1
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Vistain L, Keisham B, Xia J, Phan HV, Tay S. Proximity sequencing for the detection of mRNA, extracellular proteins and extracellular protein complexes in single cells. Nat Protoc 2024:10.1038/s41596-024-01030-x. [PMID: 39147984 DOI: 10.1038/s41596-024-01030-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 05/24/2024] [Indexed: 08/17/2024]
Abstract
Complex cellular functions occur via the coordinated formation and dissociation of protein complexes. Functions such as the response to a signaling ligand can incorporate dozens of proteins and hundreds of complexes. Until recently, it has been difficult to measure multiple protein complexes at the single-cell level. Here, we present a step-by-step procedure for proximity sequencing, which enables the simultaneous measurement of proteins, mRNA and hundreds of protein complexes located on the outer membrane of cells. We guide the user through probe creation, sample preparation, staining, sequencing and computational quantification of protein complexes. This protocol empowers researchers to study, for example, the interplay between transcriptional states and cellular functions by coupling measurements of transcription to measurements of linked effector molecules, yet could be generalizable to other paired events. The protocol requires roughly 16 h spread over several days to complete by users with expertise in basic molecular biology and single-cell sequencing.
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Affiliation(s)
- Luke Vistain
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
- Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Bijentimala Keisham
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | - Junjie Xia
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | - Hoang Van Phan
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
- Division of Infectious Disease, University of California, San Francisco, San Francisco, CA, USA
| | - Savaş Tay
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA.
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2
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Wu R, Veličković M, Burnum-Johnson KE. From single cell to spatial multi-omics: unveiling molecular mechanisms in dynamic and heterogeneous systems. Curr Opin Biotechnol 2024; 89:103174. [PMID: 39126877 DOI: 10.1016/j.copbio.2024.103174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 07/02/2024] [Indexed: 08/12/2024]
Abstract
Single-cell multi-omics and spatial technology have been widely applied to biomedical studies and recently to environmental studies. The cell size detected by single-cell omics ranges from ∼2 µm (e.g., Bacillus subtilis) to ∼120 µm (e.g., human oocytes). Simultaneous detection of single-cell multi-omics is available to human and plant tissues while limited to microbial samples. Spatial technology enables mapping the detected biomolecules in situ. The recent advances in Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging and Micro/Nanodroplet Processing in One Pot for Trace Samples for the first time allow the application of spatial multi-omics in highly heterogeneous environmental samples composed of plants, fungi, and bacteria. We envision that these technologies will continue to advance our understanding of unique cell types, their developmental trajectory, and the intercellular signaling and interaction within biological samples.
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Affiliation(s)
- Ruonan Wu
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marija Veličković
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Kristin E Burnum-Johnson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.
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3
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Wang Y, Han J, Yang G, Zheng S, Zhou G, Liu X, Cao X, Li G, Zhang B, Xie Z, Li L, Zhang M, Li X, Chen M, Zhang S. Therapeutic potential of the secreted Kazal-type serine protease inhibitor SPINK4 in colitis. Nat Commun 2024; 15:5874. [PMID: 38997284 PMCID: PMC11245600 DOI: 10.1038/s41467-024-50048-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 06/28/2024] [Indexed: 07/14/2024] Open
Abstract
Mucus injury associated with goblet cell (GC) depletion constitutes an early event in inflammatory bowel disease (IBD). Using single-cell sequencing to detect critical events in mucus dysfunction, we discover that the Kazal-type serine protease inhibitor SPINK4 is dynamically regulated in colitic intestine in parallel with disease activities. Under chemically induced colitic conditions, the grim status in Spink4-conditional knockout mice is successfully rescued by recombinant murine SPINK4. Notably, its therapeutic potential is synergistic with existing TNF-α inhibitor infliximab in colitis treatment. Mechanistically, SPINK4 promotes GC differentiation using a Kazal-like motif to modulate EGFR-Wnt/β-catenin and -Hippo pathways. Microbiota-derived diacylated lipoprotein Pam2CSK4 triggers SPINK4 production. We also show that monitoring SPINK4 in circulation is a reliable noninvasive technique to distinguish IBD patients from healthy controls and assess disease activity. Thus, SPINK4 serves as a serologic biomarker of IBD and has therapeutic potential for colitis via intrinsic EGFR activation in intestinal homeostasis.
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Affiliation(s)
- Ying Wang
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Jing Han
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
- Division of Gastroenterology, Guangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, Nanning, P. R. China
| | - Guang Yang
- Department of Minimally Invasive Intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Shuhui Zheng
- Research Center for Translational Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Gaoshi Zhou
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Xinjuan Liu
- Department of Gastroenterology, Beijing Chaoyang Hospital, Capital Medical University, Chaoyang District, Beijing, P. R. China
| | - Xiaocang Cao
- Department of Hepato-Gastroenterology, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, P. R. China
| | - Guang Li
- Department of Gastroenterology, Beijing Chaoyang Hospital, Capital Medical University, Chaoyang District, Beijing, P. R. China
| | - Bowen Zhang
- College of Life Sciences, Beijing Normal University, Beijing, P. R. China
| | - Zhuo Xie
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Li Li
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Mudan Zhang
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Xiaoling Li
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Minhu Chen
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Shenghong Zhang
- Division of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P. R. China.
- Division of Gastroenterology, Guangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, Nanning, P. R. China.
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4
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Rhomberg-Kauert J, Karlsson M, Thiagarajan D, Kallas T, Karlsson F, Fredriksson S, Dahlberg J, Martinez Barrio A. Using adjusted local assortativity with Molecular Pixelation unveils colocalization of membrane proteins with immunological significance. Front Immunol 2024; 15:1309916. [PMID: 38983848 PMCID: PMC11231075 DOI: 10.3389/fimmu.2024.1309916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 04/09/2024] [Indexed: 07/11/2024] Open
Abstract
Advances in spatial proteomics and protein colocalization are a driving force in the understanding of cellular mechanisms and their influence on biological processes. New methods in the field of spatial proteomics call for the development of algorithms and open up new avenues of research. The newly introduced Molecular Pixelation (MPX) provides spatial information on surface proteins and their relationship with each other in single cells. This allows for in silico representation of neighborhoods of membrane proteins as graphs. In order to analyze this new data modality, we adapted local assortativity in networks of MPX single-cell graphs and created a method that is able to capture detailed information on the spatial relationships of proteins. The introduced method can evaluate the pairwise colocalization of proteins and access higher-order similarity to investigate the colocalization of multiple proteins at the same time. We evaluated the method using publicly available MPX datasets where T cells were treated with a chemokine to study uropod formation. We demonstrate that adjusted local assortativity detects the effects of the stimuli at both single- and multiple-marker levels, which enhances our understanding of the uropod formation. We also applied our method to treating cancerous B-cell lines using a therapeutic antibody. With the adjusted local assortativity, we recapitulated the effect of rituximab on the polarity of CD20. Our computational method together with MPX improves our understanding of not only the formation of cell polarity and protein colocalization under stimuli but also advancing the overall insight into immune reaction and reorganization of cell surface proteins, which in turn allows the design of novel therapies. We foresee its applicability to other types of biological spatial data when represented as undirected graphs.
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Affiliation(s)
- Jan Rhomberg-Kauert
- Pixelgen Technologies AB, Stockholm, Sweden
- Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
| | | | | | | | | | - Simon Fredriksson
- Pixelgen Technologies AB, Stockholm, Sweden
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
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5
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Curion F, Theis FJ. Machine learning integrative approaches to advance computational immunology. Genome Med 2024; 16:80. [PMID: 38862979 PMCID: PMC11165829 DOI: 10.1186/s13073-024-01350-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 05/23/2024] [Indexed: 06/13/2024] Open
Abstract
The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond traditional protein marker identification to encompass a more detailed view of cellular phenotypes and their functional roles. Recent technological advancements allow the simultaneous measurements of multiple cellular components-transcriptome, proteome, chromatin, epigenetic modifications and metabolites-within single cells, including in spatial contexts within tissues. This has led to the generation of complex multiscale datasets that can include multimodal measurements from the same cells or a mix of paired and unpaired modalities. Modern machine learning (ML) techniques allow for the integration of multiple "omics" data without the need for extensive independent modelling of each modality. This review focuses on recent advancements in ML integrative approaches applied to immunological studies. We highlight the importance of these methods in creating a unified representation of multiscale data collections, particularly for single-cell and spatial profiling technologies. Finally, we discuss the challenges of these holistic approaches and how they will be instrumental in the development of a common coordinate framework for multiscale studies, thereby accelerating research and enabling discoveries in the computational immunology field.
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Affiliation(s)
- Fabiola Curion
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany.
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
- School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.
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6
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Hu X, van Sluijs B, García-Blay Ó, Stepanov Y, Rietrae K, Huck WTS, Hansen MMK. ARTseq-FISH reveals position-dependent differences in gene expression of micropatterned mESCs. Nat Commun 2024; 15:3918. [PMID: 38724524 PMCID: PMC11082235 DOI: 10.1038/s41467-024-48107-5] [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: 02/17/2023] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
Differences in gene-expression profiles between individual cells can give rise to distinct cell fate decisions. Yet how localisation on a micropattern impacts initial changes in mRNA, protein, and phosphoprotein abundance remains unclear. To identify the effect of cellular position on gene expression, we developed a scalable antibody and mRNA targeting sequential fluorescence in situ hybridisation (ARTseq-FISH) method capable of simultaneously profiling mRNAs, proteins, and phosphoproteins in single cells. We studied 67 (phospho-)protein and mRNA targets in individual mouse embryonic stem cells (mESCs) cultured on circular micropatterns. ARTseq-FISH reveals relative changes in both abundance and localisation of mRNAs and (phospho-)proteins during the first 48 hours of exit from pluripotency. We confirm these changes by conventional immunofluorescence and time-lapse microscopy. Chemical labelling, immunofluorescence, and single-cell time-lapse microscopy further show that cells closer to the edge of the micropattern exhibit increased proliferation compared to cells at the centre. Together these data suggest that while gene expression is still highly heterogeneous position-dependent differences in mRNA and protein levels emerge as early as 12 hours after LIF withdrawal.
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Affiliation(s)
- Xinyu Hu
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands
- Oncode Institute, Nijmegen, The Netherlands
| | - Bob van Sluijs
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands
| | - Óscar García-Blay
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands
- Oncode Institute, Nijmegen, The Netherlands
| | - Yury Stepanov
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands
| | - Koen Rietrae
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands
| | - Wilhelm T S Huck
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands.
| | - Maike M K Hansen
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, the Netherlands.
- Oncode Institute, Nijmegen, The Netherlands.
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7
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Tian T, Lin S, Yang C. Beyond single cells: microfluidics empowering multiomics analysis. Anal Bioanal Chem 2024; 416:2203-2220. [PMID: 38008783 DOI: 10.1007/s00216-023-05028-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 11/28/2023]
Abstract
Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.
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Affiliation(s)
- Tian Tian
- Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Shichao Lin
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Xiamen, 361005, China
| | - Chaoyong Yang
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Xiamen, 361005, China.
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
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8
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Udani S, Langerman J, Koo D, Baghdasarian S, Cheng B, Kang S, Soemardy C, de Rutte J, Plath K, Di Carlo D. Associating growth factor secretions and transcriptomes of single cells in nanovials using SEC-seq. NATURE NANOTECHNOLOGY 2024; 19:354-363. [PMID: 38082117 DOI: 10.1038/s41565-023-01560-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 10/31/2023] [Indexed: 01/23/2024]
Abstract
Cells secrete numerous bioactive molecules that are essential for the function of healthy organisms. However, scalable methods are needed to link individual cell secretions to their transcriptional state over time. Here, by developing and using secretion-encoded single-cell sequencing (SEC-seq), which exploits hydrogel particles with subnanolitre cavities (nanovials) to capture individual cells and their secretions, we simultaneously measured the secretion of vascular endothelial growth factor A (VEGF-A) and the transcriptome for thousands of individual mesenchymal stromal cells. Our data indicate that VEGF-A secretion is heterogeneous across the cell population and is poorly correlated with the VEGFA transcript level. The highest VEGF-A secretion occurs in a subpopulation of mesenchymal stromal cells characterized by a unique gene expression signature comprising a surface marker, interleukin-13 receptor subunit alpha 2 (IL13RA2), which allowed the enrichment of this subpopulation. SEC-seq enables the identification of gene signatures linked to specific secretory states, facilitating mechanistic studies, the isolation of secretory subpopulations and the development of means to modulate cellular secretion.
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Affiliation(s)
- Shreya Udani
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Justin Langerman
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Doyeon Koo
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Sevana Baghdasarian
- Department of Chemical and Biomolecular Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Brian Cheng
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Simran Kang
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Citradewi Soemardy
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Kathrin Plath
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA, USA.
- Eli and Edythe Broad Stem Cell Research Center, University of California Los Angeles, Los Angeles, CA, USA.
| | - Dino Di Carlo
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA.
- Partillion Bioscience, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Mechanical and Aerospace Engineering, University of California Los Angeles, Los Angeles, CA, USA.
- California NanoSystems Institute (CNSI), University of California Los Angeles, Los Angeles, CA, USA.
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9
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Xia J, Phan HV, Vistain L, Chen M, Khan AA, Tay S. Computational prediction of protein interactions in single cells by proximity sequencing. PLoS Comput Biol 2024; 20:e1011915. [PMID: 38483861 PMCID: PMC10939233 DOI: 10.1371/journal.pcbi.1011915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 02/13/2024] [Indexed: 03/17/2024] Open
Abstract
Proximity sequencing (Prox-seq) simultaneously measures gene expression, protein expression and protein complexes on single cells. Using information from dual-antibody binding events, Prox-seq infers surface protein dimers at the single-cell level. Prox-seq provides multi-dimensional phenotyping of single cells in high throughput, and was recently used to track the formation of receptor complexes during cell signaling and discovered a novel interaction between CD9 and CD8 in naïve T cells. The distribution of protein abundance can affect identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model of Prox-seq and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq data, which resulted in more accurate and robust quantification of protein complexes. Finally, our Prox-seq model offers a simple way to investigate the behavior of Prox-seq data under various biological conditions and guide users toward selecting the best analysis method for their data.
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Affiliation(s)
- Junjie Xia
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois, United States of America
| | - Hoang Van Phan
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois, United States of America
| | - Luke Vistain
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois, United States of America
| | - Mengjie Chen
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, Illinois, United States of America
- Department Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Aly A. Khan
- Department of Pathology, The University of Chicago, Chicago, Illinois, United States of America
| | - Savaş Tay
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois, United States of America
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10
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Shi Q, Chen X, Zhang Z. Decoding Human Biology and Disease Using Single-cell Omics Technologies. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:926-949. [PMID: 37739168 PMCID: PMC10928380 DOI: 10.1016/j.gpb.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/22/2023] [Accepted: 06/08/2023] [Indexed: 09/24/2023]
Abstract
Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.
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Affiliation(s)
- Qiang Shi
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Xueyan Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Changping Laboratory, Beijing 102206, China.
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11
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Xia J, Van Phan H, Vistain L, Chen M, Khan AA, Tay S. Computational prediction of protein interactions on single cells by proximity sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.27.550388. [PMID: 37546806 PMCID: PMC10402170 DOI: 10.1101/2023.07.27.550388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Proximity sequencing (Prox-seq) measures gene expression, protein expression, and protein complexes at the single cell level, using information from dual-antibody binding events and a single cell sequencing readout. Prox-seq provides multi-dimensional phenotyping of single cells and was recently used to track the formation of receptor complexes during inflammatory signaling in macrophages and to discover a new interaction between CD9/CD8 proteins on naïve T cells. The distribution of protein abundance affects identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model for protein dimer formation on single cells and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq single-cell data, which resulted in more accurate and robust quantification of protein complexes. Finally, our model offers a simple way to investigate the behavior of Prox-seq under various biological conditions and guide users toward selecting the best analysis method for their data.
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Affiliation(s)
- Junjie Xia
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA
| | - Hoang Van Phan
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA
- Present address: Division of Infectious Disease, University of California, San Francisco, CA, 94143, USA
| | - Luke Vistain
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA
- Present address: Lymphocyte Biology Section, Laboratory of Immune Systems Biology, NIAID, NIH, Bethesda, MD, 20892, USA
| | - Mengjie Chen
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, 60637, USA
- Department Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Aly A. Khan
- Department of Pathology, The University of Chicago, Chicago, IL, 60637, USA
| | - Savaş Tay
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA
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12
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Rosti RO, Williams ES. Proximity Sequencing Enables Measurement of Protein Complexes in Single Cells. Clin Chem 2023; 69:665-666. [PMID: 37258486 DOI: 10.1093/clinchem/hvad024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 02/10/2023] [Indexed: 06/02/2023]
Affiliation(s)
- R Ozgur Rosti
- Department of Pathology, University of Virginia, Charlottesville, VA, United States
| | - Eli S Williams
- Department of Pathology, University of Virginia, Charlottesville, VA, United States
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13
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Lin X, Huang Q. Editorial: Smart nanomaterials for biosensing and therapy applications. Front Bioeng Biotechnol 2023; 11:1137508. [PMID: 36733966 PMCID: PMC9887176 DOI: 10.3389/fbioe.2023.1137508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 01/06/2023] [Indexed: 01/19/2023] Open
Affiliation(s)
- Xiaofeng Lin
- Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases of Ministry of Education, Key Laboratory of Biomaterials and Biofabrication in Tissue Engineering of Jiangxi Province, Key Laboratory of Biomedical Sensors of Ganzhou, School of Medical and Information Engineering, Science Research Center, Gannan Medical University, Ganzhou, China,*Correspondence: Xiaofeng Lin, ; Qitong Huang,
| | - Qitong Huang
- Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases of Ministry of Education, Key Laboratory of Biomaterials and Biofabrication in Tissue Engineering of Jiangxi Province, Key Laboratory of Biomedical Sensors of Ganzhou, School of Medical and Information Engineering, Science Research Center, Gannan Medical University, Ganzhou, China,Oil-Tea in Medical Healthcare and Functional Product Development Engineering Research Center in Jiangxi, Gannan Medical University, Ganzhou, China,*Correspondence: Xiaofeng Lin, ; Qitong Huang,
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Udani S, Langerman J, Koo D, Baghdasarian S, Cheng B, Kang S, Soemardy C, de Rutte J, Plath K, Carlo DD. Secretion encoded single-cell sequencing (SEC-seq) uncovers gene expression signatures associated with high VEGF-A secretion in mesenchymal stromal cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.07.523110. [PMID: 36711480 PMCID: PMC9881958 DOI: 10.1101/2023.01.07.523110] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Cells secrete numerous bioactive molecules essential for the function of healthy organisms. However, there are no scalable methods to link individual cell secretions to their transcriptional state. By developing and using secretion encoded single-cell sequencing (SEC-seq), which exploits hydrogel nanovials to capture individual cells and their secretions, we simultaneously measured the secretion of vascular endothelial growth factor A (VEGF-A) and the transcriptome for thousands of individual mesenchymal stromal cells (MSCs). We found that VEGF-A secretion is heterogeneous across the cell population and lowly correlated with the VEGFA transcript level. While there is a modest population-wide increase in VEGF-A secretion by hypoxic induction, highest VEGF-A secretion across normoxic and hypoxic culture conditions occurs in a subpopulation of MSCs characterized by a unique gene expression signature. Taken together, SEC-seq enables the identification of specific genes involved in the control of secretory states, which may be exploited for developing means to modulate cellular secretion for disease treatment.
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Affiliation(s)
- Shreya Udani
- Department of Bioengineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Justin Langerman
- Department of Biological Chemistry, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Doyeon Koo
- Department of Bioengineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Sevana Baghdasarian
- Department of Chemical and Biomolecular Engineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Brian Cheng
- Department of Bioengineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Simran Kang
- Department of Bioengineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Citradewi Soemardy
- Department of Bioengineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | | | - Kathrin Plath
- Department of Biological Chemistry, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, University of California - Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Stem Cell Research Center, University of California - Los Angeles, Los Angeles, CA 90095, USA
| | - Dino Di Carlo
- Department of Bioengineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
- Partillion Bioscience, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, University of California - Los Angeles, Los Angeles, CA 90095, USA
- Department of Mechanical and Aerospace Engineering, University of California - Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute (CNSI), University of California - Los Angeles, Los Angeles, CA 90095, USA
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