than 5 had shared association with any given regulator), but functional categories including \u0026lsquo;Alternative splicing\u0026rsquo; exhibited significant enrichment (Table\u0026nbsp;1). Abnormalities in alternative splicing have been implicated in the development of myeloproliferative disorders that increase in prevalence with age, with over 50% of myelodysplastic syndromes harboring spliceosome factor mutations in the dominant clone\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. The current analysis suggests dmPGE\u003csub\u003e2\u003c/sub\u003e-responsive genes that become less responsive with age tend to be those with alternative splice variants, and tend to have higher mRNA levels detectable in old HSCs pre-stimulation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, the current experimental design did not distinguish between splice variants, and further investigation is needed to determine whether these transcripts could be affected by dysregulated splicing in HSCs of advanced age.\u003c/p\u003e\u003cp\u003eSeveral specific genes were identified as significantly \u003cem\u003eoppositely\u003c/em\u003e affected by dmPGE\u003csub\u003e2\u003c/sub\u003e stimulation in old versus young HSCs, revealing divergent molecular responses potentially related to aging defects. \u003cem\u003eCcbe1\u003c/em\u003e and \u003cem\u003eRorb\u003c/em\u003e were particularly elevated with age and strongly decreased by dmPGE\u003csub\u003e2\u003c/sub\u003e only in old HSCs. \u003cem\u003eCcbe1\u003c/em\u003e, encoding for collagen and calcium binding EGF domains 1 (CCBE1), is a secreted protein thought to function in remodeling of extracellular matrix and cell migration, and is an important factor in lymphangiogenesis\u003csup\u003e\u003cspan additionalcitationids=\"CR74\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. It is also an essential mediator of erythroblastic island formation for erythropoiesis in fetal liver, though it is not required for postnatal erythropoiesis\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. This gene has otherwise not been associated with hematopoiesis, and gene expression levels found here in young HSCs were near-zero at baseline with a very slight elevation by dmPGE\u003csub\u003e2\u003c/sub\u003e. However, the \u003cem\u003eCcbe1\u003c/em\u003e transcript was much more detectable in aged HSCs and was strongly and consistently downregulated by dmPGE\u003csub\u003e2\u003c/sub\u003e stimulation. Thus, transcription of Ccbe1 appears to be \u0026lsquo;turned on\u0026rsquo; in HSCs by an unknown aging factor that may be sensitive to \u0026lsquo;turning back off\u0026rsquo; by dmPGE\u003csub\u003e2\u003c/sub\u003e signaling. However, a potential role for this protein in aged HSCs remains to be explored.\u003c/p\u003e\u003cp\u003eA more substantial target may be \u003cem\u003eRorb\u003c/em\u003e, which encodes for RAR related orphan receptor B (RORβ), a member of the highly conserved ROR family of receptor tyrosine kinases\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. These kinases, including RORβ, are known to negatively regulate WNT/B-catenin signaling\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e, an important facilitator of HSC fate decisions\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. In the context of dmPGE\u003csub\u003e2\u003c/sub\u003e stimulation, dmPGE\u003csub\u003e2\u003c/sub\u003e enhanced WNT signaling during zebrafish embryogenesis and was required for WNT-mediated regulation of HSC development\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. In addition, RORβ is elevated with age in marrow-derived osteoprogenitor cells, contributing to development of osteoporosis\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. Our study reveals that RORβ is elevated with age in HSCs, and decreased in response to dmPGE\u003csub\u003e2\u003c/sub\u003e in an age-dependent manner. \u003cem\u003eRora\u003c/em\u003e and \u003cem\u003eRorc\u003c/em\u003e also exhibited unique expression patterns affected by both age and dmPGE\u003csub\u003e2\u003c/sub\u003e treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Together, these findings may indicate a novel mechanism of age-associated dysregulation of HSC fate decisions through increased ROR expression, and reveal an intriguing avenue for downregulation of RORβ in aged HSCs through the PGE\u003csub\u003e2\u003c/sub\u003e signaling pathway.\u003c/p\u003e\u003cp\u003eIn conclusion, this study has identified that aged HSCs primarily retain the molecular capacity to respond to dmPGE\u003csub\u003e2\u003c/sub\u003e pulse exposure and initiate transcriptional programs enhancing survival and long-term repopulating function, which has potential importance toward the goal of enhancing aged human grafts for transplantation. Moreover, age-related alterations in HSC signaling in response to PGE\u003csub\u003e2\u003c/sub\u003e were identified as potential targets for treatment of age-related defects.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Indiana University Cooperative Center for Excellence in Hematology CCEH (U54 DK106846) through a Pilot and Feasibility award (AMP), the National Institute on Aging (AG046246) (LMP, CMO), and the National Institute of Allergy and Infectious Diseases (AI128894) (CMO). We thank the In Vivo Therapeutics Core at the Indiana University Melvin and Bren Simon Comprehensive Cancer Center for providing mice for these studies. Flow cytometry was performed at the Flow Cytometry Resource Facility of the IU Simon Comprehensive Cancer Center (National Cancer Institute [NCI] grant P30 CA082709). Flow cytometry was supported in part by a Center of Excellence Grant in Molecular Hematology (PO1 DK090948). Sequencing analysis was carried out in the Center for Medical Genomics at Indiana University School of Medicine, which is partially supported by the Indiana University Grand Challenges Precision Health Initiative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003eThis work was supported by the Indiana University Cooperative Center for Excellence in Hematology CCEH (U54 DK106846), the National Institute on Aging (AG046246), and the National Institute of Allergy and Infectious Diseases (AI128894).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest: \u003c/strong\u003eThe authors have no conflicts of interest to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e All murine studies were approved by the Indiana University School of Medicine Institutional Animal Care and Use Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate: \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication: \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material (data transparency): \u003c/strong\u003eThe accession number for the RNA-seq data reported in this paper is GEO: (TBD).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability: \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions: \u003c/strong\u003eAll authors made substantial contributions to this study. AMP conceived, designed, and performed studies, acquired and analyzed data, interpreted results, visualized the data and prepared the figures, and wrote the manuscript. PAP and CHS contributed to study design and methodology, performed studies, and acquired data. ES and YL performed RNA sequencing and analysis. LMP and CMO contributed to study conception and design and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMorrison SJ, Wandycz AM, Akashi K, Globerson A, Weissman IL. The aging of hematopoietic stem cells. \u003cem\u003eNat Med. \u003c/em\u003e1996;2(9):1011-1016.\u003c/li\u003e\n\u003cli\u003eRossi DJ, Bryder D, Zahn JM, et al. Cell intrinsic alterations underlie hematopoietic stem cell aging. \u003cem\u003eProc Natl Acad Sci U S A. \u003c/em\u003e2005;102(26):9194-9199.\u003c/li\u003e\n\u003cli\u003eLiang Y, Van Zant G, Szilvassy SJ. 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Examination of nuclear receptor expression in osteoblasts reveals Rorbeta as an important regulator of osteogenesis. \u003cem\u003eJ Bone Miner Res. \u003c/em\u003e2012;27(4):891-901.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"stem-cell-reviews-and-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"stcr","sideBox":"Learn more about [Stem Cell Reviews and Reports](https://www.springer.com/journal/12015)","snPcode":"12015","submissionUrl":"https://submission.nature.com/new-submission/12015/3","title":"Stem Cell Reviews and Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"hematopoietic stem cells (HSCs), hematopoiesis, HSC transplantation, cell survival","lastPublishedDoi":"10.21203/rs.3.rs-224253/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-224253/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAging of hematopoiesis is associated with increased frequency and clonality of hematopoietic stem cells (HSCs), along with functional compromise and myeloid bias, with donor age being a significant variable in survival after HSC transplantation. No clinical methods currently exist to enhance aged HSC function, and little is known regarding how aging affects molecular responses of HSCs to biological stimuli. Exposure of HSCs from young fish, mice, nonhuman primates, and humans to 16,16-dimethyl prostaglandin E\u003csub\u003e2\u003c/sub\u003e (dmPGE\u003csub\u003e2\u003c/sub\u003e) enhances transplantation, but the effect of dmPGE\u003csub\u003e2\u003c/sub\u003e on aged HSCs is unknown. Here we show that ex vivo pulse of bone marrow cells from young adult (3 mo) and aged (25 mo) mice with dmPGE\u003csub\u003e2\u003c/sub\u003e prior to serial competitive transplantation significantly enhanced long-term repopulation from aged grafts in primary and secondary transplantation (27% increase in chimerism) to a similar degree as young grafts (21% increase in chimerism; both p\u0026lt;0.05). RNA sequencing of phenotypically-isolated HSCs indicated that the molecular responses to dmPGE\u003csub\u003e2\u003c/sub\u003e are similar in young and old, including CREB1 activation and increased cell survival and homeostasis. Common genes within these pathways identified likely key mediators of HSC enhancement by dmPGE\u003csub\u003e2\u003c/sub\u003e and age-related signaling differences. HSC expression of the PGE\u003csub\u003e2\u003c/sub\u003e receptor EP4, implicated in HSC function, increased with age in both mRNA and surface protein. This work suggests that aging does not alter the major dmPGE\u003csub\u003e2\u003c/sub\u003e response pathways in HSCs which mediate enhancement of both young and old HSC function, with significant implications for expanding the therapeutic potential of elderly HSC transplantation.\u003c/p\u003e","manuscriptTitle":"Prostaglandin E2 Enhances Aged Hematopoietic Stem Cell Function","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-02-11 23:45:23","doi":"10.21203/rs.3.rs-224253/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revisions Needed","date":"2021-03-02T11:52:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Stem Cell Reviews and Reports","date":"2021-02-08T14:35:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-02-08T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-02-08T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-02-08T00:00:00+00:00","index":0,"fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"stem-cell-reviews-and-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"stcr","sideBox":"Learn more about [Stem Cell Reviews and Reports](https://www.springer.com/journal/12015)","snPcode":"12015","submissionUrl":"https://submission.nature.com/new-submission/12015/3","title":"Stem Cell Reviews and Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1a79b32a-4092-467d-840a-adf5a12bbcb5","owner":[],"postedDate":"February 11th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":2363836,"name":"Stem Cell \u0026 Developmental Cell Biology"}],"tags":[],"updatedAt":"2021-04-28T19:19:44+00:00","versionOfRecord":[],"versionCreatedAt":"2021-02-11 23:45:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-224253","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-224253","identity":"rs-224253","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}