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chromatin remodeling proteins and histone modifiers. This results in accurate and precise local and global chro- matin organization. Chromatin immunoprecipitation sequencing (ChIP-seq) analyses together with RNA expression profiling underscore the importance of KLF1 in red cell biology, demonstrating its multifunctional roles in tissue-specific gene expression, lineage determination, and terminal maturation.
Over 70 human mutations in KLF1 have been identified over recent years.19,20 Monoallelic mutation of KLF1 in humans usually leads to a benign outcome that is nonetheless phenotypically important.20-24 Expression of certain cell surface markers, such as CD44 and Lutheran antigen, are affected but do not exert any physiological effect.25 Expansion of these cells in culture is also not affected.10,25 Of clinical importance, however, haploinsuffi- cient levels of KLF1 lead to altered β-globin switching and elevated g-globin expression, which can be advantageous, particularly in areas with endemic β-thalassemia.26 Related to this, some single and compound mutations in human KLF1 lead to anemias in addition to CDA such as sphero- cytosis, microcytic hypochromic anemia, pyruvate kinase deficiency,10,27,28 or in the most extreme case, hydrops fetalis.29 Expression of about 700 genes is dependent on KLF1 in humans. As a result of its central importance, one might predict an extensive cascade of changes would fol- low from the KLF1-E325K mutation, particularly likely in this case given the broad role of KLF1 in the control of ery- thropoiesis.
Two sets of observations in the mouse are particularly informative for the present study. One is from studies of the monoallelic mouse neonatal anemia (Nan) mutation that resides at the same amino acid of KLF1, albeit with an aspartate substitution (E339D).30,31 These mice exhibit a lifelong anemia due to a distorted erythroid transcriptional output. The E339D mutation not only yields a variant with a more circumscribed binding specificity compared to wild type (WT),31 but also one that recognizes a novel, more degenerate target sequence uniquely recognized by Nan-KLF1.32,33 The second observation is that, unlike the Nan mutant, mouse erythroid cells totally ablated in KLF1 do not enucleate, but instead stall at the orthochromatic erythroblast stage.34 Many of these cells are also bi-nucle- ated. As a result, mutant expression or insufficient levels of KLF1 can separately contribute to defective erythroid expression and phenotypic properties.
Although the CDA type IV red cell cellular and pheno- typic properties have been described, the molecular mech- anism/details by which the KLF1-E325K mutation exerts its effect and causes these significant changes has not been previously addressed. A limitation of studying this disease has been the paucity of starting material due to its rarity. As a result, we directed our efforts towards analysis of derived erythroid cells from the peripheral blood of our published patient.
Methods
Cell sources
Analysis used RNA from patient peripheral blood cells leftover from our previously published study5 that had received Institutional Review Board approval; no new patient material was obtained for the present study. Mononuclear cells from the periph- eral blood (PBMC) had been isolated and cryopreserved as
KLF1 mutation in human anemia described.35 Non-patient PBMC were purchased from AllCells
(PB003F).
Human erythroid massive amplification protocol
Peripheral blood mononuclear cells underwent a two-step cul- ture;36,37 one for proliferation, with harvests at day (d)11 and d15; the second for differentiation that was harvested after the d11 culture was differentiated for an additional five days. Under these conditions, the normal sample attained CD235a+ levels of over 70% (data not shown). As a result, we used these prescreened reagents and conditions for the proliferation/differentiation experiment of normal cells in parallel with the patient PBMC sample.
Peripheral blood mononuclear cells (10E6 cells/ml) were cul- tured in IMDM plus 20% FBS, SCF (100 ng/mL), IL-3 (1 ng/mL), EPO (5 U/mL), dexamethasone and estradiol (both 1 uM). Also included were deionized human serum albumin (5%), human iron saturated transferrin, liposomes plus cholesterol (400 μg/mL), and lecithin (1.2 mg/mL).36,37 Differentiation was enabled by increasing erythropoietin (EPO) to 10 U/mL, removing dex- amethasone, and including recombinant human insulin (40 ng/mL) and T3 (1 uM). Both cell sources were successfully cul- tured and expanded in this way, giving us confidence that the human erythroid massive amplification (HEMA) approach enables direct analysis of CDA patient erythroid samples.
Morphological analysis of d11 expanding cells was derived from analysis of three sets of cytospins from two experiments, each analyzed and quantified independently by two of the authors.
RNA isolation and analysis
Total RNA from all samples was isolated with Trizol (Sigma). Bioanalyzer (Agilent) analysis showed that RIN values were all between 7.8-8.7 except for the normal differentiated d5 sample, which had a value of 3.4. These samples were used for polyA+ library preparation using the Bioo Scientific (NEXTflex) Rapid Directional kit (NOVA-5138-07). Next generation sequencing was performed on an Illumina NextSeq 500. Sequencing yielded 75 nt single end reads, >30 million per sample.
RNA-seq data have been submitted to the Gene Expression Omnibus GSE128718.
Real-time qualitative polymerase chain reaction (RT-qPCR) was performed on cDNA generated with a mix of oligo-dT and ran- dom hexamers (Quantabio 95048-025). Primers were as previous- ly described.38 Errors after combining quantities with their own uncertainties were calculated as in http://lectureonline.cl. msu.edu/~mmp/labs/error/e2.htm.
Bioinformatics
Expression data from human in vitro expanded primary ery- throid cells analyzed at 5 stages (Pimentel, 2014 #2477) was obtained from GEO (GSE53635). Sequenced reads were mapped to the human genome (hg38) using Tophat2. Accepted hits were tested for differential expression analysis using Cuffdiff2 with the blind dispersion method. Heatmap plots for gene clusters were created in R package pHeatmap.
Gene set enrichment analysis (GSEA) (http://software.broadinsti- tute.org/gsea/index.jsp) was performed {Subramanian, 2005 #2464;Mootha, 2003 #2465} using gene set lists from selected expression clusters (described by Li et al.).39 Venn diagrams were generated with Venny (http://bioinfogp.cnb.csic.es/tools/venny/ or https://www.stefanjol.nl/venny) or BioVenn (http://www. biovenn.nl/index.php) and were used to identify non-overlapping genes within sets. The DAVID analysis tool v6.8 (https://david.ncifcrf.gov/) was used as described.40
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