
最新の実験的および計算的手法を活用して、大腸菌の四次構造プロテオームを網羅的に注釈付けし、細胞機能の分子レベルの理解を得ることができる。


coremsg

A critical body of knowledge has developed through advances in protein microscopy, protein-fold modeling, structural biology software, availability of sequenced bacterial genomes, large-scale mutation databases, and genome-scale models. Based on these recent advances, we develop a computational framework that; i) identifies the oligomeric structural proteome encoded by an organism’s genome from available structural resources; ii) maps multi-strain alleleomic variation, resulting in the structural proteome for a species; and iii) calculates the 3D orientation of proteins across subcellular compartments with residue-level precision. Using the platform, we; iv) compute the quaternary E. coli K-12 MG1655 structural proteome; v) use a dataset of 12,000 mutations to build Random Forest classifiers that can predict the severity of mutations; and, in combination with a genome-scale model that computes proteome allocation, vi) obtain the spatial allocation of the E. coli proteome. Thus, in conjunction with relevant datasets and increasingly accurate computational models, we can now annotate quaternary structural proteomes, at genome-scale, to obtain a molecular-level understanding of whole-cell functions.

Significance Advancements in experimental and computational methods have revealed the shapes of multi-subunit proteins. The absence of a unified platform that maps actionable datatypes onto these increasingly accurate structures creates a barrier to structural analyses, especially at the genome-scale. Here, we describe QSPACE, a computational annotation platform that evaluates existing resources to identify the best-available structure for each protein in a user’s query, maps the 3D location of actionable datatypes ( e.g. , active sites, published mutations) onto the selected structures, and uses third-party APIs to determine the subcellular compartment of all amino acids of a protein. As proof-of-concept, we deployed QSPACE to generate the quaternary structural proteome of E. coli MG1655 and demonstrate two use-cases involving large-scale mutant analysis and genome-scale modelling.

### Competing Interest Statement

The authors have declared no competing interest.

Establishing comprehensive quaternary structural proteomes from genome sequence

e-coli-の四次構造プロテオームを網羅的に解析するための計算フレームワークの開発


E. coli の四次構造プロテオームを網羅的に解析するための計算フレームワークの開発


title_rewrite


CodonMPNNは、タンパク質の立体構造と生物種情報を入力として、高発現のコドン配列を生成することができる。


生物種特異的で最適なコドン配列を生成するcodonmpnn


生物種特異的で最適なコドン配列を生成するCodonMPNN



大規模なRNAランゲージモデルと距離変換器(DiT)を組み合わせることで、RNAの一次配列からその距離行列を正確に予測できる。この中間レベルの構造情報は、より正確な3Dモデリングを導くことができる。


大規模言語モデルを用いたrna距離行列の予測


大規模言語モデルを用いたRNA距離行列の予測



代謝ネットワークの構造的特徴を学習することで、実験データに依存せずに欠落反応を自動的に予測することができる。


代謝ネットワークの欠落反応を深層学習を用いて自動的に補完する汎用的なフレームワーク


時系列単一細胞データと遺伝子ノックアウト実験を組み合わせることで、細胞の動態と遺伝子ネットワークを同時に推定することができる。


遺伝子発現動態と遺伝子ネットワークの同時推定


本研究では、カオスゲーム表現(CGR)を用いてタンパク質配列からカレイドスコープ画像を生成し、深層学習モデルを用いてこれらの画像を分類することで、タンパク質の構造的および機能的特性を明らかにする。


深層学習を用いたカオス強化カレイドスコープ画像によるタンパク質配列の分析


ヒトゲノムプロジェクトの完了後、タンパク質の多様性を説明するためには、ゲノム上の20,000の遺伝子配列だけでは不十分であることが明らかになった。


How to customize proteins to enable their sequences to be probed.

Thread, read, rewind, repeat: towards using nanopores for protein sequencing

タンパク質シーケンシングにナノポアを使用するための道のり


単一分子レベルでの完全長タンパク質の配列決定と特性解析を可能にする新しい手法の開発


A technique for threading long protein strands through a nanopore by electrophoresis and back using a protein unfoldase motor, ClpX, enables single protein molecules to be analyzed multiple times with single-amino-acid sensitivity.

Multi-pass, single-molecule nanopore reading of long protein strands - Nature

長いタンパク質鎖の単一分子ナノポア読み取りにおける多重パス


Fyv6は、スプライソームの2段階目の反応において、ブランチポイントから遠い3'スプライスサイトの使用を促進する。


Pre-mRNA splicing is catalyzed in two steps: 5’ splice site (SS) cleavage and exon ligation. A number of proteins transiently associate with spliceosomes to specifically impact these steps (1st and 2nd step factors). We recently identified Fyv6 (FAM192A in humans) as a 2nd step factor in S. cerevisiae ; however, we did not determine how widespread Fyv6’s impact is on the transcriptome. To answer this question, we have used RNA-seq to analyze changes in splicing. These results show that loss of Fyv6 results in activation of non-consensus, branch point (BP) proximal 3’ SS transcriptome-wide. To identify the molecular basis of these observations, we determined a high-resolution cryo-EM structure of a yeast product complex spliceosome containing Fyv6 at 2.3 Å. The structure reveals that Fyv6 is the only 2nd step factor that contacts the Prp22 ATPase and that Fyv6 binding is mutually exclusive with that of the 1st step factor Yju2. We then use this structure to dissect Fyv6 functional domains and interpret results of a genetic screen for fyv61 suppressor mutations. The combined transcriptomic, structural, and genetic studies allow us to propose a model in which Yju2/Fyv6 exchange facilitates exon ligation and Fyv6 promotes usage of consensus, BP distal 3’ SS.

### Competing Interest Statement

AAH is a member of the scientific advisory board and carrying out sponsored research for Remix Therapeutics.

Control of 3’ splice site selection by the yeast splicing factor Fyv6

酵母スプライシング因子fyv6による3-スプライスサイト選択の制御


酵母スプライシング因子Fyv6による3'スプライスサイト選択の制御



ゲノムワイド条件性デグロン・ライブラリーを構築し、DNA損傷応答因子の同定に応用することで、機能ゲノミクスの新たなツールを提供する。


The yeast knockout library, comprised of strains carrying precise deletions of individual open reading frames (ORFs), has been a vital resource to understand gene function. However, accumulation of suppressor mutations in knockout strains can lead to erroneous functional annotations. Moreover, the library is limited to non-essential ORFs, and must be complemented with hypomorphic alleles of essential ORFs for genome-wide studies. To address these limitations, we constructed genome-wide libraries of conditional alleles based on the auxin-inducible degron (AID) system for conditional degradation of AID-tagged proteins. First, we determined that N-terminal tagging is at least twice more likely to inadvertently impair protein function across the proteome. We thus constructed two genome-wide libraries with over 5600 essential and non-essential proteins fused at the C-terminus with an AID tag and an optional fluorescent protein. Almost 90% of AID-tagged proteins were completely or partially degraded in the presence of auxin, with protein abundance and tag accessibility as limiting factors. Genome-wide screens for DNA damage response factors with the AID libraries revealed a role for the glucose signaling factor GSF2 in resistance to hydroxyurea, highlighting how these resources extend the toolbox for functional genomics in yeast.

### Competing Interest Statement

The authors have declared no competing interest.

Genome-wide conditional degron libraries for functional genomics

ゲノムワイド条件性デグロン-ライブラリーによる機能ゲノミクス


ゲノムワイド条件性デグロン・ライブラリーによる機能ゲノミクス
