1
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Saarenpää S, Shalev O, Ashkenazy H, Carlos V, Lundberg DS, Weigel D, Giacomello S. Spatial metatranscriptomics resolves host-bacteria-fungi interactomes. Nat Biotechnol 2023:10.1038/s41587-023-01979-2. [PMID: 37985875 DOI: 10.1038/s41587-023-01979-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 09/06/2023] [Indexed: 11/22/2023]
Abstract
The interactions of microorganisms among themselves and with their multicellular host take place at the microscale, forming complex networks and spatial patterns. Existing technology does not allow the simultaneous investigation of spatial interactions between a host and the multitude of its colonizing microorganisms, which limits our understanding of host-microorganism interactions within a plant or animal tissue. Here we present spatial metatranscriptomics (SmT), a sequencing-based approach that leverages 16S/18S/ITS/poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-µm resolution. We showcase SmT in outdoor-grown Arabidopsis thaliana leaves as a model system, and find tissue-scale bacterial and fungal hotspots. By network analysis, we study inter- and intrakingdom spatial interactions among microorganisms, as well as the host response to microbial hotspots. SmT provides an approach for answering fundamental questions on host-microbiome interplay.
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Affiliation(s)
- Sami Saarenpää
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Or Shalev
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Systems Biology of Microbial Communities, University of Tübingen, Tübingen, Germany
| | - Haim Ashkenazy
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
| | - Vanessa Carlos
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
| | - Derek Severi Lundberg
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Detlef Weigel
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Stefania Giacomello
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
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2
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Cheng M, Jiang Y, Xu J, Mentis AFA, Wang S, Zheng H, Sahu SK, Liu L, Xu X. Spatially resolved transcriptomics: a comprehensive review of their technological advances, applications, and challenges. J Genet Genomics 2023; 50:625-640. [PMID: 36990426 DOI: 10.1016/j.jgg.2023.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 03/11/2023] [Accepted: 03/16/2023] [Indexed: 03/29/2023]
Abstract
The ability to explore life kingdoms is largely driven by innovations and breakthroughs in technology, from the invention of the microscope 350 years ago to the recent emergence of single-cell sequencing, by which the scientific community has been able to visualize life at an unprecedented resolution. Most recently, the Spatially Resolved Transcriptomics (SRT) technologies have filled the gap in probing the spatial or even three-dimensional organization of the molecular foundation behind the molecular mysteries of life, including the origin of different cellular populations developed from totipotent cells and human diseases. In this review, we introduce recent progresses and challenges on SRT from the perspectives of technologies and bioinformatic tools, as well as the representative SRT applications. With the currently fast-moving progress of the SRT technologies and promising results from early adopted research projects, we can foresee the bright future of such new tools in understanding life at the most profound analytical level.
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Affiliation(s)
| | - Yujia Jiang
- BGI-Hangzhou, Hangzhou, Zhejiang 310012, China
| | | | | | - Shuai Wang
- BGI-Hangzhou, Hangzhou, Zhejiang 310012, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Sunil Kumar Sahu
- BGI-Shenzhen, Shenzhen, Guangdong 518103, China; State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Longqi Liu
- BGI-Hangzhou, Hangzhou, Zhejiang 310012, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Xun Xu
- BGI-Hangzhou, Hangzhou, Zhejiang 310012, China; BGI-Shenzhen, Shenzhen, Guangdong 518103, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, Guangdong 518120, China.
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3
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Kalikiri MKR, Manjunath HS, Vempalli FR, Mathew LS, Liu L, Wang L, Wang G, Wang K, Soloviov O, Lorenz S, Tomei S. Technical assessment of different extraction methods and transcriptome profiling of RNA isolated from small volumes of blood. Sci Rep 2023; 13:3598. [PMID: 36869090 PMCID: PMC9984369 DOI: 10.1038/s41598-023-30629-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 02/27/2023] [Indexed: 03/05/2023] Open
Abstract
Transcriptome profiling of human whole blood is used to discover biomarkers of diseases and to assess phenotypic traits. Recently, finger-stick blood collection systems have allowed a less invasive and quicker collection of peripheral blood. Such non-invasive sampling of small volumes of blood offers practical advantages. The quality of gene expression data is strictly dependent on the steps used for the sample collection, extraction, preparation and sequencing. Here we have: (i) compared the manual and automated RNA extraction of small volumes of blood using the Tempus Spin RNA isolation kit and the MagMAX for Stabilized Blood RNA Isolation kit , respectively; and (ii) assessed the effect of TURBO DNA Free treatment on the transcriptomic data of RNA isolated from small volumes of blood. We have used the QuantSeq 3' FWD mRNA-Seq Library Prep kit to prepare RNA-seq libraries, which were sequenced on the Illumina NextSeq 500 system. The samples isolated manually displayed a higher variability in the transcriptomic data as compared to the other samples. The TURBO DNA Free treatment affected the RNA samples negatively, decreasing the RNA yield and reducing the quality and reproducibility of the transcriptomic data. We conclude that automated extraction systems should be preferred over manual extraction systems for data consistency, and that the TURBO DNA Free treatment should be avoided when working on RNA samples isolated manually from small volumes of blood.
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Affiliation(s)
| | | | | | - Lisa Sara Mathew
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Li Liu
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Li Wang
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Guishuang Wang
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Kun Wang
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Oleksandr Soloviov
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Stephan Lorenz
- Clinical Genomics Laboratory, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
- Omics Core, Integrated Genomic Services, Sidra Medicine, Doha, Qatar
- Bioinformatics Core, Integrated Genomics Services, Sidra Medicine, Doha, Qatar
| | - Sara Tomei
- Omics Core, Integrated Genomic Services, Sidra Medicine, Doha, Qatar.
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4
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Overbey EG, Das S, Cope H, Madrigal P, Andrusivova Z, Frapard S, Klotz R, Bezdan D, Gupta A, Scott RT, Park J, Chirko D, Galazka JM, Costes SV, Mason CE, Herranz R, Szewczyk NJ, Borg J, Giacomello S. Challenges and considerations for single-cell and spatially resolved transcriptomics sample collection during spaceflight. CELL REPORTS METHODS 2022; 2:100325. [PMID: 36452864 PMCID: PMC9701605 DOI: 10.1016/j.crmeth.2022.100325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) have experienced rapid development in recent years. The findings of spaceflight-based scRNA-seq and SRT investigations are likely to improve our understanding of life in space and our comprehension of gene expression in various cell systems and tissue dynamics. However, compared to their Earth-based counterparts, gene expression experiments conducted in spaceflight have not experienced the same pace of development. Out of the hundreds of spaceflight gene expression datasets available, only a few used scRNA-seq and SRT. In this perspective piece, we explore the growing importance of scRNA-seq and SRT in space biology and discuss the challenges and considerations relevant to robust experimental design to enable growth of these methods in the field.
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Affiliation(s)
- Eliah G. Overbey
- Weill Cornell Medicine, New York, NY, USA
- Institute for Computational Biomedicine, New York, NY, USA
| | - Saswati Das
- Department of Biochemistry, Atal Bihari Vajpayee Institute of Medical Sciences & Dr. Ram Manohar Lohia Hospital, New Delhi, India
| | - Henry Cope
- School of Medicine, University of Nottingham, Derby DE22 3DT, UK
| | - Pedro Madrigal
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Zaneta Andrusivova
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Solène Frapard
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Rebecca Klotz
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA
| | - Daniela Bezdan
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen 72076, Germany
- NGS Competence Center Tübingen (NCCT), University of Tübingen, Tübingen, German
- yuri GmbH, Meckenbeuren, Germany
| | | | - Ryan T. Scott
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA
| | | | | | - Jonathan M. Galazka
- Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA
| | - Sylvain V. Costes
- Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA
| | - Christopher E. Mason
- Weill Cornell Medicine, New York, NY, USA
- Institute for Computational Biomedicine, New York, NY, USA
- The Feil Family Brain and Mind Research Institute, New York, NY, USA
- The WorldQuant Initiative for Quantitative Prediction, New York, NY, USA
| | - Raul Herranz
- Centro de Investigaciones Biológicas Margarita Salas (CSIC), Madrid 28040, Spain
| | - Nathaniel J. Szewczyk
- School of Medicine, University of Nottingham, Derby DE22 3DT, UK
- Department of Biomedical Sciences, Heritage College of Osteopathic Medicine, Ohio University, Athens, OH 45701, USA
| | - Joseph Borg
- Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta, Msida, Malta
| | - Stefania Giacomello
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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5
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Torres-Acosta MA, Lye GJ, Dikicioglu D. Automated liquid-handling operations for robust, resilient, and efficient bio-based laboratory practices. Biochem Eng J 2022. [DOI: 10.1016/j.bej.2022.108713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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6
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Enabling automated and reproducible spatially resolved transcriptomics at scale. Heliyon 2022; 8:e09651. [PMID: 35756107 PMCID: PMC9213715 DOI: 10.1016/j.heliyon.2022.e09651] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 05/13/2022] [Accepted: 05/31/2022] [Indexed: 12/02/2022] Open
Abstract
Spatial information of tissues is an essential component to reach a holistic overview of gene expression mechanisms. The sequencing-based Spatial transcriptomics approach allows to spatially barcode the whole transcriptome of tissue sections using microarray glass slides. However, manual preparation of high-quality tissue sequencing libraries is time-consuming and subjected to technical variability. Here, we present an automated adaptation of the 10x Genomics Visium library construction on the widely used Agilent Bravo Liquid Handling Platform. Compared to the manual Visium library preparation, our automated approach reduces hands-on time by over 80% and provides higher throughput and robustness. Our automated Visium library preparation protocol provides a new strategy to standardize spatially resolved transcriptomics analysis of tissues at scale.
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7
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Liu Y, Wang T, Duggan B, Sharpnack M, Huang K, Zhang J, Ye X, Johnson TS. SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression. Brief Bioinform 2022; 23:bbac116. [PMID: 35380614 PMCID: PMC9116229 DOI: 10.1093/bib/bbac116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 02/24/2022] [Accepted: 03/09/2022] [Indexed: 11/12/2022] Open
Abstract
High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).
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Affiliation(s)
- Yusong Liu
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, China
| | - Tongxin Wang
- Department of Computer Science, Indiana University Bloomington, Bloomington, IN 47408, USA
| | - Ben Duggan
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Michael Sharpnack
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Kun Huang
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Jie Zhang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Xiufen Ye
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, China
| | - Travis S Johnson
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Indiana Biosciences Research Institute, Indianapolis, IN 46202, USA
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8
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Heins A, Hoang MD, Weuster‐Botz D. Advances in automated real-time flow cytometry for monitoring of bioreactor processes. Eng Life Sci 2022; 22:260-278. [PMID: 35382548 PMCID: PMC8961054 DOI: 10.1002/elsc.202100082] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/22/2021] [Accepted: 10/27/2021] [Indexed: 12/18/2022] Open
Abstract
Flow cytometry and its technological possibilities have greatly advanced in the past decade as analysis tool for single cell properties and population distributions of different cell types in bioreactors. Along the way, some solutions for automated real-time flow cytometry (ART-FCM) were developed for monitoring of bioreactor processes without operator interference over extended periods with variable sampling frequency. However, there is still great potential for ART-FCM to evolve and possibly become a standard application in bioprocess monitoring and process control. This review first addresses different components of an ART-FCM, including the sampling device, the sample-processing unit, the unit for sample delivery to the flow cytometer and the settings for measurement of pre-processed samples. Also, available algorithms are presented for automated data analysis of multi-parameter fluorescence datasets derived from ART-FCM experiments. Furthermore, challenges are discussed for integration of fluorescence-activated cell sorting into an ART-FCM setup for isolation and separation of interesting subpopulations that can be further characterized by for instance omics-methods. As the application of ART-FCM is especially of interest for bioreactor process monitoring, including investigation of population heterogeneity and automated process control, a summary of already existing setups for these purposes is given. Additionally, the general future potential of ART-FCM is addressed.
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Affiliation(s)
- Anna‐Lena Heins
- Institute of Biochemical EngineeringTechnical University of MunichGarchingGermany
| | - Manh Dat Hoang
- Institute of Biochemical EngineeringTechnical University of MunichGarchingGermany
| | - Dirk Weuster‐Botz
- Institute of Biochemical EngineeringTechnical University of MunichGarchingGermany
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9
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Vickovic S, Schapiro D, Carlberg K, Lötstedt B, Larsson L, Hildebrandt F, Korotkova M, Hensvold AH, Catrina AI, Sorger PK, Malmström V, Regev A, Ståhl PL. Three-dimensional spatial transcriptomics uncovers cell type localizations in the human rheumatoid arthritis synovium. Commun Biol 2022; 5:129. [PMID: 35149753 PMCID: PMC8837632 DOI: 10.1038/s42003-022-03050-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 01/10/2022] [Indexed: 12/14/2022] Open
Abstract
The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA is spatially labeled in situ with barcodes in a transcriptome-wide fashion, to study local tissue interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-Seq data coupled to cell type-specific localization patterns at and around organized structures of infiltrating leukocyte cells in the synovium. Combining morphological features and high-throughput spatially resolved transcriptomics may be able to provide higher statistical power and more insights into monitoring disease severity and treatment-specific responses in seropositive and seronegative rheumatoid arthritis.
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Affiliation(s)
- Sanja Vickovic
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden. .,New York Genome Center, New York, NY, USA.
| | - Denis Schapiro
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.,Institute for Computational Biomedicine and Institute of Pathology, Faculty of Medicine, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany
| | - Konstantin Carlberg
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Britta Lötstedt
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Ludvig Larsson
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Franziska Hildebrandt
- Department of Molecular Biosciences, the Wenner Gren Institute, Stockholm University, Stockholm, Sweden
| | - Marina Korotkova
- Karolinska Institutet, Division of Rheumatology, Department of Medicine, Center for Molecular Medicine, Stockholm, Sweden.,Unit of Rheumatology, Karolinska University Hospital, Stockholm, Sweden
| | - Aase H Hensvold
- Karolinska Institutet, Division of Rheumatology, Department of Medicine, Center for Molecular Medicine, Stockholm, Sweden.,Unit of Rheumatology, Karolinska University Hospital, Stockholm, Sweden
| | - Anca I Catrina
- Karolinska Institutet, Division of Rheumatology, Department of Medicine, Center for Molecular Medicine, Stockholm, Sweden.,Unit of Rheumatology, Karolinska University Hospital, Stockholm, Sweden
| | - Peter K Sorger
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Vivianne Malmström
- Karolinska Institutet, Division of Rheumatology, Department of Medicine, Center for Molecular Medicine, Stockholm, Sweden.,Unit of Rheumatology, Karolinska University Hospital, Stockholm, Sweden
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Howard Hughes Medical Institute and Koch Institute for Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.,Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - Patrik L Ståhl
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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10
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Vickovic S, Lötstedt B, Klughammer J, Mages S, Segerstolpe Å, Rozenblatt-Rosen O, Regev A. SM-Omics is an automated platform for high-throughput spatial multi-omics. Nat Commun 2022; 13:795. [PMID: 35145087 PMCID: PMC8831571 DOI: 10.1038/s41467-022-28445-y] [Citation(s) in RCA: 63] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 01/24/2022] [Indexed: 12/12/2022] Open
Abstract
The spatial organization of cells and molecules plays a key role in tissue function in homeostasis and disease. Spatial transcriptomics has recently emerged as a key technique to capture and positionally barcode RNAs directly in tissues. Here, we advance the application of spatial transcriptomics at scale, by presenting Spatial Multi-Omics (SM-Omics) as a fully automated, high-throughput all-sequencing based platform for combined and spatially resolved transcriptomics and antibody-based protein measurements. SM-Omics uses DNA-barcoded antibodies, immunofluorescence or a combination thereof, to scale and combine spatial transcriptomics and spatial antibody-based multiplex protein detection. SM-Omics allows processing of up to 64 in situ spatial reactions or up to 96 sequencing-ready libraries, of high complexity, in a ~2 days process. We demonstrate SM-Omics in the mouse brain, spleen and colorectal cancer model, showing its broad utility as a high-throughput platform for spatial multi-omics.
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Affiliation(s)
- S Vickovic
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. .,New York Genome Center, New York, NY, USA. .,Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden.
| | - B Lötstedt
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - J Klughammer
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - S Mages
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Å Segerstolpe
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - O Rozenblatt-Rosen
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - A Regev
- Klarman Cell Observatory Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Howard Hughes Medical Institute and Koch Institute for Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Genentech, 1 DNA Way, South San Francisco, CA, USA.
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11
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Ahmed R, Augustine R, Valera E, Ganguli A, Mesaeli N, Ahmad IS, Bashir R, Hasan A. Spatial mapping of cancer tissues by OMICS technologies. Biochim Biophys Acta Rev Cancer 2021; 1877:188663. [PMID: 34861353 DOI: 10.1016/j.bbcan.2021.188663] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 11/15/2021] [Accepted: 11/26/2021] [Indexed: 12/14/2022]
Abstract
Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding of cancers and help in the rapid detection of cancers with high accuracy and reliability. Significant advancements have been made in recent years in OMICS technologies, which possess the strong potential to be applied in the spatial mapping of biopsy tissue samples and their molecular profiling to a single-cell level. The clinical application of OMICS technologies in spatial profiling of cancer tissues is also advancing. The current review presents recent advancements and prospects of applying OMICS technologies to the spatial mapping of various analytes in cancer tissues. We benchmark the current state of the art in the field to advance existing OMICS technologies for high throughput spatial profiling. The factors taken into consideration include spatial resolution, types of biomolecules, number of different biomolecules that can be detected from the same assay, labeled versus label-free approaches, and approximate time required for each assay. Further advancements are still needed for the widespread application of OMICs technologies in performing fast and high throughput spatial mapping of cancer tissues as well as their effective use in research and clinical applications.
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Affiliation(s)
- Rashid Ahmed
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar; Biomedical Research Center (BRC), Qatar University, Doha 2713, Qatar; Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA
| | - Robin Augustine
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar; Biomedical Research Center (BRC), Qatar University, Doha 2713, Qatar
| | - Enrique Valera
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA; Department of Bioengineering, University of Illinois at Urbana Champaign, IL, USA
| | - Anurup Ganguli
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA; Department of Bioengineering, University of Illinois at Urbana Champaign, IL, USA
| | - Nasrin Mesaeli
- Department of Biochemistry, Weill Cornell Medicine in Qatar, Qatar Foundation, Doha, Qatar
| | - Irfan S Ahmad
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA
| | - Rashid Bashir
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA; Department of Bioengineering, University of Illinois at Urbana Champaign, IL, USA; Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
| | - Anwarul Hasan
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar; Biomedical Research Center (BRC), Qatar University, Doha 2713, Qatar.
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12
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Tegally H, San JE, Giandhari J, de Oliveira T. Unlocking the efficiency of genomics laboratories with robotic liquid-handling. BMC Genomics 2020; 21:729. [PMID: 33081689 PMCID: PMC7576741 DOI: 10.1186/s12864-020-07137-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 10/11/2020] [Indexed: 02/08/2023] Open
Abstract
In research and clinical genomics laboratories today, sample preparation is the bottleneck of experiments, particularly when it comes to high-throughput next generation sequencing (NGS). More genomics laboratories are now considering liquid-handling automation to make the sequencing workflow more efficient and cost effective. The question remains as to its suitability and return on investment. A number of points need to be carefully considered before introducing robots into biological laboratories. Here, we describe the state-of-the-art technology of both sophisticated and do-it-yourself (DIY) robotic liquid-handlers and provide a practical review of the motivation, implications and requirements of laboratory automation for genome sequencing experiments.
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Affiliation(s)
- Houriiyah Tegally
- Kwazulu-Natal Research and Innovation Sequencing Platform (KRISP), College of Health Sciences, K-RITH Tower Building, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, 719 Umbilo Road, Durban, South Africa.
| | - James Emmanuel San
- Kwazulu-Natal Research and Innovation Sequencing Platform (KRISP), College of Health Sciences, K-RITH Tower Building, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, 719 Umbilo Road, Durban, South Africa
| | - Jennifer Giandhari
- Kwazulu-Natal Research and Innovation Sequencing Platform (KRISP), College of Health Sciences, K-RITH Tower Building, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, 719 Umbilo Road, Durban, South Africa
| | - Tulio de Oliveira
- Kwazulu-Natal Research and Innovation Sequencing Platform (KRISP), College of Health Sciences, K-RITH Tower Building, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, 719 Umbilo Road, Durban, South Africa.
- Department of Global Health, University of Washington, 908 Jefferson Street, 13th Floor, Seattle, WA, 98104, USA.
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Kucharski M, Tripathi J, Nayak S, Zhu L, Wirjanata G, van der Pluijm RW, Dhorda M, Dondorp A, Bozdech Z. A comprehensive RNA handling and transcriptomics guide for high-throughput processing of Plasmodium blood-stage samples. Malar J 2020; 19:363. [PMID: 33036628 PMCID: PMC7547485 DOI: 10.1186/s12936-020-03436-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 10/01/2020] [Indexed: 02/06/2023] Open
Abstract
Background Sequencing technology advancements opened new opportunities to use transcriptomics for studying malaria pathology and epidemiology. Even though in recent years the study of whole parasite transcriptome proved to be essential in understanding parasite biology there is no compiled up-to-date reference protocol for the efficient generation of transcriptome data from growing number of samples. Here, a comprehensive methodology on how to preserve, extract, amplify, and sequence full-length mRNA transcripts from Plasmodium-infected blood samples is presented that can be fully streamlined for high-throughput studies. Results The utility of various commercially available RNA-preserving reagents in a range of storage conditions was evaluated. Similarly, several RNA extraction protocols were compared and the one most suitable method for the extraction of high-quality total RNA from low-parasitaemia and low-volume blood samples was established. Furthermore, the criteria needed to evaluate the quality and integrity of Plasmodium RNA in the presence of human RNA was updated. Optimization of SMART-seq2 amplification method to better suit AT-rich Plasmodium falciparum RNA samples allowed us to generate high-quality transcriptomes from as little as 10 ng of total RNA and a lower parasitaemia limit of 0.05%. Finally, a modified method for depletion of unwanted human haemoglobin transcripts using in vitro CRISPR-Cas9 treatment was designed, thus improving parasite transcriptome coverage in low parasitaemia samples. To prove the functionality of the pipeline for both laboratory and field strains, the highest 2-hour resolution RNA-seq transcriptome for P. falciparum 3D7 intraerythrocytic life cycle available to date was generated, and the entire protocol was applied to create the largest transcriptome data from Southeast Asian field isolates. Conclusions Overall, the presented methodology is an inclusive pipeline for generation of good quality transcriptomic data from a diverse range of Plasmodium-infected blood samples with varying parasitaemia and RNA inputs. The flexibility of this pipeline to be adapted to robotic handling will facilitate both small and large-scale future transcriptomic studies in the field of malaria.
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Affiliation(s)
- Michal Kucharski
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
| | - Jaishree Tripathi
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
| | - Sourav Nayak
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore
| | - Lei Zhu
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore
| | - Grennady Wirjanata
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore
| | - Rob W van der Pluijm
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Mehul Dhorda
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,WorldWide Antimalarial Resistance Network-Asia Regional Centre, Bangkok, Thailand
| | - Arjen Dondorp
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Zbynek Bozdech
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
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