SETD3 is a member of the SET (Su(var)3–9, Enhancer of zeste, and Trithorax) domain protein superfamily and plays important roles in hypoxic pulmonary hypertension, muscle differentiation, and carcinogenesis. Previously, we identified SETD3 as the actin-specific methyltransferase that methylates the N3 of His73 on β-actin (Kwiatkowski et al., 2018). Here, we present two structures of S-adenosyl-L-homocysteine-bound SETD3 in complex with either an unmodified β-actin peptide or its His-methylated variant. Structural analyses, supported by biochemical experiments and enzyme activity assays, indicate that the recognition and methylation of β-actin by SETD3 are highly sequence specific, and that both SETD3 and β-actin adopt pronounced conformational changes upon binding to each other. In conclusion, this study is the first to show a catalytic mechanism of SETD3-mediated histidine methylation on β-actin, which not only throws light on the protein histidine methylation phenomenon but also facilitates the design of small molecule inhibitors of SETD3.
31SETD3 is a member of SET (Su(var)3-9, Enhancer of zeste, and Trithorax) domain 32 protein superfamily and plays important roles in hypoxic pulmonary hypertension, 33 muscle differentiation, and carcinogenesis. In a previous paper (Kwiatkowski et al. 34 2018), we have identified SETD3 as the actin-specific methyltransferase that 35 methylates the N 3 of His73 on β-actin. Here we present two structures of 36 S-adenosyl-L-homocysteine-bound SETD3 in complex with either an unmodified 37 β-actin peptide or its His-methylated variant. Structural analyses supported by the 38 site-directed mutagenesis experiments and the enzyme activity assays indicated that 39 the recognition and methylation of β-actin by SETD3 is highly sequence specific, and 40 both SETD3 and β-actin adopt pronounce conformational changes upon binding to 41 each other. In conclusion, the structural research uncovers the molecular mechanism 42 of sequence-selective histidine methylation by SETD3, which not only throws light on 43 protein histidine methylation phenomenon, but also facilitates the design of small 44 molecule inhibitors of SETD3. 45 46 91 by SETD3. 92 93With the two solved β-actin peptide-SETD3 structures, we uncover that SETD3 94 recognizes a fragment of β-actin in a sequence-dependent manner and utilizes a 95 specific pocket to catalyze the N 3 -methylation of His73. Moreover, a comprehensive 96 structural, biochemical and enzymatic profiling of SETD3 allows us to pinpoint its 97 key residues important for substrate recognition and subsequent methylation. 98Therefore, the structural research, supplemented by biochemical and enzymatic 99 experiments, not only provides insights into the catalytic mechanism of SETD3, but 100 also will facilitate the design of specific inhibitors of SETD3 enzyme. 101 102 RESULTS 103SETD3 binds to and methylates β-actin 104 Since SETD3 was identified as a histidine methyltransferase that methylates His73 of 105 β-actin (Kwiatkowski et al., 2018, Wilkinson et al., 2019, we purified the core region 106 of SETD3 (aa 2-502) and studied by ITC its binding to a His73-containing fragment 107 of β-actin (aa 66-88) ( Figures 1A). The ITC binding experiment showed that SETD3 108 bound to the β-actin peptide with a Kd of 0.17 μM ( Figure 1B and Table 1). Given 109 that SETD3 was also reported to be a putative lysine methyltransferase that 110 methylates Lys4 and Lys36 of histone H3 (Eom et al., 2011), we also verified the 111 binding of SETD3 to two different histone peptides, H3K4(1-23) and H3K36(25-47), 112 and found that neither of them binds to SETD3 (Table 1).113 114 Furthermore, we tested the activity of SETD3 on β-actin(66-88), H3K4(1-23), and 115 H3K36(25-47) by mass spectrometry, and we found that SETD3 methylates β-actin 116 peptide (Figure 1-figure supplement 1A), but does not modify either H3K4 or H3K36 117 (Figure 1-figure supplement 1B-1C). No methylated product was detected for any of 118 above peptides in the presence of AdoMet without the addition of SETD3 (Figure 119 1-figure supple...
Background Brain endothelial cell-based in vitro models are among the most versatile tools in blood–brain barrier research for testing drug penetration to the central nervous system. Transcytosis of large pharmaceuticals across the brain capillary endothelium involves the complex endo-lysosomal system. This system consists of several types of vesicle, such as early, late and recycling endosomes, retromer-positive structures, and lysosomes. Since the endo-lysosomal system in endothelial cell lines of in vitro blood–brain barrier models has not been investigated in detail, our aim was to characterize this system in different models. Methods For the investigation, we have chosen two widely-used models for in vitro drug transport studies: the bEnd.3 mouse and the hCMEC/D3 human brain endothelial cell line. We compared the structures and attributes of their endo-lysosomal system to that of primary porcine brain endothelial cells. Results We detected significant differences in the vesicular network regarding number, morphology, subcellular distribution and lysosomal activity. The retromer-positive vesicles of the primary cells were distinct in many ways from those of the cell lines. However, the cell lines showed higher lysosomal degradation activity than the primary cells. Additionally, the hCMEC/D3 possessed a strikingly unique ratio of recycling endosomes to late endosomes. Conclusions Taken together our data identify differences in the trafficking network of brain endothelial cells, essentially mapping the endo-lysosomal system of in vitro blood–brain barrier models. This knowledge is valuable for planning the optimal route across the blood–brain barrier and advancing drug delivery to the brain. Electronic supplementary material The online version of this article (10.1186/s12987-019-0134-9) contains supplementary material, which is available to authorized users.
Insulin secretion from β-cells is reduced at the onset of type-1 and during type-2 diabetes. Although inflammation and metabolic dysfunction of β-cells elicit secretory defects associated with type-1 or type-2 diabetes, accompanying changes to insulin granules have not been established. To address this, we performed detailed functional analyses of insulin granules purified from cells subjected to model treatments that mimic type-1 and type-2 diabetic conditions and discovered striking shifts in calcium affinities and fusion characteristics. We show that this behavior is correlated with two subpopulations of insulin granules whose relative abundance is differentially shifted depending on diabetic model condition. The two types of granules have different release characteristics, distinct lipid and protein compositions, and package different secretory contents alongside insulin. This complexity of β-cell secretory physiology establishes a direct link between granule subpopulation and type of diabetes and leads to a revised model of secretory changes in the diabetogenic process.
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