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Aging-associated decrease in the histone acetyltransferase KAT6B is linked to altered hematopoietic stem cell differentiation

Open AccessPublished:January 31, 2020DOI:https://doi.org/10.1016/j.exphem.2020.01.014

      Highlights

      • Histone acetyltransferase Kat6b is highly expressed in hematopoietic stem cells
      • KAT6B expression is reduced in hematopoietic stem cells with aging
      • Reduced Kat6b causes decreased erythropoietic activity and increased myeloid differentiation
      Aged hematopoietic stem cells (HSCs) undergo biased lineage priming and differentiation toward production of myeloid cells. A comprehensive understanding of gene regulatory mechanisms causing HSC aging is needed to devise new strategies to sustainably improve immune function in aged individuals. Here, a focused short hairpin RNA screen of epigenetic factors reveals that the histone acetyltransferase Kat6b regulates myeloid cell production from hematopoietic progenitor cells. Within the stem and progenitor cell compartment, Kat6b is highly expressed in long-term (LT)–HSCs and is significantly decreased with aging at the transcript and protein levels. Knockdown of Kat6b in young LT-HSCs causes skewed production of myeloid cells at the expense of erythroid cells both in vitro and in vivo. Transcriptome analysis identifies enrichment of aging and macrophage-associated gene signatures alongside reduced expression of self-renewal and multilineage priming signatures. Together, our work identifies KAT6B as a novel epigenetic regulator of hematopoietic differentiation and a target to improve aged immune function.
      Aging involves progressive decline in many cellular systems, including the immune system. Elderly individuals are more susceptible to infections, leading to more frequent and severe illness [
      • Dorshkind K
      • Swain S
      Age-associated declines in immune system development and function: causes, consequences, and reversal.
      ]. With the global population of individuals aged 65 years and older expected to reach 1.6 billion by 2050 [
      • Gasteiger R
      • Janiga G
      • Stucht D
      • et al.
      An Aging World: 2015. International Population Reports.
      ], there is a pressing need to develop novel therapeutic strategies to ameliorate aging-associated decline in immune function.
      All mature blood and immune cells are derived from hematopoietic stem cells (HSCs). Changes in HSCs with aging, including increased frequency, enhanced differentiation toward myeloid cells, and reduction in regeneration capacity [
      • Verovskaya EV
      • Dellorusso PV
      • Passegué E
      Losing sense of self and surroundings: hematopoietic stem cell aging and leukemic transformation.
      ], contribute to aging-associated decline in immune function. Molecular features of aged HSCs include decline in mitochondrial function and epigenetic drift. A global increase in DNA methylation has been identified [
      • Beerman I
      • Bock C
      • Garrison BS
      • et al.
      Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging.
      ,
      • Sun D
      • Luo M
      • Jeong M
      • et al.
      Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal.
      ], as well as altered levels of histone H3 lysine 4 trimethylation (H3K4me3) and lysine 27 trimethylation (H3K27me3) in both aged murine and human HSCs [
      • Sun D
      • Luo M
      • Jeong M
      • et al.
      Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal.
      ,
      • Adelman ER
      • Huang H-T
      • Roisman A
      • et al.
      Aging human hematopoietic stem cells manifest profound epigenetic reprogramming of enhancers that may predispose to leukemia.
      ]. Moreover, diminished levels and polarity of histone H4 lysine 16 acetylation (H4K16ac) are associated with loss of regenerative capacity and myeloid lineage skewing of old long-term HSCs (LT-HSCs) [
      • Florian MC
      • Dörr K
      • Niebel A
      • et al.
      Cdc42 activity regulates hematopoietic stem cell aging and rejuvenation.
      ]. Although these studies support involvement of epigenetic regulatory processes in HSC aging, there remains a lack of comprehensive knowledge of the extent to which epigenetic alterations cause aging-associated changes in HSC function. The goal of this study was to identify epigenetic regulators that cause altered differentiation of HSCs in the context of aging. We report a functional screen to uncover novel epigenetic regulators of altered HSC differentiation with aging, identifying the lysine acetyltransferase Kat6b.
      KAT6B (MORF) belongs to the MYST family of histone acetyltransferases and is responsible for acetylation of the lysine 23 residue of histone H3 (H3K23ac) [
      • Simó-Riudalbas L
      • Pérez-Salvia M
      • Setien F
      • et al.
      KAT6B is a tumor suppressor histone H3 lysine 23 acetyltransferase undergoing genomic loss in small cell lung cancer.
      ]. Other members of the MYST family, KAT6A (MOZ) and KAT8 (MOF), have known functional roles in hematopoiesis. KAT6A, which catalyzes acetylation of lysine 9 (H3K9ac) and lysine 14 (H3K14ac) residues [
      • Huang F
      • Abmayr SM
      • Workman JL
      Regulation of KAT6 acetyltransferases and their roles in cell cycle progression, stem cell maintenance, and human disease.
      ], is critical for the emergence and maintenance of HSCs [
      • Katsumoto T
      • Aikawa Y
      • Iwama A
      • et al.
      MOZ is essential for maintenance of hematopoietic stem cells.
      ,
      • Perez-Campo FM
      • Borrow J
      • Kouskoff V
      • Lacaud G
      The histone acetyl transferase activity of monocytic leukemia zinc finger is critical for the proliferation of hematopoietic precursors.
      ,
      • Sheikh BN
      • Yang Y
      • Schreuder J
      • et al.
      MOZ (KAT6A) is essential for the maintenance of classically defined adult hematopoietic stem cells.
      ]. KAT8, which catalyzes acetylation of H4K16ac, is critical for adult but not early fetal hematopoiesis [
      • Valerio DG
      • Xu H
      • Eisold ME
      • Woolthuis CM
      • Pandita TK
      • Armstrong SA
      Histone acetyltransferase activity of MOF is required for adult but not early fetal hematopoiesis in mice.
      ]. Here, we investigate and describe a novel role for KAT6B in lineage differentiation of phenotypic LT-HSCs.

      Methods

      Experimental animals

      Young (2–4 months) and old (20–23 months) female C57BL/6J and B6.SJL-PtprcaPepcb/BoyJ (B6.CD45.1) were obtained from, and aged within, The Jackson Laboratory. All experiments were approved by The Jackson Laboratory's Institutional Animal Care and Use Committee (IACUC).

      Lentiviral supernatant

      The pLKO.1 short hairpin (shRNA) expression plasmids (Sigma; Supplemental Table E1, online only, available at www.exphem.org) were modified by cloning in the green fluorescent protein (GFP) cassette from pLKO.3G, a gift from Christophe Benoist and Diane Mathis (Addgene) (primers listed in Supplemental Table E2, online only, available at www.exphem.org). The shRNA expression plasmids, RC-CMV-Rev1b, HDM-Hgpm2 (gag-pol), HDM-tat1b, HDM-VSV-G were transfected into HEK-293T cells (ATCC) using CalPhos Mammalian Transfection Kit (Takara Bio). Media was changed after 24 hours and virus was collected after 48 hours. Virus was titered using NIH/3T3 cells (ATCC).
      Supplemental Table 1shRNA Plasmids
      Target Gene SymbolTarget Gene NameClone Number (Sigma)
      NTCMISSION® pLKO.1-puro Non-Target shRNA Control Plasmid DNA or TRC2 pLKO.5-puro Non-Mammalian shRNA Control Plasmid DNASHC202 or SHC016
      Kat6b sh1K(lysine) acetyltransferase 6BTRCN0000287544
      Kat6b sh2K(lysine) acetyltransferase 6BTRCN0000039341
      CrebbpCREB binding proteinTRCN0000012725
      Rnf40ring finger protein 40TRCN0000041048
      Kmt5alysine methyltransferase 5ATRCN0000241070
      Atxn7l3ataxin 7-like 3TRCN0000251735
      Tbl1xtransducin (beta)-like 1 X-linkedTRCN0000109355
      Atxn7l1ataxin 7-like 1TRCN0000348933
      NdnnecdinTRCN0000312951
      Ezh1enhancer of zeste 1 polycomb repressive complex 2 subunitTRCN0000317140
      Kdm5blysine (K)-specific demethylase 5BTRCN0000113491
      Ncor2nuclear receptor co-repressor 2TRCN0000095283
      Suv39h2suppressor of variegation 3–9 2TRCN0000353741
      Prdm16PR domain containing 16TRCN0000075459
      Cxxc1CXXC finger 1 (PHD domain)TRCN0000257088
      Dach1dachshund family transcription factor 1TRCN0000433533
      Supplemental Table 2Primer Sequences
      TargetPurposeForward Primer (5’)Reverse Primer (5’)
      eGFPCloningGCAGTCGGCTCCCTCGTTGACCGACTGCACGCTCCCGTCCTCGATGTT
      B2mReal-time PCRCAGTATGTTCGGCTTCCCATTCTTCTGGTGCTTGTCTCACTGA
      Kat6b set 1Real-time PCRReferencesGTCGTAAACGGTGGGAATGCTTTCCTCAGAA
      Kat6b set 2Real-time PCRAGCTTCTGTTTGGGGACTAAAGGTGTCCACTACTGCCACAATC
      CrebbpReal-time PCRCCAAACGAGCCAAACTCAGCTTTGGACGCAGCATCTGGAA
      Rnf40Real-time PCRGACCCTACGGTGACGGAAGTCCAGTAGCGGTTGACGATGT
      Kmt5aReal-time PCRCAGACCAAACTGCACGACATCCTTGCTTCGGTCCCCATAGT
      Atxn7l3Real-time PCRAAGGAGTGTGTTTGCCCCAAAGACTTGGATCTTCGAGGGGA
      Tbl1xReal-time PCRCACAAGTTGCACGGCTCGACTGTGGCTTTACTCGGTGG
      Atxn7l1Real-time PCRCAAGCCCTAGAACAGCGTCAAGCAAGTTTCTGCCCTCACA
      NdnReal-time PCRCCAGAGGAGCTAGACAGGGTACGCCTGGGGATCTTTCTTG
      Ezh1Real-time PCRCAACACTTCCCGCTGCATTCGGCGCTTCCGTTTTCTTGTT
      Kdm5bReal-time PCRCGAGCTGGGAAGAGTTCGCATCACAAGCGAATGGTGGCT
      Ncor2Real-time PCRCCTGGTGGAAGTTCGTGGACGCTCCTGAGACCGTTCACTC
      Suv39h2Real-time PCRGACCGCGCCAGTTTGAATGCTAAAGGTGGGCCCTCCAAG
      Prdm16Real-time PCRATGGATCCCATCTACAGGGTACATTGCATATGCCTCCGGGT
      Cxxc1Real-time PCRGATGATCACGGCCTACCCTGGCCGTTTGTACCTCTCCTCC
      Dach1Real-time PCRGGCTTTCGACCTGTTCCTGAAGGAAGTTCCAGTCCAACACT

      Primary cell isolation

      Femurs, tibiae, and iliac crests were harvested to isolate hematopoietic cells from the bone marrow (BM). Ficoll-Paque (GE Healthcare) centrifugation was used to isolate BM mononuclear cells (MNCs). MNCs were stained with fluorochrome-conjugated antibodies from BioLegend, eBiosciences or BD Biosciences: c-Kit (clone 2B8), CD48 (clone HM48-1), CD150 (clone TC15-12F12.2), Sca-1 (clone D7), FLT3 (clone A2F10), mature lineage (Lin) marker mix (B220 (clone RA3-6B2), CD11b (clone M1/70), CD4 (clone RM4-5), CD8a (clone 53–67), Ter-119 (clone TER-119), Gr-1 (clone RB6-8C5), CD5 (clone 53–7.3) and viability stain propidium iodide (PI). Cells were sorted on a FACSAria (BD Biosciences) as follows: LT-HSC (Lin Sca+ c-Kit+ Flt3 CD150+ CD48) and multipotent progenitor (MPP4) cells (Lin Sca+ c-Kit+ Flt3+ CD150).

      Transduction of LT-HSC and MPP4 cells

      LT-HSCs were resuspended in serum-free expansion medium II (SFEM II) (StemCell Technologies) supplemented with growth factors described previously [
      • Holmfeldt P
      • Ganuza M
      • Marathe H
      • et al.
      Functional screen identifies regulators of murine hematopoietic stem cell repopulation.
      ]: stem cell factor (SCF; 10 ng/mL), thrombopoietin (TPO; 20 ng/mL), insulin-like growth factor 2 (IGF2; 20 ng/mL), and fibroblast growth factor (FGF; 10 ng/mL) (BioLegend or StemCell Technologies) along with 5 μg/mL polybrene (Sigma) and 1,000 MOI lentiviral supernatant. Cells were spun at 2,500 rpm for 60 min then cultured at 37°C and 5% CO2 for 48 hours. Transduced GFP+ cells were sorted on a FACSAria (BD Biosciences). MPP4 cells were transduced as described earlier in media containing Iscove's Modified Dulbecco's Medium (IMDM) plus 10% fetal bovine serum (FBS), interleukin-3 (IL-3, 10 ng/mL), IL-6, 10 μg/mL, IL-7, 20 ng/μL), SCF (100 ng/mL), and leukemia inhibitory factor (LIF, 20 ng/mL) (Peprotech).

      Colony forming unit assays

      For B-lymphoid colony-forming unit (CFU) assays, 100 GFP+ cells from transduced MPP4 cells were plated in Methocult M3630 (StemCell Technologies) supplemented with FMS-like tyrosine kinase like 3 ligand (FLT3L; 25 ng/mL) and SCF (50 ng/mL) (Peprotech). For myeloid CFU assays, 100 GFP+ cells from transduced MPP4 cells or 200 GFP+ cells from transduced LT-HSCs were plated in Methocult GF M3434 (StemCell Technologies) and cultured at 37°C and 5% CO2. Scoring of colonies was done between days 7 and 10 using a Nikon Eclipse TS100 inverted microscope. CFU cloning efficiency was calculated as the sum of the myeloid and B-lymphoid colonies divided by the sum of the myeloid and B-lymphoid colonies in the nontargeting control (NTC) group.

      Real-time PCR

      Real-time polymerase chain reaction (PCR) testing was performed using RT2 SYBR Green ROX qPCR Mastermix (Qiagen) using the Viaa7 or QuantStudio 7 Flex (Applied Biosystems). Primer sequences are in Supplemental Table E2 (online only, available at www.exphem.org).

      Immunofluorescence staining of LT-HSCs

      Sorted LT-HSCs were seeded on retronectin-coated coverslips in SFEM II supplemented with SCF (10 ng/mL), TPO (20 ng/μL), IGF2 (20 ng/μL), and FGF (10 ng/μL) (BioLegend or StemCell Technologies) for 2 hours, then fixed in 4% paraformaldehyde (PFA). Cells were washed with phosphate buffered saline (PBS), permeabilized with 0.2% Triton X-100 in PBS for 20 min and blocked with 10% goat serum (ThermoFisher Scientific) for 20 min. Cells were stained with α-KAT6B (NBP1-92036; Novus Biologicals) for 1 hour at room temperature. For secondary antibody, cells were stained with α-rabbit conjugated with Alexa-568 (A-11036; ThermoFisher Scientific) for 1 hour. For antibody blocking experiments, control peptides and peptides encoding the immunogen for the KAT6B antibody (GenScript) were incubated overnight at 4 °C with α-KAT6B before staining as described earlier. Coverslips were mounted on slides with Gold Antifade with DAPI (4′,6-diamidino-2-phenylindole). Imaging was performed with Leica SP8 confocal microscope. Z-stack images were summed and quantification of individual fluorescence intensities was performed by Fiji software [
      • Schindelin J
      • Arganda-Carreras I
      • Frise E
      • et al.
      Fiji: an open-source platform for biological-image analysis.
      ]. Scale bars in images represent 5 μm.

      In vivo transplantation

      A total of 200–350 transduced GFP+ cells were combined with 5 × 105 MNCs from B6.CD45.1 mice and retro-orbitally injected into recipient B6.CD45.1 mice after 10 G. Peripheral blood (PB) from recipient mice was analyzed by flow cytometry 1 month after transplant using CD45.1 (clone A201.7 or clone A20), CD45.2 (clone 104), B220 (clone RA3-6B2), CD3e (clone 145-2C11), CD11b (clone M1/70), Ly6g (clone 1A8), Ly6c (clone HK1.4), Ter-119 (clone TER-119), GR1 (clone RB6-8C5), CD4 (clone GK1.5), CD8a (clone 53–6.72), and CD41 (clone MWReg30) (all BioLegend or BD Biosciences). PB was analyzed on a FACSymphony A5 (BD Biosciences), and data were analyzed using FlowJo software (FlowJo, LLC).

      RNA sequencing

      Transduced GFP+ LT-HSCs from 3 independent biological replicates were sorted directly into RLT buffer (Qiagen). Total RNA was isolated from cells using the RNeasy Micro kit (Qiagen). Sample quality was assessed using the Nanodrop 2000 spectrophotometer (ThermoFisher Scientific) and the RNA 6000 Pico LabChip assay (Agilent Technologies). Libraries were prepared by the Genome Technologies core facility at The Jackson Laboratory using the Ovation RNA-seq System V2 (NuGEN Technologies) and Hyper Prep Kit (Kapa Biosystems). Libraries were checked for quality and concentration using the D5000 ScreenTape assay (Agilent Technologies) and quantitative PCR (Kapa Biosystems), according to the manufacturers’ instructions. Libraries were pooled and sequenced 75 bp single-end on the NextSeq 500 (Illumina) using NextSeq High Output Kit v2.5 reagents. Raw and processed data were deposited in the Gene Expression Omnibus (GEO accession GSE133304).

      RNA sequencing analysis

      Trimmed alignment files (with trimmed base quality value <30, and 70% of read bases surpassing that threshold) were processed using the RSEM (v1.2.12; RNA-Seq by Expectation-Maximization) software [
      • Li B
      • Dewey CN
      RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.
      ] and the Mus Musculus reference GRCm38. Alignment was completed using Bowtie 2 (v2.2.0) [
      • Langmead B
      • Salzberg SL
      Fast gapped-read alignment with Bowtie 2.
      ,
      • Li H
      • Handsaker B
      • Wysoker A
      • et al.
      The sequence alignment/map format and SAMtools.
      ] and processed using SAMtools (v0.1.18). Fragment length mean was set to 280 and standard deviation to 50. Expected read counts per gene produced by RSEM were rounded to integer values, filtered to include only genes that have at least two samples within a sample group having a count per million reads > 1.0, and were passed to edgeR (v3.5.3) [
      • Robinson MD
      • Mccarthy DJ
      • Smyth GK
      edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
      ] for differential expression analysis. The negative binomial conditional common likelihood was maximized to estimate a common dispersion value across all genes. Exact tests were used to elucidate statistical differences between the two sample groups of negative binomially distributed counts producing p values per test. Benjamini and Hochberg's algorithm was used to control the false discovery rate (FDR). Features with an FDR-adjusted p value < 0.05 were declared significantly differentially expressed. Gene set enrichment analysis (GSEA) [
      • Daly MJ
      • Patterson N
      • Mesirov JP
      PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.
      ,
      • Subramanian A
      • Subramanian A
      • Tamayo P
      • et al.
      Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
      ] was performed using previously published old LT-HSC RNA sequencing (RNA-seq) data [
      • Sun D
      • Luo M
      • Jeong M
      • et al.
      Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal.
      ] and previously defined gene signatures representing HSCs [
      • Chambers SM
      • Boles NC
      • Lin K-YK
      • et al.
      Hematopoietic fingerprints: an expression database of stem cells and their progeny.
      ], the self-renewal program [
      • Krivtsov AV
      • Twomey D
      • Feng Z
      • et al.
      Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9.
      ], hematopoietic progenitor cell populations (lymphoid [common lymphoid progenitor, CLP], granulocyte-macrophage (preGM) and erythroid-megakaryocyte (preMegE, preCFU-E, MkP) [
      • Sanjuan-Pla A
      • Macaulay IC
      • Jensen CT
      • et al.
      Platelet-biased stem cells reside at the apex of the haematopoietic stem-cell hierarchy.
      ], and mature hematopoietic cell populations (M1 and M2 macrophages, monocytes, granulocytes, erythrocytes, CD4+ naïve T cells, CD8+ naïve and activated T cells, B cells, and NK cells) [
      • Chambers SM
      • Boles NC
      • Lin K-YK
      • et al.
      Hematopoietic fingerprints: an expression database of stem cells and their progeny.
      ,
      • Engler JR
      • Robinson AE
      • Smirnov I
      • Hodgson JG
      • Berger MS
      Increased Microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas.
      ,
      • Mantovani A
      • Sozzani S
      • Locati M
      • Allavena P
      • Sica A
      Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes.
      ,
      • Martinez FO
      • Gordon S
      • Locati M
      • Mantovani A
      Transcriptional profiling of the human monocyte-to-macrophage differentiation and polarization: new molecules and patterns of gene expression.
      ] (Supplemental Table E3; online only, available at www.exphem.org).

      Statistical analysis

      Sample groups were compared using an unpaired t test, Mann-Whitney test, one-way analysis of variance (ANOVA), and Holm-Sidak's multiple comparisons test, or two-way ANOVA and Dunnett's multiple comparisons test as indicated in figure legends. Prism (GraphPad Software) was used for statistical calculations and graphing.

      Results

      An shRNA screen identifies Kat6b as a novel regulator of hematopoietic differentiation

      To identify epigenetic regulators with a functional role in hematopoietic stem and progenitor cell differentiation, we conducted an in vitro shRNA screen. To derive candidates for this screen, we used gene expression commons (GEXC) [
      • Seita J
      • Sahoo D
      • Rossi DJ
      • et al.
      Gene expression commons: an open platform for absolute gene expression profiling.
      ] to define 2,766 differentially expressed genes between granulocyte-macrophage progenitors (GMPs; Lin Sca c-Kit+ CD34+ FcgRII/III+) and CLPs (Lin c-Kitint Flt3+ IL7Ra+ CD27+ Ly6d), which are committed progenitors for the myeloid and lymphoid lineages, respectively (Figure 1A) [
      • Motonari K
      Lymphoid and myeloid lineage commintment in multipotent hematopoietic progenitors.
      ]. Among these 2,766 genes, gene ontology (GO) enrichment analysis of Reactome pathways [
      • Mi H
      • Huang X
      • Muruganujan A
      • et al.
      PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.
      ,
      • Ashburner M
      • Ball CA
      • Blake JA
      • et al.
      Gene ontology: tool for the unification of biology.
      ] revealed significant enrichment of chromatin-modifying enzymes (Figure 1B). The 40 enriched genes encoding chromatin-modifying enzymes were further subset to 30 genes based on overlap with the GO annotation “regulation of gene expression” (GO:0010468) (Supplemental Figure E1A; online only, available at www.exphem.org). Lastly, this gene list was filtered to include those with commercially available shRNA constructs with verified knockdown in murine cell lines, resulting in 16 genes (Supplemental Table E4; online only, available at www.exphem.org). To begin functional screening, shRNA expression plasmids for 6 of these 16 genes were obtained. In addition, shRNA constructs were obtained for eight genes hypothesized to regulate lineage differentiation using a candidate gene approach (Supplemental Table E5; online only, available at www.exphem.org). After cloning, we validated reduced target gene expression from each of these shRNA constructs in the murine 3T3 cells (Supplemental Figure E1B; online only, available at www.exphem.org).
      Figure 1
      Figure 1Functional shRNA screen for epigenetic regulators of myeloid versus B-lymphoid differentiation identifies Kat6b. (A) Hierarchy of hematopoietic differentiation showing cellular states leading to mature myeloid and lymphoid cells. (B) Schematic of candidate selection criteria to identify chromatin regulatory genes involved in myeloid versus B-lymphoid differentiation of hematopoietic stem and progenitor cells. (C) Schematic of experimental design to test epigenetic regulatory gene candidates using shRNA-mediated knockdown in lymphoid-primed MPP4 and CFU assays. (D) (top panel) Frequency of myeloid and B-lymphoid colonies out of total colonies and (bottom panel) CFU cloning efficiency calculated as the total number of myeloid and B-lymphoid colonies after shRNA knockdown of the indicated target genes divided by the total number of myeloid and B-lymphoid colonies in NTC. Bars represent mean ± SEM of n ≥ 2 biological replicates. *p < 0.05; **p < 0.01; ***p < 0.001 by two-way ANOVA and Dunnett's multiple comparisons test or one-way ANOVA and Holm-Sidak's multiple comparisons test.
      Supplemental Table 4Sixteen Chromatin Regulatory Genes for shRNA Screening Identified Using Unbiased Differential Expression Approach
      Gene SymbolGene Name
      Kat6bK(lysine) acetyltransferase 6B
      Kmt5alysine methyltransferase 5A
      Tbl1xtransducin (beta)-like 1 X-linked
      Kdm5blysine (K)-specific demethylase 5B
      Ncor2nuclear receptor co-repressor 2
      Suv39h2suppressor of variegation 3–9 2
      Mta3metastasis associated 3
      Carm1coactivator-associated arginine methyltransferase 1
      Dot1lDOT1-like, histone H3 methyltransferase (S. cerevisiae)
      Kmt2elysine (K)-specific methyltransferase 2E
      Arid1aAT rich interactive domain 1A (SWI-like)
      Kdm5clysine(K)-specific demethylase 5C
      Smarcc2SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily c, member 2
      Sap30lSAP30-like
      Jmjd6jumonji domain containing 6
      Padi2peptidyl arginine deiminase, type II
      Supplemental Table 5Eight Chromatin Regulatory Genes for shRNA Screening Identified Using Candidate Gene Approach
      Gene SymbolGene Name
      Rnf40ring finger protein 40
      Atxn7l3ataxin 7-like 3
      Prdm16PR domain containing 16
      Cxxc1CXXC finger 1 (PHD domain)
      Dach1dachshund family transcription factor 1
      Atxn7l1ataxin 7-like 1
      Ndnnecdin
      Ezh1enhancer of zeste 1 polycomb repressive complex 2 subunit
      Our in vitro screen (Figure 1C) used MPP4 cells rather than purified LT-HSCs because MPP4 cells have both myeloid and lymphoid differentiation potential (Figure 1A) [
      • Pietras EM
      • Reynaud D
      • Kang Y-A
      • et al.
      Functionally distinct subsets of lineage-biased multipotent progenitors control blood production in normal and regenerative conditions.
      ] and, in contrast to LT-HSCs, have efficient clonal in vitro differentiation capacity giving rise to both myeloid and lymphoid cells [
      • Young K
      • Borikar S
      • Bell R
      • Kuffler L
      • Philip V
      • Trowbridge JJ
      Progressive alterations in multipotent hematopoietic progenitors underlie lymphoid cell loss in aging.
      ]. Relative to NTC, we found that knockdown of our positive control, Crebbp, resulted in a near-complete loss of CFU capacity and the residual colonies that formed were predominantly myeloid (Figure 1D), consistent with the expected phenotype of Crebbp loss [
      • Chan W-I
      • Hannah RL
      • Dawson MA
      • et al.
      The transcriptional coactivator Cbp regulates self-renewal and differentiation in adult hematopoietic stem cells.
      ]. In two out of the 14 shRNA constructs evaluated, Rnf40 (ring finger protein 40) and Kat6b, we observed a significant increase in the proportion of myeloid relative to B-lymphoid colonies (Figure 1D, top panel). Of these, only knockdown of Kat6b was found not to alter overall cloning efficiency (Figure 1D, bottom panel) and was pursued as a candidate epigenetic regulator of hematopoietic stem and progenitor cell differentiation.

      KAT6B decreases at the transcript and protein level in old LT-HSCs

      Because the goal of this study was to identify epigenetic regulators that cause altered differentiation of HSCs in the context of aging, we sought to determine whether Kat6b is expressed in phenotypic HSCs and whether this expression is altered with aging. We isolated LT-HSCs (Lin Sca+ c-Kit+ Flt3 CD150+ CD48) and MPP4 cells (Lin Sca+ c-Kit+ Flt3+ CD150) by FACS from young (2–4 month) and old (20–23 month) mice. By real-time PCR, we found that the Kat6b transcript is expressed in LT-HSCs and that its expression decreases 2.8-fold with age in LT-HSCs but not in MPP4 cells (Figure 2A). This is consistent with previous studies finding a decrease in Kat6b expression in aged murine LT-HSCs [
      • Sun D
      • Luo M
      • Jeong M
      • et al.
      Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal.
      ] and a decrease in KAT6B expression in aged human HSCs [
      • Adelman ER
      • Huang H-T
      • Roisman A
      • et al.
      Aging human hematopoietic stem cells manifest profound epigenetic reprogramming of enhancers that may predispose to leukemia.
      ]. To analyze KAT6B at the protein level, we immunostained LT-HSCs from young and old mice with a KAT6B antibody (Figure 2B; Supplemental Figure E2, online only, available at www.exphem.org). We found that KAT6B expression in LT-HSCs from old mice was significantly lower than in young mice (Figure 2C). Together, our results indicate that KAT6B is significantly decreased at both the transcript and protein levels in old LT-HSCs.
      Figure 2
      Figure 2KAT6B is decreased in old LT-HSCs. (A) Relative expression of Kat6b in LT-HSCs and MPP4 cells isolated from young (2–4 month) and old (20–23 month) mice. Bars represent mean ± SEM of n ≥ 3 biological replicates. *p < 0.05 by unpaired t test. (B) Representative immunofluorescence images of KAT6B and DAPI in LT-HSCs isolated from young and old mice. Scale bar equals 5 um. (C) Violin plots of mean fluorescence intensity (MFI) of KAT6B in LT-HSCs isolated from young and old mice. Solid lines indicate median and dotted lines indicate quartiles. Data points include n = 17–64 individual cells sampled from n = 4 biological replicate animals. ***p < 0.001 by unpaired t test.

      Knockdown of Kat6b in phenotypic LT-HSCs causes reduced erythropoietic activity in vitro

      To evaluate the functional consequence of reduced expression of Kat6b as identified in old LT-HSCs, we used a shRNA knockdown approach. LT-HSCs isolated from young mice were transduced with lentivirus containing NTC or a Kat6b shRNA expression plasmid (Figure 3A) and plated into in vitro myeloerythroid differentiation CFU assays. From the resultant colonies, we determined that Kat6b transcript was reduced by 4.8-fold (Figure 3B). The total number of colonies was not significantly altered compared with NTC (Figure 3C); however, differences were identified with respect to colony composition. On knockdown of Kat6b, we found a significant increase in the number of granulocyte-macrophage (CFU-GM) colonies, a significant decrease in the number of granulocyte-erythrocyte-macrophage-megakaryocyte (CFU-GEMM) colonies, and no change in the number of macrophage-only (CFU-M) colonies (Figure 3D). These phenotypes were replicated using a second, independent hairpin against Kat6b (Supplemental Figure E3; online only, available at www.exphem.org). Our results indicate that knockdown of Kat6b results in reduced erythropoietic activity and increased myeloid differentiation from phenotypic LT-HSCs in vitro.
      Figure 3
      Figure 3Kat6b knockdown results in loss of erythropoietic activity from phenotypic LT-HSCs in vitro. (A) Schematic of experimental design to knockdown Kat6b in LT-HSCs and assess differentiation in the myeloid CFU assay. (B) Relative expression of Kat6b in colonies after shRNA-mediated knockdown of Kat6b or NTC. Bars represent mean ± SEM of n ≥ 3 biological replicates performed in independent experiments. ***p < 0.001 by unpaired t test. (C) Total number of colonies produced and (D) colony subtype distribution from 200 GFP+ cells after transduction of LT-HSCs. Dots denote biological replicates and bars represent mean ± SEM of n ≥ 3 biological replicates performed in independent experiments. *p < 0.05; ***p < 0.001 by unpaired t test.

      Knockdown of Kat6b in phenotypic LT-HSCs causes increased myeloid differentiation and reduced erythropoietic activity in vivo

      To evaluate the functional consequence of reduced levels of Kat6b in LT-HSCs in vivo, we transduced phenotypic LT-HSCs with Kat6b knockdown or NTC and transplanted GFP+ cells into lethally irradiated B6.CD45.1 recipient mice (Figure 4A). In total, 15 recipient mice were transplanted with NTC-transduced cells and 16 recipient mice were transplanted with Kat6b sh1-transduced cells. From these, 7 out of 15 (46%) and 8 out of 16 (50%) were found to have multilineage engraftment greater than a threshold of 0.1% donor-derived PB cells at 1 month after transplant. Donor-derived engraftment was not significantly different between NTC and Kat6b sh1 (Figure 4B). However, mice transplanted with Kat6b knockdown cells had a significant increase in the proportion of donor-derived myeloid cells in the PB compared with NTC (Figure 4C). In addition, there was a significant decrease in donor-derived erythroid cells in the PB of mice transplanted with Kat6b knockdown cells compared with NTC (Figure 4D). A trend toward decreased frequency of donor-derived B and T lymphocytes in Kat6b knockdown compared with NTC did not reach statistical significance (Figure 4E, F). Together, these results indicate that knockdown of Kat6b causes reduced erythropoietic activity and increased myeloid differentiation in vivo without significantly altering repopulation capacity.
      Figure 4
      Figure 4Kat6b knockdown alters myeloid and erythroid differentiation of phenotypic LT-HSCs in vivo. (A) Schematic of experimental design to knockdown Kat6b in LT-HSCs and assess hematopoietic reconstitution in lethally irradiated recipient mice compared with NTC-transduced LT-HSCs. (B) Frequency of donor-derived cells (CD45.2+ GFP+) in the PB of recipient mice, (C) myeloid cells (CD11b+) within donor-derived PB cells (CD45.2+ GFP+), and (D) erythroid cells (Ter119+) within donor-derived PB cells (GFP+) 1 month after transplant. (E) Frequency of B cells (B220+) and (F) T cells (CD3+) within donor-derived PB cells 1 month after transplant. Each dot represents one recipient mouse. Lines represent mean ± SEM of n ≥ 7 biological replicates. *p < 0.05; ***p < 0.001 by Mann-Whitney test.

      Knockdown of Kat6b in LT-HSCs promotes expression of aging- and inflammation-associated gene signatures

      To investigate the molecular mechanisms underlying altered differentiation after Kat6b knockdown, we transduced LT-HSCs with NTC or Kat6b sh1 and performed RNA-seq. Unsupervised clustering separated NTC and Kat6b knockdown samples (Figure 5A). A total of 252 significantly differentially expressed genes were identified, out of which 127 genes were upregulated and 125 genes were downregulated in Kat6b knockdown compared with NTC (Figure 5B). No other KAT histone lysine acetyltransferases were found to be significantly up- or downregulated after Kat6b knockdown (Supplemental Figure E4; online only, available at www.exphem.com), supporting minimal off-target effects of our shRNA construct on highly related genes and a lack of compensatory upregulation of other family members in this setting.
      Figure 5
      Figure 5Kat6b knockdown alters gene expression programs critical for multilineage differentiation. (A) PCA plot showing unsupervised clustering of gene expression profiles from Kat6b sh1 (n = 3) and NTC (n = 3). Each color represents a set of biological replicate samples. (B) Volcano plot showing log fold changes of genes against –log10 of FDR. Points in red highlight genes with FDR < 0.05. (C) Intersection of gene signatures upregulated in young versus old LT-HSCs (top) and GSEA of NTC and Kat6b sh1 RNA-seq data using this derived signature (bottom). (D) Intersection of gene signatures upregulated in old versus young LT-HSCs (top) and GSEA of NTC and Kat6b sh1 RNA-seq data using this derived signature (bottom). (E) Top GO terms enriched in genes found to be significantly differentially expressed in Kat6b sh1 versus NTC (fold change > 2 and p < 0.05). (F) Normalized enrichment score from GSEA analysis of the indicated datasets in Kat6b sh1 versus NTC. Black bars indicate FDR < 0.05, white bars indicate FDR > 0.05.
      Supplemental Figure 1
      Supplemental Figure 1Validation of shRNA constructs used for screening epigenetic regulators of myeloid versus B-lymphoid differentiation. (A) GO enrichment analysis of 2,766 genes identified as differentially expressed between GMP versus CLP. (B) Relative expression of shRNA target genes following knockdown in NIH/3T3 cells. Bars represent mean of n = 3 technical replicates.
      Supplemental Figure 2
      Supplemental Figure 2KAT6B antibody evaluation. (A) Representative immunofluorescence images of KAT6B and DAPI in hematopoietic stem and progenitor cells. KAT6B antibody was pre-incubated with a control, non-specific peptide or the immunizing KAT6B peptide. (B) Frequency of hematopoietic stem and progenitor (LSK) cells with KAT6B nuclear staining, in control or immunizing peptide pre-incubation conditions. Bars represent mean ± SEM of n = 30–40 individual cells. ***p < 0.001 by unpaired t test.
      Supplemental Figure 3
      Supplemental Figure 3Kat6b knockdown results in reduced erythropoietic activity from phenotypic LT-HSCs in vitro. (A) Relative expression of Kat6b in colonies following shRNA-mediated knockdown of Kat6b or NTC. Bars represent mean ± SEM of n ≥ 3 biological replicates performed in independent experiments. (B) Total number of colonies produced and (C) colony subtype distribution from 200 GFP+ cells post-transduction of LT-HSCs. CFU-M; macrophage, CFU-GM; granulocyte-macrophage, CFU-GEMM; granulocyte-erythrocyte-macrophage-megakaryocyte. Dots denote biological replicates and bars represent mean ± SEM of n ≥ 3 biological replicates performed in independent experiments. ***p < 0.001 by unpaired t test.
      Supplemental Figure 4
      Supplemental Figure 4Kat6b knockdown does not alter expression of other KAT family genes. (A) Logue fold change of Kat genes after knockdown of Kat6b or NTC. (B) Significance (p) value of differential expression between Kat6b sh1 knockdown and NTC.
      To test the hypothesis that Kat6b knockdown alters expression of gene programs associated with aging and differentiation of LT-HSCs, we performed GSEA [
      • Subramanian A
      • Subramanian A
      • Tamayo P
      • et al.
      Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
      ]. Comparing our RNA-seq data with a compiled LT-HSC aging gene signature (based on the intersection between published datasets by Sun et al. [2014] [
      • Sun D
      • Luo M
      • Jeong M
      • et al.
      Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal.
      ], Wahlestedt et al. [2013] [
      • Wahlestedt M
      • Norddahl GL
      • Sten G
      • et al.
      An epigenetic component of hematopoietic stem cell aging amenable to reprogramming into a young state.
      ], and Beerman et al. [2013] [
      • Beerman I
      • Bock C
      • Garrison BS
      • et al.
      Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging.
      ]) revealed that genes more highly expressed in young versus old LT-HSCs were significantly enriched in NTC versus Kat6b knockdown (Figure 5C). Conversely, genes more highly expressed in old versus young LT-HSCs were enriched in Kat6b knockdown versus NTC (Figure 5D).
      To further interrogate mechanisms underlying the identified change in differentiation of Kat6b knockdown cells, unbiased GO enrichment analysis was used. This analysis revealed significant alteration of signatures associated with inflammatory response, cytokine production, and defense response in Kat6b knockdown versus NTC cells (Figure 5E). We then compared our dataset with previously defined gene signatures representing HSCs [
      • Chambers SM
      • Boles NC
      • Lin K-YK
      • et al.
      Hematopoietic fingerprints: an expression database of stem cells and their progeny.
      ], the self-renewal program [
      • Krivtsov AV
      • Twomey D
      • Feng Z
      • et al.
      Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9.
      ], hematopoietic progenitor cell populations (lymphoid (CLP), granulocyte-macrophage (preGM) and erythroid-megakaryocyte (preMegE, preCFU-E, MkP) [
      • Sanjuan-Pla A
      • Macaulay IC
      • Jensen CT
      • et al.
      Platelet-biased stem cells reside at the apex of the haematopoietic stem-cell hierarchy.
      ], and mature hematopoietic cell populations (M1 and M2 macrophages, monocytes, granulocytes, erythrocytes, CD4+ naïve T cells, CD8+ naïve and activated T cells, B cells, and NK cells) [
      • Chambers SM
      • Boles NC
      • Lin K-YK
      • et al.
      Hematopoietic fingerprints: an expression database of stem cells and their progeny.
      ,
      • Engler JR
      • Robinson AE
      • Smirnov I
      • Hodgson JG
      • Berger MS
      Increased Microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas.
      ,
      • Mantovani A
      • Sozzani S
      • Locati M
      • Allavena P
      • Sica A
      Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes.
      ,
      • Martinez FO
      • Gordon S
      • Locati M
      • Mantovani A
      Transcriptional profiling of the human monocyte-to-macrophage differentiation and polarization: new molecules and patterns of gene expression.
      ] (Supplemental Table E3; online only, available at www.exphem.org). This analysis revealed that Kat6b knockdown resulted in a significant enrichment of an M1 macrophage signature, whereas NTC cells were enriched in HSC/self-renewal, preGM, monocyte, CLP, NK, and CD8+ naïve T-cell signatures (Figure 5F). Together, these data suggest that decreased expression of Kat6b in phenotypic LT-HSCs impairs multilineage differentiation, as supported by our in vitro and in vivo data, and permits a transcriptional program promoting myeloid differentiation that is associated with aging.

      Discussion

      In this study, by employing an shRNA-mediated screen of epigenetic regulators, we have discovered a novel role for Kat6b in the context of LT-HSC differentiation with relevance to aging. We have found that KAT6B decreases in old LT-HSCs at the transcript and protein levels. Knockdown of Kat6b resulted in an increase in the proportion of myeloid cells and decrease in the proportion of erythroid cells in vitro and in vivo. Transcriptome analysis performed immediately after Kat6b knockdown in LT-HSCs revealed that knockdown resulted in loss of multilineage priming signatures while gaining an expression signature associated with inflammation and M1 proinflammatory macrophages. Interestingly, it has been reported that Kat6b expression is reduced in macrophages under LPS stimulation, conditions that result in M1 activation [
      • Shukla S
      • Levine C
      • Sripathi RP
      • et al.
      The Kat in the HAT: the histone acetyl transferase Kat6b (MYST4) is downregulated in murine macrophages in response to LPS.
      ]. Whether decreased Kat6b results in priming toward myeloid, and in particular macrophage, differentiation or decreased Kat6b results in a transcriptional state primed for response to inflammation remains to be tested. Together, our results support that Kat6b functions as a regulator of hematopoietic differentiation and that decrease in Kat6b, as observed in aging, favors myeloid differentiation at the expense of erythroid differentiation.
      Our work builds on literature identifying the importance of the MYST family of acetyltransferases for hematopoietic function. KAT6A, a paralogue of KAT6B [
      • Simpson MA
      • Deshpande C
      • Dafou D
      • et al.
      De novo mutations of the gene encoding the histone acetyltransferase KAT6B cause genitopatellar syndrome.
      ], is critical for differentiation potential of HSCs [
      • Sheikh BN
      • Yang Y
      • Schreuder J
      • et al.
      MOZ (KAT6A) is essential for the maintenance of classically defined adult hematopoietic stem cells.
      ]. In vitro, Kat6a-deficient BM has reduced total number of colonies in CFU assays and no difference in colony subtypes [
      • Sheikh BN
      • Yang Y
      • Schreuder J
      • et al.
      MOZ (KAT6A) is essential for the maintenance of classically defined adult hematopoietic stem cells.
      ], whereas we found that Kat6b knockdown results in no change in total number of colonies and a reduction in erythroid-containing colonies. In vivo, conditional knockout of Kat6a resulted in impaired competitive repopulation capacity and increased ratio of myeloid to lymphoid differentiation [
      • Sheikh BN
      • Yang Y
      • Schreuder J
      • et al.
      MOZ (KAT6A) is essential for the maintenance of classically defined adult hematopoietic stem cells.
      ], whereas Kat6b knockdown resulted in increased frequency of myeloid cells and decreased frequency of red blood cells. Thus, we propose that KAT6A and KAT6B may have overlapping but distinct roles in hematopoiesis.
      In the context of our experiments, LT-HSCs were cultured under ex vivo conditions which have been reported to promote HSC self-renewal [
      • Holmfeldt P
      • Ganuza M
      • Marathe H
      • et al.
      Functional screen identifies regulators of murine hematopoietic stem cell repopulation.
      ]. However, this requirement for ex vivo culture for lentiviral transduction is also a caveat in the interpretation of our results. It is possible that some or all of the LT-HSCs seeded into ex vivo culture differentiate to progenitors during the 48-hour transduction culture period. Thus, the Kat6b knockdown phenotype we identified may be manifest in either HSCs or their progenitor progeny. We did not find any erythroid burst-forming unit (BFU-E)–only colonies in our in vitro CFU assays, which could be lost as a result of the effect of our culture conditions on erythroid differentiation potential of LT-HSCs.
      We speculate that therapeutically increasing levels of KAT6B in old HSCs may rejuvenate aspects of altered functionality, particularly with respect to lineage-balanced differentiation. A recent report by Adelman et al. (2019) [
      • Adelman ER
      • Huang H-T
      • Roisman A
      • et al.
      Aging human hematopoietic stem cells manifest profound epigenetic reprogramming of enhancers that may predispose to leukemia.
      ] reported a reduction in active enhancer-associated chromatin modifications at a KAT6B-proximal enhancer region in aged versus young human HSCs, suggesting that therapeutic approaches to increase enhancer activity may be a viable strategy to boost Kat6b expression in old HSCs. Further studies will be required to test whether restoring expression of Kat6b in old HSCs to levels found in young HSCs is sufficient to restore balanced lineage differentiation.

      Acknowledgments

      This work was supported by the National Institutes of Diabetes and Digestive and Kidney Diseases (NIDDK) Grants R01DK118072 and R56DK112947, the Ellison Medical Foundation New Scholar Award in Aging, and pilot funds from The Jackson Laboratory's Nathan Shock Center for Excellence in the Basic Biology of Aging (P30AG038070) (Dr. Trowbridge). Dr. Khokar was supported by Thurgood Marshall Tuition Scholarship from University of Maine. Dr. Young received support from T32HD007065, the Pyewacket Fund, and the American Society of Hematology (ASH) Scholar Award. We thank Tina Mujica, Jennifer SanMiguel, Olivia Erickson, Tara Murphy and Kaiden Waldron-Francis for technical help and experimental and laboratory support. We thank members of Trowbridge Laboratory, Christopher Baker, Luanne Peters, Derry Roopenian, and Dustin Updike for helpful discussions. We acknowledge Mingyang Lu and Vivek Kohar for computational assistance. We thank Genetic Engineering Technologies, Microscopy, Genome Technologies, and Flow Cytometry scientific services at The Jackson Laboratory for their contribution to these studies.

      Appendix. Supplementary materials

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