A reagent kit for spatial transcriptomic analysis

项目摘要 大规模平行单细胞基因组技术的最新进展使 研究人员以高分辨率研究基因组和基因表达。然而，这些 这些技术不能保留组织内单个细胞的空间背景，并且可能会偏向 在应用之前，由于细胞分离而导致的各种细胞类型的表示 这些技巧。空间基因组技术的商业可获得性很少。我们有 最近与Slide-Seq技术的学术发明者一起创立了Atlas Bio，以便 将这项技术商业化。Slide-Seq是一种简单易用但又敏感的测量方法 组织切片的空间转录本，2019年首次出版(Rodrique SG et.艾尔，科学 2019年)。该技术利用了空间条形码珠基、一组酶 试剂和缓冲液，以及定制的生物信息学管道。它不需要任何特殊的 除了使用下一代测序仪之外的其他仪器。在年的头两个月 经过公司的运作，我们已经成功复制了Slide-Seq 对衬底进行空间条形化处理，并测试其性能。拟议的第二阶段的目标是 该项目是进一步开发Slide-Seq技术，使其能够广泛传播 并且可以扩展到不同的应用，例如那些需要高空间分辨率的应用 和检测灵敏度。具体来说，该项目将解决可伸缩性、健壮性和 空间条形码衬底的可制造性，这是 技术。我们还将开发解决方案，以方便技术的传播 通过开发消耗品、试剂盒、生物信息学管道和基础数据 可视化工具，目的是降低空间转录分析的准入门槛。 最后，我们将致力于提高空间转录技术在 在空间分辨率和灵敏度方面，并扩展新鲜冷冻的可工作组织类型 致FFPE。通过商业化将该技术标准化，并将其提供给 更多的观众，我们希望加速新一轮的生物发现。

Project Summary Recent advances in massively parallel single cell genomic techniques have enabled researchers to study genomic and gene expression in high resolution. However, these techniques do not preserve spatial context of individual cells within the tissue and can bias representation of various cell types due to cell dissociation that is required before application of the techniques. Commercial availability of spatial genomic techniques is sparse. We have recently founded Atlas Bio with the academic inventors of the Slide-Seq technique in order to commercialize the technology. Slide-Seq is an easy-to-use yet sensitive method for measuring spatial transcriptomes in tissue slices, first published in 2019 (Rodriques SG et. al, Science 2019). The technique makes use of a spatially barcoded bead substrate, a set of enzymatic reagents and buffers, and a custom bioinformatics pipeline. It does not require any special instrumentation other than access to a next-generation sequencer. In the first two months of operation of the company, we have successfully replicated the production of the Slide-Seq spatially barcoded substrates and tested their performance. The goal of the proposed Phase II project is to further develop the Slide-Seq technology such that it can be widely disseminated and can be expanded to different applications such as those that require high spatial resolution and detection sensitivity. Specifically, the project will address the scalability, robustness, and manufacturability of the spatially barcoded substrate, which is the key component of the technique. We will also develop solutions to facilitate easy dissemination of the technology through development of consumables, reagent kits, bioinformatics pipeline, and basic data visualization tools, with the goal to lower the barrier of entry to spatial transcriptomic analyses. Lastly, we will work on improving the performance of the spatial transcriptomic technique in terms of spatial resolution and sensitivity, and expand the workable tissue type from fresh frozen to FFPE. By standardizing the technique through commercialization and making it available to a wider audience, we hope to accelerate a new wave of biological discoveries.