信号調節器の発見と特徴づけのための繰り返し,多様式,スケーラブルな単細胞プロファイリング
bioRxiv : the preprint server for biology
|September 5, 2025
まとめ
単細胞タンパク質,RNA,CRISPRデータを組み合わせた 新しい方法を開発しました 信号伝達経路のレギュレータを発見するためです このアプローチにより,mTORシグナル伝達の新しいレギュレータを成功裏に特定し,細胞プロセスに関する理解を深めました.
科学分野:
- 分子生物学
- システム生物学
- ゲノミクス
背景:
- 細胞シグナル伝達は 細胞の機能に不可欠ですが 調節因子と結果を特定することは 複雑です
- 信号伝達経路を理解するには,分子変化と細胞状態を結びつけるための統合的なアプローチが必要です.
研究 の 目的:
- シグナル伝達タンパク質の調節因子を特定し,特徴づけるための繰り返し実験的および計算的枠組みを開発し,検証する.
- phosphorylated RPS6 (pRPS6) のケーススタディを用いて,mTORシグナル伝達経路の新しいレギュレータを指名する.
主な方法:
- 単細胞タンパク質,RNA,およびCRISPRの混乱を共同プロファイリングするために10xFlexアッセイによるカスタマイズされたワークフローを使用しました.
- 予測モデルを訓練するために,標的の混乱を介してペアリングされたタンパク質-RNA測定データセットを生成しました.
- トランスクリプトミカルベースの予測モデルを,全ゲノムにわたるPerturb-seqデータセットに*in silico*スクリーニングに適用した.
主要な成果:
- トランスクリプトミックのデータをpRPS6レベルにリンクする予測モデルを成功裏に訓練しました.
- 全ゲノムスクリーニングによるmTORシグナル伝達の新しいレギュレータ
- 実験的検証により,予測が確認され,アナボリック活動,増殖,ストレス経路を含む様々な調節メカニズムが明らかになった.
結論:
- 統合された実験的および計算的フレームワークは,スケーラブルなマルチモダルのフェノタイプ化とシグナルレギュレータの発見を可能にします.
- このアプローチは,経路調節体を特定するための堅固な方法を提供することによって,細胞信号伝達の研究を進めます.
- 生物学的発見のための単細胞マルチオミクスを組み合わせる力を示した.
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