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PocketAnchor: Learning structure-based pocket representations for protein-ligand interaction prediction. PocketAnchor:学习基于结构的口袋表示,用于蛋白质-配体相互作用预测。
IF 9.3 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-07-01 DOI: 10.2139/ssrn.4161090
Shuya Li, Tingzhong Tian, Ziting Zhang, Ziheng Zou, Dan Zhao, Jianyang Zeng
Protein-ligand interactions are essential for cellular activities and drug discovery processes. Appropriately and effectively representing protein features is of vital importance for developing computational approaches, especially data-driven methods, for predicting protein-ligand interactions. However, existing approaches may not fully investigate the features of the ligand-occupying regions in the protein pockets. Here, we design a structure-based protein representation method, named PocketAnchor, for capturing the local environmental and spatial features of protein pockets to facilitate protein-ligand interaction-related learning tasks. We define "anchors" as probe points reaching into the cavities and those located near the surface of proteins, and we design a specific message passing strategy for gathering local information from the atoms and surface neighboring these anchors. Comprehensive evaluation of our method demonstrated its successful applications in pocket detection and binding affinity prediction, which indicated that our anchor-based approach can provide effective protein feature representations for improving the prediction of protein-ligand interactions.
蛋白质-配体相互作用对细胞活动和药物发现过程至关重要。适当有效地表示蛋白质特征对于开发预测蛋白质-配体相互作用的计算方法,特别是数据驱动方法至关重要。然而,现有的方法可能无法完全研究蛋白质口袋中配体占据区域的特征。在这里,我们设计了一种基于结构的蛋白质表示方法,名为PocketAnchor,用于捕捉蛋白质口袋的局部环境和空间特征,以促进蛋白质-配体相互作用相关的学习任务。我们将“锚”定义为进入空腔的探针点和位于蛋白质表面附近的探针点,并设计了一种特定的信息传递策略,用于从这些锚附近的原子和表面收集局部信息。对我们方法的全面评估证明了它在口袋检测和结合亲和力预测中的成功应用,这表明我们基于锚的方法可以为改进蛋白质-配体相互作用的预测提供有效的蛋白质特征表示。
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引用次数: 0
The time-resolved genomic impact of Wnt/β-catenin signaling. Wnt/β-catenin信号传导的时间分辨基因组影响。
IF 9.3 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-07-01 DOI: 10.2139/ssrn.4208342
P. Pagella, Simon Söderholm, A. Nordin, Gianluca Zambanini, Valeria Ghezzi, Amaia Jauregi-Miguel, C. Cantú
Wnt signaling orchestrates gene expression via its effector, β-catenin. However, it is unknown whether β-catenin binds its target genomic regions simultaneously and how this impacts chromatin dynamics to modulate cell behavior. Using a combination of time-resolved CUT&RUN against β-catenin, ATAC-seq, and perturbation assays in different cell types, we show that Wnt/β-catenin physical targets are tissue-specific, β-catenin "moves" on different loci over time, and its association to DNA accompanies changing chromatin accessibility landscapes that determine cell behavior. In particular, Wnt/β-catenin progressively shapes the chromatin of human embryonic stem cells (hESCs) as they undergo mesodermal differentiation, a behavior that we define as "plastic." In HEK293T cells, on the other hand, Wnt/β-catenin drives a transient chromatin opening, followed by re-establishment of the pre-stimulation state, a response that we define as "elastic." Future experiments shall assess whether other cell communication mechanisms, in addition to Wnt signaling, are ruled by time, cellular idiosyncrasies, and chromatin constraints. A record of this paper's transparent peer review process is included in the supplemental information.
Wnt信号通过其效应子β-连环蛋白协调基因表达。然而,尚不清楚β-连环蛋白是否同时结合其靶基因组区域,以及这如何影响染色质动力学以调节细胞行为。使用针对β-连环蛋白的时间分辨CUT和RUN、ATAC-seq和不同细胞类型的扰动分析相结合,我们发现Wnt/β-连环素物理靶标是组织特异性的,β-连环肽随着时间的推移在不同的基因座上“移动”,其与DNA的关联伴随着决定细胞行为的染色质可及性景观的变化。特别是,Wnt/β-catenin在人类胚胎干细胞(hESCs)经历中胚层分化时逐渐形成染色质,我们将这种行为定义为“可塑性”。另一方面,在HEK293T细胞中,Wnt-β-caten驱动短暂的染色质开放,然后重新建立预刺激状态,我们将其定义为“弹性”的反应。“未来的实验将评估除了Wnt信号外,其他细胞通讯机制是否受时间、细胞特性和染色质限制的支配。补充信息中包含了本文透明同行评审过程的记录。
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引用次数: 4
A multi-scale map of protein assemblies in the DNA damage response. DNA 损伤反应中蛋白质组装的多尺度图谱。
IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 Epub Date: 2023-05-22 DOI: 10.1016/j.cels.2023.04.007
Anton Kratz, Minkyu Kim, Marcus R Kelly, Fan Zheng, Christopher A Koczor, Jianfeng Li, Keiichiro Ono, Yue Qin, Christopher Churas, Jing Chen, Rudolf T Pillich, Jisoo Park, Maya Modak, Rachel Collier, Kate Licon, Dexter Pratt, Robert W Sobol, Nevan J Krogan, Trey Ideker

The DNA damage response (DDR) ensures error-free DNA replication and transcription and is disrupted in numerous diseases. An ongoing challenge is to determine the proteins orchestrating DDR and their organization into complexes, including constitutive interactions and those responding to genomic insult. Here, we use multi-conditional network analysis to systematically map DDR assemblies at multiple scales. Affinity purifications of 21 DDR proteins, with/without genotoxin exposure, are combined with multi-omics data to reveal a hierarchical organization of 605 proteins into 109 assemblies. The map captures canonical repair mechanisms and proposes new DDR-associated proteins extending to stress, transport, and chromatin functions. We find that protein assemblies closely align with genetic dependencies in processing specific genotoxins and that proteins in multiple assemblies typically act in multiple genotoxin responses. Follow-up by DDR functional readouts newly implicates 12 assembly members in double-strand-break repair. The DNA damage response assemblies map is available for interactive visualization and query (ccmi.org/ddram/).

DNA 损伤应答(DDR)确保了无差错的 DNA 复制和转录,并在许多疾病中被破坏。目前的一项挑战是确定协调 DDR 的蛋白质及其复合物组织,包括组成性相互作用和对基因组损伤的反应。在这里,我们利用多条件网络分析系统地绘制了多种尺度的 DDR 组合图。21 种 DDR 蛋白的亲和纯化(有/无基因毒性暴露)与多组学数据相结合,揭示了 605 种蛋白组成 109 个集合体的分层组织。该图谱捕捉到了典型的修复机制,并提出了扩展到应激、转运和染色质功能的新的 DDR 相关蛋白。我们发现,蛋白质组合与处理特定基因毒素的遗传依赖性密切相关,多个组合中的蛋白质通常在多种基因毒素反应中发挥作用。通过对 DDR 功能读数的跟踪,新发现有 12 个集合体成员参与了双链断裂修复。DNA损伤应答装配图可用于交互式可视化和查询(ccmi.org/ddram/)。
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引用次数: 0
Positional influence on cellular transcriptional identity revealed through spatially segmented single-cell transcriptomics. 通过空间分割的单细胞转录组学揭示了位置对细胞转录特性的影响。
IF 9.3 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.003
David B Morse, Aleksandra M Michalowski, Michele Ceribelli, Joachim De Jonghe, Maria Vias, Deanna Riley, Theresa Davies-Hill, Ty Voss, Stefania Pittaluga, Christoph Muus, Jiamin Liu, Samantha Boyle, David A Weitz, James D Brenton, Jason D Buenrostro, Tuomas P J Knowles, Craig J Thomas

Single-cell RNA sequencing (scRNA-seq) is a powerful technique for describing cell states. Identifying the spatial arrangement of these states in tissues remains challenging, with the existing methods requiring niche methodologies and expertise. Here, we describe segmentation by exogenous perfusion (SEEP), a rapid and integrated method to link surface proximity and environment accessibility to transcriptional identity within three-dimensional (3D) disease models. The method utilizes the steady-state diffusion kinetics of a fluorescent dye to establish a gradient along the radial axis of disease models. Classification of sample layers based on dye accessibility enables dissociated and sorted cells to be characterized by transcriptomic and regional identities. Using SEEP, we analyze spheroid, organoid, and in vivo tumor models of high-grade serous ovarian cancer (HGSOC). The results validate long-standing beliefs about the relationship between cell state and position while revealing new concepts regarding how spatially unique microenvironments influence the identity of individual cells within tumors.

单细胞RNA测序(scRNA-seq)是一种描述细胞状态的强大技术。确定这些状态在组织中的空间排列仍然具有挑战性,现有的方法需要利基方法和专业知识。在这里,我们描述了通过外源性灌注(SEEP)进行分割,这是一种在三维(3D)疾病模型中将表面接近性和环境可及性与转录特性联系起来的快速综合方法。该方法利用荧光染料的稳态扩散动力学来建立沿着疾病模型的径向轴的梯度。基于染料可及性的样品层分类使解离和分选的细胞能够通过转录组和区域身份进行表征。使用SEEP,我们分析了高级别浆液性癌症(HGSOC)的球体、类器官和体内肿瘤模型。该结果验证了关于细胞状态和位置之间关系的长期信念,同时揭示了关于空间独特的微环境如何影响肿瘤内单个细胞身份的新概念。
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引用次数: 0
Single-cell A/B testing for cell-cell communication. 用于蜂窝通信的单蜂窝 A/B 测试。
IF 9.3 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.006
Caitlin M Aamodt, Nathan E Lewis

A new method developed by Francisco Quintana's group, systematic perturbation of encapsulated associated cells followed by sequencing (SPEAC-seq), applies a CRISPR screen to co-cultured interacting cells to identify the ligands mediating cell-cell communication. Using this approach, the authors discover the molecular basis of a microglia-astrocyte feedback loop that suppresses neuroinflammatory disease.

弗朗西斯科-金塔纳(Francisco Quintana)研究小组开发的一种新方法--系统扰动包囊关联细胞并测序(SPEAC-seq)--将CRISPR筛选应用于共培养的相互作用细胞,以确定介导细胞间通讯的配体。利用这种方法,作者发现了抑制神经炎性疾病的小胶质细胞-胃细胞反馈环路的分子基础。
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引用次数: 0
BioAutoMATED: An end-to-end automated machine learning tool for explanation and design of biological sequences. BioAutoMATED:一个端到端的自动化机器学习工具,用于解释和设计生物序列。
IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.007
Jacqueline A Valeri, Luis R Soenksen, Katherine M Collins, Pradeep Ramesh, George Cai, Rani Powers, Nicolaas M Angenent-Mari, Diogo M Camacho, Felix Wong, Timothy K Lu, James J Collins

The design choices underlying machine-learning (ML) models present important barriers to entry for many biologists who aim to incorporate ML in their research. Automated machine-learning (AutoML) algorithms can address many challenges that come with applying ML to the life sciences. However, these algorithms are rarely used in systems and synthetic biology studies because they typically do not explicitly handle biological sequences (e.g., nucleotide, amino acid, or glycan sequences) and cannot be easily compared with other AutoML algorithms. Here, we present BioAutoMATED, an AutoML platform for biological sequence analysis that integrates multiple AutoML methods into a unified framework. Users are automatically provided with relevant techniques for analyzing, interpreting, and designing biological sequences. BioAutoMATED predicts gene regulation, peptide-drug interactions, and glycan annotation, and designs optimized synthetic biology components, revealing salient sequence characteristics. By automating sequence modeling, BioAutoMATED allows life scientists to incorporate ML more readily into their work.

机器学习(ML)模型的设计选择为许多旨在将ML纳入研究的生物学家提供了重要的入门障碍。自动机器学习(AutoML)算法可以解决将ML应用于生命科学所带来的许多挑战。然而,这些算法很少用于系统和合成生物学研究,因为它们通常不明确处理生物序列(例如核苷酸、氨基酸或聚糖序列),并且不能容易地与其他AutoML算法进行比较。在这里,我们介绍了BioAutoMATED,一个用于生物序列分析的AutoML平台,它将多种AutoML方法集成到一个统一的框架中。自动向用户提供用于分析、解释和设计生物序列的相关技术。BioAutoMATED预测基因调控、肽-药物相互作用和聚糖注释,并设计优化的合成生物学成分,揭示显著的序列特征。通过自动化序列建模,BioAutoMATED使生命科学家能够更容易地将ML纳入他们的工作中。
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引用次数: 0
Redesign of an Escherichia coli Nissle treatment for phenylketonuria using insulated genomic landing pads and genetic circuits to reduce burden. 利用绝缘基因组着陆垫和基因电路重新设计治疗苯丙酮尿症的大肠杆菌尼氏疗法,以减轻负担。
IF 9.3 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.004
Alexander J Triassi, Brandon D Fields, Catherine E Monahan, Jillian M Means, Yongjin Park, Hamid Doosthosseini, Jai P Padmakumar, Vincent M Isabella, Christopher A Voigt

To build therapeutic strains, Escherichia coli Nissle (EcN) have been engineered to express antibiotics, toxin-degrading enzymes, immunoregulators, and anti-cancer chemotherapies. For efficacy, the recombinant genes need to be highly expressed, but this imposes a burden on the cell, and plasmids are difficult to maintain in the body. To address these problems, we have developed landing pads in the EcN genome and genetic circuits to control therapeutic gene expression. These tools were applied to EcN SYNB1618, undergoing clinical trials as a phenylketonuria treatment. The pathway for converting phenylalanine to trans-cinnamic acid was moved to a landing pad under the control of a circuit that keeps the pathway off during storage. The resulting strain (EcN SYN8784) achieved higher activity than EcN SYNB1618, reaching levels near when the pathway is carried on a plasmid. This work demonstrates a simple system for engineering EcN that aids quantitative strain design for therapeutics.

为了构建治疗菌株,人们设计了大肠杆菌 Nissle(EcN)来表达抗生素、毒素降解酶、免疫调节剂和抗癌化疗药物。为了达到疗效,重组基因需要高度表达,但这给细胞带来了负担,而且质粒在体内难以维持。为了解决这些问题,我们在 EcN 基因组中开发了着陆垫和基因回路,以控制治疗基因的表达。这些工具已应用于正在进行苯丙酮尿症临床试验的 EcN SYNB1618。将苯丙氨酸转化为反式肉桂酸的途径被转移到了一个着陆垫上,该着陆垫由一个电路控制,可在储存期间关闭该途径。由此产生的菌株(EcN SYN8784)比 EcN SYNB1618 具有更高的活性,达到了质粒上携带该途径时的水平。这项工作展示了一种简单的 EcN 工程系统,有助于定量设计用于治疗的菌株。
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引用次数: 0
The trans-regulatory landscape of gene networks in plants. 植物基因网络的跨调控格局。
IF 9.3 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.002
Niklas F C Hummel, Andy Zhou, Baohua Li, Kasey Markel, Izaiah J Ornelas, Patrick M Shih

The transcriptional effector domains of transcription factors play a key role in controlling gene expression; however, their functional nature is poorly understood, hampering our ability to explore this fundamental dimension of gene regulatory networks. To map the trans-regulatory landscape in a complex eukaryote, we systematically characterized the putative transcriptional effector domains of over 400 Arabidopsis thaliana transcription factors for their capacity to modulate transcription. We demonstrate that transcriptional effector activity can be integrated into gene regulatory networks capable of elucidating the functional dynamics underlying gene expression patterns. We further show how our characterized domains can enhance genome engineering efforts and reveal how plant transcriptional activators share regulatory features conserved across distantly related eukaryotes. Our results provide a framework to systematically characterize the regulatory role of transcription factors at a genome-scale in order to understand the transcriptional wiring of biological systems.

转录因子的转录效应结构域在控制基因表达方面起着关键作用;然而,人们对它们的功能性质知之甚少,这阻碍了我们探索基因调控网络这一基本层面的能力。为了绘制复杂真核生物的转录调控图谱,我们系统地鉴定了拟南芥 400 多个转录因子的推测转录效应结构域,以确定它们的转录调控能力。我们证明,转录效应器活性可被整合到基因调控网络中,从而阐明基因表达模式背后的功能动态。我们进一步展示了我们表征的结构域如何增强基因组工程工作,并揭示了植物转录激活因子如何与远缘真核生物共享调控特征。我们的研究结果为在基因组尺度上系统描述转录因子的调控作用提供了一个框架,以便了解生物系统的转录线路。
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引用次数: 0
The computational capabilities of many-to-many protein interaction networks. 多对多蛋白质相互作用网络的计算能力。
IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.001
Heidi E Klumpe, Jordi Garcia-Ojalvo, Michael B Elowitz, Yaron E Antebi

Many biological circuits comprise sets of protein variants that interact with one another in a many-to-many, or promiscuous, fashion. These architectures can provide powerful computational capabilities that are especially critical in multicellular organisms. Understanding the principles of biochemical computations in these circuits could allow more precise control of cellular behaviors. However, these systems are inherently difficult to analyze, due to their large number of interacting molecular components, partial redundancies, and cell context dependence. Here, we discuss recent experimental and theoretical advances that are beginning to reveal how promiscuous circuits compute, what roles those computations play in natural biological contexts, and how promiscuous architectures can be applied for the design of synthetic multicellular behaviors.

许多生物电路由一组蛋白质变体组成,这些变体以多对多或杂交的方式相互影响。这些结构可以提供强大的计算能力,这在多细胞生物体中尤为重要。了解这些电路中的生化计算原理可以更精确地控制细胞行为。然而,由于存在大量相互作用的分子成分、部分冗余和细胞上下文依赖性,这些系统本身很难分析。在这里,我们将讨论最近在实验和理论方面取得的进展,这些进展开始揭示杂交电路是如何计算的、这些计算在自然生物环境中扮演什么角色,以及如何将杂交架构应用于合成多细胞行为的设计。
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引用次数: 0
High-throughput discovery and characterization of viral transcriptional effectors in human cells. 人类细胞中病毒转录效应物的高通量发现和表征。
IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2023-06-21 DOI: 10.1016/j.cels.2023.05.008
Connor H Ludwig, Abby R Thurm, David W Morgens, Kevin J Yang, Josh Tycko, Michael C Bassik, Britt A Glaunsinger, Lacramioara Bintu

Viruses encode transcriptional regulatory proteins critical for controlling viral and host gene expression. Given their multifunctional nature and high sequence divergence, it is unclear which viral proteins can affect transcription and which specific sequences contribute to this function. Using a high-throughput assay, we measured the transcriptional regulatory potential of over 60,000 protein tiles across ∼1,500 proteins from 11 coronaviruses and all nine human herpesviruses. We discovered hundreds of transcriptional effector domains, including a conserved repression domain in all coronavirus Spike homologs, dual activation-repression domains in viral interferon regulatory factors (VIRFs), and an activation domain in six herpesvirus homologs of the single-stranded DNA-binding protein that we show is important for viral replication and late gene expression in Kaposi's sarcoma-associated herpesvirus (KSHV). For the effector domains we identified, we investigated their mechanisms via high-throughput sequence and chemical perturbations, pinpointing sequence motifs essential for function. This work massively expands viral protein annotations, serving as a springboard for studying their biological and health implications and providing new candidates for compact gene regulation tools.

病毒编码对控制病毒和宿主基因表达至关重要的转录调控蛋白。鉴于其多功能性和高度序列差异,目前尚不清楚哪些病毒蛋白可以影响转录,哪些特定序列有助于这种功能。使用高通量分析,我们测量了来自11种冠状病毒和所有9种人类疱疹病毒的约1500种蛋白质中超过60000个蛋白质瓦片的转录调控潜力。我们发现了数百个转录效应结构域,包括所有冠状病毒刺突同源物中的保守抑制结构域、病毒干扰素调节因子(VIRF)中的双重激活抑制结构域,以及单链DNA结合蛋白的六种疱疹病毒同源物中的激活结构域,我们发现该激活结构域对卡波西肉瘤相关疱疹病毒(KSHV)的病毒复制和晚期基因表达很重要。对于我们鉴定的效应结构域,我们通过高通量序列和化学扰动研究了它们的机制,精确定位了功能所必需的序列基序。这项工作极大地扩展了病毒蛋白注释,为研究其生物学和健康意义提供了跳板,并为紧凑型基因调控工具提供了新的候选者。
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引用次数: 0
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Cell Systems
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