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Islam MT, Liu Y, Hassan MM, Abraham PE, Merlet J, Townsend A, Jacobson D, Buell CR, Tuskan GA, Yang X. Advances in the Application of Single-Cell Transcriptomics in Plant Systems and Synthetic Biology. Biodes Res 2024; 6:0029. [PMID: 38435807 PMCID: PMC10905259 DOI: 10.34133/bdr.0029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/28/2024] [Indexed: 03/05/2024] Open
Abstract
Plants are complex systems hierarchically organized and composed of various cell types. To understand the molecular underpinnings of complex plant systems, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for revealing high resolution of gene expression patterns at the cellular level and investigating the cell-type heterogeneity. Furthermore, scRNA-seq analysis of plant biosystems has great potential for generating new knowledge to inform plant biosystems design and synthetic biology, which aims to modify plants genetically/epigenetically through genome editing, engineering, or re-writing based on rational design for increasing crop yield and quality, promoting the bioeconomy and enhancing environmental sustainability. In particular, data from scRNA-seq studies can be utilized to facilitate the development of high-precision Build-Design-Test-Learn capabilities for maximizing the targeted performance of engineered plant biosystems while minimizing unintended side effects. To date, scRNA-seq has been demonstrated in a limited number of plant species, including model plants (e.g., Arabidopsis thaliana), agricultural crops (e.g., Oryza sativa), and bioenergy crops (e.g., Populus spp.). It is expected that future technical advancements will reduce the cost of scRNA-seq and consequently accelerate the application of this emerging technology in plants. In this review, we summarize current technical advancements in plant scRNA-seq, including sample preparation, sequencing, and data analysis, to provide guidance on how to choose the appropriate scRNA-seq methods for different types of plant samples. We then highlight various applications of scRNA-seq in both plant systems biology and plant synthetic biology research. Finally, we discuss the challenges and opportunities for the application of scRNA-seq in plants.
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Affiliation(s)
- Md Torikul Islam
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Yang Liu
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Md Mahmudul Hassan
- Department of Genetics and Plant Breeding,
Patuakhali Science and Technology University, Dumki, Patuakhali 8602, Bangladesh
| | - Paul E. Abraham
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Jean Merlet
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research and Graduate Education,
University of Tennessee Knoxville, Knoxville, TN 37996, USA
| | - Alice Townsend
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research and Graduate Education,
University of Tennessee Knoxville, Knoxville, TN 37996, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - C. Robin Buell
- Center for Applied Genetic Technologies,
University of Georgia, Athens, GA 30602, USA
- Department of Crop and Soil Sciences,
University of Georgia, Athens, GA 30602, USA
- Institute of Plant Breeding, Genetics, and Genomics,
University of Georgia, Athens, GA 30602, USA
| | - Gerald A. Tuskan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Xiaohan Yang
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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Zhu KL, Su F, Yang JR, Xiao RW, Wu RY, Cao MY, Ling XL, Zhang T. TP53 to mediate immune escape in tumor microenvironment: an overview of the research progress. Mol Biol Rep 2024; 51:205. [PMID: 38270700 PMCID: PMC10811008 DOI: 10.1007/s11033-023-09097-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 12/04/2023] [Indexed: 01/26/2024]
Abstract
Increasing evidence suggests that key cancer-causing driver genes continue to exert a sustained influence on the tumor microenvironment (TME), highlighting the importance of immunotherapeutic targeting of gene mutations in governing tumor progression. TP53 is a prominent tumor suppressor that encodes the p53 protein, which controls the initiation and progression of different tumor types. Wild-type p53 maintains cell homeostasis and genomic instability through complex pathways, and mutant p53 (Mut p53) promotes tumor occurrence and development by regulating the TME. To date, it has been wildly considered that TP53 is able to mediate tumor immune escape. Herein, we summarized the relationship between TP53 gene and tumors, discussed the mechanism of Mut p53 mediated tumor immune escape, and summarized the progress of applying p53 protein in immunotherapy. This study will provide a basic basis for further exploration of therapeutic strategies targeting p53 protein.
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Affiliation(s)
- Kai-Li Zhu
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
| | - Fei Su
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
| | - Jing-Ru Yang
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
| | - Ruo-Wen Xiao
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
| | - Rui-Yue Wu
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
| | - Meng-Yue Cao
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China
| | - Xiao-Ling Ling
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China.
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China.
| | - Tao Zhang
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China.
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China.
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Jiang X, Dong L, Wang S, Wen Z, Chen M, Xu L, Xiao G, Li Q. Reconstructing Spatial Transcriptomics at the Single-cell Resolution with BayesDeep. bioRxiv 2023:2023.12.07.570715. [PMID: 38106214 PMCID: PMC10723442 DOI: 10.1101/2023.12.07.570715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Spatially resolved transcriptomics (SRT) techniques have revolutionized the characterization of molecular profiles while preserving spatial and morphological context. However, most next-generation sequencing-based SRT techniques are limited to measuring gene expression in a confined array of spots, capturing only a fraction of the spatial domain. Typically, these spots encompass gene expression from a few to hundreds of cells, underscoring a critical need for more detailed, single-cell resolution SRT data to enhance our understanding of biological functions within the tissue context. Addressing this challenge, we introduce BayesDeep, a novel Bayesian hierarchical model that leverages cellular morphological data from histology images, commonly paired with SRT data, to reconstruct SRT data at the single-cell resolution. BayesDeep effectively model count data from SRT studies via a negative binomial regression model. This model incorporates explanatory variables such as cell types and nuclei-shape information for each cell extracted from the paired histology image. A feature selection scheme is integrated to examine the association between the morphological and molecular profiles, thereby improving the model robustness. We applied BayesDeep to two real SRT datasets, successfully demonstrating its capability to reconstruct SRT data at the single-cell resolution. This advancement not only yields new biological insights but also significantly enhances various downstream analyses, such as pseudotime and cell-cell communication.
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Affiliation(s)
- Xi Jiang
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
- Department of Statistics and Data Science, Southern Methodist University, Dallas, Texas, U.S.A
| | - Lei Dong
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
| | - Shidan Wang
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
| | - Zhuoyu Wen
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
| | - Mingyi Chen
- Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
| | - Lin Xu
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
| | - Guanghua Xiao
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A
| | - Qiwei Li
- Department of Mathematical Sciences, The University of Texas at Dallas, Richardson, Texas, U.S.A
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Khodayari S, Khodayari H, Saeedi E, Mahmoodzadeh H, Sadrkhah A, Nayernia K. Single-Cell Transcriptomics for Unlocking Personalized Cancer Immunotherapy: Toward Targeting the Origin of Tumor Development Immunogenicity. Cancers (Basel) 2023; 15:3615. [PMID: 37509276 PMCID: PMC10377122 DOI: 10.3390/cancers15143615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/11/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023] Open
Abstract
Cancer immunotherapy is a promising approach for treating malignancies through the activation of anti-tumor immunity. However, the effectiveness and safety of immunotherapy can be limited by tumor complexity and heterogeneity, caused by the diverse molecular and cellular features of tumors and their microenvironments. Undifferentiated tumor cell niches, which we refer to as the "Origin of Tumor Development" (OTD) cellular population, are believed to be the source of these variations and cellular heterogeneity. From our perspective, the existence of distinct features within the OTD is expected to play a significant role in shaping the unique tumor characteristics observed in each patient. Single-cell transcriptomics is a high-resolution and high-throughput technique that provides insights into the genetic signatures of individual tumor cells, revealing mechanisms of tumor development, progression, and immune evasion. In this review, we explain how single-cell transcriptomics can be used to develop personalized cancer immunotherapy by identifying potential biomarkers and targets specific to each patient, such as immune checkpoint and tumor-infiltrating lymphocyte function, for targeting the OTD. Furthermore, in addition to offering a possible workflow, we discuss the future directions of, and perspectives on, single-cell transcriptomics, such as the development of powerful analytical tools and databases, that will aid in unlocking personalized cancer immunotherapy through the targeting of the patient's cellular OTD.
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Affiliation(s)
- Saeed Khodayari
- International Center for Personalized Medicine (P7MEDICINE), Luise-Rainer-Str. 6-12, 40235 Düsseldorf, Germany
| | - Hamid Khodayari
- International Center for Personalized Medicine (P7MEDICINE), Luise-Rainer-Str. 6-12, 40235 Düsseldorf, Germany
| | - Elnaz Saeedi
- Oxford Clinical Trials Research Unit, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford OX3 7LD, UK
| | - Habibollah Mahmoodzadeh
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran 1819613844, Iran
| | | | - Karim Nayernia
- International Center for Personalized Medicine (P7MEDICINE), Luise-Rainer-Str. 6-12, 40235 Düsseldorf, Germany
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