Literature DB >> 35132261

Spatial components of molecular tissue biology.

Giovanni Palla1,2, David S Fischer1,2, Aviv Regev3,4, Fabian J Theis5,6.   

Abstract

Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis. Also, optimal ways to compare different tissue samples at various length scales are still being sought. Grouping these biological problems and related computational algorithms into classes across length scales, thus characterizing common issues that need to be addressed, will facilitate further progress in spatial transcriptomics and proteomics.
© 2022. Springer Nature America, Inc.

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Year:  2022        PMID: 35132261     DOI: 10.1038/s41587-021-01182-1

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   68.164


  105 in total

Review 1.  Tissue biology perspective on macrophages.

Authors:  Yasutaka Okabe; Ruslan Medzhitov
Journal:  Nat Immunol       Date:  2016-01       Impact factor: 25.606

2.  Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.

Authors:  Samuel G Rodriques; Robert R Stickels; Aleksandrina Goeva; Carly A Martin; Evan Murray; Charles R Vanderburg; Joshua Welch; Linlin M Chen; Fei Chen; Evan Z Macosko
Journal:  Science       Date:  2019-03-28       Impact factor: 47.728

3.  Cyclic Immunofluorescence (CycIF), A Highly Multiplexed Method for Single-cell Imaging.

Authors:  Jia-Ren Lin; Mohammad Fallahi-Sichani; Jia-Yun Chen; Peter K Sorger
Journal:  Curr Protoc Chem Biol       Date:  2016-12-07

4.  Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry.

Authors:  Charlotte Giesen; Hao A O Wang; Denis Schapiro; Nevena Zivanovic; Andrea Jacobs; Bodo Hattendorf; Peter J Schüffler; Daniel Grolimund; Joachim M Buhmann; Simone Brandt; Zsuzsanna Varga; Peter J Wild; Detlef Günther; Bernd Bodenmiller
Journal:  Nat Methods       Date:  2014-03-02       Impact factor: 28.547

5.  Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.

Authors:  Patrik L Ståhl; Fredrik Salmén; Sanja Vickovic; Anna Lundmark; José Fernández Navarro; Jens Magnusson; Stefania Giacomello; Michaela Asp; Jakub O Westholm; Mikael Huss; Annelie Mollbrink; Sten Linnarsson; Simone Codeluppi; Åke Borg; Fredrik Pontén; Paul Igor Costea; Pelin Sahlén; Jan Mulder; Olaf Bergmann; Joakim Lundeberg; Jonas Frisén
Journal:  Science       Date:  2016-07-01       Impact factor: 47.728

6.  Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections.

Authors:  Fredrik Salmén; Patrik L Ståhl; Annelie Mollbrink; José Fernández Navarro; Sanja Vickovic; Jonas Frisén; Joakim Lundeberg
Journal:  Nat Protoc       Date:  2018-11       Impact factor: 13.491

7.  Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence.

Authors:  Theodore Alexandrov
Journal:  Annu Rev Biomed Data Sci       Date:  2020-04-13

8.  Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH.

Authors:  Chee-Huat Linus Eng; Michael Lawson; Qian Zhu; Ruben Dries; Noushin Koulena; Yodai Takei; Jina Yun; Christopher Cronin; Christoph Karp; Guo-Cheng Yuan; Long Cai
Journal:  Nature       Date:  2019-03-25       Impact factor: 49.962

9.  High-definition spatial transcriptomics for in situ tissue profiling.

Authors:  Gökcen Eraslan; Fredrik Salmén; Johanna Klughammer; Linnea Stenbeck; Sanja Vickovic; Denis Schapiro; Tarmo Äijö; Richard Bonneau; Ludvig Bergenstråhle; José Fernandéz Navarro; Joshua Gould; Gabriel K Griffin; Åke Borg; Mostafa Ronaghi; Jonas Frisén; Joakim Lundeberg; Aviv Regev; Patrik L Ståhl
Journal:  Nat Methods       Date:  2019-09-09       Impact factor: 28.547

10.  Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression.

Authors:  Chenglong Xia; Jean Fan; George Emanuel; Junjie Hao; Xiaowei Zhuang
Journal:  Proc Natl Acad Sci U S A       Date:  2019-09-09       Impact factor: 11.205

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  8 in total

Review 1.  The expanding vistas of spatial transcriptomics.

Authors:  Luyi Tian; Fei Chen; Evan Z Macosko
Journal:  Nat Biotechnol       Date:  2022-10-03       Impact factor: 68.164

2.  Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data.

Authors:  Alberto Valdeolivas; Aurélien Dugourd; Daniel Dimitrov; Dénes Türei; Martin Garrido-Rodriguez; Paul L Burmedi; James S Nagai; Charlotte Boys; Ricardo O Ramirez Flores; Hyojin Kim; Bence Szalai; Ivan G Costa; Julio Saez-Rodriguez
Journal:  Nat Commun       Date:  2022-06-09       Impact factor: 17.694

3.  Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data.

Authors:  Melissa Grant-Peters; Charlotte Rich-Griffin; Jonathan E Grant-Peters; Gianfelice Cinque; Calliope A Dendrou
Journal:  Bioinformatics       Date:  2022-05-24       Impact factor: 6.931

4.  Spatial proteomics reveals subcellular reorganization in human keratinocytes exposed to UVA light.

Authors:  Hellen Paula Valerio; Felipe Gustavo Ravagnani; Angela Paola Yaya Candela; Bruna Dias Carvalho da Costa; Graziella Eliza Ronsein; Paolo Di Mascio
Journal:  iScience       Date:  2022-03-16

5.  Identifying multicellular spatiotemporal organization of cells with SpaceFlow.

Authors:  Honglei Ren; Benjamin L Walker; Zixuan Cang; Qing Nie
Journal:  Nat Commun       Date:  2022-07-14       Impact factor: 17.694

6.  Inference on spatial heterogeneity in tumor microenvironment using spatial transcriptomics data.

Authors:  Antara Biswas; Bassel Ghaddar; Gregory Riedlinger; Subhajyoti De
Journal:  Comput Syst Oncol       Date:  2022-08-11

Review 7.  Computational solutions for spatial transcriptomics.

Authors:  Iivari Kleino; Paulina Frolovaitė; Tomi Suomi; Laura L Elo
Journal:  Comput Struct Biotechnol J       Date:  2022-09-01       Impact factor: 6.155

8.  Identification of spatially variable genes with graph cuts.

Authors:  Ke Zhang; Wanwan Feng; Peng Wang
Journal:  Nat Commun       Date:  2022-09-19       Impact factor: 17.694

  8 in total

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