Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.0030
Dean M. Pucciarelli, Benjamin Y. Lu, Inti Zlobec, Marcello DiStasio
Spatial omics technologies, including highly multiplexed histologic protein assays, nucleic acid abundance and/or sequence mapping, and spatial epigenetics assays, offer powerful tools for interrogating the complex biology of human tissues. These technologies have been broadly applied in basic and translational research, which presages deployment in clinical settings as well. In this article, we discuss spatial omics technologies with an emphasis on retrieval of disease-related information in single samples, with potential clinical applications in specialties such as oncology and immunology, and in the development of personalized treatment. Capable of localizing detailed molecular information within histologic structures, spatial omics technologies provide both cell-intrinsic information and microenvironmental interaction context. This will allow more precise diagnostic and prognostic classifications and more accurate predictions about treatment responses to be made. While technical and financial challenges to widespread deployment in clinical laboratories remain, spatial omics technologies are expected to dramatically expand actionable information obtained by human tissue sampling for pathologic analysis.
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Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.29115.sro
Sachin Rawat
GEN BiotechnologyVol. 2, No. 5 News Feature: Spatial OmicsFree AccessSpatial Omics Spotlights the Players in the Tumor MicroenvironmentSachin RawatSachin Rawat*Address correspondence to: Sachin Rawat, Freelance Science Writer. E-mail Address: [email protected]Freelance Science Writer.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29115.sroAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Researchers are using spatial omics to look deeper into the tumor microenvironment and unravel tumor heterogeneity with an eye on gleaning important clinical insights.Tumor immune microenvironment of human colorectal cancer. Cancer cells in green and immune cells in magenta. (Credit: NanoString Technologies)Many hard-to-treat cancers often recur months or years after successful treatment. “You could have one cell that escapes treatment and it's that one cell that will populate and be resistant and allow for a recurrence to happen,” said Jasmine Plummer, founding director of the Center for Spatial Omics at St. Jude Children's Research Hospital.Investigating such tumors with even single-cell omics technologies could miss these resistant cells. Before analysis, single-cell technologies destroy the cancer tissue to look at what's happening in the tissue as a whole. However, a lot of the interesting stuff inside tumors happens at the level of individual cells and depends on the context in which they exist. Single-cell technologies lose this spatial context when the cells are broken up.This is where spatial omics come in.With advances in omics technologies, cancer biologists have extensive information on the genes, proteins, and other metabolites that make up the messy environment of a tumor. Single-cell omics goes further, enabling the identification of all cell types in a tumor sample. This has only deepened our understanding of the extreme heterogeneity of tumor cells. Spatial omics technologies are placing these insights in the spatial context.Jasmine Plummer, Founding Director of the Center for Spatial Omics at St. Jude Children's Research HospitalTake gene expression, for example. Single-cell transcriptomics reveals which genes are being expressed across different cell types. But it doesn't say where these cells are in the tumor. Spatial transcriptomics technologies fill this gap by simultaneously recording spatial coordinates with gene expression data. This is the crux of the growing field of spatial omics: assigning pin codes to omics data.Spatial transcriptomics technologies such as in situ hybridization and in situ sequencing allow researchers to capture transcriptomes without losing spatial information. The former uses fluorescent, gene-specific probes that bind mRNAs, whereas the latter sequences the transcripts directly in a section of a fixed tissue.Complementing these imaging-ba
创BiotechnologyVol。空间组学聚焦肿瘤微环境中的参与者地址通信:Sachin Rawat，自由科学作家。电子邮件地址:[email protected]自由科学作家。搜索本文作者的更多论文发表在线:2023年10月16日https://doi.org/10.1089/genbio.2023.29115.sroAboutSectionsPDF/EPUB权限和引文下载CitationsTrack引文添加到收藏返回出版物共享分享在facebook上推特链接InRedditEmail研究人员正在使用空间组学来深入研究肿瘤微环境，揭示肿瘤异质性，并着眼于收集重要的临床见解。人类结直肠癌肿瘤免疫微环境的研究。绿色是癌细胞，品红是免疫细胞。许多难以治疗的癌症通常在成功治疗数月或数年后复发。St. Jude儿童研究医院空间组学中心的创始主任Jasmine Plummer说:“你可能有一个细胞逃脱了治疗，这个细胞会繁殖并产生抗药性，并允许复发。”即使用单细胞组学技术来研究这类肿瘤，也可能错过这些耐药细胞。在分析之前，单细胞技术会破坏癌症组织，从整体上观察组织中发生了什么。然而，肿瘤内部的许多有趣的事情发生在单个细胞的水平上，并取决于它们存在的环境。当细胞被分解时，单细胞技术就失去了这种空间背景。这就是空间组学的用武之地。随着组学技术的进步，癌症生物学家对构成肿瘤混乱环境的基因、蛋白质和其他代谢物有了广泛的了解。单细胞组学则更进一步，能够识别肿瘤样本中的所有细胞类型。这只加深了我们对肿瘤细胞极端异质性的理解。空间组学技术将这些见解置于空间环境中。Jasmine Plummer, St. Jude儿童研究医院空间组学中心创始主任，以基因表达为例。单细胞转录组学揭示了哪些基因在不同的细胞类型中被表达。但它没有说明这些细胞在肿瘤中的位置。空间转录组学技术通过同时记录空间坐标和基因表达数据来填补这一空白。这是不断发展的空间组学领域的关键:为组学数据分配pin码。空间转录组学技术，如原位杂交和原位测序，使研究人员能够在不丢失空间信息的情况下捕获转录组。前者使用结合mrna的荧光基因特异性探针，而后者直接在固定组织的一部分中对转录本进行测序。补充这些基于成像的方法是基于下一代测序的其他空间技术。其中包括高清晰度空间转录组学(HDST)和用于空间组学测序的组织确定性条形码(DBiT-Seq)。HDST使用空间条形码头阵列将RNA映射到组织学切片上的位置。DBiT对蛋白质和RNA都做同样的工作，使研究RNA-蛋白质在空间背景下的相互作用成为可能。研究蛋白质和其他代谢物的技术在原则上与研究转录物的技术相似。最近，一次调查多层信息的努力推动了空间多组学工具(如DBiT)的发展。癌细胞必须不断地逃避免疫系统，同时建立基础设施来支持其不受控制的生长。这种基础设施需要与不同的小圈子进行仔细的沟通。它包括宿主组织中的健康细胞、必须被欺骗的免疫细胞、肿瘤扩散所需的血管等。这些构成了一个被称为肿瘤微环境(TME)1的动态生态系统，它在肿瘤的生长和扩散中起着关键作用。Charlotte Stadler是空间和单细胞生物学平台(SSCB)的联合主任，也是sciilifelabby空间蛋白质组学单元的负责人，他整合了单细胞组学和空间组学，研究人员终于找到了一种方法来绘制包括癌症在内的不同组织的详细地图。在《分子系统生物学》上发表的一篇文章中，研究人员创建了人类肝脏tme的单细胞图谱。2研究人员发现癌细胞和周围的基质细胞之间反复发生相互作用，这表明针对这些相互作用的药物可能更广泛地适用。在《细胞》杂志发表的另一项研究中，科学家发现免疫T细胞在乳腺TME中表现出显著的表型多样性。 它们不仅在数量上远远超过健康乳腺组织中的T细胞类型，而且肿瘤T细胞类型的激活状态也是连续的。此外，该研究表明，免疫细胞的多样性是肿瘤内局部微环境多样性的结果。法裔美国人工智能生物技术初创公司Owkin的研发战略高级副总裁约瑟夫·勒哈尔(Joseph Lehar)说，肿瘤具有复杂的免疫生态，可以帮助它们“变得对免疫系统不透明，或者告诉免疫系统停止嗅探，让它找不到它，或者告诉T细胞不要试图杀死肿瘤细胞”。在肿瘤免疫生物学中，细胞关于是否杀死疑似肿瘤细胞的决定是高度局部化的。Lehar补充说:“这都是关于一个特定的肿瘤细胞或一组细胞的样子，免疫细胞感知到它，然后以一种特定的方式对它做出反应。”对肿瘤免疫微环境的空间理解对于治疗无法治愈的癌症至关重要。这是因为肿瘤逃避免疫系统的能力是它如何建立生长所需结构和如何抵抗治疗的核心。TME的另一个关键方面是缺氧生态位的存在。这是恶性肿瘤的标志，这是一种低于生理水平的氧气，是肿瘤内不同细胞信号结构的基础。在发表在《免疫》杂志上的一项研究中，研究人员表明，缺氧生态位吸引并隐藏了肿瘤免疫细胞结合空间信息和单细胞转录组学，他们证明了胶质母细胞瘤和免疫细胞在缺氧生态位中的串音在抑制免疫系统中是至关重要的。TME还包括其他机制，通过与癌症细胞和健康细胞的相互作用来塑造肿瘤的命运。这些包括细胞外基质，游离脂质和机械线索，仅举几例。为了沿着肿瘤绘制这些成分，研究人员利用了其他空间分析技术，这些技术通常与空间组学结合使用，如多路成像和细胞计数。在多路成像中，“我们使用抗体在同一组织切片中检测大量不同的蛋白质，”Charlotte Stadler说，她是空间和单细胞生物学平台的联合主任，也是瑞典国家研究中心SciLifeLab空间蛋白质组学部门的负责人(图1)。这使得研究人员能够进行“深度表型分析，并了解哪些细胞类型在空间上接近，并且可能相互作用。”深度表型是一个在精准医学领域日益受到关注的术语，它指的是组学数据在多个层面上的表型。1. Charlotte Stadler在SciLifeLab的研究小组开发并使用空间蛋白质组学方法用于癌症的临床应用。同样，与传统的细胞计数技术相比，大规模细胞计数技术可以让研究人员追踪到更多的代谢物。这种空间剖面技术对于实现三维(3D)空间组学也是至关重要的。虽然空间组学获得的肿瘤地图通常是二维(2D)，但肿瘤本身存在于3D中。3D空间组学提供了肿瘤内部发生情况的完整图像，从而提供了更好的见解。肿瘤具有高度的异质性肿瘤内不同的细胞具有不同的基因型和表型组成。即使在肿瘤内基因纯合的癌细胞群中，细胞在表型上也有相当大的差异基因组不稳定性被认为是肿瘤发展的一个重要标志，是肿瘤中高细胞多样性的主要驱动因素。伊拉斯谟大学医学中心(Erasmus University Medical Center)的癌症研究员达纳·阿德尔·穆斯塔法(Dana Adel Mustafa)说，肿瘤内细胞的高度多样性“对于理解肿瘤细胞的多方面功能及其与微环境的复杂关系至关重要”。通过将空间组学技术应用于癌症组织，生物学家正在更多地了解不同肿瘤的异质性。空间组学技术通过产生关于肿瘤异质性的假设数据，正在迅速推进癌症研究。例如，在《癌细胞》杂志上发表的一项研究中，研究人员使用空间转录组学研究肾细胞癌的异质性。他们观察到，在肾癌中，肿瘤内的异质性远远超过了体细胞突变。更具体地说，免疫T细胞在组织中的位置，而不是它们积累的突变，主要决定了它们功能障碍的
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Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.29114.fli
Fay Lin
GEN BiotechnologyVol. 2, No. 5 News FeaturesFree AccessDiffusion Evolution: New Artificial Intelligence Models Break Barriers in Protein DesignFay LinFay LinE-mail Address: [email protected]Senior Editor, GEN BiotechnologySearch for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29114.fliAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Diffusion models, a form of generative artificial intelligence, are a rising tool for protein design, showing improved experimental success and new potential for biotechnological applications.This protein fold is one of thousands designed from scratch using new machine learning methods. (Credit: Ian C. Haydon/UW Institute for Protein Design)In July 2023, scientists in David Baker's laboratory at the University of Washington (UW) published a report in Nature detailing a new deep-learning framework for de novo protein design called RoseTTAFold diffusion (RFdiffusion), in Nature.1 Since then, the scientific community has been buzzing about RFdiffusion's unprecedented experimental success rate and ease of use.David Juergens, a graduate student in Baker's laboratory and one of seven co-lead authors of the Nature article, shared an anecdote about a scientist working in a lab in China, who posted on social media how “they designed a protein in a browser, ordered the sequence, purified the protein, crystallized it, and then got a crystal structure that was half an angstrom away from the design that was on the computer. It was amazing!” Juergens told me.David Baker, Professor in Biochemistry and Director of the Institute for Protein Design at UWSome of the applications of RFdiffusion, documented with experimental validation in the Nature article, include design of symmetric oligomers for vaccine platforms and delivery vehicles and generation of high-affinity binders for therapeutics.1 In another project, the Baker laboratory has applied RFdiffusion to design proteins that bind peptide hormones—established biomarkers for clinical care and biomedical research—for diagnostic applications.2Box 1. Let's Generate interactionsGenerate: Biomedicines is a Boston-based therapeutics company at the intersection of machine learning, biological engineering, and medicine. Molly Gibson, cofounder and chief strategy and innovation officer, says the company focuses on designing protein–protein interactions for therapeutic applications.“If you think about biologics, the most important function that a protein takes is creating very specific and potent binding with its target. This could be things like an antibody where we know exactly where we want to neutralize a target, or where we want to agonize and potentiate function,” said Gibson.One project at Generate: Biomedicines has worked to create a broadly neutralizing antibody for coronavirus. Gibson notes that the virus activel
创BiotechnologyVol。扩散进化:新的人工智能模型打破了蛋白质设计的障碍fay LinFay LinE-mail地址:[email protected] GEN biotechnology高级编辑搜索本文作者更多论文发布在线:2023年10月16日https://doi.org/10.1089/genbio.2023.29114.fliAboutSectionsPDF/EPUB权限与引用次数下载CitationsTrack引用次数添加到收藏返回发布分享分享在facebook上分享推特链接InRedditEmail扩散模型是一种生成式人工智能，是蛋白质设计的新兴工具。显示出改进的实验成功和生物技术应用的新潜力。这种蛋白质折叠是使用新的机器学习方法从零开始设计的数千种蛋白质折叠之一。2023年7月，华盛顿大学(UW) David Baker实验室的科学家们在《自然》杂志上发表了一篇报告，详细介绍了一种新的深度学习框架，用于从头开始的蛋白质设计，称为RoseTTAFold扩散(RFdiffusion)。从那时起，科学界就一直在谈论RFdiffusion前所未有的实验成功率和易用性。大卫·尤尔根斯(David Juergens)是贝克实验室的研究生，也是《自然》杂志那篇文章的七名共同主要作者之一，他分享了一个在中国实验室工作的科学家的轶事，他在社交媒体上发布了“他们如何在浏览器中设计一种蛋白质，对其排序，纯化蛋白质，使其结晶，然后得到一个晶体结构，与计算机上的设计相差半埃。”太神奇了!”杰庚斯告诉我的。David Baker, uww生物化学教授和蛋白质设计研究所主任，一些RFdiffusion的应用，在Nature文章中得到了实验验证，包括设计用于疫苗平台和递送载体的对称寡聚物，以及用于治疗的高亲和力结合物的生成在另一个项目中，Baker实验室应用射频扩散来设计结合肽激素的蛋白质——已建立的临床护理和生物医学研究的生物标志物——用于诊断应用。2箱1。让我们产生互动产生:生物医药是一家总部位于波士顿的治疗公司，在机器学习，生物工程和医学的交叉点。联合创始人兼首席战略和创新官莫莉·吉布森(Molly Gibson)表示，该公司专注于设计用于治疗用途的蛋白质-蛋白质相互作用。“如果你想到生物制剂，蛋白质最重要的功能是与目标产生非常特定和有效的结合。这可能是像抗体这样的东西，我们确切地知道我们想要在哪里中和一个目标，或者我们想要在哪里痛苦和增强功能，”吉布森说。Generate: Biomedicines的一个项目致力于为冠状病毒创造一种广泛中和的抗体。Gibson指出，病毒在生物制剂靶向的表位上主动变异，导致许多COVID治疗药物失去紧急使用授权(EUA)。“我们知道病毒的某些部分不会突变，但有趣的是，我们的免疫系统和动物的免疫系统，我们传统上获得的抗体通常不会产生针对病毒非突变部分的抗体，”吉布森继续说道。她补充说，针对这些非突变区域使治疗不太可能因未来的病毒突变而无效。今年9月，Generate: Biomedicines宣布了他们对GB-0669的首次临床试验，这是一种针对SARS-CoV-2刺突蛋白高度保守区域的单克隆抗体。该公司还希望在2023年第四季度初为其抗哮喘tslp单克隆抗体提交临床试验申请，预计此后不久将进入临床试验。生物医学有一个多模态的治疗重点项目在传染病，肿瘤学和免疫学。吉布森说:“我们真正专注于建立一套多样化的专业知识，不仅在蛋白质设计方面，而且在临床开发和生产方面。”通过整合不同领域的专业知识，“我们能够以影响人们的方式使用这项技术，”她补充说。其中一个关键工具是新的低温电子显微镜(CryoEM)设备，用于生成大规模结构数据，以补充公司内部的蛋白质设计机器学习工具，并促进药物发现过程。这个位于马萨诸塞州安多弗的70,000平方英尺的场地于6月揭幕，是美国最大的私营CryoEM实验室之一。贝克实验室并不是唯一一个开发所谓扩散模型的团队，扩散模型是一类利用生成式人工智能(AI)进行蛋白质设计的模型。去年12月，该实验室首次在bioRxiv上发布了一篇关于rf扩散的预印本。 与此同时，专注于人工智能的治疗公司Generate: Biomedicines发布了名为Chroma的扩散模型作为预印本一个月后，哥伦比亚大学系统生物学助理教授Mohammed AlQuraishi的实验室发布了他们自己的扩散模型genie的预印本。“所有这些不同的团队几乎在同一时间都在考虑这些模型，”AlQuraishi告诉GEN Biotechnology。“射频扩散效果很好。当然，这是(目前)已发表的方法中最有效的。”虽然Chroma不是公开的，但是Genie的代码是公开的。AlQuraishi还表示，Genie的实验验证正在进行中。RFdiffusion在一个用户友好的在线Google协作笔记本中公开提供尽管许多经验丰富的科学家正在将rf扩散应用于他们的蛋白质设计工作，并在实验室中验证他们的设计，但“任何有浏览器的人”都可以在计算机上设计出自然界从未见过的蛋白质……并在社交媒体上分享。不需要编码知识。哥伦比亚大学系统生物学助理教授Mohammed AlQuraishi在人工智能革命之前，蛋白质设计方法仅限于根据自然界现有的蛋白质生成设计。这些标准方法有局限性，因为大自然只对可能的蛋白质景观中的一小部分进行了采样，而且进化并不一定选择从制药或生物技术的角度来看所需要的属性。从应用和可扩展性的角度来看，溶解度、稳定性、易于生产和低免疫原性是许多至关重要的特性中的一些。相比之下，生成式人工智能方法强调从头开始的蛋白质设计——从头开始设计新的蛋白质——其目标是扩大功能和理想属性的范围，超越自然界已经实现的功能。自从具有里程碑意义的alphafold6发布以来，人工智能驱动的蛋白质设计一直是一股新兴力量，为生物技术应用带来了新的可能性。alphafold6是谷歌DeepMind备受赞誉的人工智能程序，在解决生物学最大的问题之一方面取得了重大飞跃，从序列中确定了蛋白质的3D结构。从历史上看，蛋白质结构的预测和设计是一个耗时的过程，因为计算得出的结构的实验验证率很低。像AlphaFold这样的人工智能工具可以以前所未有的速度和准确性预测蛋白质结构，简化药物发现、工业应用等方面的研究过程。9月，AlphaFold的开发者Demis Hassabis和John Jumper获得了2023年拉斯克奖(Lasker Awards)。这个享有盛誉的奖项旨在表彰对医学科学做出重大贡献的个人。在上个月的The State of Biotech-GEN年度旗舰虚拟活动中，著名的华盛顿大学结构生物学家David Baker讨论了首个获批的新设计药物SKYCovione，这是SK Bioscience和华盛顿大学蛋白质设计研究所(IPD)开发的一种COVID疫苗，于6月在韩国获批用于成人。“这是蛋白质设计的一个激动人心的时刻!Baker强调说，蛋白质设计领域已经看到了一个重大转变，从主要的生物物理方法，基于蛋白质折叠到最低能量结构的想法，到应用深度学习。贝克是生物化学教授、西澳大学生物科学研究所主任、霍华德·休斯医学研
{"title":"Diffusion Evolution: New Artificial Intelligence Models Break Barriers in Protein Design","authors":"Fay Lin","doi":"10.1089/genbio.2023.29114.fli","DOIUrl":"https://doi.org/10.1089/genbio.2023.29114.fli","url":null,"abstract":"GEN BiotechnologyVol. 2, No. 5 News FeaturesFree AccessDiffusion Evolution: New Artificial Intelligence Models Break Barriers in Protein DesignFay LinFay LinE-mail Address: [email protected]Senior Editor, GEN BiotechnologySearch for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29114.fliAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Diffusion models, a form of generative artificial intelligence, are a rising tool for protein design, showing improved experimental success and new potential for biotechnological applications.This protein fold is one of thousands designed from scratch using new machine learning methods. (Credit: Ian C. Haydon/UW Institute for Protein Design)In July 2023, scientists in David Baker's laboratory at the University of Washington (UW) published a report in Nature detailing a new deep-learning framework for de novo protein design called RoseTTAFold diffusion (RFdiffusion), in Nature.1 Since then, the scientific community has been buzzing about RFdiffusion's unprecedented experimental success rate and ease of use.David Juergens, a graduate student in Baker's laboratory and one of seven co-lead authors of the Nature article, shared an anecdote about a scientist working in a lab in China, who posted on social media how “they designed a protein in a browser, ordered the sequence, purified the protein, crystallized it, and then got a crystal structure that was half an angstrom away from the design that was on the computer. It was amazing!” Juergens told me.David Baker, Professor in Biochemistry and Director of the Institute for Protein Design at UWSome of the applications of RFdiffusion, documented with experimental validation in the Nature article, include design of symmetric oligomers for vaccine platforms and delivery vehicles and generation of high-affinity binders for therapeutics.1 In another project, the Baker laboratory has applied RFdiffusion to design proteins that bind peptide hormones—established biomarkers for clinical care and biomedical research—for diagnostic applications.2Box 1. Let's Generate interactionsGenerate: Biomedicines is a Boston-based therapeutics company at the intersection of machine learning, biological engineering, and medicine. Molly Gibson, cofounder and chief strategy and innovation officer, says the company focuses on designing protein–protein interactions for therapeutic applications.“If you think about biologics, the most important function that a protein takes is creating very specific and potent binding with its target. This could be things like an antibody where we know exactly where we want to neutralize a target, or where we want to agonize and potentiate function,” said Gibson.One project at Generate: Biomedicines has worked to create a broadly neutralizing antibody for coronavirus. Gibson notes that the virus activel","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.0032
Guohao Liang, Hong Yin, Fangyuan Ding
Transcriptomics is one of the largest areas of research in biological sciences. Aside from RNA expression levels, the significance of RNA spatial context has also been unveiled in the recent decade, playing a critical role in diverse biological processes, from subcellular kinetic regulation to cell communication, from tissue architecture to tumor microenvironment, and more. To systematically unravel the positional patterns of RNA molecules across subcellular, cellular, and tissue levels, spatial transcriptomics techniques have emerged and rapidly became an irreplaceable tool set. Herein, we review and compare current spatial transcriptomics techniques on their methods, advantages, and limitations, as well as applications across a wide range of biological investigations. This review serves as a comprehensive guide to spatial transcriptomics for researchers interested in adopting this powerful suite of technologies.
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Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.0019
Sang Ho Kwon, Sowmya Parthiban, Madhavi Tippani, Heena R. Divecha, Nicholas J. Eagles, Jashandeep S. Lobana, Stephen R. Williams, Michelle Mak, Rahul A. Bharadwaj, Joel E. Kleinman, Thomas M. Hyde, Stephanie C. Page, Stephanie C. Hicks, Keri Martinowich, Kristen R. Maynard, Leonardo Collado-Torres
Neuropathological lesions in the brains of individuals affected with neurodegenerative disorders are hypothesized to trigger molecular and cellular processes that disturb the homeostasis of local microenvironments. Here, we applied the 10x Genomics Visium Spatial Proteogenomics (Visium-SPG) platform, which couples spatial gene expression with immunofluorescence (IF) protein co-detection, to evaluate its ability to quantify changes in spatial gene expression with respect to amyloid-beta (Aβ) and hyperphosphorylated tau (pTau) pathology in post-mortem human brain tissue from individuals with Alzheimer's disease (AD). We identified transcriptomic signatures associated with proximity to Aβ in the human inferior temporal cortex during late-stage AD, which we further investigated at cellular resolution with combined IF and single-molecule fluorescent in situ hybridization (smFISH). The study provides a data analysis workflow for Visium-SPG, and the data represent a proof-of-principle for the power of multi-omic profiling in identifying changes in molecular dynamics that are spatially associated with pathology in the human brain. We provide the scientific community with web-based, interactive resources to access the datasets of the spatially resolved AD-related transcriptomes.
{"title":"Influence of Alzheimer's Disease Related Neuropathology on Local Microenvironment Gene Expression in the Human Inferior Temporal Cortex","authors":"Sang Ho Kwon, Sowmya Parthiban, Madhavi Tippani, Heena R. Divecha, Nicholas J. Eagles, Jashandeep S. Lobana, Stephen R. Williams, Michelle Mak, Rahul A. Bharadwaj, Joel E. Kleinman, Thomas M. Hyde, Stephanie C. Page, Stephanie C. Hicks, Keri Martinowich, Kristen R. Maynard, Leonardo Collado-Torres","doi":"10.1089/genbio.2023.0019","DOIUrl":"https://doi.org/10.1089/genbio.2023.0019","url":null,"abstract":"Neuropathological lesions in the brains of individuals affected with neurodegenerative disorders are hypothesized to trigger molecular and cellular processes that disturb the homeostasis of local microenvironments. Here, we applied the 10x Genomics Visium Spatial Proteogenomics (Visium-SPG) platform, which couples spatial gene expression with immunofluorescence (IF) protein co-detection, to evaluate its ability to quantify changes in spatial gene expression with respect to amyloid-beta (Aβ) and hyperphosphorylated tau (pTau) pathology in post-mortem human brain tissue from individuals with Alzheimer's disease (AD). We identified transcriptomic signatures associated with proximity to Aβ in the human inferior temporal cortex during late-stage AD, which we further investigated at cellular resolution with combined IF and single-molecule fluorescent in situ hybridization (smFISH). The study provides a data analysis workflow for Visium-SPG, and the data represent a proof-of-principle for the power of multi-omic profiling in identifying changes in molecular dynamics that are spatially associated with pathology in the human brain. We provide the scientific community with web-based, interactive resources to access the datasets of the spatially resolved AD-related transcriptomes.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.0039
Nicholas Zhang, Denis Ohlstrom, Sicheng Pang, Nivik Sanjay Bharadwaj, Aaron Qu, Hans Grossniklaus, Ahmet F. Coskun
Recently, organoids, or three-dimensional (3D) cellular assemblies, have demonstrated promise as viable models for organ development and disease study. In contrast to challenging preclinical models, organoids are advantageous due to rapid fabrication times and greater patient specificity. The advent of spatial transcriptomics and single cell technologies has also enhanced the characterization of intraorganoid heterogeneity, thus highlighting 3D cell signaling and organ development at micro scales. In this study, we describe ongoing and future directions in spatial omics integrated with various imaging technologies for two-dimensional/3D organoid characterization. Utilizing both retinal organoids and native retinal tissues, we undertook an analysis to deconstruct the cellular compositions and structural attributes of their respective cell layers. Our findings indicate that the spatial organization of cell phenotypes is similar between organoids and native retinal tissue. However, it is noteworthy that native retinal tissue possesses thinner yet distinctly separated cell layers compared with the organoids.
{"title":"Tissue Spatial Omics Dissects Organoid Biomimicry","authors":"Nicholas Zhang, Denis Ohlstrom, Sicheng Pang, Nivik Sanjay Bharadwaj, Aaron Qu, Hans Grossniklaus, Ahmet F. Coskun","doi":"10.1089/genbio.2023.0039","DOIUrl":"https://doi.org/10.1089/genbio.2023.0039","url":null,"abstract":"Recently, organoids, or three-dimensional (3D) cellular assemblies, have demonstrated promise as viable models for organ development and disease study. In contrast to challenging preclinical models, organoids are advantageous due to rapid fabrication times and greater patient specificity. The advent of spatial transcriptomics and single cell technologies has also enhanced the characterization of intraorganoid heterogeneity, thus highlighting 3D cell signaling and organ development at micro scales. In this study, we describe ongoing and future directions in spatial omics integrated with various imaging technologies for two-dimensional/3D organoid characterization. Utilizing both retinal organoids and native retinal tissues, we undertook an analysis to deconstruct the cellular compositions and structural attributes of their respective cell layers. Our findings indicate that the spatial organization of cell phenotypes is similar between organoids and native retinal tissue. However, it is noteworthy that native retinal tissue possesses thinner yet distinctly separated cell layers compared with the organoids.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135810501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.29117.editorial
Rong Fan, Fay Lin
GEN BiotechnologyVol. 2, No. 5 Guest Editorial: Spatial OmicsFree AccessSpatial DeliveryRong Fan and Fay LinRong Fan*Address correspondence to: Rong Fan E-mail Address: [email protected]Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.Guest Editor, GEN Biotechnology.Search for more papers by this author and Fay Lin*Address correspondence to: Fay Lin E-mail Address: [email protected]Senior Editor, GEN Biotechnology.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29117.editorialAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Spatial omics enables the profiling of a variety of biomolecules with high spatial resolution across the central dogma of molecular biology directly in the natural tissue context. It has emerged as a powerful tool to analyze clinical samples for human biology research, therapeutic discovery, and translational medicine. As one of the fastest growing areas in the biotech industry, spatial omics is poised to drive the next biology revolution with broad impact across life science and medicine.In this debut special issue of GEN Biotechnology, we are delighted to feature a collection of spatial omics perspectives, reviews, and original research articles capturing the breadth of the field from cancer research to the newest advances in imaging methods.Lift OffThe historical roots of visualizing biological function date back 300 years with the invention of the compound microscope by Robert Hooke. Individual cells were seen for the first time in a plant leaf, and researchers could already visualize highly heterogeneous cell morphology implicated in distinct functions in various tissue regions. While the modern era of molecular and cell biology associates morphological heterogeneity with differential gene expression, it was the rise of single-cell genomewide gene expression measured by next-generation sequencing (NGS) platforms that allowed for detailed quantification of cellular heterogeneity in gene expression. Further breakthroughs in massively parallel single-cell sequencing via cellular barcoding enabled the gene expression profiling of thousands of single cells, thereby dissecting cell types and states in large cell populations. But despite these major breakthroughs in single-cell omics, analyzing cellular heterogeneity in the tissue context remained a challenge.Over the past decade, we have witnessed the exponential growth of an emerging field—spatial omics. The goal is to map genomewide biomolecular information pixel-by-pixel in undissociated tissue to yield a holistic view of cell type, state, and function in the native tissue context. Broadly speaking, there are two avenues to achieve this goal—one based on imaging, and the other based on NGS.Imaging-based spatial omicsAlthough single-molecule imaging and fluorescence
{"title":"Spatial Delivery","authors":"Rong Fan, Fay Lin","doi":"10.1089/genbio.2023.29117.editorial","DOIUrl":"https://doi.org/10.1089/genbio.2023.29117.editorial","url":null,"abstract":"GEN BiotechnologyVol. 2, No. 5 Guest Editorial: Spatial OmicsFree AccessSpatial DeliveryRong Fan and Fay LinRong Fan*Address correspondence to: Rong Fan E-mail Address: [email protected]Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.Guest Editor, GEN Biotechnology.Search for more papers by this author and Fay Lin*Address correspondence to: Fay Lin E-mail Address: [email protected]Senior Editor, GEN Biotechnology.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29117.editorialAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Spatial omics enables the profiling of a variety of biomolecules with high spatial resolution across the central dogma of molecular biology directly in the natural tissue context. It has emerged as a powerful tool to analyze clinical samples for human biology research, therapeutic discovery, and translational medicine. As one of the fastest growing areas in the biotech industry, spatial omics is poised to drive the next biology revolution with broad impact across life science and medicine.In this debut special issue of GEN Biotechnology, we are delighted to feature a collection of spatial omics perspectives, reviews, and original research articles capturing the breadth of the field from cancer research to the newest advances in imaging methods.Lift OffThe historical roots of visualizing biological function date back 300 years with the invention of the compound microscope by Robert Hooke. Individual cells were seen for the first time in a plant leaf, and researchers could already visualize highly heterogeneous cell morphology implicated in distinct functions in various tissue regions. While the modern era of molecular and cell biology associates morphological heterogeneity with differential gene expression, it was the rise of single-cell genomewide gene expression measured by next-generation sequencing (NGS) platforms that allowed for detailed quantification of cellular heterogeneity in gene expression. Further breakthroughs in massively parallel single-cell sequencing via cellular barcoding enabled the gene expression profiling of thousands of single cells, thereby dissecting cell types and states in large cell populations. But despite these major breakthroughs in single-cell omics, analyzing cellular heterogeneity in the tissue context remained a challenge.Over the past decade, we have witnessed the exponential growth of an emerging field—spatial omics. The goal is to map genomewide biomolecular information pixel-by-pixel in undissociated tissue to yield a holistic view of cell type, state, and function in the native tissue context. Broadly speaking, there are two avenues to achieve this goal—one based on imaging, and the other based on NGS.Imaging-based spatial omicsAlthough single-molecule imaging and fluorescence ","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135811665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.29116.jgr
Jonathan D. Grinstein
GEN BiotechnologyVol. 2, No. 5 News FeaturesFree AccessKallyope Is Digesting Gut–Brain Biology into MedicinesJonathan D. GrinsteinJonathan D. GrinsteinE-mail Address: [email protected]Senior Editor, GEN Media Group.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29116.jgrAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Founded by Columbia University stalwarts Charles Zuker, Richard Axel, and Tom Maniatis, the New York City company is advancing a portfolio of oral small-molecule therapies across metabolism, gastrointestinal disease, and neurological disorders.Charles Zuker, Professor of Biochemistry & Molecular Biophysics and a Professor of Neuroscience at Columbia UniversityCharles Zuker had been studying taste for decades when his lab performed an experiment knocking out the receptor for sweetness in mice to test whether it would be able to distinguish sugar water from plain old water.At first, the mice lacking sweet receptors drink equal amounts of each type of water, whereas a wild-type mouse soon figures out that one of the two is sugar-laden and consequently favor the sweet one. But return 2 days later, the mice are drinking exclusively from the sugar-rich water, even if they lack the receptor for sweetness.1“We figured that there has to be some post-ingestive effect that's triggering this preference. We discovered that this maniacal desire to consume sugar—not sweet, but sugar in particular—was driven by the activation of the gut-brain circuit,” said Zuker when describing the discovery that was the basis for his a-ha moment.“That led to the idea that, my goodness, if activating the circuit can so dramatically transform an animal's behavior, then maybe accessing the gut-brain circuit could also be used to change physiology, metabolism, and so forth,” said Zuker, who is a Professor of Biochemistry and Molecular Biophysics and a Professor of Neuroscience at Columbia University and a Howard Hughes Medical Institute Investigator (Box 1).Box 1. The gut–brain axis: a critical conduit for neural signals informing the brain of the body's metabolic and physiologic stateSurvival requires the integration of external information from senses such as sight, smell, sound, touch, and taste as well as internal sensory cues from the digestive tract.2 To guarantee proper regulation of body physiological processes and behaviors and to promote overall health, informational elements, such as ingested food, energy homeostasis, inflammatory signals, and digestive progress, need to be monitored from the gut.3 The intricate network of neural, sympathetic, endocrine, immune, humoral, and gut microbiota connections—also known as the “brain–gut axis”—controls gastrointestinal homeostasis and connects the brain's emotional and cognitive centers to the gut's functions. This network enables two-wa
{"title":"Kallyope Is Digesting Gut–Brain Biology into Medicines","authors":"Jonathan D. Grinstein","doi":"10.1089/genbio.2023.29116.jgr","DOIUrl":"https://doi.org/10.1089/genbio.2023.29116.jgr","url":null,"abstract":"GEN BiotechnologyVol. 2, No. 5 News FeaturesFree AccessKallyope Is Digesting Gut–Brain Biology into MedicinesJonathan D. GrinsteinJonathan D. GrinsteinE-mail Address: [email protected]Senior Editor, GEN Media Group.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29116.jgrAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Founded by Columbia University stalwarts Charles Zuker, Richard Axel, and Tom Maniatis, the New York City company is advancing a portfolio of oral small-molecule therapies across metabolism, gastrointestinal disease, and neurological disorders.Charles Zuker, Professor of Biochemistry & Molecular Biophysics and a Professor of Neuroscience at Columbia UniversityCharles Zuker had been studying taste for decades when his lab performed an experiment knocking out the receptor for sweetness in mice to test whether it would be able to distinguish sugar water from plain old water.At first, the mice lacking sweet receptors drink equal amounts of each type of water, whereas a wild-type mouse soon figures out that one of the two is sugar-laden and consequently favor the sweet one. But return 2 days later, the mice are drinking exclusively from the sugar-rich water, even if they lack the receptor for sweetness.1“We figured that there has to be some post-ingestive effect that's triggering this preference. We discovered that this maniacal desire to consume sugar—not sweet, but sugar in particular—was driven by the activation of the gut-brain circuit,” said Zuker when describing the discovery that was the basis for his a-ha moment.“That led to the idea that, my goodness, if activating the circuit can so dramatically transform an animal's behavior, then maybe accessing the gut-brain circuit could also be used to change physiology, metabolism, and so forth,” said Zuker, who is a Professor of Biochemistry and Molecular Biophysics and a Professor of Neuroscience at Columbia University and a Howard Hughes Medical Institute Investigator (Box 1).Box 1. The gut–brain axis: a critical conduit for neural signals informing the brain of the body's metabolic and physiologic stateSurvival requires the integration of external information from senses such as sight, smell, sound, touch, and taste as well as internal sensory cues from the digestive tract.2 To guarantee proper regulation of body physiological processes and behaviors and to promote overall health, informational elements, such as ingested food, energy homeostasis, inflammatory signals, and digestive progress, need to be monitored from the gut.3 The intricate network of neural, sympathetic, endocrine, immune, humoral, and gut microbiota connections—also known as the “brain–gut axis”—controls gastrointestinal homeostasis and connects the brain's emotional and cognitive centers to the gut's functions. This network enables two-wa","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135811830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.0033
Ana C. Puhl, Sarah Negri, Maggie A.Z. Hupcey, Sean Ekins
There are thousands of rare genetic diseases lacking an approved treatment, many of which are life limiting to children. Those caused by a missing protein may represent a target for protein replacement either by enzyme replacement therapy or by gene therapy. One of the many challenges working on these types of genetic diseases is the availability of funding, as these diseases typically affect very small number of patients. Here we offer a novel case study of our approach to developing a treatment for one such rare disease, which has not required venture capital, angel investment, or funding by foundations to date. We have instead pursued NIH small business grants to fund the early preclinical work performed by our academic collaborators and ourselves. Our approach to developing a treatment for a rare disease on a shoestring budget is unlike any of the alternative approaches to funding.
{"title":"Developing Treatments for Rare Diseases on a Shoestring","authors":"Ana C. Puhl, Sarah Negri, Maggie A.Z. Hupcey, Sean Ekins","doi":"10.1089/genbio.2023.0033","DOIUrl":"https://doi.org/10.1089/genbio.2023.0033","url":null,"abstract":"There are thousands of rare genetic diseases lacking an approved treatment, many of which are life limiting to children. Those caused by a missing protein may represent a target for protein replacement either by enzyme replacement therapy or by gene therapy. One of the many challenges working on these types of genetic diseases is the availability of funding, as these diseases typically affect very small number of patients. Here we offer a novel case study of our approach to developing a treatment for one such rare disease, which has not required venture capital, angel investment, or funding by foundations to date. We have instead pursued NIH small business grants to fund the early preclinical work performed by our academic collaborators and ourselves. Our approach to developing a treatment for a rare disease on a shoestring budget is unlike any of the alternative approaches to funding.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1089/genbio.2023.0035
Qiangzhou Rong, Carlos Taboada, Ángela del Águila, Ilaria Merutka, Nishad Jayasundara, Yushun Zeng, Wei Yang, Qifa Zhou, Junjie Yao
Hyperspectral imaging has emerged as a valuable technique for analyzing biological tissue compositions by probing intrinsic or exogenous biomolecules. However, conventional hyperspectral imaging methods predominantly rely on fluorescent signatures, limiting their application to nonfluorescent samples. To overcome this limitation, a label-free reflection-mode hyperspectral photoacoustic microscopy (RHS-PAM) system has been developed. RHS-PAM enables the imaging of thick biological samples with a wide range of intrinsic contrasts using excitation wavelengths ranging from ultraviolet to near infrared. RHS-PAM eliminates the need for tissue staining, and has achieved cellular-level spatial resolution and automatic image coregistrations at all wavelengths. Proof-of-concept applications of RHS-PAM have been demonstrated on various model organisms, including Caenorhabditis elegans, frog tadpole, zebrafish, and mouse. The technique has successfully imaged a wealth of structural and molecular features in these organisms, utilizing the optical absorption contrast of nucleic acids, proteins, hemoglobin, melanin, and lipids. The results highlight the capability of RHS-PAM to provide rich optical contrast, high spatial resolution, and an extended spectral range for label-free imaging. We believe that RHS-PAM represents a highly promising tool for single-cell biochemical mapping of diverse biological tissues.
{"title":"From Ultraviolet to Near-Infrared: Label-Free Reflection-Mode Hyperspectral Photoacoustic Microscopy for Single-Cell Biochemical Mapping","authors":"Qiangzhou Rong, Carlos Taboada, Ángela del Águila, Ilaria Merutka, Nishad Jayasundara, Yushun Zeng, Wei Yang, Qifa Zhou, Junjie Yao","doi":"10.1089/genbio.2023.0035","DOIUrl":"https://doi.org/10.1089/genbio.2023.0035","url":null,"abstract":"Hyperspectral imaging has emerged as a valuable technique for analyzing biological tissue compositions by probing intrinsic or exogenous biomolecules. However, conventional hyperspectral imaging methods predominantly rely on fluorescent signatures, limiting their application to nonfluorescent samples. To overcome this limitation, a label-free reflection-mode hyperspectral photoacoustic microscopy (RHS-PAM) system has been developed. RHS-PAM enables the imaging of thick biological samples with a wide range of intrinsic contrasts using excitation wavelengths ranging from ultraviolet to near infrared. RHS-PAM eliminates the need for tissue staining, and has achieved cellular-level spatial resolution and automatic image coregistrations at all wavelengths. Proof-of-concept applications of RHS-PAM have been demonstrated on various model organisms, including Caenorhabditis elegans, frog tadpole, zebrafish, and mouse. The technique has successfully imaged a wealth of structural and molecular features in these organisms, utilizing the optical absorption contrast of nucleic acids, proteins, hemoglobin, melanin, and lipids. The results highlight the capability of RHS-PAM to provide rich optical contrast, high spatial resolution, and an extended spectral range for label-free imaging. We believe that RHS-PAM represents a highly promising tool for single-cell biochemical mapping of diverse biological tissues.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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