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Comprehensive Report on Stem Cell Banking Market 2021 | Trends, Growth Demand, Opportunities & Forecast To 2027 |Cordlife, Cryo-Cell…

Stem Cell Banking Market research report is the new statistical data source added by A2Z Market Research.

Stem Cell Banking Market is growing at a High CAGR during the forecast period 2021-2027. The increasing interest of the individuals in this industry is that the major reason for the expansion of this market.

Stem Cell Banking Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis.

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Top Key Players Profiled in this report are:

Cordlife, Cryo-Cell International, Cryo-Save Ag (A Subsidiary Of Esperite N.V), Lifecell International, Stemcyte, Viacord (A Subsidiary Of Perkinelmer), Global Cord Blood, Smart Cells International, Vita34, Cryoholdco.

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Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Stem Cell Banking market. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market. The influence of the latest government guidelines is also analyzed in detail in the report. It studies the Stem Cell Banking markets trajectory between forecast periods.

Regions Covered in the Global Stem Cell Banking Market Report 2021: The Middle East and Africa (GCC Countries and Egypt) North America (the United States, Mexico, and Canada) South America (Brazil etc.) Europe (Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

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The cost analysis of the Global Stem Cell Banking Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.

The report provides insights on the following pointers:

Market Penetration: Comprehensive information on the product portfolios of the top players in the Stem Cell Banking market.

Product Development/Innovation: Detailed insights on the upcoming technologies, R&D activities, and product launches in the market.

Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the market.

Market Development: Comprehensive information about emerging markets. This report analyzes the market for various segments across geographies.

Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the Stem Cell Banking market.

Table of Contents

Global Stem Cell Banking Market Research Report 2021 2027

Chapter 1 Stem Cell Banking Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Stem Cell Banking Market Forecast

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Comprehensive Report on Stem Cell Banking Market 2021 | Trends, Growth Demand, Opportunities & Forecast To 2027 |Cordlife, Cryo-Cell...

The chromosomal protein SMCHD1 regulates DNA methylation and the 2c-like state of embryonic stem cells by antagonizing TET proteins – Science Advances

RESULTS Identification of SMCHD1 as a protein associated with TET proteins

Using mass spectrometry (MS), we identified SMCHD1 as a protein interacting with FLAG-tagged TET3 in 293T cells (Fig. 1, A and B, and table S1), where it scored among the eight most significantly enriched proteins, which included TET3 itself and the known TET3 binding partner O-linked -N-acetylglucosamine transferase (OGT) (2729). To verify the SMCHD1-TET interaction further, we created ES cell lines by homologous recombination that carried a FLAG tag at the C terminus of the endogenous Smchd1 coding sequence (fig. S1A). We carried out anti-FLAG pulldown with one of the clones and performed proteomics analysis. Among the identified proteins were SMCHD1 itself as the highest-scoring protein (54% coverage) (fig. S1B and table S2). We detected the known SMCHD1-interacting protein, LRIF1 (12.3% coverage) (30). There were also several components of the PRC2 complex (EZH2, SUZ12, and MTF2; 4.5 to 15% coverage) but no PRC1 components. SMCHD1 has been shown to be a protecting factor against formation of histone H3 lysine 27 trimethylation (H3K27me3) by the Polycomb complex (25). In this proteomics experiment, we specifically recovered the TET2 protein (4.92% coverage), as associated with SMCHD1, but not TET1. TET3 is expressed at very low levels in ES cells. The known TET-interacting protein OGT (2729) was also identified (9.37%). We then transfected FLAG-tagged TET2 into 293T cells. Although TET2 itself was identified at only 4.0% coverage (fig. S1C and table S2), we still found SMCHD1 (11.4% coverage) and OGT (46%) as TET2-interacting proteins.

(A) Flag purification of TET3FL and TET3S from 293T cells. The purified samples were subjected to Coomassie blue staining (left) and Western blotting (right). The gel segments indicated were analyzed by MS. M, molecular weight markers; IB, immunoblot. (B) Identification of SMCHD1 as a binding partner of TET3 by MS. TET3S was expressed in 293T cells and immunoprecipitated with anti-FLAG beads. Gel segment 2 (A) was subjected to LC-MS/MS (liquid chromatographytandem MS) analysis (see Materials and Methods and table S1). The top eight highest-scoring proteins are shown. M.W., molecular weight. (C) Endogenous coimmunoprecipitation (co-IP) of SMCHD1 with TET1, TET2, and TET3FL. (D) Interaction between TET proteins and SMCHD1 by co-IP using expression of tagged proteins in 293T cells. (E) Different domains of TET3 were cotransfected with full-length SMCHD1 into 293T cells. After IP, the interacting proteins were identified by Western blotting. Stars indicate IgG (immunoglobulin G) bands. aa, amino acids. (F) Different domains of SMCHD1 were cotransfected with TET3FL into 293T cells. After IP, the interacting proteins were identified by Western blotting. Stars indicate IgG bands. HATPase, histidine kinase-like ATPase domain.

Using coimmunoprecipitation (co-IP), we found that all mouse TET proteins, including the long and short isoforms of TET3 [TET3FL (full-length TET3) and TET3S, respectively (31)], and TET1 and TET2 interact with SMCHD1 as endogenous proteins in cell types in which the proteins are expressed at substantial levels (TET1 and TET2 in ES cells and TET3 in Neuro2a cells) (Fig. 1C). These interactions were confirmed by cotransfection of the respective expression constructs and IP experiments (Fig. 1D).

To further substantiate the SMCHD1-TET interactions in cells, we performed bimolecular fluorescence complementation (BiFC) experiments (32, 33) with SMCHD1 and TET3 (fig. S2). The data suggest an efficient interaction of TET3 and SMCHD1 at a level similar to a positive control (P.C.) experiment with TET3 and OGT. The latter two proteins are interaction partners, as reported previously (27, 28). Although this assay does not determine that the two proteins interact directly, it is an independent confirmation of the in vivo TET-SMCHD1 interaction, for example, within a protein complex.

We then determined the interacting domains of TET3 and SMCHD1 by cotransfection experiments. We found that the C-terminal double-stranded -helix domain of TET3, which represents the core catalytic region conserved between all three TET proteins (8, 20, 34), interacts strongly with SMCHD1 (Fig. 1E). Analyzing SMCHD1 domains, we found that the N-terminal region including the GHKL adenosine triphosphatase (ATPase) domain interacted most efficiently with TET3FL (fragment F1; Fig. 1F), but the long central domain and the C-terminal hinge domain did not show any appreciable binding.

We then examined whether SMCHD1 and TET proteins can interact directly in vitro. We initially failed to observe a direct interaction between the recombinant N-terminal (ATPase) domain of SMCHD1 and the TET2 catalytic domain (TET2-CD). Next, we prepared recombinant full-length SMCHD1 and recombinant TET2-CD or TETFL proteins. These proteins were purified from either baculovirus-infected cells (SMCHD1 and TET2-CD) or from mammalian cells (TET2FL or TET1FL). We used the AlphaScreen system (fig. S3A) for assessing binding reactions in a quantitative biophysical assay. In these assays, SMCHD1-FLAG was biotinylated via an introduced C-terminal biotinylation sequence (AviTag) and was coexpressed along with biotin ligase (BirA) in baculovirus-infected insect cells. This SMCHD1 protein could be collected on streptavidin beads indicating that it was biotinylated successfully (fig. S3B). The mammalian TET proteins were expressed as C-terminal His-tagged proteins (fig. S3B). In the AlphaScreen assays, binding between a biotinylated protein captured on streptavidin AlphaScreen donor beads and a His-tagged protein captured on nickel chelate (Ninitrilotriacetic acid) AlphaScreen acceptor beads is measured. After performing these assays, we did not observe any direct binding between SMCHD1 and TET2 proteins (TET1 tested negatively as well) (fig. S3C). We also performed in vitro biotinylation of SMCHD1 using biotinylation kits, or we biotinylated the anti-SMCHD1 antibody followed by SMCHD1 binding. We concluded that our consistently observed interactions between SMCHD1 and TET proteins in cells are most likely based on an indirect interaction, perhaps involving a larger protein complex or a bridging protein. One potential candidate for such a protein is OGT, which we recovered in SMCHD1 and TET protein complexes and which is known to interact with the TET2/3-CDs (27, 29, 35, 36).

When SMCHD1 was coexpressed in 293T cells together with TET3FL, TET activity was inhibited in an SMCHD1 dose-dependent manner, leading to the formation of lower amounts of the TET reaction product 5hmC (Fig. 2A), while total levels of 5mC did not change appreciably. Another in vivo assay of TET activity is based on demethylation and reactivation of a luciferase vector that is methylated in vitro at all CpG sites before transfection. In this assay, TET3S is more active than TET3FL (31). The luciferase activity of the fully CpG-methylated luciferase reporter vector was increased by cotransfection of TET3S, as reported previously (Fig. 2B) (31). This TET-induced activity was inhibited by SMCHD1, which did not reduce the activity of an unmethylated control reporter (Fig. 2B).

(A) Reduction in 5hmC levels by coexpression of SMCHD1 with TET3 in 293T cells. 5hmC and 5mC contents were assessed using antibody-based dot blots. One-way analysis of variance (ANOVA) was performed comparing the mean of each group with the mean of the second group (**P < 0.01 and ***P < 0.001; mean SEM). ns, not significant. (B) Inhibition of TET3S-induced reactivation of a methylation-silenced luciferase construct by SMCHD1 in 293T cells (top). One-way ANOVA was performed (**P < 0.01 and ****P < 0.0001). Data are for means SEM of three independent experiments. An unmethylated luciferase vector was used as a control (bottom). (C) FLAG purification of TET2-CD and SMCHD1 full length (SMCHD1-FL) from Sf9 insect cells. Coomassie blue staining. (D) Inhibition of TET2-CD activity on fully methylated DNA in the presence of SMCHD1 as shown by combined bisulfite restriction analysis (COBRA) assay (BstU I cleavage indicates methylation). P.C., positive control with excess TET protein (18 g); N.C., negative control without TET treatment. Different molar ratios of SMCHD1 and TET protein (1.15 g) are shown. The H19 imprinting control region was analyzed. (E) Bisulfite sequencing analysis of H19 methylation analyzed in duplicates. Solid black circles indicate modified CpGs; open circles indicate TET-oxidized mCpGs. The purple arrows indicate BstU I sites. (F) Percentages of modified cytosines (%Me) of the different samples. P values were determined by Fishers exact test (two sided).

We then proceeded to purify recombinant active TET proteins (TET2-CD and TET2FL) and full-length SMCHD1 from baculovirus-infected cells (Fig. 2C). TET2-CD was catalytically more active than TET2FL and was therefore used in our in vitro activity assays. The in vitro activity of TET2 was initially tested using combined bisulfite restriction analysis (COBRA) (37), an assay in which cleavage with BstU I (5CGCG) indicates methylation at those sites. In this assay, addition of SMCHD1 inhibited TET activity in a dose-dependent manner (Fig. 2D). We further verified this effect by sodium bisulfite sequencing (Fig. 2, E and F). This assay monitors the end-product of TET activity, 5caC, which scores as unmodified cytosine in bisulfite sequencing due to decarboxylation and deamination of 5caC. SMCHD1 inhibited TET activity effectively at a 1:1 molar ratio and caused almost complete inhibition at a ratio of 2:1 (Fig. 2E). SMCHD1 is a DNA-binding protein with binding likely mediated through its hinge domain (3840). We propose that binding of SMCHD1 to DNA leads to an occlusion of TET activity from its DNA target.

Next, we created and verified several Smchd1 knockout (KO) clones of male mouse ES cells (mESCs) using CRISPR-Cas9 technology (Fig. 3A and fig. S4A). Using immuno-dot blots, we determined that these KO clones have moderately increased levels of 5hmC (fig. S4B), suggesting that the lack of SMCHD1 leads to stimulation of the 5mC oxidation process, which is consistent with the in vitro data showing that SMCHD1 inhibits TET activity. Globally, TET and DNMT protein expression was not significantly altered in SMCHD1-deficient cells (fig. S4, C and D).

(A) Absence of SMCHD1 protein in three CRISPR-Cas9 KO ES cell clones. (B) Heatmap of RNA-seq data indicates differentially expressed genes between WT (n = 3 clones) and SMCHD1 KO (n = 3 clones) ES cells. (C) Gene set enrichment analysis (GSEA) of the 2c-like ES cell signature. The gene set represents genes activated during zygotic genome activation in 2c mouse embryos and enriched in 2C::tomato+ cells (42). The x axis shows the log2 fold change of the KO/WT-ranked transcriptome. GSEA analysis was performed as previously described (49). (D) The heatmap indicates the differentially expressed 2c-like genes between WT (n = 6) and SMCHD1 KO (n = 6) ES cells including two technical replicates for each clone. Typical 2c-like genes, such as Dux (indicated by red arrow), Zscan4c, Dub1, and Usp17l family members (indicated by purple arrows) are indicated. (E) The density plot indicates activation of repeat elements in SMCHD1 KO cells. The x axis shows the log2 (fold change of KO/WT) of repeat element expression. The y axis shows the density.

Next, we performed whole-genome bisulfite sequencing (WGBS) on three wild-type (WT) and three Smchd1 KO ES cell clones. We observed lower levels of modified cytosines in the knockouts on all chromosomes except for the Y chromosome, which became hypermethylated (fig. S5A). This moderate global reduction of modified cytosines affected all genomic compartments except for CpG islands, which have constitutively very low levels of methylation (fig. S5B). Using DMRseq analysis (41), we identified 283 hypomethylated and 223 hypermethylated differentially methylated regions (DMRs) in the clones lacking SMCHD1 (fig. S5C and table S3). One extensively hypomethylated genomic region was the Pcdha gene cluster, which is a known binding region for SMCHD1 (40).

To look for functionally relevant epigenetic changes upon loss of SMCHD1, we performed RNA sequencing (RNA-seq) and identified 1236 up-regulated and 256 down-regulated genes [fold change > 2, false discovery rate (FDR) < 0.05] in the Smchd1 KO cells compared to WT cells (Fig. 3B and table S3). This is consistent with a role of SMCHD1 as a transcriptional repressor. Up-regulated genes, but not down-regulated or unchanged genes, had slightly reduced levels of DNA methylation near the transcription start sites (TSSs) (fig. S5, D to F). There was an overall negative correlation between the direction of methylation change in the SMCHD1 knockouts and the expression change of the DMR-associated genes (fig. S3G). Gene ontology analysis for DMR-associated differentially expressed genes pointed to an enrichment of pattern-specific and organ developmentspecific processes (fig. S3H).

Using gene set enrichment analysis (GSEA), one notably up-regulated set of genes was identified as 2c embryolike genes (Fig. 3, C and D), which reflected the up-regulation of 136 genes normally expressed in 2c mouse embryos as a feature of the initial wave of zygotic genome activation (ZGA) (42). A similar set of genes found in ZSCAN4+ mESCs (43) or in CAF1 knockdown ES cells (44) was also enriched in the group of genes up-regulated in SMCHD1 KO cells. A small percentage of WT ES cells sporadically express 2c embryo stagespecific (2C) transcripts, such as Zscan4, and cycle in and out of this specialized state (42). Among the genes up-regulated in the absence of SMCHD1 was the Zscan4 gene cluster (Fig. 4A). The up-regulation of Zscan4, which encodes a protein involved in telomere maintenance (45), was confirmed at the protein level using a pan-ZSCAN4 antibody (Fig. 4B). The fraction of ZSCAN4-positive cells in the ES cell population increased from ~1.5% in WT cells to about 12% in the SMCHD1 KO cells (Fig. 4, C and D). Various repetitive element families, such as murine endogenous retroviruses (MERVK and MERVL), which are activated by ZSCAN4 (46) and also derepressed during ZGA (42), showed increased expression upon loss of SMCHD1 (Fig. 3E).

(A) Integrative Genomics Viewer screenshots of RNA-seq track peaks across all Zscan4 family members in WT and SMCHD1 KO ES cells. (B) Up-regulation of ZSCAN4 protein in SMCHD1 KO cell lines. (C) The fraction of ZSCAN4-positive cells in the ES cell population is increased in the absence of SMCHD1. ES cells were immunostained for ZSCAN4 (green). DNA was counterstained with DAPI (4,6-diamidino-2-phenylindole) (blue). Scale bars, 50 m. (D) Fractions of ZSCAN4+ cells in WT ES cells and Smchd1-KO ES cells. t test was performed for statistical analysis (P < 0.001). Error bars indicate SEM (six independent experiments). (E) Browser view of RNA-seq tracks across the Dux locus in WT and SMCHD1 KO ES cells. The Dux gene itself is shaded in yellow. (F) Quantitative real-time polymerase chain reaction (qRT-PCR) data confirm Dux activation upon SMCHD1 loss. -Actin was used as a control. One-way ANOVA was performed for statistical analysis, comparing the mean of each group with the mean of the WT group (***P < 0.001). Data are for means SEM of three independent KO clones.

We then focused our attention on the Dux locus, which encodes a double-homeobox transcription factor (DUX) implicated in ZGA and in 2c-like transcriptomes (4749). We found that Dux is strongly (>10-fold) activated in SMCHD1-deficient ES cells (Fig. 4, E and F). Within the same locus, several other transcripts including the 5UTR (5 untranslated region) of a Dux pseudogene (Gm4981) were also up-regulated upon loss of SMCHD1 (Fig. 4E). WGBS (Fig. 5A) and manual bisulfite sequencing (Fig. 5B) revealed substantial demethylation of the Dux promoter in the SMCHD1 KO clones (WGBS, P < 1 105; manual bisulfite sequencing, P < 0.01; t test). We then incorporated a MERVL-promoter-dTomato reporter construct into the SMCHD1 KO and WT ES cells and purified dTomato-expressing (2c-like) cells by fluorescence-activated cell sorting (FACS) (Fig. 5C). In this cell population, methylation of the Dux promoter was even further reduced compared to unsorted cell populations, and methylation levels were lowest in the sorted SMCHD1 KO cells (Fig. 5, D and E). Using chromatin IP (ChIP) and quantitative polymerase chain reaction (qPCR), we observed that the SMCHD1 protein is present at the two different locations examined in the mouse Dux promoter in WT, but not in SMCHD1 KO ES cells (fig. S6A).

(A) Single CpG modification levels of WT and SMCHD1 KO samples at the Dux locus, as determined by WGBS. The differential methylation region is shaded in purple. CpGs are denoted with tick marks. Red circles, WT; blue circles, SMCHD1 KO. Circle size is proportional to coverage. A smoothed line is shown for each sample. (B) Manual bisulfite sequencing of the Dux promoter in WT and SMCHD1 KO cells. Solid black circles indicate modified CpG sites; open circles indicate unmodified CpG sites. Total percentages of modified cytosines (%Me) are shown. The primers are also indicated in (A). (C) Representative fluorescence image and FACS plot of 2C::tdTomato+ cells in the Smchd1 KO ES cell populations. (D) Methylation of the Dux promoter in the dTomato-expressing (FACS-sorted) Smchd1 KO cell population is further reduced. The data show bisulfite sequencing analysis of the Dux promoter in reporter-expressing WT and SMCHD1 KO ES cells. Total percentages of modified cytosines (%Me) are shown. (E) Percentages of modified cytosines at the Dux promoter determined from (B) and (D). One-way ANOVA was performed (*P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001). Error bars indicate SEM from triplicate clones (WT and Smchd1-KO) or duplicate samples (FACS-sorted 2c-Smchd1-KO cells).

To examine whether TET-mediated 5mC oxidation is involved in demethylation of the Dux promoter when SMCHD1 is not functional, we analyzed 5hmC by a pulldown method following derivatization of the hydroxymethyl group with biotin (fig. S6B) (50) or by single-base resolution TET-assisted bisulfite sequencing [TAB sequencing; (51)] (fig. S6C; see fig. S7 for complete results). Both methods indicated a significant increase in 5hmC at the Dux promoter in SMCHD1-deficient cells. Using ChIP, we observed enhanced binding of TET1 to the R2 region of the Dux promoter in SMCHD1 KO cells (fig. S6D). This is the same location where SMCHD1 is normally bound (fig. S6A) in WT ES cells, suggesting a shielding effect of SMCHD1 toward the 5mC oxidase.

To delineate the contribution of Dux to the entire set of genes up-regulated after loss of SMCHD1, we biallelically inactivated Dux in Smchd1 KO ES cells and also in WT ES cells (confirmed by extensive DNA sequencing because no reliable anti-DUX antibody was available; Fig. 6A). The subsequent RNA-seq analysis showed that 47 of the 136 up-regulated 2c-like genes in SMCHD1 KO cells were no longer up-regulated in the absence of a functional Dux gene (Fig. 6, B and C). One example of such Dux-dependent genes is the Zscan4 gene cluster, the expression of which was strictly dependent on WT Dux (Fig. 6D). In a published study (48), 5738 genes were linked to HA-DUX peaks. On the basis of this gene set, we found that still, 49 of the 2c-like genes that are up-regulated in our Smchd1 single KO were not bound by DUX. So, we can confirm that a fraction of up-regulated 2c-like genes (49 of 136) in Smchd1-KO cells may not be directly regulated by DUX. The data indicate that DUX is a substantial but not exclusive contributor to the 2c-like transcriptome induced in the absence of SMCHD1 (Fig. 6).

(A) The small guide RNA (gRNA) targeting region is immediately downstream of the start codon (ATG) of the Dux gene. Sanger sequencing confirmed frameshift mutations. Sequences targeted by the gRNA are in blue, and the PAM (protospacer adjacent motif) sequence is shown in red. Biallelic frameshift mutation was shown for each clone. The gRNA was applied in WT and in SMCHD1 KO ES cells to obtain the Dux single-knockout and Smchd1/Dux double-knockout ES cell clones, respectively. (B) A heatmap indicates the differentially expressed 2c-like genes between Dux/Smchd1 double-knockout (n = 3 clones) and Smchd1 single-knockout (n = 3 clones, two replicates each) ES cells. The blue color indicates genes no longer up-regulated in the double knockouts. (C) The pie chart shows that 47 of the 136 single-KO up-regulated 2c-like genes were no longer up-regulated in the absence of Dux in the Smchd1/Dux double KO. (D) RNA-seq tracks generated by the GVIZ package across the Zscan4 gene family members in WT ES cells (black), Smchd1 KO ES cells (red), Dux KO ES cells (blue), and Smchd1 plus Dux (double-KO) ES cells (green).

Our data showed an interaction of SMCHD1 with TET proteins within cells (Fig. 1 and figs. S1 and S2) and an inhibition of TET-induced 5mC oxidation by SMCHD1 (Fig. 2). In the absence of SMCHD1, 5hmC levels are increased (fig. S4; fig. S6, B and C; and fig. S7), suggesting that SMCHD1 is a negative regulator of TET activities. To obtain genetic support for this interaction, we used Tet1/2/3 triple-knockout ES cells (52) and deleted SMCHD1 from these cells, as confirmed by Western blotting and DNA sequencing (Fig. 7A and fig. S8A). The Dux gene could no longer be activated upon loss of SMCHD1 in TET-TKO cells (Fig. 7, B and C; compare to Fig. 4, E and F). Consequently, DUX target genes such as Usp17lc, Zscan4f, and Zfp352 (4749), as well as other SMCHD1-regulated genes such as 1700013H16Rik and Gm12690, could also no longer be activated (Fig. 7D). Of the 136 2c-like genes up-regulated in the absence of SMCHD1, only 69 were still up-regulated in the absence of TET activities (Fig. 7E). In TET-TKO cells, the Dux promoter was >90% methylated at CpG sites. However, unlike in WT ES cells (Fig. 5B), loss of SMCHD1 in these cells did not elicit significant DNA demethylation (Fig. 7F). These experiments demonstrate that TET proteins are required to cause demethylation of the Dux promoter and activation of Dux when SMCHD1 is dysfunctional, genetically confirming that SMCHD1 operates as a negative regulator of TET activity.

(A) Absence of SMCHD1 protein in three CRISPR-Cas9targeted Tet triple-knockout ES cell clones. (B) RNA-seq tracks across Dux in WT, Tet triple-knockout ES cells, and Tet-Smchd1 quadruple-KO cells. (C) Quantitative RT-PCR analysis of Dux expression in WT, Tet triple-knockout and Tet-Smchd1 quadruple-knockout cells. One-way ANOVA was performed. Data are for means SEM of three independent clones. (D) RNA-seq analysis across different genes in WT, Smchd1 KO, Dux KO, Smchd1 and Dux (double) KO, Tet triple-knockout, and Tet-Smchd1 quadruple-knockout ES cells. One-way ANOVA was performed, comparing the mean of each group (n = 3 clones each) with the mean of the Smchd1-KO group (**P < 0.01 and ****P < 0.0001). Error bars indicate SEM. (E) The number of up-regulated 2c-like genes is decreased in the absence of TET proteins. (F) Bisulfite sequencing analysis of the Dux promoter in Tet-TKO cells and quadruple-knockout cells. Percentages of modified cytosines (%Me) are shown. (G) Eighty-nine percent (75 and 14%) of significantly up-regulated genes in the SMCHD1 single KO are no longer up-regulated in the absence of TET proteins in the Tet-Smchd1 quadruple-KO (qKO) cells. (H) Model of SMCHD1 as a negative regulator of TET proteins at the Dux promoter. Black circles, 5mC; light blue circles, 5hmC; white circles, unmethylated CpGs.

In the Smchd1, Tet1, Tet2, and Tet3 quadruple-knockout cells, a total of 921 of 1236 genes (75%), which were up-regulated in Smchd1 single-knockout cells, could no longer be activated (Fig. 7G and fig. S8B). Examples are shown in Fig. 7D. An additional 179 genes (14%), normally activated upon SMCHD1 loss, were even down-regulated in these quadruple knockouts (Fig. 7G). These data indicate that the aberrant transcriptome in the absence of SMCHD1 depends to a substantial extent on the presence of TET proteins (fig. S8, C and D).

In this study, we identified SMCHD1 as a TET-interacting protein initially by MS. There have been several previous studies in which TET- or SMCHD1-interacting proteins were analyzed by proteomics, but this interaction was not found (27, 28, 30, 53). One recent publication did identify SMCHD1 as a TET2-interacting protein in their proteomics data (54). Some studies used higher salt concentrations (300 mM) for cell lysis or washing steps (30, 53), but others used conditions similar to ours (27, 54). It is possible that the relatively milder extraction conditions we used may explain that we did find the TET-SMCHD1 association. The SMCHD1-TET complexes may be disrupted by 300 mM NaCl. Extraction and washing steps are certainly a determining factor for identification of interacting proteins. Using higher salt concentrations (>150 mM) will increase the risk of disassembling protein complexes. Other data in our manuscript, including endogenous co-IP, BiFC (which does not use cell extraction or salt washes), and the genetic studies, further support the TET-SMCHD1 interaction.

From our data, we propose a model in which SMCHD1 acts as a negative regulator of TET proteins by inhibiting their activity at target sequences (Fig. 7H). This regulation likely involves a shielding mechanism because DNA hypomethylation is most pronounced at known SMCHD1-bound genomic regions (e.g., Dux and Pcdha gene cluster). SMCHD1 may inhibit TET either by direct DNA binding or via its presence in heterochromatin. Localized TET inhibition or trapping of TET by SMCHD1 may also lead to a slight reduction in global 5mC oxidation, which is reversed upon SMCHD1 depletion leading to a moderate global DNA hypomethylation. Our data are conceptually consistent with other models that have posited that SMCHD1 functions in chromatin as an antagonistic protein against CCCTC binding factor (CTCF) binding (40), either by a shielding mechanism or by promoting DNA methylation that interferes with binding of CTCF. SMCHD1 also has been shown to be a protecting factor against formation of H3K27me3 by the Polycomb complex (25).

SMCHD1 loss-of-function mutation, often affecting its ATPase domain, is a hallmark of the human muscular dystrophy disease facioscapulohumeral dystrophy (FSHD2), which is characterized by inappropriate activation of the DUX4 gene, which is the human homolog of mouse Dux (5557). It is of interest to speculate that loss of TET restriction by dysfunction of SMCHD1 may lead to TET-induced hypomethylation of DUX4 control regions and unscheduled expression of DUX4, perhaps starting already during human embryonic development and later manifesting itself in muscle disease.

Our data suggest that SMCHD1 is critical for Dux suppression in mESCs, thus controlling the 2c-like state. Furthermore, SMCHD1 plays a key role in de novo methylation of CpG islands on the inactive X chromosome during mouse development (23). Recent data have shown, however, that loss of SMCHD1 in somatic cells does not lead to X chromosome reactivation (24, 25). Together, the existing data suggest that SMCHD1 functions in promoting de novo DNA methylation during development rather than in mediating methylation maintenance, and we propose the following mechanism: SMCHD1 operates in these critical DNA methylation events by inhibiting TET-mediated 5mC oxidation and demethylation at its target regions, as we show in this study, thereby shifting the balance of methylation versus demethylation toward the methylated state (Fig. 7H). When SMCHD1 is lost, but DNA methylation remains high in the absence of TETs (reduced DNA methylation dynamics), Dux expression may not be occurring because of inhibition of transcription by DNA methylation. On the other hand, in absence of SMCHD1 and presence of TET activity, and thus higher methylation-demethylation dynamics, Dux will be activated. This pathway is important in inhibiting the totipotent (2c-like state) of ES cells. Although a role of SMCHD1 in inactivation of Dux in late 2c mouse embryos has recently been proposed (58), this event seems initially independent of DNA methylation inasmuch as the Dux promoter region is almost completely unmethylated in 2c and 4c mouse embryos (59); therefore, the de novo methylation events must occur later during development. Further studies are needed to confirm whether SMCHD1 is responsible for the remethylation of the Dux locus during early embryo development and whether inhibition of TET proteins plays an important role in this process.

FLAG-tagged TET3FL or FLAG-tagged TET3S plasmids (31) were transfected into 293T cells. After 48 hours, cells were lysed in 10 mM tris-HCl (pH 7.4), 150 mM NaCl, 0.125% NP-40, and 2.5 mM EDTA. The lysate was added to M2 anti-FLAG affinity beads (Sigma-Aldrich), which were agitated overnight at 4C. After extensive washing with lysis buffer containing 200 mM NaCl followed by washing with 20 mM tris-HCl (pH 7.6) and 200 mM NaCl, the IP beads were mixed with 5 SDS loading buffer and heated for 10 min at 80C. Each protein sample was loaded onto 12% SDSpolyacrylamide gel electrophoresis (PAGE) gels. After visualization using Coomassie blue, the gel lanes were cut into eight segments and sliced into small pieces for in-gel digestion. Gel pieces were washed three times with distilled water to remove SDS and dehydrated using 100% acetonitrile. Proteins were treated with 10 mM dithiothreitol (DTT) in 50 mM NH4HCO3 for 45 min at 56C. After washing with 100% acetonitrile, alkylation of cysteines was performed with 55 mM iodoacetamide in 50 mM NH4HCO3 for 30 min in the dark. Last, each dehydrated gel piece was treated with sequencing-grade modified trypsin (12.5 ng/l; Promega, Madison, WI) in 50 mM NH4HCO3 buffer (pH 7.8) at 37C overnight. Following digestion, tryptic peptides were extracted with 5% formic acid in 50% acetonitrile solution at room temperature for 20 min. The supernatants were collected and dried in a SpeedVac. Samples were resuspended in 0.1% formic acid and were purified and concentrated using C18 ZipTips (Millipore, MA) before MS analysis.

Peptide separation was performed using a Dionex UltiMate 3000 RSLCnano system (Thermo Fisher Scientific). Tryptic peptides from bead columns were reconstituted using 0.1% formic acid and separated on a 50-cm EASY-Spray column with a 75-m inner diameter packed with 2-m C18 resin (Thermo Scientific, USA) over 120 min (300 nl/min) using a 0 to 45% acetonitrile gradient in 0.1% formic acid at 50C. The liquid chromatography (LC) was coupled to a Q Exactive Plus mass spectrometer with a nano-ESI source (Thermo Fisher Scientific). Mass spectra were acquired in a data-dependent mode with an automatic switch between a full scan with 10 data-dependent tandem MS (MS/MS) scans. Target value for the full-scan MS spectra was 3,000,000 with a maximum injection time of 120 ms and a resolution of 70,000 at mass/charge ratio (m/z) of 400. The ion target value for MS/MS was set to 1,000,000 with a maximum injection time of 120 ms and a resolution of 17,500 at m/z 400. Dynamic exclusion of repeated peptides was applied for 20 s.

The acquired MS/MS spectra were searched using SequestHT on Proteome Discoverer (version 2.2, Thermo Fisher Scientific) against the Swiss-Prot database. Briefly, precursor mass tolerance was set to 10 ppm (parts per million) and MS/MS tolerance was set at 0.02 Da. FDRs were set at 1% for each analysis using Percolator. From the Sequest search output, peptide data were default values of Proteome Discoverer. Label-free quantitation was performed using peak intensity for unique and razor peptides of each protein. Normalization was done using total peptide amount.

To identify TET2 interaction partners, we transfected FLAG-tagged TET2FL with N-terminal FLAG and HA tags (Addgene plasmid no. 41710; a gift from A. Rao) into 293T cells, harvested the cells after 48 hours, and processed them similar as described below for ES cells. ES cells in which the SMCHD1 protein was tagged endogenously with a C-terminal FLAG tag were prepared as follows: We followed the protocol of CETCh-seq (60). Briefly, we designed guide RNA (gRNA; 5GTCTTCAGAAATGCTCAGTT) and cloned it into pSpCas9-2A-puromycin (PX459, Addgene; a gift from F. Zhang) to target and cut near SMCHD1s stop codon. We cloned 700 to 800base pair(bp)long homology arms of Smchd1 into the pFETCh-donor backbone vector (Addgene plasmid no. 63934; gift from E. Mendenhall and R. M. Myers) by Gibson assembly reaction. Then, we cotransfected the donor plasmid and gRNA plasmid at a ratio of 2:1. The single FLAG-tagged cell clones were selected in puromycin (1.5 g/ml) and G418 (200 g/ml). The DNA of selected clones was extracted and sequenced to detect the presence of the FLAG tag. Tagged SMCHD1 protein was detected by Western blot with anti-FLAG antibody and anti-SMCHD1 antibody.

The cells were harvested and lysed in ice-cold lysis buffer consisting of 10 mM tris-HCl (pH 7.4), 150 mM NaCl, 0.125% (v/v) NP-40, cOmplete protease inhibitor tablets (Sigma-Aldrich; 1 tablet/10 ml), and 2.5 mM EDTA at 4C for 1 hour. We centrifuged the cell lysate at 40,000g for 60 min at 4C, then transferred the supernatant onto equilibrated anti-FLAG M2 affinity beads (Sigma-Aldrich), and incubated the slurry on a rotation wheel overnight at 4C. We washed the beads with ice-cold wash buffer containing 10 mM tris-HCl (pH 7.4), 250 mM NaCl, 0.125% (v/v) NP-40, cOmplete (1 tablet/10 ml), and 2.5 mM EDTA on a rotation wheel at 4C for 5 min and repeated the washing five times. Following the final wash, the beads were then eluted twice with elution buffer containing 20 mM tris-HCl (pH 7.5), 150 mM NaCl, 0.02% (v/v) Tween 20, and 3 FLAG peptide (150 g/ml) for 5 min. The eluted samples were then mixed with 5 SDS loading buffer and denatured for 10 min at 99C. The protein samples were loaded and separated on a mini gel (Bio-Rad Mini-PROTEAN TGX 4 to 20%). The gel was stained using Coomassie blue and destained water. The cut gel samples were digested with trypsin and injected into a Thermo Orbitrap Fusion Lumos mass spectrometer at the University of Massachusetts Proteomics Core Facility. The data were searched against the Swiss-Prot human/mouse database using the Mascot search engine through Proteome Discoverer software.

Full-length SMCHD1 was cloned into the pFastBac vector (Thermo Fisher Scientific) with a FLAG tag. We confirmed all expression vectors by Sanger sequencing. For FLAG-tagged SMCHD1 and TET2 protein expression, the bacmid DNA was transfected into Sf9 cells (Bac-to-Bac baculovirus expression system; Thermo Fisher Scientific) to obtain the passage 0 (P0) baculovirus at 96 hours after transfection. Then, we continued to generate P1 baculovirus by infecting the cells with P0 baculovirus. Proteins were expressed for 72 hours using 1000 ml of insect cells (2 million cells/ml) after transfecting P1 virus, and the cell pellet was resuspended in lysis buffer [50 mM Hepes (pH 7.5), 300 mM NaCl, 0.2% (v/v) NP-40, cOmplete, EDTA-free Protease Inhibitor Cocktail (Roche, 1 tablet/10 ml), and Benzonase Nuclease (10 U/ml) (Millipore) to destroy nucleic acids]. The lysate was cleared by centrifugation at 20,000g for 60 min. Anti-FLAG M2 affinity gel (Sigma-Aldrich) was equilibrated in lysis buffer following the manufacturers instructions. We incubated the cleared lysate with equilibrated FLAG M2 affinity gel at 4C for 2 hours. Bound protein was then washed five times with wash buffer [50 mM Hepes (pH 7.5), 150 mM NaCl, and 15% (v/v) glycerol]. We eluted the protein with the wash buffer containing 3 FLAG peptide (100 g/ml) (Sigma-Aldrich). Purified FLAG-tagged proteins were concentrated by Amicon Ultra Centrifugal Filters and DTT was added to 1 mM, then aliquots were flash-frozen in liquid nitrogen, and stored at 80C. The purification of TET proteins from mammalian cells was performed as described using anti-FLAG purification, as described above.

We performed TET protein in vitro assays on the basis of the established TET oxidation reaction (see TAB sequencing reactions for details). For a P.C., 18 g of TET2-CD protein was used to treat 500 ng of Sss Imethylated genomic DNA to get fully oxidized DNA containing 5caC. For a negative control (N.C.), no TET protein was used. For the testing samples, 1.15 g of TET protein was used to treat Sss Imethylated genomic DNA, and different amounts of recombinant full-length SMCHD1 were added into the TET oxidation reaction. Bovine serum albumin (BSA) was used as a control. For a blank control, only the elution buffer for protein purification was used to keep the volume of the reactions identical. After the TET oxidation reaction, we performed bisulfite conversion treatment on the purified DNA with the EZ DNA Methylation-Gold Kit (Zymo Research). This treatment converts the TET reaction product 5caC to uracil. For COBRA, BstU I was used to digest the PCR products obtained after bisulfite conversion. For sequence analysis, the PCR products obtained after bisulfite conversion were cloned into the Topo TA cloning vector, and clones were sequenced.

J1 mESCs (from American Type Culture Collection) were cultured under feeder-free conditions on 0.1% gelatincoated tissue culture plates in KO DMEM (Dulbeccos modified Eagles medium; Gibco, 10829-018) supplemented with 15% fetal bovine serum, LIF (1000 U/ml) (Millipore, ESG1106), 1 nonessential amino acids (Gibco, 11140-050), 100 M -mercaptoethanol (Invitrogen, 21985-203), and 2 mM l-glutamine (Gibco, 25030-081).

mESCs were transfected with pSpCas9-2A-puromycin (PX459) plasmids (Addgene plasmid no. 62988; a gift from F. Zhang) carrying the appropriate Smchd1 sgRNAs, by using the BioT transfection reagent (Bioland, B01-01) according to the manufacturers instructions. Single-cell clones were selected in puromycin (1.5 g/ml). To inactivate the Dux gene in WT and Smchd1 KO ES cell clones, we transfected WT cells or Smchd1 KO ES cells with a pSpCas9-2A-blasticidin plasmid carrying the appropriate Dux sgRNA. Single-cell clones were selected with blasticidin (8 g/ml). We used the same pSpCas9-2A-puromycin-gRNA vector to knock out Smchd1 in Tet1/Tet2/Tet3 triple-knockout ES cells. The DNA was extracted and sequenced to detect the presence of WT and/or mutant alleles. Three independently derived WT, three homozygous mutant Smchd1-KO clones, three homozygous Dux-knockout clones, three homozygous Smchd1/Dux double-knockout clones, and three homozygous mutant Tet1/Tet2/Tet3/Smchd1 quadruple-knockout clones were selected and used in this study.

For mammalian expression vectors, the Tet3FL, Tet3S, and Tet1 expression vectors were constructed as previously described (31). The pEF-Smchd1-FLAG expression vector was a gift from M. Blewitt. The pFastBac1-hTET2-CS construct was provided by R. Kohli (61). Fragments of TET3 and SMCHD1 were cloned into pEF-DEST51 expression vectors (Invitrogen, 430106). For co-IP of exogenously expressed full-length proteins, 293T cells were transfected by using a BioT transfection regent with plasmids expressing the appropriate FLAG- or V5-tagged proteins (5 g of each plasmid on a 10-cm dish). 293T cells were harvested at 48 hours after transfection, and nuclear lysates were purified by NE-PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Fisher Scientific, 78835) according to the manufacturers instructions. The nuclear lysates were incubated with 2 g of the appropriate antibody for 2 hours and then incubated with 20 l of Dynabeads Protein G (Invitrogen, 00671375) overnight to collect the immune complexes. We washed the immune complexes with ice-cold wash buffer containing 10 mM tris-HCl (pH 7.4), 150 mM NaCl, 0.125% (v/v) NP-40, cOmplete (1 tablet/10 ml), and 2.5 mM EDTA. The samples were boiled in SDS-PAGE loading buffer, followed by SDS-PAGE, and Western blotting. For co-IP of protein domains, 293T cells were transfected with plasmids expressing the appropriate FLAG- or V5-tagged proteins (5 g of each plasmid on a 10-cm dish). 293T cells were harvested 48 hours after transfection and lysed in IP buffer [10 mM tris-HCl (pH 7.4), 150 mM NaCl, 0.125% NP-40, and 2.5 mM EDTA], supplemented with protease inhibitor cocktail (Roche).The cell lysate was centrifuged at 12,000g for 15 to 30 min at 4C, incubated with 2 g of the appropriate antibody for 2 hours, and then incubated with 20 l of Dynabeads Protein G (Invitrogen, 00671375) overnight. The beads were then washed six times with IP buffer [10 mM tris-HCl (pH 7.4), 150 mM NaCl, 0.125% NP-40, and 2.5 mM EDTA]. Last, the samples were boiled in SDS-PAGE sample loading buffer, followed by SDS-PAGE, and Western blotting with the indicated antibodies. For endogenous co-IP, preparation of nuclear extract, buffer preparation, and co-IP, we used the Nuclear Complex Co-IP Kit (Active Motif, 54001) according to the manufacturers instructions. We used 5 g of antibody for endogenous co-IP: SMCHD1 (Bethyl, A302-871A), TET1 antibody (GeneTex, GTX124207), TET2 antibody (Cell Signaling Technology, 92529), and TET3 antibody (31). After the IP reactions, we performed Western blotting with the indicated antibodies.

ES cells were washed twice with phosphate-buffered saline (PBS) and fixed in 4% paraformaldehyde in PBS for 15 min at room temperature. The fixed cells were permeabilized in 0.4% Triton X-100 in PBS at room temperature for 30 min, washed twice with PBS, and blocked for 30 min with 1% BSA in PBS. Cells were then incubated for 1 hour with anti-ZSCAN4 antibody (1:1000; Millipore, ab4340). After washing several times in 0.05% Tween 20 in PBS, the cells were incubated with Alexa Fluor 488 goat anti-rabbit (1:1000; Invitrogen, A27034) secondary antibody at room temperature for 1 hour and washed again three times. Then, we treated the cells with ProLong Gold anti-fade reagent with DAPI (4,6-diamidino-2-phenylindole) (Invitrogen, P36935) and acquired fluorescence images using a Nikon TE300 microscope with NIS-Elements AR 4.20.01.

FACS analysis was performed with a Beckman cell sorting system. Smchd1-KO mESCs or WT cells containing the 2C::tdTomato reporter (Addgene plasmid no. 40281; a gift from S. Pfaff) were subjected to FACS sorting with a MoFlo Astrios instrument (Beckman Coulter).

We seeded 1 105 293T cells into 24-well plates before transfection. Cells were transfected with the TET3S and SMCHD1 expression vectors, 47.5 ng of pGL3 luciferase reporter vector (methylated or unmethylated), and 2.5 ng of internal control Renilla luciferase reporter vector (pRL-CMV, Promega, Madison, WI). We harvested the cells 48 hours after transfection. All transfections were carried out at least in three independent experiments and in triplicate. Firefly and Renilla luciferase activities were assayed with the Dual-Luciferase assay kit (Promega) according to the manufacturers instructions. The firefly luciferase activities were normalized relative to Renilla activity.

BiFC assays were performed for determining the in vivo interaction between SMCHD1 and TET3. The assay is based on interactions between bait and prey proteins that bring together two nonfluorescent fragments of a fluorescent protein (GFP) and then form a functional chromophore. In this study, all recombinant expression vectors were constructed on empty backbones of HA-GFP1-10-pDEST-C and FLAG-GFP11-pDEST-C (Addgene plasmid nos. 118369 and 118367; gifts from M. Vartiainen). We used human embryonic kidney 293T cells, which were cotransfected with pEF-SMCHD1-HA-GFP1-10 and pEF-TET3-FLAG-GFP11 expression vectors using the BioT transfection regent. At 48 hours after transfection, the cells were analyzed by confocal microscopy (Zeiss LSM 880 microscope) and by Cell Cytometer Counter (Celigo) to identify the interactions. Cotransfection of pEF-OGT-HA-GFP1-10 and pEF-TET3-FLAG-GFP11 was used as a P.C. Cotransfection of pEF-SMCHD1-HA-GFP1-10 and pEF-ccdB-FLAG-GFP11 and cotransfection of pEF-ccdB-HA-GFP1-10 and pEF-TET3-FLAG-GFP11 were the N.C.s.

AlphaScreen (PerkinElmer) assays were performed for determining the in vitro interaction between biotin-SMCHD1 and His-tagged TET proteins following the manufacturers protocol. Briefly, 200 nM SMCHD1-biotin and 200 nM TET2FL-His or TET2-CD-His were incubated at room temperature for 1 hour. The protein sample was then incubated with streptavidin-coated donor beads (final concentration of 10 g/ml) and nickel-chelate acceptor beads (final concentration of 10 g/ml) in a total volume of 100 l of AlphaScreen buffer containing 50 mM MOPS (pH 7.4), 50 mM NaF, 50 mM 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate, and BSA (0.1 mg/ml) for 1 hour in the dark at room temperature. The photon counts were detected in 384-well plates by the EnVision Alpha reader (PerkinElmer).

Western blots and dots blot were performed as previously described (31), with minor modifications. For Western blots, we lysed the cells in buffer containing 50 mM tris-HCl (pH 7.4), 150 mM NaCl, 1% Triton X-100, 1 mM EDTA, and proteinase inhibitor cocktail (Roche, 11873580001) on ice for 60 min followed by centrifugation at 12,000g for 15 min at 4C. The lysates were separated on 4 to 15% SDS-polyacrylamide gels and transferred onto PVDF (polyvinylidene difluoride) membranes (Bio-Rad) by wet transfer at 4C. We incubated the membranes with blocking buffer (5% nonfat milk and 0.1% Tween 20 in PBS) for 1 hour at room temperature and then with the indicated primary antibody at 4C overnight. After washing with PBS-Tween (0.1%), the membranes were incubated with peroxidase-conjugated secondary antibodies for 1 hour at room temperature. Signals were detected using an ECL Prime detection reagent (GE Healthcare). Antibodies used for Western blots were as follows: anti-SMCHD1 (1:2500; Abcam, ab31865), anti-SMCHD1 (1:2500; Bethyl, A302-871A), anti-TET1 (1:1000; GeneTex, GTX124207), anti-TET2 (1:2000; Cell Signaling Technology, 92529) or anti-TET2 (1:1000; ProteinTech, 21207-1-AP), anti-DNMT1 (1:1000; Novus Biologicals, NB100-56519), anti-DNMT3A (1:1000; Novus Biologicals, NB120-13888), anti-DNMT3B (1:1000; Novus Biologicals, NB300-516), anti-tubulin (1:10,000; Abcam, ab7291), anti-ZSCAN4 (1:2500; Millipore, AB4340), HRP (horseradish peroxidase) goat anti-rabbit immunoglobulin G (IgG) (1:10,000; Active Motif, 15015), and HRP goat anti-mouse IgG (1:10,000; Active Motif, 15014). For dot blots, genomic DNA was purified with Quick-DNA Miniprep Plus kits (Zymo Research, D4070) followed by ribonuclease A treatment. The DNAs were then sonicated and purified using a QIAquick PCR purification kit (Qiagen, 28104). The purified DNAs were serially diluted and denatured in TE buffer at 98C for 10 min and then immediately chilled on ice for 10 min. The DNAs were then spotted onto a wetted GeneScreen Plus hybridization nylon membrane (PerkinElmer, NEF988001PK) with a Bio-Dot apparatus (96-well; Bio-Rad). The blotted membranes were ultraviolet cross-linked. After incubation with the blocking buffer (5% nonfat milk and 0.15% Tween 20 in PBS) for 2 hours at room temperature, the membranes were then incubated with anti-5hmC antibody (1:8000; Active Motif, 39769) or anti-5mC antibody (1:1000; Active Motif, 39649) for 1 hour at room temperature. After washing with PBS-Tween (0.15%), the membranes were incubated with peroxidase-conjugated secondary antibodies for 1 hour at room temperature. Signals were detected using an ECL Prime detection reagent (GE Healthcare).

DNA was purified with a Quick-DNA Miniprep Plus kit (Zymo Research, D4070). The bisulfite conversion was performed with the EZ DNA Methylation-Gold Kit (Zymo Research, D5005) according to the manufacturers instructions. PCR primer sequences for amplification of specific targets in bisulfite-treated DNA were 5TTTGTTAGGGATGAGGAGTT (forward) and 5AAACCTCTAATAAACCTCTTTA (reverse) for the Dux promoter. For sequence analysis, the PCR products obtained after bisulfite conversion were cloned into the Topo TA cloning vector (Thermo Fisher Scientific, 450030), and clones were sequenced. For TAB sequencing, 500 ng of genomic DNA was incubated with T4-glucosyltransferase (10 U/l) [New England Biolabs (NEB)], 2 mM uridine diphosphateglucose (NEB), and 10 CutSmart Buffer (NEB) at 37C overnight, and then DNA was purified using standard phenol chloroform extraction followed by ethanol precipitation. Next, we performed the TET oxidation reaction as follows: The purified DNA was incubated with 12.5 g of in-house purified TET2-CD protein, gelatin (1600 g/ml), TET oxidation buffer 1 [1.5 mM Fe(NH4)2(SO4)2], and TET oxidation buffer 2 [83 mM NaCl, 167 mM Hepes (pH 7.5), 4 mM ATP, 8.3 mM DTT, 3.3 mM -ketoglutarate, and 6.7 mM sodium ascorbate] at 37C for 2 hours. Then, we added 1 l of proteinase K (20 mg/ml) to the reaction, mixed well, and incubated at 50C for 10 min. We performed phenol/chloroform purification and ethanol precipitation and dissolved the purified DNA in TE buffer [10 mM tris-HCl (pH 8.0) and 0.1 mM EDTA]. Last, we performed the bisulfite conversion treatment of the purified DNA with the EZ DNA Methylation-Gold Kit (Zymo Research). For sequence analysis, the PCR products obtained after bisulfite conversion were cloned into the Topo TA cloning vector and clones were sequenced.

Total RNA was extracted from whole cells with a PureLink RNA mini kit (Ambion, 12183020), according to the manufacturers instructions. Total RNA integrity was verified with an Agilent 2100 Bioanalyzer (Agilent Technologies) and quantified with a NanoDrop 8000 instrument (Thermo Fisher Scientific). RNA-seq libraries were prepared from total RNA with the KAPA RNA HyperPrep kit with RiboErase (KAPA Biosystems). Library size distributions were validated on the Bioanalyzer (Agilent Technologies). Sequencing was performed with an Illumina NextSeq500 machine and 75-bp single-end reads were obtained. Library demultiplexing was performed following Illumina standards.

Trim Galore (version 0.4.0) was used to trim the 75-bp single-end reads. Reads were aligned to the mouse genome mm9 with STAR (version 2.5.1), and gene count was performed with STAR. Gene counts matrix was imported into R (version 3.5.1). Differential gene expression was determined with the Limma (version 3.38.2) statistical package19. Differential expression P values were adjusted for multiple testing correction using the Benjamini-Hochberg method in the stats package. Statistical significance for differentially expressed genes was fold change > 2 with q < 0.05. Heatmaps were generated with Pheatmap package. GSEA was performed with the GSEA preranked module of the Broad Institutes GenePattern algorithm (62). For the GSEA analysis, all data were compared with the 2c-like gene set of Macfarlan et al. (42). One thousand gene-list permutations were used to determine the FDR value and the classic scoring scheme, according to methods previously described (49). Repeat element analysis was done by calculating read counts falling completely within RepeatMasker-annotated repeat elements, and the density plot was generated with R.

For the WGBS library preparations, we used Swift, Accel-NGS Methyl-Seq DNA Library Kit (Swift Biosciences, 30024), and Zymos EZ DNA Methylation-Lightning kit (Zymo Research, D5030), according to the manufacturers instructions. Sequencing was performed with an Illumina HiSeq X with 150-bp paired-end read runs.

Paired-end whole-genome bisulfite reads were trimmed using TrimGalore!, version 0.5.0 (https://github.com/FelixKrueger/TrimGalore) with the following parameters to remove library preparation artifacts and low quality bases: --length 50, --clip_R1 10, --clip_R2 18, --three_prime_clip_R1 10, and --three_prime_clip_R2 10. Trimmed reads were aligned to the mm9 primary chromosomes using Bismark version 0.19.0 (63) and Bowtie2 version 2.3.3.1 (64) with the following parameters: -X 1000, --nucleotide_coverage, and --bowtie2. Duplicates were marked and removed using the deduplicate_bismark script provided with Bismark. CpG methylation values were extracted using the bismark_methylation_extractor script provided with Bismark and the following parameters: --no_overlap, --comprehensive, --merge_non_CpG, and --cytosine_report. We used DMRseq version 0.99.0 (41) to identify DMRs. Briefly, CpG loci with fewer than five reads were not considered for DMR calling, and a single CpG coefficient cutoff of 0.05 was used for candidate regions. Significant DMRs were identified using a q value < 0.05. Each CpG methylation value was averaged based on groups. t test showed a significant methylation difference between WT and KO (P < 2.2 1016). DMR-related genes were determined by defining a DMR within a genes proximity. DMRs were identified by bedtools (TSS 2K) and the Genomic Regions Enrichment Annotations Tool (GREAT) (65) and by long-range interaction between the DMRs and differentially expressed genes. We identified long-range interactions between the DMRs and differentially expressed genes by analyzing the Hi-C data in J1 ESC downloaded from GEO (Gene Expression Omnibus) dataset GSM862720 (SRR443885). Trim Galore (version 0.4.3) was used for adapter trimming for Hi-C data; HICCUP (version 0.5.9) was used for mapping and performing quality control. Significant interactions (default: P < 0.001 and z score > 1.0) were identified with HOMER, with a 40-kb resolution. Hi-C gene annotation involved identifying interactions with gene promoters, defined as 2 kb of a gene TSS (fig. S5G).

5hmC containing DNA was enriched by the EpiJET 5hmC Enrichment Kit (Thermo Fisher Scientific, K1491BID), according to the manufacturers instructions. The enriched DNA was then used for qPCR analysis of the Dux locus. qPCR reactions with target-specific primers included the forward (5GCTTTGCTACCAGGGAGGAG) and reverse (5GATCTTGAGCTGTGGGCCTG) primers for Dux region 1 and the forward (5CTAGCGACTTGCCCTCCTTC) and reverse (5GCTGATCAAGGAGGGGTTCC) primers for Dux region 2. PCR reactions were performed at 95C for 10 min followed by 50 cycles at 95C for 15 s, 57C for 30 s, and 72C for 30 s, using Power SYBR Green master mix (Applied Biosystems, 1809579) on a CFX96 real-time PCR cycler (Bio-Rad).

Total RNAs were isolated from cultured cells by using the PureLink RNA Mini Kit (Ambion). The SuperScriptIII reverse transcriptase (Invitrogen, 18080051) was used for reverse transcription of RNA, according to the manufacturers instructions. Real-time qPCR reactions with target-specific primers (available upon request) were performed at 50C for 2 min and 95C for 10 min followed by 50 cycles at 95C for 15 s and 60C for 1 min using TaqMan Gene Expression master mix (Applied Biosystems, 4369016) on a CFX96 real-time PCR cycler (Bio-Rad). The cDNA levels of target genes were analyzed using comparative Ct methods and normalized to internal standard, -actin.

ChIP was performed as previously described (31), with minor modifications. Briefly, cells were cross-linked with 1% formaldehyde (Thermo Fisher Scientific, 28908) in fixing buffer [50 mM Hepes (pH 7.5), 100 mM NaCl, 1 mM EDTA, and 0.5 mM EGTA] for 10 min at room temperature, and chromatin from lysed nuclei was sheared to 300- to 500-bp fragments using a Covaris E220 sonicator (Covaris; Woburn, MA). Chromatin fragments were incubated with 5 g of the appropriate antibody [SMCHD1 (Abcam, ab31865), TET1 (GeneTex, GTX125888), or IgG control (Santa Cruz Biotechnology; SC-2027)] overnight at 4C with rotation. For ChIP-qPCR, real-time qPCR was carried out with a CFX96 real-time PCR cycler (Bio-Rad). Each sample was analyzed in quadruplicate. Data were analyzed according to the 2(Ct of IP sample Ct of IgG sample) method and are presented as fold change of a percentage of input. PCR primer sequences are available upon request.

Acknowledgments: We thank G. Xu for providing Tet1/2/3 triple-knockout ES cells and H. Liu, P. Li, Z. Yuan, M. Du, K. Melcher, and S.-G. Jin for the advice and discussions. We thank the genomics, flow cytometry, high-throughput computing, and bioinformatics core facilities at the Van Andel Institute for the support. Funding: This work was supported by an Innovation Award from the Van Andel Institute. Author contributions: Z.H., J.Y., and G.P.P. designed and initiated the study and planned experiments; Z.H. performed interaction studies, genetic knockouts, and epigenomics and transcriptomics experiments; J.Y. and K.K. performed MS and analyzed the data; Z.H. analyzed the DNA methylation and gene expression data, with support from B.K.J.; W.C. provided experimental support; Z.H. and G.P.P. prepared the manuscript. All authors discussed the results and commented on the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. Genome-wide datasets generated in this study were deposited at the GEO database under the accession numbers GSE126468.

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The chromosomal protein SMCHD1 regulates DNA methylation and the 2c-like state of embryonic stem cells by antagonizing TET proteins - Science Advances

North America to be the Torchbearer to Stem Cell Characterization And Analysis Tools Market NeighborWebSJ – NeighborWebSJ

Stem cell characterization is the study of tissue-specific differentiation. Thera are various type of stem cell such as embryonic stem cell, epithelial stem cell and others. Further, various techniques are used to characterized stem cells such as immunological techniques, used for depiction of different population of stem cells. These techniques are generally based on immunochemistry using staining technique or florescent microscopy. Besides, stem cells characterization and analysis tools are used against target chronic diseases. In 2014, the San Diego (UCSD) Health System and Sanford Stem Cell Clinical Center at the University of California announced the launch of a clinical trial, in order to assess the safety of neural stem cellbased therapy in patients with chronic spinal cord injury.

The factors driving the growth of stem cell characterization and analysis tools market due to increasing chronic disorders such as cancer, a diabetes and others. In addition, increasing awareness about among people about the therapeutic potency of stem cells characterization in the management of effective diseases is anticipated to increase the demand for stem cell characterization and analysis tools. Further, there are various technologies such as flow cytometry which is used to characterize the cell surface profiling of human-bone marrow and other related purposes are expected to increase the growth of stem cell characterization and analysis tools market. In addition, increasing investment by private and public organization for research activities are likely to supplement the market growth in near future.

On the other hand, the unclear guidelines and the technical limitation for the development of the product are expected to hamper the growth of stem cell characterization and analysis tools market.

Rapid increase in corona virus all around the world is expected to hamper the growth of stem cell characterization and analysis tools market. The virus outburst has become one of the threats to the global economy and financial markets. The impact has made immense decrease in revenue generation in the field of all healthcare industry growth for the market in terms of compatibility and it has led in huge financial losses and human life which has hit very hard to the core of developing as well as emerging economies in healthcare sector. It further anticipated that such gloomy epidemiological pandemic environment is going to remain in next for at least some months, and this is going to also affect the life-science market which also include the market of stem cell characterization and analysis tools market.

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Based on the Products and Service Type, stem cell characterization and analysis tools market are segmented into:

Based on the Technology, stem cell characterization and analysis tools market are segmented into:

Based on the Applications, stem cell characterization and analysis tools market are segmented into:

Based on the End User, stem cell characterization and analysis tools market are segmented into:

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Based on the segmentation, human embryonic stem cell is expected to dominate the market due to their indefinite life span and higher totipotency as compared to other stem cells. Further, on the basis of technology segmentations, cell production is anticipated to increase the demand for stem cell characterization and analysis tools due to their emerging applications for stem cells in drug testing in the management of the effective diseases. Furthermore, on the basis of application segmentations, oncology is expected to show significant growth rate due to increase in the number of pipelines products for the treatment of cancers or tumors. Based on the end user, pharmaceutical and biotechnology companies are expected to dominate the market due to rising global awareness about the therapeutics research activities.

Geographically, the global stem cell characterization and analysis tools market is segmented into regions such as Latin America, Europe, North America, South Asia, East Asia Middle East & Africa and Oceania. North America is projected to emerge as prominent market in the global stem cell characterization and analysis tools market due to growing cases of target chronic diseases and increasing investments for research activities. Europe is the second leading region to dominate the market due to technological advancement and also surge in therapeutic activities, funded by government across the world. Asia-pacific is likely to witness maximum growth in near future due to increasing disposable income and with the development of infrastructure.

Some of the major key players competing in the global stem cell characterization and analysis tools market are Osiris Therapeutics, Inc., Caladrius Biosciences, Inc., U.S. Stem Cell, Inc., Astellas Pharma Inc., TEMCELL Technologies Inc., BioTime Inc., Cellular Engineering Technologies Inc., Cytori Therapeutics, Inc., and BrainStorm Cell Therapeutics Inc.

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North America to be the Torchbearer to Stem Cell Characterization And Analysis Tools Market NeighborWebSJ - NeighborWebSJ

New Research Grant Seeks to Clarify the Role Genes Play in Modulating Inflammation – NYU Langone Health

Researchers have implicated the pro-inflammatory cytokine interleukin-1 (IL-1) in a wide variety of diseases such as osteoarthritis, rheumatoid arthritis (RA), diabetes, and obesity. Steven Abramson, MD, the Frederick H. King Professor of Internal Medicine, professor of pathology, and chair of the Department of Medicine at NYU Langone Health, has long studied how IL-1 can propagate and exacerbate the disease process. That research effort has more recently expanded to include investigations into how the anti-inflammatory IL-1 receptor antagonist, IL-1Ra, can counter IL-1 and modulate the inflammatory response. Based on intriguing findings about how certain gene variants may influence osteoarthritis risk and severity, a new National Institutes of Health (NIH) research grant will help Dr. Abramson and collaborators seek out IL-1related targets for inflammatory disease prevention and treatment.

To help clarify the inflammatory process, Dr. Abramson and collaborators including Mukundan G. Attur, PhD, associate professor of medicine, and Jonathan Samuels, MD, associate professor of medicine, examined several variants of the IL-1Raencoding IL1RN gene in the knee joints and cells of osteoarthritis and rheumatoid arthritis patients. In particular, a haplotype designated TTG predicted which at-risk patients would go on to develop knee osteoarthritis and was associated with more severe radiographic osteoarthritis as well as new onset RA. Its a marker of both severity and increased risk for incident osteoarthritis, Dr. Abramson says.

Their 2019 study in osteoarthritis patients, published in Annals of the Rheumatic Diseases, suggested that the IL1RN TTG haplotype produced less IL-1Ra protein. So one explanation for the finding is that these people with the gene are deficient in the endogenous inhibitor of IL-1, which is driving the disease, Dr. Abramson says. Conversely, a separate haplotype called CTA yields more IL-1Ra protein production and may be protective.

In collaboration with Jef D. Boeke, PhD, professor of biochemistry and molecular pharmacology and director of the Institute for Systems Genetics, a new NIH grant may help clarify how each gene haplotype modulates inflammation, influences the associated gene regulatory networks, and contributes to the mechanics of disease pathogenesis. In particular, the research will focus on a haplotype block, or a section of DNA including multiple genes adjacent to the IL1RN gene. The researchers hope to learn whether any of the neighboring genes have inflammatory properties of their own, a synergistic effect on IL1RN, or even a more dominant effect on the underlying inflammatory pathway. One reason to do that is if youre developing a drug, you might find that one of these other genes is a better target than IL1RN, Dr. Abramson says.

One key to the unique research effort is Dr. Boekes expertise in using CRISPR-Cas9 gene editing technology to construct a series of what his lab calls assemblons, or precisely altered haplotype blocks. Led by Dr. Attur, the collaborators will then transfect embryonic stem cells with the manipulated DNA and use in vitro assays to gauge the effects of the putative risk and protective IL1RN haplotypes. The genetic manipulation is very technical. But if we can succeed, it allows us to really define the role of these haplotypes, not just in osteoarthritis but in other IL-1driven diseases, Dr. Abramson says.

After differentiating the engineered embryonic stem cells into macrophage cells, the researchers will measure production of the IL-1Ra protein. Well also be stimulating the macrophages in an inflammatory way and looking at the profile of inflammatory mediators that they produce, Dr. Abramson says. Experiments may reveal whether stimulated macrophages that carry the protective IL1RN CTA haplotype, for example, produce more IL1-Ra protein and fewer pro-inflammatory mediators such as IL-1, cyclooxygenase-2 (COX-2), and tumor necrosis factor (TNF). In the same way, sequential knockouts of other genes in the assemblon may clarify their own contributions to each haplotypes effects.

If the researchers can zero in on the principal drivers of disease through their in vitro experiments, they plan to inject the engineered embryonic stem cells into mice models of osteoarthritis and RA. The in vivo studies of the gene regulatory network may help determine how specific gene variants influence disease outcomes.

The research could have broad implications for understanding IL-1associated inflammatory diseases and for personalizing antiIL-1 therapies. It might be that in personalized medicine, antiIL-1 treatments will be more effective in patients who have a deficiency of IL-1 receptor antagonist, Dr. Abramson says. A patient who produces abundant IL-1Ra, on the other hand, may not benefit from receiving more of it as a therapy. Alternatively, the research may suggest that the IL1RN haplotypes are exerting their influence mainly by modulating other genes with key roles in the disease pathogenesis. It may be that they will emerge as targets that people hadnt even thought about in those diseases, he says.

Continued here:
New Research Grant Seeks to Clarify the Role Genes Play in Modulating Inflammation - NYU Langone Health

JARID2 and AEBP2 regulate PRC2 in the presence of H2AK119ub1 and other histone modifications – Science Magazine

Cryo-EM uncovers polycomb interactions

Polycomb family enzymes include the chromatin modifiers PRC1 and PRC2, which are involved in gene repression. Although the catalytic functions of these complexes are well known, their functional relationship is not. Kasinath et al. used cryoelectron microscopy (cryo-EM) to visualize the interactions between nucleosomes containing ubiquitinated histone H2A, the product of PRC1, and the PRC2-activating cofactors JARID2 and AEBP2, providing the molecular basis for PRC1-dependent recruitment of PRC2. They also show that JARID2 and AEBP2 partially overcome the inhibitory effect of PRC2 by two trimethyl lysine transcription marks on histones. This work suggests that PRC2 regulation involves an intricate interplay between PRC2 cofactors and histone posttranslational modifications.

Science, this issue p. eabc3393

Histone modification activity of the polycomb repressive complexes 1 and 2 (PRC1 and PRC2) is critical for the establishment and maintenance of gene expression patterns and, thus, to the maintenance of cell identity. Distinct classes of cofactor proteins are known to regulate the functional activity and interplay of these two complexes, but we presently lack a comprehensive, mechanistic understanding of this process. Furthermore, PRC2 cofactors like AEBP2 and JARID2 also play a role in mediating the cross-talk between different histone posttranslational modifications and PRC2 recruitment and activitya function that is important for the regulated control of gene expression.

PRC1 is an E3 ubiquitin ligase responsible for the monoubiquitination of histone H2A (H2AK119ub1), a histone mark recognized by PRC2 and linked to its genomic recruitment. We used cryoelectron microscopy (cryo-EM) and biochemical activity assays to probe the role played by PRC2 cofactors JARID2 and AEBP2 in the recognition of H2AK119ub1 and the regulation of PRC2 activity. We extended our cryo-EM and biochemical activity analysis to examine the possible role played by JARID2 and AEBP2 in the cross-talk between the histone H3K4me3, H3K36me3 modifications linked to transcriptionally active regions, and PRC2 activity.

We find that JARID2 recognizes both the ubiquitin moiety in H2AK119ub1 and the conserved histone H2A-H2B acidic patch. We also observe that the tandem zinc fingers of AEBP2 interact with ubiquitin and the histone H2A-H2B surface on the other side of the nucleosome. Biochemical assays show a secondary activation of PRC2 by JARID2 and AEBP2 on H2AK119ub1-containing nucleosomes besides the primary EED-mediated allosteric activation of PRC2 by methylated JARID2. Furthermore, we also find that the joint presence of JARID2 and AEBP2 partially reduces the inhibition of PRC2 methyltransferase activity by the transcriptionally active histone posttranslational modifications H3K4me3 and H3K36me3. Cryo-EM visualization of PRC2 that contains JARID2 and AEBP2 interacting with a H3K4me3-containing nucleosome shows the coexistence of states in which the histone H3 tail is either absent or engaged and reaching the catalytic site in PRC2, which provides a physical basis for the partial activity of the complex on H3K4me3-containing nucleosomes.

Our studies indicate that cofactors JARID2 and AEBP2 play a crucial role in both the recruitment and activation of PRC2 through their recognition of H2AK119ub1, which is generated by PRC1. Additionally, our work suggests that JARID2 and AEBP2 are likely to play a key role in regulating PRC2 activity on genomic regions with active transcription marks. The examination of the genomic distribution in embryonic stem cells of PRC2 core proteins together with JARID2 and AEBP2 will be important to further define their role in the tight regulation of PRC2 activity.

Although core PRC2 is a weak enzyme, it is allosterically activated by JARID2 and AEBP2. The presence of monoubiquitinated histone H2A, the product of PRC1 activity, is recognized by both JARID2 and AEBP2 through interactions that likely mediate recruitment of PRC2 to polycomb sites in the genome and further activate the methyltransferase activity of PRC2 on K27 of histone H3.

Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) cooperate to determine cell identity by epigenetic gene expression regulation. However, the mechanism of PRC2 recruitment by means of recognition of PRC1-mediated H2AK119ub1 remains poorly understood. Our PRC2 cryoelectron microscopy structure with cofactors JARID2 and AEBP2 bound to a H2AK119ub1-containing nucleosome reveals a bridge helix in EZH2 that connects the SET domain, H3 tail, and nucleosomal DNA. JARID2 and AEBP2 each interact with one ubiquitin and the H2A-H2B surface. JARID2 stimulates PRC2 through interactions with both the polycomb protein EED and the H2AK119-ubiquitin, whereas AEBP2 has an additional scaffolding role. The presence of these cofactors partially overcomes the inhibitory effect that H3K4me3 and H3K36me3 exert on core PRC2 (in the absence of cofactors). Our results support a key role for JARID2 and AEBP2 in the cross-talk between histone modifications and PRC2 activity.

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JARID2 and AEBP2 regulate PRC2 in the presence of H2AK119ub1 and other histone modifications - Science Magazine

Doctor: COVID-19 cases will continue to slowly go down, but were not out of the woods – Yahoo Money

The Daily Beast

Justin Tallis/GettyAs vaccine rollouts ramp upor in some cases, stumble aheadin countries across the world, the SARS-CoV-2 strain has rolled out some new features of its own, primarily in the form of rapid genetic mutations. Some evidence indicates variants of recent months have made the virus more infectious, or in one case, possibly more deadly.Virus variants are inevitable and often benign. The new coronavirus has likely mutated countless times without attracting the attention of epidemiologists. But new strains identified in the U.K., South Africa, Brazil, and California have given some infectious disease experts pause.Several studies indicate that the strain known as the B117 variant, prevalent in the U.K., may be as much as 70 percent more transmissible than the original virus. Two analyses in California suggested that a new strain on the West Coast, called B.1.426, made up a quarter of the infections they examined. As the news whipsaws between infection spikes and inoculation efforts, it can seem like the world has entered a race between variant and vaccine.Is the South African COVID-19 Mutation a Vaccine Killer?The change through mutation is quite rapid, said Dr. Irwin Redlener, pediatric physician and disaster preparedness adviser to New York City Mayor Bill de Blasio. We dont know where its going. This is the reality, that we dont know what to expect. The thing that were more worried about is that it could mutate to become resistant to the vaccines or partially resistant to the vaccines. That would be horrendous. We could make amendments to the vaccine, but it would slow everything down.Overall, the arrival of new, threatening strains should not change the average persons behavior, three epidemiologists and public health advisers told the Daily Beast. In terms of vaccines and mitigation, this doesnt change the mitigation strategies because we know the mitigation works, said Dr. Arnold Monto, University of Michigan epidemiologist and professor of Public Health. But it just means that we have to be all the more serious about following these kinds of rules.I think primarily this reinforces the urgency of every aspect of the pandemic response, echoed Dr. Joshua Sharfstein, vice dean at the Johns Hopkins Bloomberg School of Public Health. Not just vaccination, but also testing contact tracing, precaution taking, and general vigilance it will take much more than vaccinations, because we dont have enough vaccines overall in the short term.The U.K. StrainHealth officials in the U.K. first announced detection of a new strain in mid-Decemberjust one week after it became the first country in the world to start administering a vaccine. In a press conference, National Health Secretary Matt Hancock revealed that the new mutation had been observed in more than 1,000 patients there, prompting a new wave of strict lockdowns across the country. The strain was thought to date back to mid-September. By late December, its spread correlated with a massive uptick in the number of COVID-19 infections throughout the county.The phrase more infectious can be misleading, said Monto. Data on the new strain does not tell us, for example, that someone exposed to it will become infected faster than someone exposed to the old strain under identical conditions. It refers specifically to the rate at which the viruses reproduce.Lets look at this in terms of what we know, said Monto. What we know is that this virus replicates better. In an individual, it takes less of this virus to cause an infection. How do we know this? We dont know about this in terms of people in a room and how many get infected with one variant versus the other. But what is very clear is that this virus is more efficient and has taken over versus the old virus. That tells us that it has some kind of an advantage in reproducing.Britains Mutant Coronavirus Strain Has Swamped the Nation, but a Worse Variant Has Already ArrivedOn Friday, British Prime Minister Boris Johnson announced in a press conference that the dominant variant there could be as much as 30 percent more deadly than the original. The conclusions came from a paper published by the New and Emerging Virus Threats Advisory Groupa study that was, Monto pointed out, based on a very small number of patients in just a handful of settings.Lots of other things could be related to an increase in mortality, he said, including when you have, as they do in the U.K., greater numbers of people under care. Its based on small numbers, so we really cant say anything right now. We cant speculate.It was a pronouncement that he made, Redlener said of Johnson raising the alarm. There wasnt really much evidence to go on. But he drew a conclusion and went public with it... For now, Ill say Boris Johnson should have held his statement until there was more evidence.The South Africa StrainNot long after the U.K. strain was first announced, a variant called B.1.351 emerged in South Africa. The new strain shared some mutations with its British predecessor, according to the CDC. It also seemed to have a higher rate of transmission. Most concerning about the South African strain, however, was a new mutation in its genetic code that some experts feared could reduce the efficacy of COVID-19 vaccines. Some preliminary studiesfew of them peer-reviewedfound that the mutation E484K in the South African variant limited the effectiveness of antibodies by up to 50 percent.Its definitely a concern, Redlener said, referencing a report on the studies from NBCs Richard Engel. Its a concern because a legitimate scientist mentioned it. What we dont know is how reliable his studies were that drove him to that conclusion.Monto found the conclusions less alarming, noting that the studies drew from a small body of research and very few real world cases. The bottom line is that they are trying to see in a lab if the blood from vaccines neutralize the variants as well as they do the original virus, said Dr. Monto. It looks like they are and to date now there are several papers. One says their test is good. Another says its not quite as good, but still okay.Other StrainsAnother new variant was detected in Japan among four travelers from Brazil, according to the CDC. While relatively less is known about the Brazilian variant, Reuters reported Friday that the new strain accounted for nearly half of the new infections in Manaus, the largest city in the Brazilian state of Amazonas.Last summer, a strain of SARS-CoV-2 emerged in Denmark in association with the countrys mink farming industry, according to the WHO. The country killed 17 million minks to prevent the virus from spreading to humans.Worried About Virus Mutations? Theres a Solution.In California, scientists found a new variant in late December, not long after the state underwent its deadliest surge of the pandemic. According to the Los Angeles Times, two research groups observed the new form while looking for evidence that the U.K. strain had traveled west. Also highly transmissible, it now appears to be the fastest-growing variant in the state. In spite of the discovery, local officials and media have largely placed blame on residents, whom they claim have stopped adhering to lockdown guidelines.Its a very complicated questionwhat is causing an outbreak in a particular place, Redlener said. A lot has to do with basic compliance. But on top of that there may be some other strains there that just havent been identified. Were operating in the dark on a lot of stuff. Its a lot of guesswork and speculation. We just have to keep searching.Read more at The Daily Beast.Get our top stories in your inbox every day. Sign up now!Daily Beast Membership: Beast Inside goes deeper on the stories that matter to you. Learn more.

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Doctor: COVID-19 cases will continue to slowly go down, but were not out of the woods - Yahoo Money

Global Precision Medicine Market With COVID 19 Impact Analysis| Leading Players In-depth Analysis Research Report Foresight to 2027 – KSU | The…

Databridgemarketresearch.com Present Global Precision Medicine Market Industry Trends and Forecast to 2027 new report to its research database. This Global Precision Medicine Market report is structured with the thorough market analysis carried out by a team of industry experts, dynamic analysts, skilful forecasters and well-informed researchers. And not to mention, the report is amazingly characterized by using several charts, graphs and tables depending on the extent of data and information involved. Businesses can achieve complete knowhow of general market conditions and tendencies with the information and data covered in this report. What is more, influencing factors such as market drivers, market restraints and competitive analysis is studied with the SWOT analysis which is the most established tool when it comes to generate market research report.

Global Precision Medicine Market report comprises of all the crucial parameters mentioned above hence it can be used for your business. Furthermore, systemic company profiles covered in this report also explains what recent developments, product launches, joint ventures, mergers and acquisitions are taking place by the numerous key players and brands in the market. This report also endows with company profiles and contact information of the key market players in the key manufacturers section. The report is provided with the transparent research studies which have taken place by a team work of experts in their own domain.

Global Precision Medicine Market to grow with a substantial CAGR in the forecast period of 2019-2026. Growing prevalence of cancer worldwide and accelerating demand of novel therapies to prevent of cancer related disorders are the key factors for lucrative growth of market

Key Market Players:

Few of the major competitors currently working in the global precision medicine market are Neon Therapeutics, Moderna, Inc, Merck & Co., Inc, Bayer AG, PERSONALIS INC, GENOCEA BIOSCIENCES, INC., F. Hoffmann-La Roche Ltd, CureVac AG, CELLDEX THERAPEUTICS, BIONTECH SE, Advaxis, Inc, GlaxoSmithKline plc, Bioven International Sdn Bhd, Agenus Inc., Immatics Biotechnologies GmbH, Immunovative Therapies, Bristol-Myers Squibb Company, Gritstone Oncology, NantKwest, Inc among others.

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Global Precision Medicine Market By Application (Diagnostics, Therapeutics and Others), Technologies (Pharmacogenomics, Point-of-Care Testing, Stem Cell Therapy, Pharmacoproteomics and Others), Indication (Oncology, Central Nervous System (CNS) Disorders, Immunology Disorders, Respiratory Disorders, Others), Drugs (Alectinib, Osimertinib, Mepolizumab,Aripiprazole lauroxil and Others), Route of Administration (Oral,Injectable), End- Users (Hospitals, Homecare, Specialty Clinics, Others), Geography (North America, South America, Europe, Asia-Pacific, Middle East and Africa) Industry Trends and Forecast to 2026

Competitive Analysis:

The precision medicine market is highly fragmented and is based on new product launches and clinical results of products. Hence the major players have used various strategies such as new product launches, clinical trials, market initiatives, high expense on research and development, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market. The report includes market shares of mass spectrometry market for global, Europe, North America, Asia Pacific and South America.

Market Drivers

Market Restraints

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Market Definition:

Precision medicines is also known as personalized medicines is an innovative approach to the patient care for disease treatment, diagnosis and prevention base on the persons individual genes. It allows doctors or physicians to select treatment option based on the patients genetic understanding of their disease.

According to the data published in PerMedCoalition, it was estimated that the USFDA has approved 25 novels personalized medicines in the year of 2018. These growing approvals annually by the regulatory authorities and rise in oncology and CNS disorders worldwide are the key factors for market growth.

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Key Developments in the Market:

Competitive Analysis:

Global precision medicine market is highly fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market. The report includes market shares of global precision medicine market for Global, Europe, North America, Asia-Pacific, South America and Middle East & Africa.

Market Segmentation:

By technology:- big data analytics, bioinformatics, gene sequencing, drug discovery, companion diagnostics, and others.

By application:- oncology, hematology, infectious diseases, cardiology, neurology, endocrinology, pulmonary diseases, ophthalmology, metabolic diseases, pharmagenomics, and others.

On the basis of end-users:- pharmaceuticals, biotechnology, diagnostic companies, laboratories, and healthcare it specialist.

On the basis of geography:- North America & South America, Europe, Asia-Pacific, and Middle East & Africa. U.S., Canada, Germany, France, U.K., Netherlands, Switzerland, Turkey, Russia, China, India, South Korea, Japan, Australia, Singapore, Saudi Arabia, South Africa, and Brazil among others.

In 2017, North America is expected to dominate the market.

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Global Precision Medicine Market With COVID 19 Impact Analysis| Leading Players In-depth Analysis Research Report Foresight to 2027 - KSU | The...

Groundbreaking Trial Shows Umbilical-Cord Derived Mesenchymal Stem Cell Infusions Save Lives of Sickest COVID-19 Patients – HospiMedica

Image: Camillo Ricordi, M.D., director of the Diabetes Research Institute (DRI) and Cell Transplant Center at the University of Miami Miller School of Medicine (Photo courtesy of University of Miami Health System)

Researchers at the University of Miami Miller School of Medicine (Miami, FL, USA) who led the study believe that treating COVID-19 with mesenchymal stem cells makes sense. Mesenchymal cells not only help correct immune and inflammatory responses that go awry, they also have antimicrobial activity and have been shown to promote tissue regeneration. When given intravenously, mesenchymal stem cells migrate naturally to the lungs. Thats where therapy is needed in COVID-19 patients with acute respiratory distress syndrome, a dangerous complication associated with severe inflammation and fluid buildup in the lungs.

In the new study, 24 hospitalized COVID-19 patients who had developed severe acute respiratory distress syndrome each received two infusions given days apart of either mesenchymal stem cells or a placebo. Researchers found the treatment was safe, with no infusion-related serious adverse events. Patient survival at one month was 91% in the stem cell treated group versus 42% in the control group. Among patients younger than 85 years old, 100% of those treated with mesenchymal stem cells survived at one month.

The researchers also found that recovery was faster among those in the treatment arm. More than half of patients treated with mesenchymal stem cell infusions recovered and went home from the hospital within two weeks after the last treatment. More than 80% of the treatment group recovered by day 30, versus less than 37% in the control group. The next step is to study use of the stem cells in COVID-19 patients who have not yet become severely ill but are at risk of having to be intubated, to determine if the infusions prevent disease progression.

The umbilical cord contains progenitor stem cells, or mesenchymal stem cells, that can be expanded and provide therapeutic doses for over 10,000 patients from a single umbilical cord, said the studys senior author, Camillo Ricordi, M.D., director of the Diabetes Research Institute (DRI) and Cell Transplant Center at the University of Miami Miller School of Medicine. Its a unique resource of cells that are under investigation for their possible use in cell therapy applications, anytime you have to modulate immune response or inflammatory response.

Our results confirm the powerful anti-inflammatory, immunomodulatory effect of UC-MSC (umbilical-cord derived mesenchymal stem cells). These cells have clearly inhibited the cytokine storm, a hallmark of severe COVID-19, said Giacomo Lanzoni, Ph.D., lead author of the paper and assistant research professor at the Diabetes Research Institute. The results are critically important not only for COVID-19 but also for other diseases characterized by aberrant and hyperinflammatory immune responses, such as autoimmune type 1 diabetes.

Related Links:University of Miami Miller School of Medicine

Link:
Groundbreaking Trial Shows Umbilical-Cord Derived Mesenchymal Stem Cell Infusions Save Lives of Sickest COVID-19 Patients - HospiMedica

Autologous stem cell transplantation versus bortezomib for the first line treatment of systemic light chain amyloidosis in the UK – DocWire News

This article was originally published here

Eur J Haematol. 2021 Jan 18. doi: 10.1111/ejh.13582. Online ahead of print.

ABSTRACT

OBJECTIVES: The benefit of autologous stem cell transplantation (ASCT) in the treatment of light chain (AL) amyloidosis requires re-evaluation in the modern era. This retrospective case-matched study compares ASCT to bortezomib for the treatment of patients with AL amyloidosis.

METHODS: Newly diagnosed patients with AL amyloidosis treated with ASCT or bortezomib between 2001-2018 were identified. Patients were excluded if the time from diagnosis to treatment exceeded 12 months. Patients were matched on a 1:1 basis, using a propensity matched scoring approach.

RESULTS: A total of 136 propensity-score matched patients were included (ASCT n= 68, bortezomib n=68). There was no significant difference in overall survival at two years (p=0.908, HR: 0.95, CI:0.41-2.20). For ASCT vs. bortezomib: overall haematological response rate at six months was 90.6% vs. 92.5%; organ response at 12 months: cardiac (70.0% vs. 54%, p>0.999), renal (74% vs.24%, p=0.463)) liver (21% vs. 22%, p=0.048); median progression free survival (50 vs. 42 months p=0.058, HR:0.61, CI:0.37-1.02) and time to next treatment (68 vs. 45 months, p=0.145, HR:0.61, CI:0.31-1.19). More patients required treatment in the bortezomib group compared to ASCT group at 24 months (41 vs. 23, Chi squared p=0.004) and 48 months (57 vs 41, Chi squared p= 0.004).

CONCLUSIONS: This small retrospective study suggests that there is no clear survival advantage of ASCT over bortezomib therapy. A prospective randomised controlled trial evaluating ASCT in AL amyloidosis is critically needed.

PMID:33460466 | DOI:10.1111/ejh.13582

Read more from the original source:
Autologous stem cell transplantation versus bortezomib for the first line treatment of systemic light chain amyloidosis in the UK - DocWire News

Massive Growth in Canine Stem Cell Therapy Market Set to Witness Huge Growth by 2027| VETSTEM BIOPHARMA, Cell Therapy Sciences, Regeneus, Aratana…

Canine Stem Cell Therapy Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis.

The global Canine Stem Cell Therapy Market size is expected to Expand at Significant CAGR of +4% during forecast period (2021-2027).

The non-invasive stem cell obtaining procedure, augmented possibility of accomplishing high quality cells, and lower price of therapy coupled with high success rate of positive outcomes have collectively made allogeneic stem cell therapy a preference for veterinary physicians. Moreover, allogeneic stem cell therapy is 100% safe, which further supports its demand on a global level.

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Some of the Top companies Influencing in this Market includes:

VETSTEM BIOPHARMA, Cell Therapy Sciences, Regeneus, Aratana Therapeutics, Medivet Biologics, Okyanos.

Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Canine Stem Cell Therapy market. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market. The influence of the latest government guidelines is also analyzed in detail in the report. It studies the Canine Stem Cell Therapy markets trajectory between forecast periods.

Global Canine Stem Cell Therapy Market Segmentation:

Market Segmentation: By Type

Market Segmentation: By Application

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Regions Covered in the Global Canine Stem Cell Therapy Market Report 2020: The Middle East and Africa(GCC Countries and Egypt) North America(the United States, Mexico, and Canada) South America(Brazil etc.) Europe(Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific(Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

The cost analysis of the Global Canine Stem Cell Therapy Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.

Key questions answered in the report include:

Table of Content (TOC)

Global Canine Stem Cell Therapy Market Report 2021 Growth, Trend and Forecast to 2027

Chapter 1 Canine Stem Cell Therapy Market Overview

Chapter 2 Global Economic Impact on Canine Stem Cell Therapy Industry

Chapter 3 Global Canine Stem Cell Therapy Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region (2014-2020)

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions (2014-2020)

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Canine Stem Cell Therapy Market Forecast (2020-2026)

Chapter 13 Appendix

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Massive Growth in Canine Stem Cell Therapy Market Set to Witness Huge Growth by 2027| VETSTEM BIOPHARMA, Cell Therapy Sciences, Regeneus, Aratana...