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Riboswitches01:56

Riboswitches

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Riboswitches are non-coding mRNA domains that regulate the transcription and translation of downstream genes without the help of proteins. Riboswitches bind directly to a metabolite and can form unique stem-loop or hairpin structures in response to the amount of the metabolite present. They have two distinct regions – a metabolite-binding aptamer and an expression platform.
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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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The term ribozyme is used for RNA that can act as an enzyme. Ribozymes are mainly found in selected viruses, bacteria, plant organelles, and lower eukaryotes. Ribozymes were first discovered in 1982 when Tom Cech’s laboratory observed Group I introns acting as enzymes. This was shortly followed by the discovery of another ribozyme, Ribonulcease P, by Sid Altman’s laboratory. Both Cech and Altman received the Nobel Prize in chemistry in 1989 for their work on ribozymes.
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Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
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リボコンピューティングデバイスを使用した複雑なセルロースロジック計算

Alexander A Green1,2, Jongmin Kim1,3, Duo Ma2

  • 1Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02115, USA.

Nature
|July 27, 2017
PubMed
まとめ
この要約は機械生成です。

合成生物学は,セルラーコンピューティングのための新しいRNAのみのナノデバイスで進歩しています. これは

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科学分野:

  • 合成生物学
  • 分子工学
  • バイオテクノロジー

背景:

  • 合成生物学は 細胞機能のエンジニアリング主導の プログラミングを模索しています
  • 既存の合成遺伝子回路は 制限された部品と複雑なルールにより スケールアップの課題に直面しています
  • RNAベースのシステムは,単純化され,スケーラブルな生物学的計算の可能性を提供します.

研究 の 目的:

  • 生体細胞における複雑な論理を評価するためのRNAのみのナノデバイスを開発する.
  • 転写後の生物学的計算のためのスケーラブルなプラットフォームを作成します.
  • 現在の合成遺伝子回路の限界を克服するために

主な方法:

  • 予測可能なベースペアリングルールで動作する設計されたde-novoRNAパーツ.
  • センシング,計算,出力のための自己組み立てRNA複合体を構築した.
  • ロジックゲートの性能について,Escherichia coliで評価されたリボコンピューティング装置.

主要な成果:

  • 複雑な論理操作を行うことができるRNAのみのナノデバイスを実証した.
  • 2つの入力論理ゲートで高いダイナミックレンジ (900倍まで) を達成します.
  • 4つの入力 AND,6つの入力 OR,そして12の入力式を評価するために,うまくスケールされたシステムです.

結論:

  • リボコンピューティングは 生物学的計算に予測可能でスケーラブルなアプローチを提供します
  • RNAベースのシステムは代謝コストを削減し,回路の信頼性を向上させます.
  • プログラム可能なRNAの相互作用は,様々なホストで多様なアプリケーションの道を開きます.