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"Forcing" new interpretations of molecular tension sensor studies. "迫使 "对分子张力传感器研究做出新的解释。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-07-15 DOI: 10.1016/j.crmeth.2024.100821
Matthew R Pawlak, Adam T Smiley, Wendy R Gordon

Molecular tension sensors are central tools for mechanobiology studies but have limitations in interpretation. Reporting in Cell Reports Methods, Shoyer et al. discover that fluorescent protein photoswitching in concert with sensor extension may expand the use and interpretation of common force-sensing tools.

分子张力传感器是机械生物学研究的核心工具,但在解释方面存在局限性。Shoyer 等人在《细胞报告方法》(Cell Reports Methods)上报告说,荧光蛋白光开关与传感器延伸的协同作用可能会扩大普通力传感工具的使用和解释范围。
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引用次数: 0
PANAMA-enabled high-sensitivity dual nanoflow LC-MS metabolomics and proteomics analysis. PANAMA 支持高灵敏度双纳米流 LC-MS 代谢组学和蛋白质组学分析。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-07-15 Epub Date: 2024-07-02 DOI: 10.1016/j.crmeth.2024.100803
Weiwei Lin, Fatemeh Mousavi, Benjamin C Blum, Christian F Heckendorf, Matthew Lawton, Noah Lampl, Ryan Hekman, Hongbo Guo, Mark McComb, Andrew Emili

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation.

高灵敏度纳米流液相色谱(nLC)很少用于非靶向代谢组学,因为目前的样品制备技术无法有效防止纳米毛细管色谱柱性能下降。在此,我们介绍了一种基于 nLC 的串联质谱工作流程,该流程可实现代谢组学(包括脂质组学)和蛋白质组学的无缝联合分析和整合,而无需重复使用仪器。该工作流程基于一个强大的固相微萃取步骤,用于常规样品净化和生物活性分子富集。我们的方法被称为蛋白质组和纳米流代谢组分析(PANAMA),与现有的广泛使用的分析程序相比,它提高了化合物的分辨率和检测灵敏度,同时不影响覆盖深度。值得注意的是,PANAMA 可应用于多种样本,包括生物流体、细胞系和组织样本。它能生成高质量、信息丰富的代谢物-蛋白质数据集,而无需专门的仪器。
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引用次数: 0
A practical introduction to holo-omics. 整体组学实用入门。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-07-15 Epub Date: 2024-07-09 DOI: 10.1016/j.crmeth.2024.100820
Iñaki Odriozola, Jacob A Rasmussen, M Thomas P Gilbert, Morten T Limborg, Antton Alberdi

Holo-omics refers to the joint study of non-targeted molecular data layers from host-microbiota systems or holobionts, which is increasingly employed to disentangle the complex interactions between the elements that compose them. We navigate through the generation, analysis, and integration of omics data, focusing on the commonalities and main differences to generate and analyze the various types of omics, with a special focus on optimizing data generation and integration. We advocate for careful generation and distillation of data, followed by independent exploration and analyses of the single omic layers to obtain a better understanding of the study system, before the integration of multiple omic layers in a final model is attempted. We highlight critical decision points to achieve this aim and flag the main challenges to address complex biological questions regarding the integrative study of host-microbiota relationships.

整体组学(Holo-omics)指的是对宿主-微生物群系统或整体生物体的非目标分子数据层进行联合研究,这种研究越来越多地被用来揭示组成宿主-微生物群系统或整体生物体的各要素之间复杂的相互作用。我们将通过生成、分析和整合 omics 数据,重点介绍生成和分析各种类型 omics 的共性和主要差异,尤其关注优化数据生成和整合。我们主张仔细生成和提炼数据,然后对单个 omic 层进行独立探索和分析,以便更好地了解研究系统,最后再尝试将多个 omic 层整合到最终模型中。我们强调了实现这一目标的关键决策点,并指出了解决有关宿主-微生物群关系综合研究的复杂生物学问题所面临的主要挑战。
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引用次数: 0
A co-culture system of macrophages with breast cancer tumoroids to study cell interactions and therapeutic responses. 用于研究细胞相互作用和治疗反应的巨噬细胞与乳腺癌肿瘤细胞共培养系统。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 Epub Date: 2024-06-10 DOI: 10.1016/j.crmeth.2024.100792
Antonella Raffo-Romero, Lydia Ziane-Chaouche, Sophie Salomé-Desnoulez, Nawale Hajjaji, Isabelle Fournier, Michel Salzet, Marie Duhamel

3D tumoroids have revolutionized in vitro/ex vivo cancer biology by recapitulating the complex diversity of tumors. While tumoroids provide new insights into cancer development and treatment response, several limitations remain. As the tumor microenvironment, especially the immune system, strongly influences tumor development, the absence of immune cells in tumoroids may lead to inappropriate conclusions. Macrophages, key players in tumor progression, are particularly challenging to integrate into the tumoroids. In this study, we established three optimized and standardized methods for co-culturing human macrophages with breast cancer tumoroids: a semi-liquid model and two matrix-embedded models tailored for specific applications. We then tracked interactions and macrophage infiltration in these systems using flow cytometry and light sheet microscopy and showed that macrophages influenced not only tumoroid molecular profiles but also chemotherapy response. This underscores the importance of increasing the complexity of 3D models to more accurately reflect in vivo conditions.

三维肿瘤模型再现了肿瘤的复杂多样性,从而彻底改变了体外/体内癌症生物学。虽然三维肿瘤实体为了解癌症发展和治疗反应提供了新的视角,但仍存在一些局限性。由于肿瘤微环境,尤其是免疫系统,对肿瘤发生发展有很大影响,肿瘤组织中免疫细胞的缺失可能导致不恰当的结论。巨噬细胞是肿瘤进展过程中的关键角色,要将其整合到肿瘤组织中尤其具有挑战性。在这项研究中,我们建立了三种优化和标准化的方法来共同培养人巨噬细胞与乳腺癌瘤体:一种半液体模型和两种为特定应用定制的基质包埋模型。然后,我们使用流式细胞术和光片显微镜跟踪了这些系统中的相互作用和巨噬细胞浸润情况,结果表明巨噬细胞不仅影响肿瘤分子特征,还影响化疗反应。这强调了增加三维模型复杂性以更准确地反映体内情况的重要性。
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引用次数: 0
DNA-PAINT adaptors make for efficient multiplexing. DNA-PAINT 适配器可实现高效的多路复用。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 DOI: 10.1016/j.crmeth.2024.100801
Matthew D Lycas, Suliana Manley

Multiplexed super-resolution imaging offers a route to spatial proteomics; however, time-efficient mapping of many protein species has been challenging. Two recent works in Cell highlight SUM-PAINT and FLASH-PAINT, methods that leverage adaptor DNA strand design to combine advances in multiplexing with increases in speed of label exchange. These advances permit unbiased omics-style analyses to advance biological insights from super-resolution images.

多路复用超分辨率成像为空间蛋白质组学提供了一条途径;然而,许多蛋白质种类的时间效率绘图一直是个挑战。最近发表在《细胞》(Cell)杂志上的两篇论文重点介绍了SUM-PAINT和FLASH-PAINT,这两种方法利用适配器DNA链的设计,将多路复用技术的进步与标签交换速度的提高结合起来。这些进步使得无偏见的omics式分析得以从超分辨率图像中推进生物洞察力。
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引用次数: 0
ElecFeX is a user-friendly toolbox for efficient feature extraction from single-cell electrophysiological recordings. ElecFeX 是一个用户友好型工具箱,用于从单细胞电生理记录中高效提取特征。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 Epub Date: 2024-06-06 DOI: 10.1016/j.crmeth.2024.100791
Xinyue Ma, Loïs S Miraucourt, Haoyi Qiu, Mengyi Xu, Erik P Cook, Arjun Krishnaswamy, Reza Sharif-Naeini, Anmar Khadra

Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets.

要了解行为和认知功能的神经基础,就必须通过神经元的电生理表型来确定其特征。技术的发展使我们能够收集数以百计的神经记录,这就需要能够高效进行特征提取的新工具。为了满足对功能强大且易于使用的工具的迫切需求,我们开发了基于 MATLAB 的开源工具箱 ElecFeX,该工具箱(1)具有直观的图形用户界面,(2)可对多种电生理特征进行自定义测量,(3)通过批量分析毫不费力地处理大型数据集,(4)提供格式化输出以供进一步分析。我们在一组不同的神经记录中实施了 ElecFeX,证明了它在捕捉电特征方面的功能性、通用性和效率,并确定了它在区分不同脑区和物种的神经元亚群方面的重要性。因此,ElecFeX 是一个用户友好型工具箱,可最大限度地缩短从电生理数据集中提取特征所需的时间,从而造福于神经科学界。
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引用次数: 0
Improved detection of tryptic immunoglobulin variable region peptides by chromatographic and gas-phase fractionation techniques. 利用色谱和气相分馏技术改进对胰蛋白酶免疫球蛋白可变区肽的检测。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 Epub Date: 2024-06-10 DOI: 10.1016/j.crmeth.2024.100795
Christoph Stingl, Martijn M VanDuijn, Thomas Dejoie, Peter A E Sillevis Smitt, Theo M Luider

The polyclonal repertoire of circulating antibodies potentially holds valuable information about an individual's humoral immune state. While bottom-up proteomics is well suited for serum proteomics, the vast number of antibodies and dynamic range of serum challenge this analysis. To acquire the serum proteome more comprehensively, we incorporated high-field asymmetric waveform ion-mobility spectrometry (FAIMS) or two-dimensional chromatography into standard trypsin-based bottom-up proteomics. Thereby, the number of variable region (VR)-related spectra increased 1.7-fold with FAIMS and 10-fold with chromatography fractionation. To match antibody VRs to spectra, we combined de novo searching and BLAST alignment. Validation of this approach showed that, as peptide length increased, the de novo accuracy decreased and BLAST performance increased. Through in silico calculations on antibody repository sequences, we determined the uniqueness of tryptic VR peptides and their suitability as antibody surrogate. Approximately one-third of these peptides were unique, and about one-third of all antibodies contained at least one unique peptide.

循环抗体的多克隆复合物可能蕴含着有关个人体液免疫状态的宝贵信息。虽然自下而上的蛋白质组学非常适合血清蛋白质组学,但血清中大量的抗体和动态范围给这一分析带来了挑战。为了更全面地获取血清蛋白质组,我们在基于胰蛋白酶的标准自下而上蛋白质组学中加入了高场非对称波形离子迁移谱法(FAIMS)或二维色谱法。因此,可变区(VR)相关光谱的数量在使用 FAIMS 时增加了 1.7 倍,在使用色谱分馏时增加了 10 倍。为了将抗体 VR 与光谱相匹配,我们结合了从头搜索和 BLAST 比对。这种方法的验证结果表明,随着肽段长度的增加,从头搜索的准确性降低,而 BLAST 的性能提高。通过对抗体库序列进行硅计算,我们确定了胰蛋白酶 VR 肽的独特性及其作为抗体替代物的适宜性。这些肽中约有三分之一是唯一的,所有抗体中约有三分之一包含至少一个唯一的肽。
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引用次数: 0
Development of an efficient, effective, and economical technology for proteome analysis. 开发高效、有效、经济的蛋白质组分析技术。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 Epub Date: 2024-06-11 DOI: 10.1016/j.crmeth.2024.100796
Katherine R Martin, Ha T Le, Ahmed Abdelgawad, Canyuan Yang, Guotao Lu, Jessica L Keffer, Xiaohui Zhang, Zhihao Zhuang, Papa Nii Asare-Okai, Clara S Chan, Mona Batish, Yanbao Yu

We present an efficient, effective, and economical approach, named E3technology, for proteomics sample preparation. By immobilizing silica microparticles into the polytetrafluoroethylene matrix, we develop a robust membrane medium, which could serve as a reliable platform to generate proteomics-friendly samples in a rapid and low-cost fashion. We benchmark its performance using different formats and demonstrate them with a variety of sample types of varied complexity, quantity, and volume. Our data suggest that E3technology provides proteome-wide identification and quantitation performance equivalent or superior to many existing methods. We further propose an enhanced single-vessel approach, named E4technology, which performs on-filter in-cell digestion with minimal sample loss and high sensitivity, enabling low-input and low-cell proteomics. Lastly, we utilized the above technologies to investigate RNA-binding proteins and profile the intact bacterial cell proteome.

我们提出了一种高效、有效、经济的蛋白质组学样品制备方法,命名为 E3 技术。通过将二氧化硅微颗粒固定在聚四氟乙烯基质中,我们开发出了一种坚固的膜介质,它可以作为一种可靠的平台,以快速、低成本的方式生成蛋白质组学友好型样品。我们使用不同的格式对其性能进行了基准测试,并通过各种复杂程度、数量和体积的样品类型进行了演示。我们的数据表明,E3 技术的蛋白质组鉴定和定量性能相当于或优于许多现有方法。我们进一步提出了一种增强型单血管方法,命名为 E4 技术,它能在滤器上进行细胞内消化,样品损失极少,灵敏度高,从而实现了低投入和低细胞蛋白质组学。最后,我们利用上述技术研究了 RNA 结合蛋白和完整细菌细胞蛋白质组。
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引用次数: 0
Recapitulating the tumor microenvironment in a dish, one cell type at a time. 在培养皿中重现肿瘤微环境,一次只重现一种细胞类型。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 DOI: 10.1016/j.crmeth.2024.100800
Benjamin N Ostendorf

The tumor microenvironment harbors a variety of different cell types that differentially impact tumor biology. In this issue of Cell Reports Methods, Raffo-Romero et al. standardized and optimized 3D tumor organoids to model the interactions between tumor-associated macrophages and tumor cells in vitro.

肿瘤微环境中存在多种不同类型的细胞,它们对肿瘤生物学产生不同的影响。在本期《细胞报告方法》(Cell Reports Methods)杂志上,Raffo-Romero 等人对三维肿瘤器官组织进行了标准化和优化,以便在体外模拟肿瘤相关巨噬细胞和肿瘤细胞之间的相互作用。
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引用次数: 0
Bioengineering methods for vascularizing organoids. 血管化器官组织的生物工程方法。
IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-06-17 Epub Date: 2024-05-16 DOI: 10.1016/j.crmeth.2024.100779
Peter N Nwokoye, Oscar J Abilez

Organoids, self-organizing three-dimensional (3D) structures derived from stem cells, offer unique advantages for studying organ development, modeling diseases, and screening potential therapeutics. However, their translational potential and ability to mimic complex in vivo functions are often hindered by the lack of an integrated vascular network. To address this critical limitation, bioengineering strategies are rapidly advancing to enable efficient vascularization of organoids. These methods encompass co-culturing organoids with various vascular cell types, co-culturing lineage-specific organoids with vascular organoids, co-differentiating stem cells into organ-specific and vascular lineages, using organoid-on-a-chip technology to integrate perfusable vasculature within organoids, and using 3D bioprinting to also create perfusable organoids. This review explores the field of organoid vascularization, examining the biological principles that inform bioengineering approaches. Additionally, this review envisions how the converging disciplines of stem cell biology, biomaterials, and advanced fabrication technologies will propel the creation of increasingly sophisticated organoid models, ultimately accelerating biomedical discoveries and innovations.

器官组织是源自干细胞的自组织三维(3D)结构,具有研究器官发育、疾病建模和筛选潜在疗法的独特优势。然而,它们的转化潜力和模拟复杂体内功能的能力往往因缺乏综合血管网络而受到阻碍。为了解决这一关键限制,生物工程策略正在迅速发展,以实现器官组织的高效血管化。这些方法包括与各种血管细胞类型共同培养类器官、与血管类器官共同培养特异性类器官、将干细胞共同分化成特异性类器官和血管系、使用类器官芯片技术在类器官内整合可灌注血管,以及使用三维生物打印技术创建可灌注类器官。本综述探讨了类器官血管化领域,研究了生物工程方法的生物学原理。此外,本综述还设想了干细胞生物学、生物材料和先进制造技术等学科的融合将如何推动创建日益复杂的类器官模型,最终加速生物医学的发现和创新。
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引用次数: 0
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Cell Reports Methods
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