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Absolute quantitative and base-resolution sequencing reveals comprehensive landscape of pseudouridine across the human transcriptome 绝对定量和碱基分辨率测序揭示了假尿苷在人类转录组中的全面分布。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-30 DOI: 10.1038/s41592-024-02439-8
Haiqi Xu, Linzhen Kong, Jingfei Cheng, Khatoun Al Moussawi, Xiufei Chen, Aleema Iqbal, Peter A. C. Wing, James M. Harris, Senko Tsukuda, Azman Embarc-Buh, Guifeng Wei, Alfredo Castello, Skirmantas Kriaucionis, Jane A. McKeating, Xin Lu, Chun-Xiao Song
Pseudouridine (Ψ) is one of the most abundant modifications in cellular RNA. However, its function remains elusive, mainly due to the lack of highly sensitive and accurate detection methods. Here, we introduced 2-bromoacrylamide-assisted cyclization sequencing (BACS), which enables Ψ-to-C transitions, for quantitative profiling of Ψ at single-base resolution. BACS allowed the precise identification of Ψ positions, especially in densely modified Ψ regions and consecutive uridine sequences. BACS detected all known Ψ sites in human rRNA and spliceosomal small nuclear RNAs and generated the quantitative Ψ map of human small nucleolar RNA and tRNA. Furthermore, BACS simultaneously detected adenosine-to-inosine editing sites and N1-methyladenosine. Depletion of pseudouridine synthases TRUB1, PUS7 and PUS1 elucidated their targets and sequence motifs. We further identified a highly abundant Ψ114 site in Epstein–Barr virus-encoded small RNA EBER2. Surprisingly, applying BACS to a panel of RNA viruses demonstrated the absence of Ψ in their viral transcripts or genomes, shedding light on differences in pseudouridylation across virus families. This study introduces a chemical method, BACS, that generates Ψ-to-C mutation signatures, allowing for sequencing and quantification of Ψ at single-base resolution.
伪尿嘧啶(Ψ)是细胞 RNA 中最丰富的修饰之一。然而,主要由于缺乏高灵敏度和精确的检测方法,其功能仍然难以捉摸。在这里,我们引入了 2-溴丙烯酰胺辅助环化测序(BACS),它能实现Ψ到C的转变,以单碱基分辨率定量分析Ψ。BACS 能够精确鉴定Ψ位置,尤其是在密集修饰的Ψ区域和连续尿苷序列中。BACS 检测了人类 rRNA 和剪接体小核 RNA 中所有已知的 Ψ 位点,并生成了人类小核 RNA 和 tRNA 的定量 Ψ 图谱。此外,BACS 还能同时检测腺苷-肌苷编辑位点和 N1-甲基腺苷。假尿嘧啶合成酶 TRUB1、PUS7 和 PUS1 的消耗阐明了它们的靶标和序列基序。我们还在 Epstein-Barr 病毒编码的小 RNA EBER2 中发现了一个高含量的 Ψ114 位点。令人惊讶的是,将 BACS 应用于一组 RNA 病毒时,发现它们的病毒转录本或基因组中没有Ψ,从而揭示了不同病毒家族中假酰化的差异。
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引用次数: 0
Making fluorescence-based integrative structures and associated kinetic information accessible 使基于荧光的整合结构和相关动力学信息变得易于获取。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-30 DOI: 10.1038/s41592-024-02428-x
Christian A. Hanke, John D. Westbrook, Benjamin M. Webb, Thomas-O. Peulen, Catherine L. Lawson, Andrej Sali, Helen M. Berman, Claus A. M. Seidel, Brinda Vallat
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引用次数: 0
Tracking neurons across days with high-density probes. 利用高密度探针跨天追踪神经元
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-27 DOI: 10.1038/s41592-024-02440-1
Enny H van Beest, Célian Bimbard, Julie M J Fabre, Sam W Dodgson, Flóra Takács, Philip Coen, Anna Lebedeva, Kenneth D Harris, Matteo Carandini

Neural activity spans multiple time scales, from milliseconds to months. Its evolution can be recorded with chronic high-density arrays such as Neuropixels probes, which can measure each spike at tens of sites and record hundreds of neurons. These probes produce vast amounts of data that require different approaches for tracking neurons across recordings. Here, to meet this need, we developed UnitMatch, a pipeline that operates after spike sorting, based only on each unit's average spike waveform. We tested UnitMatch in Neuropixels recordings from the mouse brain, where it tracked neurons across weeks. Across the brain, neurons had distinctive inter-spike interval distributions. Their correlations with other neurons remained stable over weeks. In the visual cortex, the neurons' selectivity for visual stimuli remained similarly stable. In the striatum, however, neuronal responses changed across days during learning of a task. UnitMatch is thus a promising tool to reveal both invariance and plasticity in neural activity across days.

神经活动跨越多个时间尺度,从毫秒到数月不等。神经活动的演变可以通过神经像素探针等慢性高密度阵列记录下来,这些探针可以在数十个点测量每个尖峰,记录数百个神经元。这些探针能产生大量数据,因此需要不同的方法来跟踪记录中的神经元。为了满足这一需求,我们开发了单元匹配(UnitMatch),这是一种在尖峰分类后仅根据每个单元的平均尖峰波形进行操作的管道。我们在小鼠大脑的 Neuropixels 记录中对 UnitMatch 进行了测试,它可以追踪数周内的神经元。在整个大脑中,神经元具有独特的尖峰间期分布。它们与其他神经元的相关性在数周内保持稳定。在视觉皮层,神经元对视觉刺激的选择性同样保持稳定。然而,在纹状体中,神经元的反应会在学习任务的不同天数中发生变化。因此,UnitMatch 是一种很有前途的工具,可以揭示神经活动在不同天数中的不变性和可塑性。
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引用次数: 0
Vitessce: integrative visualization of multimodal and spatially resolved single-cell data. Vitessce:多模态和空间分辨单细胞数据的综合可视化。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-27 DOI: 10.1038/s41592-024-02436-x
Mark S Keller, Ilan Gold, Chuck McCallum, Trevor Manz, Peter V Kharchenko, Nils Gehlenborg

Multiomics technologies with single-cell and spatial resolution make it possible to measure thousands of features across millions of cells. However, visual analysis of high-dimensional transcriptomic, proteomic, genome-mapped and imaging data types simultaneously remains a challenge. Here we describe Vitessce, an interactive web-based visualization framework for exploration of multimodal and spatially resolved single-cell data. We demonstrate integrative visualization of millions of data points, including cell-type annotations, gene expression quantities, spatially resolved transcripts and cell segmentations, across multiple coordinated views. The open-source software is available at http://vitessce.io .

具有单细胞和空间分辨率的多组学技术使测量数百万个细胞的数千个特征成为可能。然而,同时对高维转录组学、蛋白质组学、基因组图谱和成像数据类型进行可视化分析仍然是一项挑战。在这里,我们介绍了 Vitessce,这是一个基于网络的交互式可视化框架,用于探索多模态和空间分辨单细胞数据。我们展示了数百万个数据点的综合可视化,包括跨多个协调视图的细胞类型注释、基因表达量、空间解析转录本和细胞分割。开源软件见 http://vitessce.io。
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引用次数: 0
Strainy: phasing and assembly of strain haplotypes from long-read metagenome sequencing 菌株:长线程元基因组测序中菌株单倍型的分期和组装。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-26 DOI: 10.1038/s41592-024-02424-1
Ekaterina Kazantseva, Ataberk Donmez, Maria Frolova, Mihai Pop, Mikhail Kolmogorov
Bacterial species in microbial communities are often represented by mixtures of strains, distinguished by small variations in their genomes. Short-read approaches can be used to detect small-scale variation between strains but fail to phase these variants into contiguous haplotypes. Long-read metagenome assemblers can generate contiguous bacterial chromosomes but often suppress strain-level variation in favor of species-level consensus. Here we present Strainy, an algorithm for strain-level metagenome assembly and phasing from Nanopore and PacBio reads. Strainy takes a de novo metagenomic assembly as input and identifies strain variants, which are then phased and assembled into contiguous haplotypes. Using simulated and mock Nanopore and PacBio metagenome data, we show that Strainy assembles accurate and complete strain haplotypes, outperforming current Nanopore-based methods and comparable with PacBio-based algorithms in completeness and accuracy. We then use Strainy to assemble strain haplotypes of a complex environmental metagenome, revealing distinct strain distribution and mutational patterns in bacterial species. This work presents Strainy, a long-read metagenome assembler that allows the identification of strain distributions and mutational patterns in environmental metagenomes.
微生物群落中的细菌物种通常由菌株混合物代表,以其基因组中的微小变异加以区分。短读数方法可用于检测菌株之间的小规模变异,但无法将这些变异分期为连续的单倍型。长读数元基因组组装器可以生成连续的细菌染色体,但往往会抑制菌株级变异,而倾向于物种级共识。在此,我们介绍 Strainy,这是一种利用 Nanopore 和 PacBio 读数进行菌株级元基因组组装和分期的算法。Strainy 将全新的元基因组组装作为输入,识别菌株变异,然后将其分期并组装成连续的单倍型。我们使用模拟和仿真的 Nanopore 和 PacBio 元基因组数据表明,Strainy 能组装出准确、完整的菌株单倍型,在完整性和准确性方面优于目前基于 Nanopore 的方法,也可与基于 PacBio 的算法媲美。然后,我们使用 Strainy 组装了复杂环境元基因组的菌株单倍型,揭示了细菌物种中独特的菌株分布和突变模式。
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引用次数: 0
Benchmarking algorithms for single-cell multi-omics prediction and integration 单细胞多组学预测和整合的基准算法。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-25 DOI: 10.1038/s41592-024-02429-w
Yinlei Hu, Siyuan Wan, Yuanhanyu Luo, Yuanzhe Li, Tong Wu, Wentao Deng, Chen Jiang, Shan Jiang, Yueping Zhang, Nianping Liu, Zongcheng Yang, Falai Chen, Bin Li, Kun Qu
The development of single-cell multi-omics technology has greatly enhanced our understanding of biology, and in parallel, numerous algorithms have been proposed to predict the protein abundance and/or chromatin accessibility of cells from single-cell transcriptomic information and to integrate various types of single-cell multi-omics data. However, few studies have systematically compared and evaluated the performance of these algorithms. Here, we present a benchmark study of 14 protein abundance/chromatin accessibility prediction algorithms and 18 single-cell multi-omics integration algorithms using 47 single-cell multi-omics datasets. Our benchmark study showed overall totalVI and scArches outperformed the other algorithms for predicting protein abundance, and LS_Lab was the top-performing algorithm for the prediction of chromatin accessibility in most cases. Seurat, MOJITOO and scAI emerge as leading algorithms for vertical integration, whereas totalVI and UINMF excel beyond their counterparts in both horizontal and mosaic integration scenarios. Additionally, we provide a pipeline to assist researchers in selecting the optimal multi-omics prediction and integration algorithm. This Analysis study compares computational methods for single-cell multi-omics prediction and integration, generating useful insights for method users and developers working with different analysis purposes and biological problems.
单细胞多组学技术的发展极大地促进了我们对生物学的理解,与此同时,人们也提出了许多算法来预测单细胞转录组信息中蛋白质的丰度和/或细胞染色质的可及性,以及整合各种类型的单细胞多组学数据。然而,很少有研究系统地比较和评估这些算法的性能。在此,我们利用 47 个单细胞多组学数据集对 14 种蛋白质丰度/染色质可及性预测算法和 18 种单细胞多组学整合算法进行了基准研究。我们的基准研究表明,在预测蛋白质丰度方面,totalVI 和 scArches 的总体表现优于其他算法,而在预测染色质可及性方面,LS_Lab 在大多数情况下是表现最好的算法。Seurat、MOJITOO 和 scAI 成为垂直整合的领先算法,而 totalVI 和 UINMF 则在水平整合和镶嵌整合场景中表现出色。此外,我们还提供了一个管道,帮助研究人员选择最佳的多组学预测和整合算法。
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引用次数: 0
Controlling the sound of light: photoswitching optoacoustic imaging 控制光声:光开关光声成像。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-25 DOI: 10.1038/s41592-024-02396-2
Andre C. Stiel, Vasilis Ntziachristos
Optoacoustic (photoacoustic) imaging advances allow high-resolution optical imaging much deeper than optical microscopy. However, while label-free optoacoustics have already entered clinical application, biological imaging is in need of ubiquitous optoacoustic labels for use in ways that are similar to how fluorescent proteins propelled optical microscopy. We review photoswitching advances that shine a new light or, in analogy, ‘bring a new sound’ to biological optoacoustic imaging. Based on engineered labels and novel devices, switching uses light or other energy forms and enables signal modulation and synchronous detection for maximizing contrast and detection sensitivity over other optoacoustic labels. Herein, we explain contrast enhancement in the spectral versus temporal domains and review labels and key concepts of switching and their properties to modulate optoacoustic signals. We further outline systems and applications and discuss how switching can enable optoacoustic imaging of cellular or molecular contrast at depths and resolutions beyond those of other optical methods. This Review describes how photoswitchable probes and associated hardware innovations are poised to transform optoacoustic imaging in life sciences research.
光声(光声)成像技术的进步使高分辨率光学成像比光学显微镜成像更深入。然而,虽然无标签光声技术已经进入临床应用,但生物成像还需要无处不在的光声标签,其使用方式类似于荧光蛋白推动光学显微镜技术的发展。我们回顾了光开关技术的进展,这些技术为生物光声成像带来了新的亮点,或者打个比方,"带来了新的声音"。与其他光声标签相比,光开关以工程标签和新型设备为基础,利用光或其他能量形式实现信号调制和同步检测,从而最大限度地提高对比度和检测灵敏度。在此,我们将解释光谱域与时间域的对比度增强,回顾标签和开关的关键概念及其调制光声信号的特性。我们进一步概述了系统和应用,并讨论了切换如何使细胞或分子对比的光声成像在深度和分辨率上超越其他光学方法。
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引用次数: 0
Neural space-time model for dynamic multi-shot imaging. 用于动态多镜头成像的神经时空模型
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-24 DOI: 10.1038/s41592-024-02417-0
Ruiming Cao, Nikita S Divekar, James K Nuñez, Srigokul Upadhyayula, Laura Waller

Computational imaging reconstructions from multiple measurements that are captured sequentially often suffer from motion artifacts if the scene is dynamic. We propose a neural space-time model (NSTM) that jointly estimates the scene and its motion dynamics, without data priors or pre-training. Hence, we can both remove motion artifacts and resolve sample dynamics from the same set of raw measurements used for the conventional reconstruction. We demonstrate NSTM in three computational imaging systems: differential phase-contrast microscopy, three-dimensional structured illumination microscopy and rolling-shutter DiffuserCam. We show that NSTM can recover subcellular motion dynamics and thus reduce the misinterpretation of living systems caused by motion artifacts.

如果场景是动态的,那么根据连续捕获的多个测量值进行的计算成像重建往往会出现运动伪影。我们提出了一种神经时空模型 (NSTM),它可以联合估计场景及其运动动态,而无需数据先验或预训练。因此,我们既能消除运动伪影,又能从用于传统重建的同一组原始测量数据中解析样本动态。我们在三个计算成像系统中演示了 NSTM:差分相位对比显微镜、三维结构照明显微镜和滚动快门 DiffuserCam。我们表明,NSTM 可以恢复亚细胞运动动态,从而减少运动伪影对生命系统的误读。
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引用次数: 0
Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs 利用增强型 ISDra2 TnpB 系统和深度学习预测的 ωRNAs 进行有效的基因组编辑。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-23 DOI: 10.1038/s41592-024-02418-z
Kim Fabiano Marquart, Nicolas Mathis, Amina Mollaysa, Saphira Müller, Lucas Kissling, Tanja Rothgangl, Lukas Schmidheini, Péter István Kulcsár, Ahmed Allam, Masako M. Kaufmann, Mai Matsushita, Tatjana Haenggi, Toni Cathomen, Manfred Kopf, Michael Krauthammer, Gerald Schwank
Transposon (IS200/IS605)-encoded TnpB proteins are predecessors of class 2 type V CRISPR effectors and have emerged as one of the most compact genome editors identified thus far. Here, we optimized the design of Deinococcus radiodurans (ISDra2) TnpB for application in mammalian cells (TnpBmax), leading to an average 4.4-fold improvement in editing. In addition, we developed variants mutated at position K76 that recognize alternative target-adjacent motifs (TAMs), expanding the targeting range of ISDra2 TnpB. We further generated an extensive dataset on TnpBmax editing efficiencies at 10,211 target sites. This enabled us to delineate rules for on-target and off-target editing and to devise a deep learning model, termed TnpB editing efficiency predictor (TEEP; https://www.tnpb.app ), capable of predicting ISDra2 TnpB guiding RNA (ωRNA) activity with high performance (r > 0.8). Employing TEEP, we achieved editing efficiencies up to 75.3% in the murine liver and 65.9% in the murine brain after adeno-associated virus (AAV) vector delivery of TnpBmax. Overall, the set of tools presented in this study facilitates the application of TnpB as an ultracompact programmable endonuclease in research and therapeutics. This work introduces engineered TnpBmax proteins with enhanced efficiency and an expanded targeting range. By leveraging an extensive dataset on editing efficiencies, it also integrates a deep learning model to predict guide RNA activity.
转座子(IS200/IS605)编码的 TnpB 蛋白是 2 类 V 型 CRISPR 效应器的前身,是迄今为止发现的最紧凑的基因组编辑器之一。在这里,我们优化了放射球菌(ISDra2)TnpB 的设计,使其适用于哺乳动物细胞(TnpBmax),从而使编辑能力平均提高了 4.4 倍。此外,我们还开发了在 K76 位发生突变的变体,它们能识别替代的靶邻接基序(TAM),从而扩大了 ISDra2 TnpB 的靶向范围。我们还在 10211 个靶点上生成了 TnpB 最大编辑效率的大量数据集。这使我们能够划定靶上编辑和脱靶编辑的规则,并设计出一种称为 TnpB 编辑效率预测器(TEEP; https://www.tnpb.app )的深度学习模型,该模型能够以高性能(r > 0.8)预测 ISDra2 TnpB 引导 RNA(ωRNA)的活性。利用 TEEP,我们在腺相关病毒(AAV)载体递送 TnpBmax 后,在小鼠肝脏和小鼠大脑中分别实现了高达 75.3% 和 65.9% 的编辑效率。总之,本研究中介绍的这套工具促进了 TnpB 作为超小型可编程内切酶在研究和治疗中的应用。
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引用次数: 0
Expanding the genome editing toolbox with designer CRISPR–Cas-like transposons 利用类似 CRISPR-Cas 的转座子扩展基因组编辑工具箱。
IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-23 DOI: 10.1038/s41592-024-02460-x
Similarly to CRISPR–Cas systems, TnpB proteins from bacterial transposons can be employed as RNA-guided endonucleases for genome editing. By combining rational protein design and machine learning, ISDra2 TnpB variants with enhanced editing efficiency and a broader targeting range were developed, along with a prediction tool to design effective guiding RNAs.
与CRISPR-Cas系统类似,细菌转座子中的TnpB蛋白也可以作为RNA引导的内切酶用于基因组编辑。通过将合理的蛋白质设计与机器学习相结合,开发出了编辑效率更高、靶向范围更广的 ISDra2 TnpB 变体,以及设计有效引导 RNA 的预测工具。
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引用次数: 0
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