Screening for Genes That Regulate the Differentiation of Human Megakaryocytic Lineage Cells

Screening for genes that regulate the differentiation of human megakaryocytic lineage cells

Fangfang Zhua,b,1, Mingye Fengc, Rahul Sinhaa,b, Jun Seitaa,b,2, Yasuo Moria,b,3, and Irving L. Weissmana,b,d,e,1

aInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305; bLudwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, CA 94305; cDepartment of Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010; dDepartment of Pathology, Stanford University School of Medicine, Stanford, CA 94305; and eDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305

Contributed by Irving L. Weissman, July 27, 2018 (sent for review April 16, 2018; reviewed by Hongkui Deng and Lishan Su) Different combinations of transcription factors (TFs) function at genes, such as KLF1 (erythroid) and GABPA, FLI1, and RUNX1 each stage of hematopoiesis, leading to distinct expression patterns (megakaryocytic) (20, 21). They coordinate the prevention of pro- of lineage-specific genes. The identification of such regulators and genitor maintenance and the activation of downstream lineage- their functions in hematopoiesis remain largely unresolved. In this specific genes and the combination of some of those genes have study, we utilized screening approaches to study the transcriptional recently been reported to either convert human and murine fibro- regulators of megakaryocyte progenitor (MkP) generation, a key blasts to MkPs (22, 23) or promote megakaryocyte generation from step before platelet production. Promising candidate genes were human pluripotent stem cell (hPSC) lines (13). Although the results generated from a microarray platform gene expression commons are encouraging, identification of megakaryocyte-unique master and individually manipulated in human hematopoietic stem and regulators, especially those involved in MEP differentiation to MkP, progenitor cells (HSPCs). Deletion of some of the candidate genes will enable avenues for MkP and platelet generation and for (the hit genes) by CRISPR/Cas9 led to decreased MkP generation mechanistic study of their regulation. during HSPC differentiation, while more MkPs were produced when The CRISPR/Cas9 adaptive immune system, originally found some hit genes were overexpressed in HSPCs. We then demonstrated in bacteria to confer resistance to foreign genetic elements, was that overexpression of these genes can increase the frequency of demonstrated to mediate efficient and precise cleavage at en- mature megakaryocytic colonies by functional colony forming unit- dogenous genomic loci in human cells (24, 25). Single-guide CELL BIOLOGY megakaryocyte (CFU-Mk) assay and the release of platelets after in RNA (sgRNA) can be synthesized to target the specific geno- vitro maturation. Finally, we showed that the histone deacetylase mic loci, and Cas9 can induce DNA double-strand breaks inhibitors could also increase MkP differentiation, possibly by regu- (DSBs), which may generate insertion/deletion mutations and lating some of the newly identified TFs. Therefore, identification of such regulators will advance the understanding of basic mechanisms result in a loss-of-function allele. Therefore, using an sgRNA library to modify specific genomic loci by CRISPR/Cas9 suggests of HSPC differentiation and conceivably enable the generation and – maturation of megakaryocytes and platelets in vitro. a way to interrogate gene function on a large scale (26 28).

megakaryocyte progenitor | transcription factors | screening | gene editing Significance

erived from megakaryocytes, platelets play a major role in Megakaryocyte progenitors (MkPs), derived from hematopoietic Dhemostasis, thrombosis, inflammation, and vascular biology, stem cells (HSCs), play major roles in hemostasis, thrombosis, in- and platelet transfusions are frequently utilized to prevent throm- flammation, and vascular biology through generating platelets. bocytopenia, which can result from cancer therapy, trauma, sepsis, However, the regulatory factors involved in MkP differentiation as well as blood disorders (1). Unfortunately, the supply of these from HSCs are largely unknown. Here, we utilized a unique ge- short-lived platelets currently come with the high cost of main- nomic approach, including the microarray gene expression com- taining quality donors, the extensive testing protocols to prevent mons platform, CRISPR/Cas9-mediated gene deletion, lentivirus- contamination or recipient infection, and the generation of allo- mediated gene overexpression, as well as multicolor flow antibodies to the platelets which limit the donor pool. Another cytometry and functional assays, and identified 10 genes that are promising strategy is to transplant ex vivo-generated megakaryo- highly expressed in MkPs and required for and can promote MkP cytes (2–5), or megakaryocyte progenitor cells (MkPs), the direct generation from HSCs. In addition, we found inhibition of histone precursor for megakaryocyte, which have proliferation capacity and deacetylase activity increased MkP differentiation. Our results will engraftment potential and may therefore provide a better clinical not only shed light on the regulations of MkPs, but also facilitate alternative to standard transfusions,orasatargetforactivityin- efficient generation of MkPs and platelets for clinical applications. ducers (6, 7). Although MkPs were identified many years ago (7), the regulatory factors involved in their differentiation from hema- Author contributions: F.Z. and I.L.W. designed research; F.Z., M.F., R.S., and Y.M. performed research; J.S. contributed new reagents/analytic tools; F.Z. analyzed data; F.Z. topoietic stem and progenitor cells (HSPCs) are largely unknown. wrote the paper; and I.L.W. revised the paper. During hematopoiesis, transcription factors (TFs) control in- Reviewers: H.D., Peking University; and L.S., University of North Carolina at Chapel Hill. duction and maintenance of the expression of lineage-specific The authors declare no conflict of interest. genes and suppression of competing gene expression of other lineages (8–14). MkPs are originally derived from hematopoietic Published under the PNAS license. 1 stem cells (HSCs) through a well-documented stepwise differ- To whom correspondence may be addressed. Email: [email protected] or irv@stanford. edu. entiation (15, 16). To date, only a few TFs have been reported to 2Present addresses: Medical Sciences Innovation Hub Program, RIKEN, Nihonbashi, 103- be involved in this process, including AML1, FLI1, GABPA, 0027 Tokyo, Japan; and Center for Integrative Medical Sciences, RIKEN, Yokohama, 230- GATA1, RUNX1, NFE2, SCL, GATA2, MYB, and LMO2 (17– 0045 Kanagawa, Japan. 19). The bipotent megakaryocyte-erythroid progenitors (MEPs) 3Present address: Department of Medicine and Biosystemic Science, Kyushu University can directly give rise to MkPs and erythroid progenitors (EPs), Graduate School of Medical Sciences, 812-8582 Fukuoka City, Japan. which further develop into megakaryocytes and erythrocytes, re- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. spectively (20). MkPs and EPs share some TFs, including GATA1, 1073/pnas.1805434115/-/DCSupplemental. FOG1, SCL, and GFI1b, but also have several lineage-specific

www.pnas.org/cgi/doi/10.1073/pnas.1805434115 PNAS Latest Articles | 1of9 Downloaded by guest on October 1, 2021 + In this study, we report a strategy to identify regulators for MkP (EP/erythrocyte marker) cells, and CD71 (erythrocyte marker) generations by genetic manipulation. Sixty candidate genes were cells (15, 35) to determine the differentiation efficiency. Flow first generated from the gene expression commons (GEXC) cytometry analysis of cell mixtures after 7–10 d of differentiation microarray platform based on their high expression level in MkPs showed the five cytokines TPO, SCF, FLT3, IL3, and IL6 in andlowinMEPsandEPs.ThenCRISPR/Cas9-mediatedgene serum-free expansion medium II (SFEMII) can lead to the highest + + + knockout as a negative screen and lentiviral-mediated gene over- percentage of CD34 CD41 MkP cells and CD41 megakaryo- expression as a positive way were utilized to determine gene func- cyte cells. Under the five-cytokine mixture culture condition, + + tions on the modulation of generation of MkPs from HSPCs. By CD34 CD41 cells represented ∼10% of the cell population after gene expression analysis, multicolor flow cytometry, colony forming in vitro differentiation (SI Appendix,Fig.S1B), and the cell can unit-megakaryocyte (CFU-Mk) functional assay, 10 regulatory genes expand 50- to 100-fold. Therefore, the five-cytokine mixture was (the hit genes) from 60 candidates were identified. Furthermore, we used for the differentiation from HSPCs into MkPs, and then showed the hit genes could promote the generation of megakaryo- TPO, SCF, and IL6 are used for megakaryocyte maturation and cytes as well as platelets. Finally, we found that inhibition of histone platelet generation in an additional 1- to 2-wk culture (Fig. 2A). deacetylase (HDAC) activity could also promote MkP differentia- The additional culture will expand cells by an additional 50- to tion, possibly by regulating some of the hit genes. 100-fold and finally each megakaryocyte can give rise to thousands of platelets. Results We then used lentiviral-mediated transduction to deliver gene Identification of Candidate TFs for MkPs from Gene Expression edits in HSPCs. However, the transduction efficiency was re- Commons. To generate the candidate gene list, we used GEXC portedly very low and it becomes an obstacle to manipulate he- (29) developed in our laboratory. GEXC is a platform for profiling matopoietic cells for basic research and disease treatment (36, 37). absolute expression of any gene using a large number (>10,000) of We performed several optimization steps on the viral gene de- varied microarray datasets (30–32). Based on our previous work on livery strategy to improve the transduction efficiency. Firstly, we mouse hematopoietic hierarchy, we generated a comprehensive used retronectin to enhance transduction by facilitating colocali- “mouse hematopoiesis and stroma” model in GEXC, composed of zation of viral particles and hematopoietic cells. Secondly, viruses + lineage-specific genes for HSPCs and mature populations in adult were highly concentrated and applied to CD34 cellswithanop- mouse bone marrow (BM), spleen, and thymus. timal mulitiplicity of infection. In addition, spin-mediated multiple- Since there are no data available for human MkPs in GEXC round virus incubation was used. Such optimization strategies and we believe the critical regulators are conserved between eventually enabled ∼90% transduction efficiency after puromycin mouse and human, we used the mouse model to generate the selection, as demonstrated in the following experiments where + MkP-specific candidate TF list and evaluated their expression human CD34 cells were treated with lentivirus-expressing EGFP pattern in human HSPCs. In addition to TFs, other proteins, (SI Appendix,Figs.S1C and S4A). such as coactivators, HDACs, and methylases, which do not have DNA-binding domains, but are essential for gene regulation, are Negative Screen for MkP Essential Genes by CRISPR-Mediated also considered. In this case, the genesets for transcription reg- Knockout. Specific sgRNAs were designed either by the sgRNA ulators in GEXC were targeted with the search term of “inactive designer tool online (crispr.mit.edu) or selected from the Human in MEP and EP, while active in MkP” (Fig. 1A and SI Appendix, GeCKO Lentiviral sgRNA Library (26, 27), which are designed Fig. S1A). By this search, we obtained a list of genes, which were to target all of the isoforms of candidate genes. Synthesized ranked by geneset activity in MkPs. sgRNA for human genes were cloned individually into the all-in- We then selected the 60 top-ranked genes to further identify one CRISPR lentiviral vector (SI Appendix, Table S1). We then SI Appendix used real-time PCR to analyze the CRISPR-mediated knockout their roles in megakaryopoiesis ( , Table S1). To our + expectation, there are some previously reported hematopoietic- of candidate genes in human CD34 cells. The results showed specific TFs, such as Fli1, Gata2, Meis1, Pbx1, Smad5, and Mecom, that most of the genes decreased their expression levels after while most of the other listed genes have not been reported in CRISPR-mediated gene knockout, compared with the control hematopoietic lineages. Fli1 is critical for megakaryopoiesis and group (Fig. 2B). For example, HOXC6 and MZF1 expression hasbeenshowntodrivecelllinestodevelopmegakaryocyticfea- decreased by around 60% while FOXB1 and HES7 expression are almost completely suppressed. Those results suggested that tures and its overexpression inhibits erythroid development (33, 34). + Therefore, we choose Fli1 as a positive control in our following we can successfully manipulate gene expression in human CD34 experiments. cells and therefore used this optimized strategy to screen genes by CRISPR in hematopoietic cells. We next validated the expression pattern of some candidate + genes in human MEPs, MkPs, and EPs by real-time PCR. Those CRISPR-mediated gene knockout in human CD34 HSPCs three populations were isolated from human bone marrow mono- cells were used for the primary loss-of-function screen. sgRNA nuclear cells (35). The results showed most of the candidate genes, targeting Escherichia coli LacZ locus delivered by the same viral such as FLI1, HOXC6, MXD3, MEIS1, ERG, PRDM16, ZBTB16, system was used as a nonsense interruption control (38). FLI1 PCGF2 GSX2 HDAC11 NPAS1 TBX6 FOXB1 was used as a positive control, the knockout of which induced , , , , ,and have a + + higher expression level in MkP than in MEP and/or EP cells, sug- significant change in CD34 CD41 cells (Fig. 2C). The screening gesting a conserved expression pattern in those populations be- experiment showed that deletion of some genes resulted in the tween mouse and human (Fig. 1B). deficiency of differentiation from HSPCs into MkPs, suggesting these genes may be critical for megakaryocyte development (Fig. Establishment of the Screen System. The rarity of the MkP pop- 2C and SI Appendix, Figs. S2 and S3A). The flow cytometry data ulation (0.01%) in total bone marrow nucleated blood cells and showed that, after deleting HOXC6, NFATC1, GSX2, or + + + + the lack of suitable cell line models hinder the identification of MXD3 et al., both CD34 /CD41 and CD34 /CD71 cells from + signals that regulate human megakaryopoiesis. Bone marrow human CD34 HSPCs were dramatically reduced. For example, + + + CD34 HSPCs can differentiate into MkPs and megakaryocytes. after NFATC1 knockout, the generation of CD34 /CD41 is + + However, the differentiation is heterogeneous and inefficient. To only 4% and CD34 /CD71 is only 10.7%, compared with LacZ establish a repeatable protocol for screening, we used a serum- control of 7% and 15%, respectively (Fig. 2D and SI Appen- free hematopoietic expansion medium supplemented with cyto- dix,Fig.S3B). The cutoff level for this screen is based on + + + + kines, and tested CD34 CD41 (MkP/megakaryocyte marker) CD34 CD41 reduction compared with virus vehicle control, + + + cells and CD41 (megakaryocyte marker) cells, CD34 CD71 and we got about 30 hits (Fig. 2C and SI Appendix, Fig. S2). We

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Fig. 1. Experiment design for the knockout screening strategy. (A) Expression of some of the candidate TFs, including Fli1, Nfatc1, Mzf1, Mxd3, Hes7, and Pcgf2, in the mouse hematopoietic system as determined in GEXC. (B) Expression analysis of some of the candidate genes in human bone marrow MEPs, EPs, and MkPs by real-time PCR. n = 3; error bar indicates SD.

Zhu et al. PNAS Latest Articles | 3of9 Downloaded by guest on October 1, 2021 Fig. 2. Identification of key TFs for human megakaryopoiesis by knockout screening. (A) Scheme of the screening process. (B) Confirmation of knockout for + + some of the candidate TFs by real-time PCR. n = 3; error bar indicates SD. (C) Summary of the FACS analysis for the increase/decrease of MkP (CD34 CD41 )- or + + + EP (CD34 CD71 )-enriched population after CRISPR/Cas9-mediated knockout of candidate TFs in CD34 HSPC culture. Here, the percentage of the control cell- derived MkP or EP is set to 1, and percentage from gene knockout cells was normalized to that. n = 3; error bar indicates SD. (D) FACS plot showed that the MkP population (CD34+CD41+) decreased after knockout of the hit TFs. (E) MkP gene expression analysis after knockout of the hit TFs. n = 3; error bar indicates SD. *P < 0.05, **P < 0.01.

4of9 | www.pnas.org/cgi/doi/10.1073/pnas.1805434115 Zhu et al. Downloaded by guest on October 1, 2021 excluded genes that have already been reported to be essential for did not increase MkP generation, such as GABPB, HLF, and MkPs development, such as GATA2, MEIS1, MECOM, PBX1, SOX6 (Fig. 3 B and C). ZBTB16, and we generated a final list of 20 genes for further study. To examine whether the MkPs generated when the selected Most of the genes on the list, to our knowledge, have not been TFs were overexpressed are functional progenitors, we investi- reported to be functional in human hematopoietic cells, especially gated their ability to generate megakaryocyte colonies (CFU-Mk) MkP differentiation from HSPCs. in semisolid media optimized for megakaryocyte colony growth. + To determine the gene expression changes after TF knockout After 2–3 wk, 5,000 BM CD34 cells expanded in the control (20), we analyzed SCL, LMO2, and RUNX1, which are essential group and overexpression group were assayed for CFU-Mk con- transcription factors for MkPs. Real-time PCR results showed, in tent. FLI1-overexpressing cells generated a fourfold increase in the knockout cells, these genes decreased compared with LacZ megakaryocyte colonies compared with the control group, which controls (Fig. 2E). FLI1 deletion led to a decrease of over 50% indicates that overexpression of FLI1 generates more megakar- of SCL, LMO2, and RUNX1 gene expression, while HOXC6 and yocyte precursors. HOXC6, HDAC11, NPAS1, and NFATC1 MZF1 deletion can lead up to 80% lost. overexpression also resulted in an approximate twofold change (SI Together, primary screen results suggested that knockout of Appendix,Fig.S5A). some candidate genes can lead to reduction of MkP differenti- We then used chemical compounds to further confirm the ation from HSPCs, indicating that these genes might be in- function of some regulators. Of all of the final 10 genes, HES7 is volved in the regulation of MkP cell fate decision during the downstream effector of the Notch pathway, and Notch an- hematopoiesis. tagonists DAPT and DBZ, the ligand DLL4 could mimic the function of HES7 knockout and overexpression, respectively. Gain-of-Function Screen of the Narrowed Candidate Genes. Next, we NFATC1 is one of the five members of the NFAT family, and performed ectopic expression of the candidate TFs in HSPCs to upon activation by calcium, it translocates to the nucleus, where it further explore their regulatory function in MkP generation. targets various genes, including the cytokine gene IL2 (41). The Genes were expressed under the murine sarcoma cell virus small molecule cyclosporin A is a well-known inhibitor for (MSCV) promoter, which exhibits activity in hematopoietic cells NFATC1. Therefore, we treated HSPCs with DLL4, DAPT, DBZ, and embryonic stem cells (39, 40), and GFP in the same con- or cyclosporine A in the differentiation culture and found that struct can be an indicator for transduced cells. We used the MkP differentiation was greatly inhibited by adding DAPT, DBZ, SI Appendix B empty viral vehicle without gene as a control. Overexpression of or cyclosporine A, but increased by DLL4 ( ,Fig.S5 ).

+ CELL BIOLOGY individual genes in human CD34 cells was confirmed by GFP MkPs generate megakaryocytes, which then produce platelets. expression (SI Appendix, Fig. S4A), and some were also con- During maturation, megakaryocytes become polyploid, show in- firmed by real-time PCR analysis. (SI Appendix, Fig. S4B). creased protein and membrane levels, and then extend branches. Overexpression of these TFs led to significant changes in the After that, one megakaryocyte will finally release thousands of production of MkP/megakaryocytes and EP/erythrocytes. FLI1 platelets in blood vessels. To determine the production of platelets + + specifically increased CD34 CD41 cells by 3- to 5-fold but not with gene overexpression, we extended the differentiation with an + + – CD34 CD71 cells. HES7, FOXB1, HOXC6, and MXD3 pro- additional 1 2 wk to induce MkPs into megakaryocytes and then + + moted the generation of CD34 CD41 cells by more than 2-fold platelets with the cytokine mixture TPO, SCF, and IL6. After that, (Fig. 3A and SI Appendix, Fig. S4 C and D), and GABPB, we used flow cytometry to analyze platelet generation. During the HDAC11, MZF1, NFATC1, NPAS1, OTP, PCGF2, PTF1A, culture, we observed large-sized polyploid megakaryocytes by + + Giemsa staining which then became tiny-sized platelets (SI Appen- HOXA9, and SOX6 led to an increase of CD34 CD41 cells by dix,Fig.S5D). We used forward/side scatter (FSC/SSC) to gate out 1.5- to 2-fold. HLF showed minor effects. small size platelets and then analyzed their surface markers, in- To explore the lineage-specific gene expression changes in cluding CD41 [glycoprotein (GP) IIb], CD42a (GP IX), and CD61 those cells, expression levels of SCL, LMO2, and RUNX1 were + (GP IIIa). Compared with the control group, gene overexpression analyzed. When FLI1 was overexpressed in CD34 cells, SCL and + + generated an approximate one- to fivefold increase in CD41 /CD42a RUNX1 increased dramatically by tens of folds. Consistently, + and CD61 cells, including HES7, HDAC11, MXD3, NFATC1, overexpression of the other narrowed genes showed comparable PCGF2, and FLI1. Significantly, HES7 can promote platelet gen- effects to FLI1, such as HOXA9, MZF1, SOX6, and PCGF2. We eration to 34.3% CD41 and CD42a dual positive cells (SI Appendix, then investigated more lineage-specific gene expressions by real- Fig. S5C). time PCR, including genes involved in erythroid differentiation Taken together, our results suggested that MZF1, GSX2, (KLF1 and EPOR), those in MkP differentiation (FLI1 and GABPA GATA1 NFE2 GATA2 HOXC6, HDAC11, HES7, FOXB1, MXD3, HOXA9, NFATC1, ), and those in both lineages ( , , , and PCGF2 are potential regulators of MkP generation. and MYB). Erythroid genes have low expression levels in all of the samples and overexpression of narrowed genes did not lead to HDAC Regulation of MkPs and the Hit TFs. HDACs are a class of significant changes, while the MkP genes were obviously up- enzymes regulating DNA deacetylation. They are therefore asso- regulated in most of the samples (SI Appendix,Fig.S4E). ciated with a variety of transcriptional repressors that control cel- Stepwise differentiation from HSCs to MkPs included several lular differentiation and proliferation. HDAC inhibition has been stages, such as HSCs, multipotent progenitors (MPPs), common reported to regulate proliferation and expansion of HSCs in vitro myeloid progenitors (CMPs), and MEPs. Different populations (42). We thus believe it is important to examine whether HDACs can be identified by multiple cell surface markers. Flow cytom- function in MkP generation and regulate the newly identified TFs. etry showed that overexpression of HOXC6 increased HSC/ To answer this question, we first determined whether HDAC MPP, CMP, MEP, EP, and MkP populations compared with the family members regulated MkP generation. The expression of control group. Importantly, no changes on MEP and granulocyte- the HDAC family members, including HDAC1-11, was analyzed monocyte progenitors (GMPs) were observed, suggesting HOXC6 by GEXC, in mouse hematopoiesis models. Except for those not may function mostly in early stage progenitors, such as HSCs, expressed in MEPs, MkPs, or EPs (HDACs 4, 6, and 9), other MPPs, and CMPs. FOXB1 and MZF1 increased MEPs as well as HDACs fall into two distinct expression patterns in MEP, MkP, MkPs and EPs at the expense of GMP, suggesting they function in and EP populations (SI Appendix, Fig. S6A). HDACs 5 and CMP stage. The function of HES7 may be at both HSC and MkP 11 are expressed in MkPs rather than MEPs or EPs, according to stages as its overexpression dramatically increased only HSCs and GEXC; real-time PCR revealed similar expression patterns in MkPs but not CMPs, MEPs, or EPs. However, some of the genes human populations (SI Appendix, Fig. S6B). Knocking out of

Zhu et al. PNAS Latest Articles | 5of9 Downloaded by guest on October 1, 2021 Fig. 3. Some hit TFs can promote MkP differentiation when overexpressed. (A and B) Summary of the FACS analysis for the increase/decrease of MkP (CD34+CD41+)- + + + or EP (CD34 CD71 )-enriched population (A) or HSPC population (B) after lentiviral vector-mediated overexpression of some hit TFs in CD34 HSPC culture. Here, the percentage of the control cell-derived MkP, EP, or other HSPCs is set to 1, and percentage from gene overexpressing cells was normalized to that. n = 3; error bars indicate SDs. (C) FACS plot to show changes of HSPC populations after lentiviral vector-mediated overexpression. Error bar indicates SD. *P < 0.05, **P < 0.01.

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+ + Fig. 4. HDAC inhibitors promote MkP differentiation. (A and B) Summary (A) or flow cytometry plot (B) for the increase/decrease of MkP (CD34 CD41 )- or EP + + + (CD34 CD71 )-enriched population after different HDAC inhibitor treatment in CD34 HSPC culture. Here, the percentage of the control cell-derived MkP- and EP-enriched populations is set to 1, and percentage from other treatments was normalized to that. n = 3; error bar indicates SD. (C and D) Summary (C) or flow cytometry plot (D)forthe + increase/decrease of different HSPC populations after different HDAC inhibitor treatment in CD34 HSPC culture. Here, the percentage of the control cell-derived HSPC populations is set to 1, and percentage from other treatments was normalized to that. n = 3; error bar indicates SD. (E) FACS analysis of platelet surface markers CD41, CD42a, and CD61 after HDAC inhibitor treatment. (F) Expression analysis of some of the hit TF changes in HDAC inhibitor-treated cells by real-time PCR. n = 3; error bar indicates SD.

Zhu et al. PNAS Latest Articles | 7of9 Downloaded by guest on October 1, 2021 + HDAC11 by CRISPR in human CD34 cells showed a decrease Interestingly, of all of the genes identified, only a few of them + + of CD34 CD41 MkP population while overexpression of HDAC11 have been shown to be involved in megakaryopoiesis, including increased this population, suggesting it could positively regulate FLI1 and MZF1. Most other genes, although they performed sim- MkP generation (Figs. 2C and 3A). ilar functions to FLI1 when deleted or overexpressed, have been Other HDACs, including 1, 2, 3, 7, 8,and10,showedhigherex- reported only in either other hematopoietic lineages or in tissues pression levels in MEP and/or EP than in MkPs (SI Appendix,Fig. outside of the hematopoietic system, etc., opening the possibility S6 A and B), which indicates that during MEP differentiation into that other lineage genes might also be expressed in megakaryocytes. MkPs, the HDAC family may repress MkP essential genes and FLI1 belongs to the Ets gene family of transcription factors, and is thus their inhibition would promote MkP generation. To test this well known for its function in erythrocyte and megakaryocyte de- hypothesis, effects of HDAC inhibitors, including Quisinostat, velopment. Inactivation of FLI1 leads to defective megakaryopoiesis Mocetinostat, and MC1568, were examined in our in vitro culture and abnormal erythroid development, while overexpression of model. Quisinostat (JNJ-26481585) 2HCl is a novel second-generation FLI1 in the K562 cell line promotes its differentiation toward the HDAC inhibitor with the highest potency for class I HDAC1 and megakaryocytic lineage (43). Nuclear factor of activated T-cells, modestly potent to HDAC2, -4, -10, and -11. MC1568 is a selective cytoplasmic 1 (NFATC1) is first described in T cells. NFATC1 is inhibitor of class IIa HDACs (including HDAC4, -5, -7, and -9). one of the five members of the NFAT family, and upon activation by Mocetinostat is an orally available inhibitor that selectively targets calcium, it translocates to the nucleus, where it targets various class I HDAC1 and -2. As expected, 10 nM Quisinostat, 2 μM + + genes, including the cytokine gene IL2 (41). It is a target of in- Mocetinostat, and 5 μM MC1568 increased CD34 CD41 pop- + A B SI Appendix hibition by immunosuppressive agents cyclosporine and FK506, ulations from human CD34 cells (Fig. 4 and and , working through calcineurin and FKBP, respectively, and was later Fig. S6C). Multiple color flow cytometry showed MkP increased found to be critical for other tissue development, such as cardiac after HDAC inhibitor treatment (Fig. 4 C and D). However, dif- development (44–47). The NFAT family is reported to negatively ferent HDAC inhibitors perform a bit differently. Quisinostat regulate megakaryopoiesis in mouse (48). Here, we identified its showed the most significant effect. Real-time PCR analysis showed expression and function in human MkP generation from HSCs and the treatment increases most known MkP-specific TFs but not EP- related genes such as KLF1 and EPOR (SI Appendix,Fig.S6D). their further differentiation into megakaryocytes. One toxicity of We then determined whether HDAC inhibitor treatment chronic cyclosporine A administration can be thrombocytopenia could affect platelet production. Since cord blood represents a (49). In addition, these studies have identified some factors that have not been reported to be involved in megakaryocyte develop- large and readily available source of hematopoietic cells, we used SI Appendix HDAC inhibitors to treat cord blood mononuclear cells dur- ment ( ,TableS2), demonstrating that our method ing their differentiation into platelets. Flow cytometry showed cannot only validate already known genes, but also help reveal + + that CD41/CD42a cells increased one- to threefold while CD61 genes critical for MkP differentiation. In one scenario, cell-specific cells increased correspondingly after HDAC inhibitor treat- inducers of the appropriate platelet production pathway might be ment of HSPCs. Mocetinostat can lead to more than 30% foundtobeaspecificandsafe alternative to TPO. + + + CD41 CD42a cells as well as CD61 cells (Fig. 4E). Taken together, our results presented here should facilitate We then examined if HDACs could regulate our newly iden- the identification of regulators for MkP differentiation from tified genes. The real-time PCR results showed GSX2, MXD3, HSPCs, which will help the development of protocols for gen- HOXC6,andHES7 are highly increased by tens of folds by the eration of MkP and platelets by manipulating these genes/path- inhibition of HDACs, indicating that HDACs might repress their ways for clinical use. Furthermore, this method could be readily expressions during hematopoiesis. PCGF2, FOXB1,andMZF1 applied to any other cell lineages for identification of critical have modest increase while no effect was observed for NPAS1 and regulators. Given the need of platelets in many pathological HOXA9 (Fig. 4F). These results suggested that those newly situations, understanding the regulation of platelet generation is identified genes might be downstream of HDAC modification. an important research field with important clinical applications. Discussion Materials and Methods In this study, we combined CRISPR and functional studies to identify Cell culture, virus production, cell transduction, colony-forming unit assay, candidate factors that regulate MkP generation from HSPCs. The flow cytometry, RNA isolation, and real-time PCR were done as described in screening initiated with a solid candidate gene list generated from SI Appendix. GEXC, a platform to analyze absolute gene expression levels based GEXC (https://gexc.riken.jp/) provides dynamic range of each gene by on microarray data. Real-time PCR was used to confirm expression metaanalysis of thousands of microarray data. Transcription factor expres- pattern of those candidate genes in human MkPs. After that, sions in the mouse hematopoietic system in GEXC were analyzed in cell CRISPR-mediated individual gene knockout, lentivirus-mediated populations of hematopoietic stem, progenitor, and mature populations in adult mouse bone marrow, spleen, and thymus. gene overexpression, lineage-specific gene expression analysis, and functional in vitro colony-forming unit assay were used for the mul- ACKNOWLEDGMENTS. We thank Tal Raveh for her help in editing this tiple rounds of screening. Using this strategy, we tested 60 candidates manuscript; Terry Storm and Tejaswitha Naik for laboratory management; revealing 10 genes that conferred a regulatory role during HSPC Patty Lovelace for help with flow cytometry; and the FACS core at Stanford differentiation to MkPs. Of these, some genes are highly up-regulated Institute for Stem Cell Biology and Regenerative Medicine. This work is after HDAC inhibition, suggesting that they might be downstream of supported by National Institutes of Health (NIH) Grants U01-HL099999- 07 and R01-CA086065 (to I.L.W.) and the Ludwig Foundation. F.Z. is a Seibel HDAC modification. Those results can provide an investigation of Scholar of the Seibel Stem Cell Institute. This work is also supported by NIH TFs as regulators in MkP generation and make it possible to change Pathway to Independence Award R00CA201075 (to M.F.) and the Damon differentiation trends from MEP into its progenies. Runyon–Dale F. Frey Award for Breakthrough Scientists DFS-22-16 (to M.F.).

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