Natural Sciences and Engineering Research Council (Canada)
418157-2012
カナダ
引用
ジャーナル: EMBO Rep / 年: 2017 タイトル: Molecular architecture of the yeast Elongator complex reveals an unexpected asymmetric subunit arrangement. 著者: Dheva T Setiaputra / Derrick Th Cheng / Shan Lu / Jesse M Hansen / Udit Dalwadi / Cindy Hy Lam / Jeffrey L To / Meng-Qiu Dong / Calvin K Yip / 要旨: Elongator is a ~850 kDa protein complex involved in multiple processes from transcription to tRNA modification. Conserved from yeast to humans, Elongator is assembled from two copies of six unique ...Elongator is a ~850 kDa protein complex involved in multiple processes from transcription to tRNA modification. Conserved from yeast to humans, Elongator is assembled from two copies of six unique subunits (Elp1 to Elp6). Despite the wealth of structural data on the individual subunits, the overall architecture and subunit organization of the full Elongator and the molecular mechanisms of how it exerts its multiple activities remain unclear. Using single-particle electron microscopy (EM), we revealed that yeast Elongator adopts a bilobal architecture and an unexpected asymmetric subunit arrangement resulting from the hexameric Elp456 subassembly anchored to one of the two Elp123 lobes that form the structural scaffold. By integrating the EM data with available subunit crystal structures and restraints generated from cross-linking coupled to mass spectrometry, we constructed a multiscale molecular model that showed the two Elp3, the main catalytic subunit, are located in two distinct environments. This work provides the first structural insights into Elongator and a framework to understand the molecular basis of its multifunctionality.
詳細: The final purification buffer was part of a glycerol gradient containing crosslinker as per the GraFix technique (Stark 2010): 40 mM HEPES, pH 7.4, 150 mM NaCl, 0.1% Tween-20, 1 mM EDTA, ~20% ...詳細: The final purification buffer was part of a glycerol gradient containing crosslinker as per the GraFix technique (Stark 2010): 40 mM HEPES, pH 7.4, 150 mM NaCl, 0.1% Tween-20, 1 mM EDTA, ~20% glycerol, ~0.02% glutaraldehyde. Fractions containing the sample were concentrated and the buffer was exchanged for the final buffer: 40 mM HEPES, pH 7.4, 150 mM NaCl, 1 mM EDTA.
染色
タイプ: NEGATIVE / 材質: Uranyl formate 詳細: Sample was applied to a glow-discharged copper grid overlaid with carbon (carbon evaporator and amyl acetate) and stained with uranyl formate.
照射モード: FLOOD BEAM / 撮影モード: BRIGHT FIELD / 倍率(公称値): 49000
試料ステージ
試料ホルダーモデル: SIDE ENTRY, EUCENTRIC
実験機器
モデル: Tecnai Spirit / 画像提供: FEI Company
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画像解析
粒子像選択
選択した数: 17074 詳細: 200 particles were manually picked to generate 5 class averages. These were used as templates for autopicking using the RELION software.
初期モデル
モデルのタイプ: RANDOM CONICAL TILT / Random conical tilt - Number images: 81 / Random conical tilt - Tilt angle: 65 degrees
最終 再構成
使用したクラス数: 4 / アルゴリズム: BACK PROJECTION / 解像度のタイプ: BY AUTHOR / 解像度: 25.2 Å / 解像度の算出法: FSC 0.143 CUT-OFF / ソフトウェア - 名称: RELION (ver. 1.3) ソフトウェア - 詳細: Output from RELION auto-refine was masked using the post-processing function to generate the final reconstruction. 詳細: The final model from RELION's auto-refine was further processed using the post-processing function in RELION to calculate the final masked map, with no map sharpening applied. 使用した粒子像数: 8190
初期 角度割当
タイプ: PROJECTION MATCHING Projection matching processing - Angular sampling: 7.5 degrees ソフトウェア - 名称: RELION (ver. 1.3) ソフトウェア - 詳細: Initial angular assignment was done using the 3D Classification function to generate a suitable model and particle set for refinement. 詳細: 3D Classification step in RELION
最終 角度割当
タイプ: PROJECTION MATCHING / ソフトウェア - 名称: RELION (ver. 1.3) ソフトウェア - 詳細: Final refinement was done using the 3D auto-refine function. 詳細: 3D auto-refine step in RELION, which automatically increments the angular sampling
最終 3次元分類
クラス数: 5 / 平均メンバー数/クラス: 1993 / ソフトウェア - 名称: RELION (ver. 1.3) ソフトウェア - 詳細: THe 3D classification function in RELION was used to characterize heterogeneity in 3D. 詳細: 2D classification was used to get rid of bad particles, and showed a high degree of preferred orientation. 3D classification was used to clean up the dataset. Most of the classes were similar ...詳細: 2D classification was used to get rid of bad particles, and showed a high degree of preferred orientation. 3D classification was used to clean up the dataset. Most of the classes were similar and were therefore merged.