1
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Zhou Z, Zhang R, Zhou A, Lv J, Chen S, Zou H, Zhang G, Lin T, Wang Z, Zhang Y, Weng S, Han X, Liu Z. Proteomics appending a complementary dimension to precision oncotherapy. Comput Struct Biotechnol J 2024; 23:1725-1739. [PMID: 38689716 PMCID: PMC11058087 DOI: 10.1016/j.csbj.2024.04.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/11/2024] [Accepted: 04/17/2024] [Indexed: 05/02/2024] Open
Abstract
Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.
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Affiliation(s)
- Zhaokai Zhou
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
| | - Ruiqi Zhang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Aoyang Zhou
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Jinxiang Lv
- Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Shuang Chen
- Center of Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Haijiao Zou
- Center of Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ge Zhang
- Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ting Lin
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Zhan Wang
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
| | - Yuyuan Zhang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Siyuan Weng
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Xinwei Han
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
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2
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Rider MH, Vertommen D, Johanns M. How mass spectrometry can be exploited to study AMPK. Essays Biochem 2024:EBC20240009. [PMID: 39056150 DOI: 10.1042/ebc20240009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 07/12/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024]
Abstract
AMP-activated protein kinase (AMPK) is a key regulator of metabolism and a recognised target for the treatment of metabolic diseases such as Type 2 diabetes (T2D). Here, we review how mass spectrometry (MS) can be used to study short-term control by AMPK via protein phosphorylation and long-term control due to changes in protein expression. We discuss how MS can quantify AMPK subunit levels in tissues from different species. We propose hydrogen-deuterium exchange (HDX)-MS to investigate molecular mechanisms of AMPK activation and thermoproteomic profiling (TPP) to assess off-target effects of pharmacological AMPK activators/inhibitors. Lastly, because large MS data sets are generated, we consider different approaches that can be used for their interpretation.
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Affiliation(s)
- Mark H Rider
- Protein Phosphorylation (PHOS) laboratory, Université catholique de Louvain and de Duve Institute, Avenue Hippocrate 75, B-1200 Brussels, Belgium
| | - Didier Vertommen
- Protein Phosphorylation (PHOS) laboratory, Université catholique de Louvain and de Duve Institute, Avenue Hippocrate 75, B-1200 Brussels, Belgium
| | - Manuel Johanns
- Protein Phosphorylation (PHOS) laboratory, Université catholique de Louvain and de Duve Institute, Avenue Hippocrate 75, B-1200 Brussels, Belgium
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3
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Juvenal G, Higa GSV, Bonfim Marques L, Tessari Zampieri T, Costa Viana FJ, Britto LR, Tang Y, Illes P, di Virgilio F, Ulrich H, de Pasquale R. Regulation of GABAergic neurotransmission by purinergic receptors in brain physiology and disease. Purinergic Signal 2024:10.1007/s11302-024-10034-x. [PMID: 39046648 DOI: 10.1007/s11302-024-10034-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/19/2024] [Indexed: 07/25/2024] Open
Abstract
Purinergic receptors regulate the processing of neural information in the hippocampus and cerebral cortex, structures related to cognitive functions. These receptors are activated when astrocytic and neuronal populations release adenosine triphosphate (ATP) in an autocrine and paracrine manner, following sustained patterns of neuronal activity. The modulation by these receptors of GABAergic transmission has only recently been studied. Through their ramifications, astrocytes and GABAergic interneurons reach large groups of excitatory pyramidal neurons. Their inhibitory effect establishes different synchronization patterns that determine gamma frequency rhythms, which characterize neural activities related to cognitive processes. During early life, GABAergic-mediated synchronization of excitatory signals directs the experience-driven maturation of cognitive development, and dysfunctions concerning this process have been associated with neurological and neuropsychiatric diseases. Purinergic receptors timely modulate GABAergic control over ongoing neural activity and deeply affect neural processing in the hippocampal and neocortical circuitry. Stimulation of A2 receptors increases GABA release from presynaptic terminals, leading to a considerable reduction in neuronal firing of pyramidal neurons. A1 receptors inhibit GABAergic activity but only act in the early postnatal period when GABA produces excitatory signals. P2X and P2Y receptors expressed in pyramidal neurons reduce the inhibitory tone by blocking GABAA receptors. Finally, P2Y receptor activation elicits depolarization of GABAergic neurons and increases GABA release, thus favoring the emergence of gamma oscillations. The present review provides an overall picture of purinergic influence on GABAergic transmission and its consequences on neural processing, extending the discussion to receptor subtypes and their involvement in the onset of brain disorders, including epilepsy and Alzheimer's disease.
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Affiliation(s)
- Guilherme Juvenal
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP, Brazil
| | - Guilherme Shigueto Vilar Higa
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP, Brazil
- Department of Biophysics and Physiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Lucas Bonfim Marques
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP, Brazil
| | - Thais Tessari Zampieri
- Department of Biophysics and Physiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Felipe José Costa Viana
- Department of Biophysics and Physiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Luiz R Britto
- Department of Biophysics and Physiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Yong Tang
- International Joint Research Centre On Purinergic Signalling, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China
- School of Health and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China
| | - Peter Illes
- International Joint Research Centre On Purinergic Signalling, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China
- School of Health and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China
- Rudolf Boehm Institute for Pharmacology and Toxicology, University of Leipzig, 04107, Leipzig, Germany
| | | | - Henning Ulrich
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP, Brazil.
- International Joint Research Centre On Purinergic Signalling, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China.
| | - Roberto de Pasquale
- Department of Biophysics and Physiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil.
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4
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Wang X, Ding L, Zhao Y, Gao X. 6-Plex Tandem Phosphorus Tags (TPT) for Accurate Quantitative Proteomics. Anal Chem 2024; 96:11644-11650. [PMID: 38991974 DOI: 10.1021/acs.analchem.4c01865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Isobaric chemical labeling is a widely used strategy for high-throughput quantitative proteomics based on mass spectrometry. However, commercially available reagents have high costs in applications as well as the sensitivity limitations for detection of the trace protein samples. Previously, we developed a 2-plex isobaric labeling strategy based on phosphorus chemistry for ultrasensitive proteome quantification with high accuracy. In this work, 6-plex tandem phosphorus tags (TPT) were developed with 3-fold increase in the multiplexing quantitative capacity compared to the 2-plex isobaric phosphorus reagents introduced previously. High isotope enrichment of 18O labeling was incorporated into the phosphoryl group with three exchangeable oxygen atoms by using commercially available H218O. The combinational incorporations of 18O atom in reporter ions and balance group set up the low-cost foundation for development of multiplex TPT reagents. The novel 6-plex TPT reagents could produce phosphoramidate as unique reporter ions with approximately 1 Da mass difference and thus enable 6-plex quantitative analysis in high-resolution ESI-MS/MS analysis. Using HeLa cell tryptic peptides, we concluded that 6-plex TPT reagents could facilitate large-scale accurate quantitative proteomics with very high labeling efficiency.
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Affiliation(s)
- Xiaoyu Wang
- Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005, China
- State Key Laboratory of Cellular Stress Biology and Fujian Provincial Key Laboratory of Innovative Drug Target Research, School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian 361102, China
| | - Lianshuai Ding
- State Key Laboratory of Cellular Stress Biology and Fujian Provincial Key Laboratory of Innovative Drug Target Research, School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian 361102, China
- School of life Sciences, Xiamen University, Xiamen, Fujian 361102, China
| | - Yufen Zhao
- Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005, China
| | - Xiang Gao
- State Key Laboratory of Cellular Stress Biology and Fujian Provincial Key Laboratory of Innovative Drug Target Research, School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian 361102, China
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen, Fujian 361102, China
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5
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Chen J, Larsson L, Swarbrick A, Lundeberg J. Spatial landscapes of cancers: insights and opportunities. Nat Rev Clin Oncol 2024:10.1038/s41571-024-00926-7. [PMID: 39043872 DOI: 10.1038/s41571-024-00926-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2024] [Indexed: 07/25/2024]
Abstract
Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.
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Affiliation(s)
- Julia Chen
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia
- Department of Medical Oncology, St George Hospital, Sydney, New South Wales, Australia
| | - Ludvig Larsson
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden.
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6
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Li Y, Zeng GH, Liang YJ, Yang HR, Zhu XL, Zhai YJ, Duan LX, Xu YY. Improving quantitative prediction of protein subcellular locations in fluorescence images through deep generative models. Comput Biol Med 2024; 179:108913. [PMID: 39047508 DOI: 10.1016/j.compbiomed.2024.108913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/21/2024] [Accepted: 07/15/2024] [Indexed: 07/27/2024]
Abstract
Machine learning has been employed in recognizing protein localization at the subcellular level, which highly facilitates the protein function studies, especially for those multi-label proteins that localize in more than one organelle. However, existing works mostly study the qualitative classification of protein subcellular locations, ignoring fraction of one multi-label protein in different locations. Actually, about 50 % proteins are multi-label proteins, and the ignorance of quantitative information highly restricts the understanding of their spatial distribution and functional mechanism. One reason of the lack of quantitative study is the insufficiency of quantitative annotations. To address the data shortage problem, here we proposed a generative model, PLocGAN, which could generate cell images with conditional quantitative annotation of the fluorescence distribution. The model was a conditional generative adversarial network, in which the condition learning utilized partial label learning to overcome the lack of training labels and allowed training with only qualitative labels. Meanwhile, it used contrastive learning to enhance diversity of the generated images. We assessed the PLocGAN on four pixel-fused synthetic datasets and one real dataset, and demonstrated that the model could generate images with good fidelity and diversity, outperforming existing state-of-the-art generative methods. To verify the utility of PLocGAN in the quantitative prediction of protein subcellular locations, we replaced the training images with generated quantitative images and built prediction models, and found that they had a boosting effect on the quantitative estimation. This work demonstrates the effectiveness of deep generative models in bioimage analysis, and provides a new solution for quantitative subcellular proteomics.
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Affiliation(s)
- Yu Li
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510515, China
| | - Guo-Hua Zeng
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510515, China
| | - Yong-Jia Liang
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510515, China
| | - Hong-Rui Yang
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510515, China
| | - Xi-Liang Zhu
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510515, China
| | - Yu-Jia Zhai
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524000, China
| | - Li-Xia Duan
- Guangzhou Red Cross Hospital, Medical College, Jinan University, Guangzhou, 510220, China
| | - Ying-Ying Xu
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510515, China.
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7
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Yin Z, Huang W, Li K, Fernie AR, Yan S. Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 38990529 DOI: 10.1111/tpj.16924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/24/2024] [Accepted: 07/01/2024] [Indexed: 07/12/2024]
Abstract
Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.
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Affiliation(s)
- Zhibin Yin
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
- Institute of Advanced Science Facilities, Shenzhen, 518107, Guangdong, China
| | - Wenjie Huang
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
| | - Kun Li
- Guangdong Key Laboratory of Crop Genetic Improvement, Crop Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
| | - Shijuan Yan
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
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8
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Nitz AA, Giraldez Chavez JH, Eliason ZG, Payne SH. Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses. J Proteome Res 2024. [PMID: 38981598 DOI: 10.1021/acs.jproteome.4c00091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.
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Affiliation(s)
- Alyssa A Nitz
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| | | | - Zachary G Eliason
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
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9
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Chen S, Zhu B, Huang S, Hickey JW, Lin KZ, Snyder M, Greenleaf WJ, Nolan GP, Zhang NR, Ma Z. Integration of spatial and single-cell data across modalities with weakly linked features. Nat Biotechnol 2024; 42:1096-1106. [PMID: 37679544 DOI: 10.1038/s41587-023-01935-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/02/2023] [Indexed: 09/09/2023]
Abstract
Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.
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Affiliation(s)
- Shuxiao Chen
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Bokai Zhu
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Sijia Huang
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - John W Hickey
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Kevin Z Lin
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Michael Snyder
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Garry P Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA.
- Department of Pathology, Stanford University, Stanford, CA, USA.
| | - Nancy R Zhang
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
| | - Zongming Ma
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
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10
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Zhang S, Tang Q, Zhang X, Chen X. Proximitomics by Reactive Species. ACS CENTRAL SCIENCE 2024; 10:1135-1147. [PMID: 38947200 PMCID: PMC11212136 DOI: 10.1021/acscentsci.4c00373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 05/25/2024] [Accepted: 05/29/2024] [Indexed: 07/02/2024]
Abstract
The proximitome is defined as the entire collection of biomolecules spatially in the proximity of a biomolecule of interest. More broadly, the concept of the proximitome can be extended to the totality of cells proximal to a specific cell type. Since the spatial organization of biomolecules and cells is essential for almost all biological processes, proximitomics has recently emerged as an active area of scientific research. One of the growing strategies for proximitomics leverages reactive species-which are generated in situ and spatially confined, to chemically tag and capture proximal biomolecules and cells for systematic analysis. In this Outlook, we summarize different types of reactive species that have been exploited for proximitomics and discuss their pros and cons for specific applications. In addition, we discuss the current challenges and future directions of this exciting field.
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Affiliation(s)
- Shaoran Zhang
- College
of Chemistry and Molecular Engineering, Peking University, Beijing 100871, People’s
Republic of China
- Peking-Tsinghua
Center for Life Sciences, Peking University, Beijing 100871, People’s Republic of China
| | - Qi Tang
- College
of Chemistry and Molecular Engineering, Peking University, Beijing 100871, People’s
Republic of China
- Beijing
National Laboratory for Molecular Sciences, Peking University, Beijing 100871, People’s
Republic of China
| | - Xu Zhang
- College
of Chemistry and Molecular Engineering, Peking University, Beijing 100871, People’s
Republic of China
- Peking-Tsinghua
Center for Life Sciences, Peking University, Beijing 100871, People’s Republic of China
| | - Xing Chen
- College
of Chemistry and Molecular Engineering, Peking University, Beijing 100871, People’s
Republic of China
- Peking-Tsinghua
Center for Life Sciences, Peking University, Beijing 100871, People’s Republic of China
- Beijing
National Laboratory for Molecular Sciences, Peking University, Beijing 100871, People’s
Republic of China
- Synthetic
and Functional Biomolecules Center, Peking
University, Beijing 100871, People’s
Republic of China
- Key
Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry
of Education, Peking University, Beijing 100871, People’s Republic of China
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11
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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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12
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Zuo C, Xia J, Chen L. Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning. Nat Commun 2024; 15:5057. [PMID: 38871687 DOI: 10.1038/s41467-024-49171-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 05/22/2024] [Indexed: 06/15/2024] Open
Abstract
Spatially resolved transcriptomics (SRT) has enabled precise dissection of tumor-microenvironment (TME) by analyzing its intracellular molecular networks and intercellular cell-cell communication (CCC). However, lacking computational exploration of complicated relations between cells, genes, and histological regions, severely limits the ability to interpret the complex structure of TME. Here, we introduce stKeep, a heterogeneous graph (HG) learning method that integrates multimodality and gene-gene interactions, in unraveling TME from SRT data. stKeep leverages HG to learn both cell-modules and gene-modules by incorporating features of diverse nodes including genes, cells, and histological regions, allows for identifying finer cell-states within TME and cell-state-specific gene-gene relations, respectively. Furthermore, stKeep employs HG to infer CCC for each cell, while ensuring that learned CCC patterns are comparable across different cell-states through contrastive learning. In various cancer samples, stKeep outperforms other tools in dissecting TME such as detecting bi-potent basal populations, neoplastic myoepithelial cells, and metastatic cells distributed within the tumor or leading-edge regions. Notably, stKeep identifies key transcription factors, ligands, and receptors relevant to disease progression, which are further validated by the functional and survival analysis of independent clinical data, thereby highlighting its clinical prognostic and immunotherapy applications.
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Affiliation(s)
- Chunman Zuo
- Institute of Artificial Intelligence, Shanghai Engineering Research Center of Industrial Big Data and Intelligent System, Donghua University, Shanghai, 201620, China.
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130022, China.
| | - Junjie Xia
- Institute of Artificial Intelligence, Shanghai Engineering Research Center of Industrial Big Data and Intelligent System, Donghua University, Shanghai, 201620, China
- Department of Applied Mathematics, Donghua University, Shanghai, 201620, China
| | - Luonan Chen
- Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, 200031, China.
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, 310024, China.
- West China Biomedical Big Data Center, Med-X center for informatics, West China Hospital, Sichuan University, Chengdu, 610041, China.
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13
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Adnane M, de Almeida AM, Chapwanya A. Unveiling the power of proteomics in advancing tropical animal health and production. Trop Anim Health Prod 2024; 56:182. [PMID: 38825622 DOI: 10.1007/s11250-024-04037-4] [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: 05/13/2024] [Accepted: 05/20/2024] [Indexed: 06/04/2024]
Abstract
Proteomics, the large-scale study of proteins in biological systems has emerged as a pivotal tool in the field of animal and veterinary sciences, mainly for investigating local and rustic breeds. Proteomics provides valuable insights into biological processes underlying animal growth, reproduction, health, and disease. In this review, we highlight the key proteomics technologies, methodologies, and their applications in domestic animals, particularly in the tropical context. We also discuss advances in proteomics research, including integration of multi-omics data, single-cell proteomics, and proteogenomics, all of which are promising for improving animal health, adaptation, welfare, and productivity. However, proteomics research in domestic animals faces challenges, such as sample preparation variation, data quality control, privacy and ethical considerations relating to animal welfare. We also provide recommendations for overcoming these challenges, emphasizing the importance of following best practices in sample preparation, data quality control, and ethical compliance. We therefore aim for this review to harness the full potential of proteomics in advancing our understanding of animal biology and ultimately improve animal health and productivity in local breeds of diverse animal species in a tropical context.
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Affiliation(s)
- Mounir Adnane
- Department of Biomedicine, Institute of Veterinary Sciences, University of Tiaret, Tiaret, 14000, Algeria.
| | - André M de Almeida
- LEAF-Linking Landscape, Environment, Agriculture and Food Research Center, Associate Laboratory TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa, 1349-017, Portugal
| | - Aspinas Chapwanya
- Department of Clinical Sciences, Ross University School of Veterinary Medicine, Basseterre, 00265, Saint Kitts and Nevis
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14
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Chamrád I, Simerský R, Lenobel R, Novák O. Exploring affinity chromatography in proteomics: A comprehensive review. Anal Chim Acta 2024; 1306:342513. [PMID: 38692783 DOI: 10.1016/j.aca.2024.342513] [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: 12/12/2023] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 05/03/2024]
Abstract
Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.
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Affiliation(s)
- Ivo Chamrád
- Laboratory of Growth Regulators, Faculty of Science, Palacký University and Institute of Experimental Botany of the Czech Academy of Sciences, Šlechtitelů 241/27, CZ-77900, Olomouc, Holice, Czech Republic.
| | - Radim Simerský
- Department of Chemical Biology, Faculty of Science, Palacký University, Šlechtitelů 241/27, CZ-77900, Olomouc, Holice, Czech Republic
| | - René Lenobel
- Laboratory of Growth Regulators, Faculty of Science, Palacký University and Institute of Experimental Botany of the Czech Academy of Sciences, Šlechtitelů 241/27, CZ-77900, Olomouc, Holice, Czech Republic
| | - Ondřej Novák
- Laboratory of Growth Regulators, Faculty of Science, Palacký University and Institute of Experimental Botany of the Czech Academy of Sciences, Šlechtitelů 241/27, CZ-77900, Olomouc, Holice, Czech Republic
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15
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Wang H, Sun F. UNC-45A: A potential therapeutic target for malignant tumors. Heliyon 2024; 10:e31276. [PMID: 38803956 PMCID: PMC11128996 DOI: 10.1016/j.heliyon.2024.e31276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 12/31/2023] [Accepted: 05/14/2024] [Indexed: 05/29/2024] Open
Abstract
Uncoordinated mutant number-45 myosin chaperone A (UNC-45A), a protein highly conserved throughout evolution, is ubiquitously expressed in somatic cells. It is correlated with tumorigenesis, proliferation, metastasis, and invasion of multiple malignant tumors. The current understanding of the role of UNC-45A in tumor progression is mainly related to the regulation of non-muscle myosin II (NM-II). However, many studies have suggested that the mechanisms by which UNC-45A is involved in tumor progression are far greater than those of NM-II regulation. UNC-45A can also promote tumor cell proliferation by regulating checkpoint kinase 1 (ChK1) phosphorylation or the transcriptional activity of nuclear receptors, and induces chemoresistance to paclitaxel in tumor cells by destabilizing microtubule activity. In this review, we discuss the recent advances illuminating the role of UNC-45A in tumor progression. We also put forward therapeutic strategies targeting UNC-45A, in the hope of paving the way the development of UNC-45A-targeted therapies for patients with malignant tumors.
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Affiliation(s)
- Hong Wang
- School of Nursing, Binzhou Medical University, Yantai, 264003, PR China
| | - Fude Sun
- Department of Anesthesiology, Yantai Penglai Traditional Chinese Medicine Hospital, Yantai, 265699, PR China
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16
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Chu LX, Wang WJ, Gu XP, Wu P, Gao C, Zhang Q, Wu J, Jiang DW, Huang JQ, Ying XW, Shen JM, Jiang Y, Luo LH, Xu JP, Ying YB, Chen HM, Fang A, Feng ZY, An SH, Li XK, Wang ZG. Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine. Mil Med Res 2024; 11:31. [PMID: 38797843 PMCID: PMC11129507 DOI: 10.1186/s40779-024-00537-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 05/07/2024] [Indexed: 05/29/2024] Open
Abstract
Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.
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Affiliation(s)
- Liu-Xi Chu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Wen-Jia Wang
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Xin-Pei Gu
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Screening, Southern Medical University, Guangzhou, 510515, China
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China
| | - Ping Wu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Chen Gao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Quan Zhang
- Integrative Muscle Biology Laboratory, Division of Regenerative and Rehabilitative Sciences, University of Tennessee Health Science Center, Memphis, TN, 38163, United States
| | - Jia Wu
- Key Laboratory for Laboratory Medicine, Ministry of Education, Zhejiang Provincial Key Laboratory of Medical Genetics, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Da-Wei Jiang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jun-Qing Huang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China
| | - Xin-Wang Ying
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jia-Men Shen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi Jiang
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Li-Hua Luo
- School and Hospital of Stomatology, Wenzhou Medical University, Wenzhou, 324025, Zhejiang, China
| | - Jun-Peng Xu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi-Bo Ying
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Hao-Man Chen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Ao Fang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Zun-Yong Feng
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore, 119074, Singapore.
- Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117599, Singapore.
- Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR), Singapore, 138673, Singapore.
| | - Shu-Hong An
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China.
| | - Xiao-Kun Li
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
| | - Zhou-Guang Wang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China.
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China.
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17
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Liu H, Deol H, Raeisbahrami A, Askari H, Wight CD, Lynch VM, Anslyn EV. A Method for Rigorously Selective Capture and Simultaneous Fluorescent Labeling of N-Terminal Glycine Peptides. J Am Chem Soc 2024; 146:13727-13732. [PMID: 38728661 DOI: 10.1021/jacs.4c04141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Although chemical methods for the selective derivatization of amino acid (AA) side chains in peptides and proteins are available, selective N-terminal labeling is challenging, especially for glycine, which has no side chain at the α-carbon position. We report here a double activation at glycine's α-methylene group that allows this AA to be differentiated from the other 19 AAs. A condensation reaction of dibenzoylmethane with glycine results in the formation of an imine, and subsequent tautomerization is followed by intramolecular cyclization, leading to the formation of a fluorescent pyrrole ring. Additionally, the approach exhibits compatibility with AAs possessing reactive side chains. Further, the method allows for selective pull-down assays of N-terminal glycine peptides from mixtures without prior knowledge of the N-terminal peptide distribution.
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Affiliation(s)
- Hongxu Liu
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Harnimarta Deol
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Ava Raeisbahrami
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Hadis Askari
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Christopher D Wight
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Vincent M Lynch
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Eric V Anslyn
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
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18
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Peters-Clarke TM, Coon JJ, Riley NM. Instrumentation at the Leading Edge of Proteomics. Anal Chem 2024; 96:7976-8010. [PMID: 38738990 DOI: 10.1021/acs.analchem.3c04497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Nicholas M Riley
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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19
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Liu X, Abad L, Chatterjee L, Cristea IM, Varjosalo M. Mapping protein-protein interactions by mass spectrometry. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38742660 DOI: 10.1002/mas.21887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 04/22/2024] [Indexed: 05/16/2024]
Abstract
Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.
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Affiliation(s)
- Xiaonan Liu
- Department of Physiology, Faculty of Medical Sciences in Katowice, Medical University of Silesia in Katowice, Katowice, Poland
- Institute of Biotechnology, HiLIFE Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
| | - Lawrence Abad
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Lopamudra Chatterjee
- Institute of Biotechnology, HiLIFE Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Ileana M Cristea
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Markku Varjosalo
- Institute of Biotechnology, HiLIFE Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
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20
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Bergeron JJM. Proteomics Impact on Cell Biology to Resolve Cell Structure and Function. Mol Cell Proteomics 2024; 23:100758. [PMID: 38574860 PMCID: PMC11070594 DOI: 10.1016/j.mcpro.2024.100758] [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: 02/07/2024] [Revised: 03/23/2024] [Accepted: 03/26/2024] [Indexed: 04/06/2024] Open
Abstract
The acceleration of advances in proteomics has enabled integration with imaging at the EM and light microscopy levels, cryo-EM of protein structures, and artificial intelligence with proteins comprehensively and accurately resolved for cell structures at nanometer to subnanometer resolution. Proteomics continues to outpace experimentally based structural imaging, but their ultimate integration is a path toward the goal of a compendium of all proteins to understand mechanistically cell structure and function.
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Affiliation(s)
- John J M Bergeron
- Department of Medicine, McGill University Hospital Research Institute, Montreal, Quebec, Canada.
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21
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Liang Z, Zhuang H, Cao X, Ma G, Shen L. Subcellular proteomics insights into Alzheimer's disease development. Proteomics Clin Appl 2024; 18:e2200112. [PMID: 37650321 DOI: 10.1002/prca.202200112] [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: 04/30/2023] [Revised: 07/27/2023] [Accepted: 08/12/2023] [Indexed: 09/01/2023]
Abstract
Alzheimer's disease (AD), one of the most common dementias, is a neurodegenerative disease characterized by cognitive impairment and decreased judgment function. The expected number of AD patient is increasing in the context of the world's advancing medical care and increasing human life expectancy. Since current molecular mechanism studies on AD pathogenesis are incomplete, there is no specific and effective therapeutic agent. Mass spectrometry (MS)-based unbiased proteomics studies provide an effective and comprehensive approach. Many advances have been made in the study of the mechanism, diagnostic markers, and drug targets of AD using proteomics. This paper focus on subcellular level studies, reviews studies using proteomics to study AD-associated mitochondrial dysfunction, synaptic, and myelin damage, the protein composition of amyloid plaques (APs) and neurofibrillary tangles (NFTs), changes in tissue extracellular vehicles (EVs) and exosome proteome, and the protein changes in ribosomes and lysosomes. The methods of sample separation and preparation and proteomic analysis as well as the main findings of these studies are involved. The results of these proteomics studies provide insights into the pathogenesis of AD and provide theoretical resource and direction for future research in AD, helping to identify new biomarkers and drugs targets for AD.
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Affiliation(s)
- Zhiyuan Liang
- College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, P. R. China
| | - Hongbin Zhuang
- College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, P. R. China
| | - Xueshan Cao
- College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, P. R. China
- College of Physics and Optoelectronics Engineering, Shenzhen University, Shenzhen, P. R. China
| | - Guanwei Ma
- School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, P. R. China
| | - Liming Shen
- College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, P. R. China
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, P. R. China
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22
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Babur O, Emili A, Aslan JE. Platelet proteomics emerges from the womb: mass spectrometry insights into neonatal platelet biology. J Thromb Haemost 2024; 22:1313-1315. [PMID: 38670684 DOI: 10.1016/j.jtha.2024.01.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 01/27/2024] [Indexed: 04/28/2024]
Affiliation(s)
- Ozgun Babur
- Department of Computer Science, University of Massachusetts, Boston, Massachusetts, USA
| | - Andrew Emili
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Joseph E Aslan
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, USA; Department of Chemical Physiology and Biochemistry, Oregon Health & Science University, Portland, Oregon, USA.
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23
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Lai D, Zhang K, He Y, Fan Y, Li W, Shi Y, Gao Y, Huang X, He J, Zhao H, Lu X, Xiao Y, Cheng J, Ruan J, Georgiev MI, Fernie AR, Zhou M. Multi-omics identification of a key glycosyl hydrolase gene FtGH1 involved in rutin hydrolysis in Tartary buckwheat (Fagopyrum tataricum). PLANT BIOTECHNOLOGY JOURNAL 2024; 22:1206-1223. [PMID: 38062934 PMCID: PMC11022807 DOI: 10.1111/pbi.14259] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/16/2023] [Accepted: 11/20/2023] [Indexed: 04/18/2024]
Abstract
Rutin, a flavonoid rich in buckwheat, is important for human health and plant resistance to external stresses. The hydrolysis of rutin to quercetin underlies the bitter taste of Tartary buckwheat. In order to identify rutin hydrolysis genes, a 200 genotypes mini-core Tartary buckwheat germplasm resource was re-sequenced with 30-fold coverage depth. By combining the content of the intermediate metabolites of rutin metabolism with genome resequencing data, metabolite genome-wide association analyses (GWAS) eventually identified a glycosyl hydrolase gene FtGH1, which could hydrolyse rutin to quercetin. This function was validated both in Tartary buckwheat overexpression hairy roots and in vitro enzyme activity assays. Mutation of the two key active sites, which were determined by molecular docking and experimentally verified via overexpression in hairy roots and transient expression in tobacco leaves, exhibited abnormal subcellular localization, suggesting functional changes. Sequence analysis revealed that mutation of the FtGH1 promoter in accessions of two haplotypes might be necessary for enzymatic activity. Co-expression analysis and GWAS revealed that FtbHLH165 not only repressed FtGH1 expression, but also increased seed length. This work reveals a potential mechanism behind rutin metabolism, which should provide both theoretical support in the study of flavonoid metabolism and in the molecular breeding of Tartary buckwheat.
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Affiliation(s)
- Dili Lai
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
- College of AgricultureGuizhou UniversityGuiyangChina
| | - Kaixuan Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yuqi He
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yu Fan
- School of Food and Biological EngineeringChengdu UniversityChengduChina
| | - Wei Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yaliang Shi
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yuanfen Gao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xu Huang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Jiayue He
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Hui Zhao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xiang Lu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yawen Xiao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | | | - Jingjun Ruan
- College of AgricultureGuizhou UniversityGuiyangChina
| | - Milen I. Georgiev
- Laboratory of Metabolomics, Institute of MicrobiologyBulgarian Academy of SciencesPlovdivBulgaria
- Center of Plant Systems Biology and BiotechnologyPlovdivBulgaria
| | - Alisdair R. Fernie
- Center of Plant Systems Biology and BiotechnologyPlovdivBulgaria
- Department of Molecular PhysiologyMax‐Planck‐Institute of Molecular Plant PhysiologyPotsdam‐GolmGermany
| | - Meiliang Zhou
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
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24
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Reicher A, Reiniš J, Ciobanu M, Růžička P, Malik M, Siklos M, Kartysh V, Tomek T, Koren A, Rendeiro AF, Kubicek S. Pooled multicolour tagging for visualizing subcellular protein dynamics. Nat Cell Biol 2024; 26:745-756. [PMID: 38641660 PMCID: PMC11098740 DOI: 10.1038/s41556-024-01407-w] [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: 07/25/2023] [Accepted: 03/18/2024] [Indexed: 04/21/2024]
Abstract
Imaging-based methods are widely used for studying the subcellular localization of proteins in living cells. While routine for individual proteins, global monitoring of protein dynamics following perturbation typically relies on arrayed panels of fluorescently tagged cell lines, limiting throughput and scalability. Here, we describe a strategy that combines high-throughput microscopy, computer vision and machine learning to detect perturbation-induced changes in multicolour tagged visual proteomics cell (vpCell) pools. We use genome-wide and cancer-focused intron-targeting sgRNA libraries to generate vpCell pools and a large, arrayed collection of clones each expressing two different endogenously tagged fluorescent proteins. Individual clones can be identified in vpCell pools by image analysis using the localization patterns and expression level of the tagged proteins as visual barcodes, enabling simultaneous live-cell monitoring of large sets of proteins. To demonstrate broad applicability and scale, we test the effects of antiproliferative compounds on a pool with cancer-related proteins, on which we identify widespread protein localization changes and new inhibitors of the nuclear import/export machinery. The time-resolved characterization of changes in subcellular localization and abundance of proteins upon perturbation in a pooled format highlights the power of the vpCell approach for drug discovery and mechanism-of-action studies.
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Affiliation(s)
- Andreas Reicher
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Jiří Reiniš
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Maria Ciobanu
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Pavel Růžička
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Monika Malik
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Marton Siklos
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Victoria Kartysh
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Tatjana Tomek
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Anna Koren
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - André F Rendeiro
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Stefan Kubicek
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
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25
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Zhu Y, Akkaya KC, Ruta J, Yokoyama N, Wang C, Ruwolt M, Lima DB, Lehmann M, Liu F. Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies. Nat Commun 2024; 15:3290. [PMID: 38632225 PMCID: PMC11024108 DOI: 10.1038/s41467-024-47569-x] [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: 03/04/2023] [Accepted: 04/05/2024] [Indexed: 04/19/2024] Open
Abstract
The functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome. Biochemical and imaging-based follow-up studies confirm that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. We also validate the CLASP concept in synaptic vesicles, demonstrating its applicability to different sub-cellular compartments. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, and establishes a method for concomitant profiling of sub-organelle and membrane proteomes.
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Affiliation(s)
- Ying Zhu
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Kerem Can Akkaya
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
- Department of Molecular Physiology and Cell Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Julia Ruta
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Nanako Yokoyama
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Cong Wang
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Max Ruwolt
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Diogo Borges Lima
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Martin Lehmann
- Department of Molecular Physiology and Cell Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany
| | - Fan Liu
- Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10 13125, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Charitépl. 1, 10117, Berlin, Germany.
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26
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Sun C. Single-Molecule-Resolution Approaches in Synaptic Biology. J Phys Chem B 2024; 128:3061-3068. [PMID: 38513216 DOI: 10.1021/acs.jpcb.3c08026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Synapses between neurons are the primary loci for information transfer and storage in the brain. An individual neuron, alone, can make over 10000 synaptic contacts. It is, however, not easy to investigate what goes on locally within a synapse because many synaptic compartments are only a few hundred nanometers wide in size─close to the diffraction limit of light. To observe the biomolecular machinery and processes within synapses, in situ single-molecule techniques are emerging as powerful tools. Guided by important biological questions, this Perspective will highlight recent advances in using these techniques to obtain in situ measurements of synaptic molecules in three aspects: the cell-biological machinery within synapses, the synaptic architecture, and the synaptic neurotransmitter receptors. These advances showcase the increasing importance of single-molecule-resolution techniques for accessing subcellular biophysical and biomolecular information related to the brain.
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Affiliation(s)
- Chao Sun
- Danish Research Institute of Translational Neuroscience - DANDRITE, Nordic-EMBL Partnership for Molecular Medicine, Department of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, 8000 Aarhus C, Denmark
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27
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Plouviez M, Dubreucq E. Key Proteomics Tools for Fundamental and Applied Microalgal Research. Proteomes 2024; 12:13. [PMID: 38651372 PMCID: PMC11036299 DOI: 10.3390/proteomes12020013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/28/2024] [Accepted: 04/02/2024] [Indexed: 04/25/2024] Open
Abstract
Microscopic, photosynthetic prokaryotes and eukaryotes, collectively referred to as microalgae, are widely studied to improve our understanding of key metabolic pathways (e.g., photosynthesis) and for the development of biotechnological applications. Omics technologies, which are now common tools in biological research, have been shown to be critical in microalgal research. In the past decade, significant technological advancements have allowed omics technologies to become more affordable and efficient, with huge datasets being generated. In particular, where studies focused on a single or few proteins decades ago, it is now possible to study the whole proteome of a microalgae. The development of mass spectrometry-based methods has provided this leap forward with the high-throughput identification and quantification of proteins. This review specifically provides an overview of the use of proteomics in fundamental (e.g., photosynthesis) and applied (e.g., lipid production for biofuel) microalgal research, and presents future research directions in this field.
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Affiliation(s)
- Maxence Plouviez
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
- The Cawthron Institute, Nelson 7010, New Zealand
| | - Eric Dubreucq
- Agropolymer Engineering and Emerging Technologies, L’Institut Agro Montpellier, 34060 Montpellier, France;
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28
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Liu Z, Guo F, Zhu Y, Qin S, Hou Y, Guo H, Lin F, Chen PR, Fan X. Bioorthogonal photocatalytic proximity labeling in primary living samples. Nat Commun 2024; 15:2712. [PMID: 38548729 PMCID: PMC10978841 DOI: 10.1038/s41467-024-46985-3] [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: 09/21/2023] [Accepted: 03/14/2024] [Indexed: 04/01/2024] Open
Abstract
In situ profiling of subcellular proteomics in primary living systems, such as native tissues or clinic samples, is crucial for understanding life processes and diseases, yet challenging due to methodological obstacles. Here we report CAT-S, a bioorthogonal photocatalytic chemistry-enabled proximity labeling method, that expands proximity labeling to a wide range of primary living samples for in situ profiling of mitochondrial proteomes. Powered by our thioQM labeling warhead development and targeted bioorthogonal photocatalytic chemistry, CAT-S enables the labeling of mitochondrial proteins in living cells with high efficiency and specificity. We apply CAT-S to diverse cell cultures, dissociated mouse tissues as well as primary T cells from human blood, portraying the native-state mitochondrial proteomic characteristics, and unveiled hidden mitochondrial proteins (PTPN1, SLC35A4 uORF, and TRABD). Furthermore, CAT-S allows quantification of proteomic perturbations on dysfunctional tissues, exampled by diabetic mouse kidneys, revealing the alterations of lipid metabolism that may drive disease progression. Given the advantages of non-genetic operation, generality, and spatiotemporal resolution, CAT-S may open exciting avenues for subcellular proteomic investigations of primary samples that are otherwise inaccessible.
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Affiliation(s)
- Ziqi Liu
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Fuhu Guo
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Yufan Zhu
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Shengnan Qin
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Yuchen Hou
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Haotian Guo
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Feng Lin
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Peng R Chen
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
| | - Xinyuan Fan
- Synthetic and Functional Biomolecules Center, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
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29
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Xiao H, Zou Y, Wang J, Wan S. A Review for Artificial Intelligence Based Protein Subcellular Localization. Biomolecules 2024; 14:409. [PMID: 38672426 PMCID: PMC11048326 DOI: 10.3390/biom14040409] [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: 02/29/2024] [Revised: 03/21/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
Proteins need to be located in appropriate spatiotemporal contexts to carry out their diverse biological functions. Mislocalized proteins may lead to a broad range of diseases, such as cancer and Alzheimer's disease. Knowing where a target protein resides within a cell will give insights into tailored drug design for a disease. As the gold validation standard, the conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, and fluorescent biomarker tags for protein subcellular location identification. However, the booming era of proteomics and high-throughput sequencing generates tons of newly discovered proteins, making protein subcellular localization by wet-lab experiments a mission impossible. To tackle this concern, in the past decades, artificial intelligence (AI) and machine learning (ML), especially deep learning methods, have made significant progress in this research area. In this article, we review the latest advances in AI-based method development in three typical types of approaches, including sequence-based, knowledge-based, and image-based methods. We also elaborately discuss existing challenges and future directions in AI-based method development in this research field.
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Affiliation(s)
- Hanyu Xiao
- Department of Genetics, Cell Biology and Anatomy, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA;
| | - Yijin Zou
- College of Veterinary Medicine, China Agricultural University, Beijing 100193, China;
| | - Jieqiong Wang
- Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA;
| | - Shibiao Wan
- Department of Genetics, Cell Biology and Anatomy, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA;
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30
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Jose A, Kulkarni P, Thilakan J, Munisamy M, Malhotra AG, Singh J, Kumar A, Rangnekar VM, Arya N, Rao M. Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine. Mol Cancer 2024; 23:50. [PMID: 38461268 PMCID: PMC10924370 DOI: 10.1186/s12943-023-01916-6] [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: 08/05/2023] [Accepted: 12/15/2023] [Indexed: 03/11/2024] Open
Abstract
Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.
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Affiliation(s)
- Anmi Jose
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - Pallavi Kulkarni
- Department of Biochemistry, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Jaya Thilakan
- Department of Biochemistry, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Murali Munisamy
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Anvita Gupta Malhotra
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Jitendra Singh
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Ashok Kumar
- Department of Biochemistry, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India
| | - Vivek M Rangnekar
- Markey Cancer Center and Department of Radiation Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Neha Arya
- Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Bhopal, Madhya Pradesh, 462020, India.
| | - Mahadev Rao
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
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31
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Ma X, Fernández FM. Advances in mass spectrometry imaging for spatial cancer metabolomics. MASS SPECTROMETRY REVIEWS 2024; 43:235-268. [PMID: 36065601 PMCID: PMC9986357 DOI: 10.1002/mas.21804] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.
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Affiliation(s)
- Xin Ma
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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32
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Davoudi F, Moradi A, Sadeghirad H, Kulasinghe A. Tissue biomarkers of immune checkpoint inhibitor therapy. Immunol Cell Biol 2024; 102:179-193. [PMID: 38228572 DOI: 10.1111/imcb.12723] [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: 09/21/2023] [Revised: 12/19/2023] [Accepted: 01/01/2024] [Indexed: 01/18/2024]
Abstract
Cancer immunotherapy has been rejuvenated by the growing understanding of the immune system's role in tumor activity over the past two decades. During cancer initiation and progression, tumor cells employ various mechanisms that resemble peripheral immune tolerance to evade the antitumor responses of the immune system. Immune checkpoint molecules are the major mechanism of immune resistance that are exploited by tumor cells to inhibit T-cell activation and suppress immune responses. The targeting of immune checkpoint pathways has led to substantial improvements in survival rates in a number of solid cancers. However, a lack of understanding of the heterogeneity of the tumor microenvironment (TME) has resulted in inefficient therapy responses. A greater understanding of the TME is needed to identify patients likely to respond, and those that will have resistance to immune checkpoint inhibitors (ICIs). Advancement in spatial single-cell technologies has allowed deeper insight into the phenotypic and functional diversities of cells in the TME. In this review, we provide an overview of ICI biomarkers and highlight how high-dimensional spatially resolved, single-cell approaches provide deep molecular insights into the TME and allow for the discovery of biomarkers of clinical benefit.
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Affiliation(s)
- Fatemeh Davoudi
- Department of Medical Genetics, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Afshin Moradi
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Habib Sadeghirad
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Arutha Kulasinghe
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
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33
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Zhang J, Zhang L, Gongol B, Hayes J, Borowsky A, Bailey-Serres J, Girke T. spatialHeatmap: visualizing spatial bulk and single-cell assays in anatomical images. NAR Genom Bioinform 2024; 6:lqae006. [PMID: 38312938 PMCID: PMC10836942 DOI: 10.1093/nargab/lqae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 12/14/2023] [Accepted: 01/18/2024] [Indexed: 02/06/2024] Open
Abstract
Visualizing spatial assay data in anatomical images is vital for understanding biological processes in cell, tissue, and organ organizations. Technologies requiring this functionality include traditional one-at-a-time assays, and bulk and single-cell omics experiments, including RNA-seq and proteomics. The spatialHeatmap software provides a series of powerful new methods for these needs, and allows users to work with adequately formatted anatomical images from public collections or custom images. It colors the spatial features (e.g. tissues) annotated in the images according to the measured or predicted abundance levels of biomolecules (e.g. mRNAs) using a color key. This core functionality of the package is called a spatial heatmap plot. Single-cell data can be co-visualized in composite plots that combine spatial heatmaps with embedding plots of high-dimensional data. The resulting spatial context information is essential for gaining insights into the tissue-level organization of single-cell data, or vice versa. Additional core functionalities include the automated identification of biomolecules with spatially selective abundance patterns and clusters of biomolecules sharing similar abundance profiles. To appeal to both non-expert and computational users, spatialHeatmap provides a graphical and a command-line interface, respectively. It is distributed as a free, open-source Bioconductor package (https://bioconductor.org/packages/spatialHeatmap) that users can install on personal computers, shared servers, or cloud systems.
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Affiliation(s)
- Jianhai Zhang
- Institute for Integrative Genome Biology, Department of Botany and Plant Sciences, 1207F Genomics Building, University of California, Riverside, CA 92521, USA
| | - Le Zhang
- Institute for Integrative Genome Biology, Department of Botany and Plant Sciences, 1207F Genomics Building, University of California, Riverside, CA 92521, USA
| | - Brendan Gongol
- Institute for Integrative Genome Biology, Department of Botany and Plant Sciences, 1207F Genomics Building, University of California, Riverside, CA 92521, USA
| | - Jordan Hayes
- Institute for Integrative Genome Biology, Department of Botany and Plant Sciences, 1207F Genomics Building, University of California, Riverside, CA 92521, USA
| | - Alexander T Borowsky
- Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Julia Bailey-Serres
- Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Thomas Girke
- Institute for Integrative Genome Biology, Department of Botany and Plant Sciences, 1207F Genomics Building, University of California, Riverside, CA 92521, USA
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Tan SX, Chong S, Rowe C, Galbraith J, Dight J, Zhou C, Malt M, Smithers BM, Khosrotehrani K. Lymphatic expression of the proliferation marker Ki67 is linked to sentinel node positivity, recurrence and mortality in primary cutaneous melanoma. Exp Dermatol 2024; 33:e15041. [PMID: 38433382 DOI: 10.1111/exd.15041] [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: 08/03/2023] [Revised: 01/12/2024] [Accepted: 02/12/2024] [Indexed: 03/05/2024]
Abstract
Lymphangiogenesis is a precursor to lymphovascular invasion, and may therefore signal a higher risk of metastasis and mortality in primary cutaneous melanoma. This retrospective longitudinal study aimed to evaluate whether emergent lymphangiogenesis, as measured through co-expression of endothelial proteins with the proliferation marker Ki67, was associated with poorer prognosis in a cohort of patients with single primary cutaneous melanoma. We screened all patients with a single locally invasive primary cutaneous melanoma who received sentinel lymph node biopsy at a tertiary dermatology centre in Brisbane, Australia between 1994 and 2007. Primary melanoma sections were stained via Opal multiplex immunofluorescence, and categorized according to the presence of Ki67 within either CD31+ or D2-40+ endothelial cells. Multivariate Cox regression modelling was used to evaluate associations between endothelial Ki67 positivity and clinical outcomes, with adjustment for age, sex, Breslow depth, ulceration, and anatomical location. Overall, 264 patients were available for analysis, with a median follow-up duration of 7.1 years. The presence of D2-40+ /Ki67+ co-expression was associated with greater melanoma-specific mortality (adjusted hazard ratio [HR]: 2.03; 95% confidence interval [CI]: 1.33-3.10; p = 0.001) and recurrence (adjusted HR: 1.70; 95% CI: 1.33-3.10; p = 0.001) relative to absence. CD31+ /Ki67+ co-expression was not prognostic in this cohort. Lymphatic proliferation, as measured through D2-40+ /Ki67+ co-expression, predicted greater melanoma-specific mortality and recurrence in this cohort of primary cutaneous melanoma.
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Affiliation(s)
- Samuel X Tan
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Sharene Chong
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Casey Rowe
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Jack Galbraith
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
| | - James Dight
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Chenhao Zhou
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Maryrose Malt
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Bernard Mark Smithers
- Queensland Melanoma Project, Princess Alexandra Hospital, University of Queensland, Brisbane, Queensland, Australia
| | - Kiarash Khosrotehrani
- Frazer Institute, University of Queensland, Brisbane, Queensland, Australia
- Department of Dermatology, Princess Alexandra Hospital, Brisbane, Queensland, Australia
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Llewellyn J, Hubbard SJ, Swift J. Translation is an emerging constraint on protein homeostasis in ageing. Trends Cell Biol 2024:S0962-8924(24)00024-2. [PMID: 38423854 DOI: 10.1016/j.tcb.2024.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/23/2024] [Accepted: 02/01/2024] [Indexed: 03/02/2024]
Abstract
Proteins are molecular machines that provide structure and perform vital transport, signalling and enzymatic roles. Proteins expressed by cells require tight regulation of their concentration, folding, localisation, and modifications; however, this state of protein homeostasis is continuously perturbed by tissue-level stresses. While cells in healthy tissues are able to buffer against these perturbations, for example, by expression of chaperone proteins, protein homeostasis is lost in ageing, and can lead to protein aggregation characteristic of protein folding diseases. Here, we review reports of a progressive disconnect between transcriptomic and proteomic regulation during cellular ageing. We discuss how age-associated changes to cellular responses to specific stressors in the tissue microenvironment are exacerbated by loss of ribosomal proteins, ribosomal pausing, and mistranslation.
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Affiliation(s)
- Jack Llewellyn
- Wellcome Centre for Cell-Matrix Research, Oxford Road, Manchester, M13 9PT, UK; Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK
| | - Simon J Hubbard
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK.
| | - Joe Swift
- Wellcome Centre for Cell-Matrix Research, Oxford Road, Manchester, M13 9PT, UK; Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK.
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36
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Fan X, Sun AR, Young RSE, Afara IO, Hamilton BR, Ong LJY, Crawford R, Prasadam I. Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications. Bone Res 2024; 12:7. [PMID: 38311627 PMCID: PMC10838951 DOI: 10.1038/s41413-023-00304-6] [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: 09/05/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 02/06/2024] Open
Abstract
Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
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Affiliation(s)
- Xiwei Fan
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonia Rujia Sun
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Reuben S E Young
- Central Analytical Research Facility, Queensland University of Technology, Brisbane, QLD, Australia
- Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Isaac O Afara
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- School of Electrical Engineering and Computer Science, Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia
| | - Brett R Hamilton
- Centre for Microscopy and Microanalysis, University of Queensland, Brisbane, QLD, Australia
| | - Louis Jun Ye Ong
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ross Crawford
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- The Prince Charles Hospital, Brisbane, QLD, Australia
| | - Indira Prasadam
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
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Pade LR, Lombard-Banek C, Li J, Nemes P. Dilute to Enrich for Deeper Proteomics: A Yolk-Depleted Carrier for Limited Populations of Embryonic (Frog) Cells. J Proteome Res 2024; 23:692-703. [PMID: 37994825 PMCID: PMC10872351 DOI: 10.1021/acs.jproteome.3c00541] [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] [Indexed: 11/24/2023]
Abstract
Abundant proteins challenge deep mass spectrometry (MS) analysis of the proteome. Yolk, the source of food in many developing vertebrate embryos, complicates chemical separation and interferes with detection. We report here a strategy that enhances bottom-up proteomics in yolk-laden specimens by diluting the interferences using a yolk-depleted carrier (YODEC) proteome via isobaric multiplexing quantification. This method was tested on embryos of the South African Clawed Frog (Xenopus laevis), where a >90% yolk proteome content challenges deep proteomics. As a proof of concept, we isolated neural and epidermal fated cell clones from the embryo by dissection or fluorescence-activated cell sorting. Compared with the standard multiplexing carrier approach, YODEC more than doubled the detectable X. laevis proteome, identifying 5,218 proteins from D11 cell clones dissected from the embryo. Ca. ∼80% of the proteins were quantified without dropouts in any of the analytical channels. YODEC with high-pH fractionation quantified 3,133 proteins from ∼8,000 V11 cells that were sorted from ca. 2 embryos (1.5 μg total, or 150 ng yolk-free proteome), marking a 15-fold improvement in proteome coverage vs the standard proteomics approach. About 60% of these proteins were only quantifiable by YODEC, including molecular adaptors, transporters, translation, and transcription factors. While this study was tailored to limited populations of Xenopus cells, we anticipate the approach of "dilute to enrich" using a depleted carrier proteome to be adaptable to other biological models in which abundant proteins challenge deep MS proteomics.
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Affiliation(s)
- Leena R. Pade
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Camille Lombard-Banek
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Jie Li
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
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Lee S, Kim G, Lee J, Lee AC, Kwon S. Mapping cancer biology in space: applications and perspectives on spatial omics for oncology. Mol Cancer 2024; 23:26. [PMID: 38291400 PMCID: PMC10826015 DOI: 10.1186/s12943-024-01941-z] [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: 06/19/2023] [Accepted: 01/12/2024] [Indexed: 02/01/2024] Open
Abstract
Technologies to decipher cellular biology, such as bulk sequencing technologies and single-cell sequencing technologies, have greatly assisted novel findings in tumor biology. Recent findings in tumor biology suggest that tumors construct architectures that influence the underlying cancerous mechanisms. Increasing research has reported novel techniques to map the tissue in a spatial context or targeted sampling-based characterization and has introduced such technologies to solve oncology regarding tumor heterogeneity, tumor microenvironment, and spatially located biomarkers. In this study, we address spatial technologies that can delineate the omics profile in a spatial context, novel findings discovered via spatial technologies in oncology, and suggest perspectives regarding therapeutic approaches and further technological developments.
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Affiliation(s)
- Sumin Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea
- Meteor Biotech,, Co. Ltd, Seoul, 08826, Republic of Korea
| | - Gyeongjun Kim
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, 08826, Republic of Korea
| | - JinYoung Lee
- Division of Engineering Science, University of Toronto, Toronto, Ontario, ON, M5S 3H6, Canada
| | - Amos C Lee
- Meteor Biotech,, Co. Ltd, Seoul, 08826, Republic of Korea.
- Bio-MAX Institute, Seoul National University, Seoul, 08826, Republic of Korea.
| | - Sunghoon Kwon
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, 08826, Republic of Korea.
- Bio-MAX Institute, Seoul National University, Seoul, 08826, Republic of Korea.
- Institutes of Entrepreneurial BioConvergence, Seoul National University, Seoul, 08826, Republic of Korea.
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
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Xiong Y, Li S, Bai Y, Chen T, Sun W, Chen L, Yu J, Sun L, Li C, Wang J, Wu B. Generating detailed intercellular communication patterns in psoriasis at the single-cell level using social networking, pattern recognition, and manifold learning methods to optimize treatment strategies. Aging (Albany NY) 2024; 16:2194-2231. [PMID: 38289616 PMCID: PMC10911347 DOI: 10.18632/aging.205478] [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: 08/21/2023] [Accepted: 12/13/2023] [Indexed: 02/22/2024]
Abstract
Psoriasis, a complex and recurrent chronic inflammatory skin disease involving various inflammatory cell types, requires effective cell communication to maintain the homeostatic balance of inflammation. However, patterns of communication at the single-cell level have not been systematically investigated. In this study, we employed social network analysis tools, pattern recognition, and manifold learning to compare molecular communication features between psoriasis cells and normal skin cells. Utilizing a process that facilitates the discovery of cell type-specific regulons, we analyzed internal regulatory networks among different cells in psoriasis. Advanced techniques for the quantitative detection of non-targeted proteins in pathological tissue sections were employed to demonstrate protein expression. Our findings revealed a synergistic interplay among the communication signals of immune cells in psoriasis. B-cells were activated, while Langerhans cells shifted into the primary signaling output mode to fulfill antigen presentation, mediating T-cell immunity. In contrast to normal skin cells, psoriasis cells shut down numerous signaling pathways, influencing the balance of skin cell renewal and differentiation. Additionally, we identified a significant number of active cell type-specific regulons of resident immune cells around the hair follicle. This study unveiled the molecular communication features of the hair follicle cell-psoriasis axis, showcasing its potential for therapeutic targeting at the single-cell level. By elucidating the pattern of immune cell communication in psoriasis and identifying new molecular features of the hair follicle cell-psoriasis axis, our findings present innovative strategies for drug targeting to enhance psoriasis treatment.
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Affiliation(s)
- Ying Xiong
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Sidi Li
- Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing 400038, China
| | - Yunmeng Bai
- Department of Nephrology, Shenzhen key Laboratory of Kidney Diseases, Shenzhen People’s Hospital, The First Affiliated Hospital, School of Medicine, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China
| | - Ting Chen
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Wenwen Sun
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Lijie Chen
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Jia Yu
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Liwei Sun
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Chijun Li
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Jiajian Wang
- Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518107, Guangdong, China
- Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518107, Guangdong, China
- Clinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen and Longgang District People’s Hospital of Shenzhen, Shenzhen 518172, China
- Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Shenzhen Key Laboratory of Metabolic Health, Shenzhen 518055, China
| | - Bo Wu
- Department of Dermatology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
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40
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Sun H, Fu B, Qian X, Xu P, Qin W. Nuclear and cytoplasmic specific RNA binding proteome enrichment and its changes upon ferroptosis induction. Nat Commun 2024; 15:852. [PMID: 38286993 PMCID: PMC10825125 DOI: 10.1038/s41467-024-44987-9] [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: 06/21/2022] [Accepted: 01/11/2024] [Indexed: 01/31/2024] Open
Abstract
The key role of RNA-binding proteins (RBPs) in posttranscriptional regulation of gene expression is intimately tied to their subcellular localization. Here, we show a subcellular-specific RNA labeling method for efficient enrichment and deep profiling of nuclear and cytoplasmic RBPs. A total of 1221 nuclear RBPs and 1333 cytoplasmic RBPs were enriched and identified using nuclear/cytoplasm targeting enrichment probes, representing an increase of 54.4% and 85.7% compared with previous reports. The probes were further applied in the omics-level investigation of subcellular-specific RBP-RNA interactions upon ferroptosis induction. Interestingly, large-scale RBPs display enhanced interaction with RNAs in nucleus but reduced association with RNAs in cytoplasm during ferroptosis process. Furthermore, we discovered dozens of nucleoplasmic translocation candidate RBPs upon ferroptosis induction and validated representative ones by immunofluorescence imaging. The enrichment of Tricarboxylic acid cycle in the translocation candidate RBPs may provide insights for investigating their possible roles in ferroptosis induced metabolism dysregulation.
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Affiliation(s)
- Haofan Sun
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Bin Fu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Xiaohong Qian
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Ping Xu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Weijie Qin
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
- College of Chemistry and Materials Science, Hebei University, Baoding, 071002, China.
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41
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Liu Y, Tan Y, Zhang Z, Yi M, Zhu L, Peng W. The interaction between ageing and Alzheimer's disease: insights from the hallmarks of ageing. Transl Neurodegener 2024; 13:7. [PMID: 38254235 PMCID: PMC10804662 DOI: 10.1186/s40035-024-00397-x] [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: 09/13/2023] [Revised: 12/31/2023] [Accepted: 01/02/2024] [Indexed: 01/24/2024] Open
Abstract
Ageing is a crucial risk factor for Alzheimer's disease (AD) and is characterised by systemic changes in both intracellular and extracellular microenvironments that affect the entire body instead of a single organ. Understanding the specific mechanisms underlying the role of ageing in disease development can facilitate the treatment of ageing-related diseases, such as AD. Signs of brain ageing have been observed in both AD patients and animal models. Alleviating the pathological changes caused by brain ageing can dramatically ameliorate the amyloid beta- and tau-induced neuropathological and memory impairments, indicating that ageing plays a crucial role in the pathophysiological process of AD. In this review, we summarize the impact of several age-related factors on AD and propose that preventing pathological changes caused by brain ageing is a promising strategy for improving cognitive health.
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Affiliation(s)
- Yuqing Liu
- Department of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China
- National Clinical Research Center for Metabolic Diseases, Changsha, 410011, People's Republic of China
| | - Yejun Tan
- School of Mathematics, University of Minnesota Twin Cities, Minneapolis, MN, 55455, USA
| | - Zheyu Zhang
- Department of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China
- National Clinical Research Center for Metabolic Diseases, Changsha, 410011, People's Republic of China
| | - Min Yi
- Department of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China
- National Clinical Research Center for Metabolic Diseases, Changsha, 410011, People's Republic of China
| | - Lemei Zhu
- Academician Workstation, Changsha Medical University, Changsha, 410219, People's Republic of China
| | - Weijun Peng
- Department of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China.
- National Clinical Research Center for Metabolic Diseases, Changsha, 410011, People's Republic of China.
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Kiessling P, Kuppe C. Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases. Genome Med 2024; 16:14. [PMID: 38238823 PMCID: PMC10795303 DOI: 10.1186/s13073-024-01282-y] [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: 08/15/2023] [Accepted: 01/02/2024] [Indexed: 01/22/2024] Open
Abstract
Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.
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Affiliation(s)
- Paul Kiessling
- Department of Nephrology, Rheumatology, and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
| | - Christoph Kuppe
- Department of Nephrology, Rheumatology, and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany.
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Singin Ö, Astapenka A, Costina V, Kühl S, Bonekamp N, Drews O, Islinger M. Analysis of the Mouse Hepatic Peroxisome Proteome-Identification of Novel Protein Constituents Using a Semi-Quantitative SWATH-MS Approach. Cells 2024; 13:176. [PMID: 38247867 PMCID: PMC10814758 DOI: 10.3390/cells13020176] [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: 12/21/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 01/23/2024] Open
Abstract
Ongoing technical and bioinformatics improvements in mass spectrometry (MS) allow for the identifying and quantifying of the enrichment of increasingly less-abundant proteins in individual fractions. Accordingly, this study reassessed the proteome of mouse liver peroxisomes by the parallel isolation of peroxisomes from a mitochondria- and a microsome-enriched prefraction, combining density-gradient centrifugation with a semi-quantitative SWATH-MS proteomics approach to unveil novel peroxisomal or peroxisome-associated proteins. In total, 1071 proteins were identified using MS and assessed in terms of their distribution in either high-density peroxisomal or low-density gradient fractions, containing the bulk of organelle material. Combining the data from both fractionation approaches allowed for the identification of specific protein profiles characteristic of mitochondria, the ER and peroxisomes. Among the proteins significantly enriched in the peroxisomal cluster were several novel peroxisomal candidates. Five of those were validated by colocalization in peroxisomes, using confocal microscopy. The peroxisomal import of HTATIP2 and PAFAH2, which contain a peroxisome-targeting sequence 1 (PTS1), could be confirmed by overexpression in HepG2 cells. The candidates SAR1B and PDCD6, which are known ER-exit-site proteins, did not directly colocalize with peroxisomes, but resided at ER sites, which frequently surrounded peroxisomes. Hence, both proteins might concentrate at presumably co-purified peroxisome-ER membrane contacts. Intriguingly, the fifth candidate, OCIA domain-containing protein 1, was previously described as decreasing mitochondrial network formation. In this work, we confirmed its peroxisomal localization and further observed a reduction in peroxisome numbers in response to OCIAD1 overexpression. Hence, OCIAD1 appears to be a novel protein, which has an impact on both mitochondrial and peroxisomal maintenance.
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Affiliation(s)
- Öznur Singin
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Artur Astapenka
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Victor Costina
- Institute of Clinical Chemistry, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (V.C.); (O.D.)
| | - Sandra Kühl
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Nina Bonekamp
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Oliver Drews
- Institute of Clinical Chemistry, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (V.C.); (O.D.)
- Biomedical Mass Spectrometry, Center for Medical Research, Johannes Kepler University Linz, 4020 Linz, Austria
| | - Markus Islinger
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
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Chau CW, Sugimura R. Organoids in COVID-19: can we break the glass ceiling? J Leukoc Biol 2024; 115:85-99. [PMID: 37616269 DOI: 10.1093/jleuko/qiad098] [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: 01/30/2023] [Revised: 07/24/2023] [Accepted: 08/07/2023] [Indexed: 08/26/2023] Open
Abstract
COVID-19 emerged in September 2020 as a disease caused by the virus SARS-CoV-2. The disease presented as pneumonia at first but later was shown to cause multisystem infections and long-term complications. Many efforts have been put into discovering the exact pathogenesis of the disease. In this review, we aim to discuss an emerging tool in disease modeling, organoids, in the investigation of COVID-19. This review will introduce some methods and breakthroughs achieved by organoids and the limitations of this system.
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Affiliation(s)
- Chiu Wang Chau
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 21 Sassoon Rd, Pokfulam 99077, Hong Kong
| | - Ryohichi Sugimura
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 21 Sassoon Rd, Pokfulam 99077, Hong Kong
- Centre for Translational Stem Cell Biology, 17 Science Park W Ave, Science Park 999077, Hong Kong
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Beauvieux A, Fromentin JM, Romero D, Couffin N, Brown A, Metral L, Bourjea J, Bertile F, Schull Q. Molecular fingerprint of gilthead seabream physiology in response to pollutant mixtures in the wild. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 340:122789. [PMID: 37913978 DOI: 10.1016/j.envpol.2023.122789] [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: 08/01/2023] [Revised: 09/29/2023] [Accepted: 10/21/2023] [Indexed: 11/03/2023]
Abstract
The increase in trace element concentrations in the aquatic environment due to anthropogenic activities, urges the need for their monitoring and potential toxicity, persistence, bioaccumulation, and biomagnification at different trophic levels. Gilthead seabream is a species of commercial importance in the Mediterranean Sea, both for the aquaculture and fisheries sectors, however very little is known about their trace element contamination accumulation and the resulting effect on their health status. In the present study, 135 juveniles were collected from seven coastal lagoons known to be essential nursery areas for this species. We measured seventeen different inorganic contaminants at the individual level in fish muscle (namely Al, As, Be, Bi, Cd, Cr, Cu, Hg, Li, Ni, Pb, Rb, Sb, Sr, Ti, Tl and Zn). Our results revealed the accumulation of multiple trace elements in individuals and distinct contamination signatures between lagoons which might lead to contrasted quality as nurseries for juveniles of numerous ecologically and economically relevant fish species in addition to seabreams. We further evaluated the potential adverse effect of these complex contamination mixtures on the liver (the main organ implicated in the metabolism of xenobiotics) and red muscle (a highly metabolic organ) using a proteomic approach. Alterations in cellular organization pathways and protein transport were detected in both tissues (albeit they were not similarly regulated). Chromosome organization and telomere maintenance in the liver appeared to be affected by contaminant mixture which could increase mortality, age-related disease risk and shorter lifetime expectancy for these juveniles. Red muscle proteome also demonstrated an upregulation of pathways involved in metabolism in response to contamination which raises the issue of potential energy allocation trade-offs between the organisms' main functions such as reproduction and growth. This study provides new insights into the cellular and molecular responses of seabreams to environmental pollution and proposed biomarkers of health effects of trace elements that could serve as a starting point for larger-scale biomonitoring programs.
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Affiliation(s)
| | | | - Diego Romero
- Toxicology Department, Faculty of Veterinary Medicine, University of Murcia, 30100, Murcia, Spain
| | - Nathan Couffin
- Université de Strasbourg, CNRS, IPHC UMR 7178, 23 rue du Loess, 67037, Strasbourg Cedex 2, France; Infrastructure Nationale de Protéomique ProFI, FR2048 CNRS, CEA, Strasbourg, 67087, France
| | - Adrien Brown
- Université de Strasbourg, CNRS, IPHC UMR 7178, 23 rue du Loess, 67037, Strasbourg Cedex 2, France; Infrastructure Nationale de Protéomique ProFI, FR2048 CNRS, CEA, Strasbourg, 67087, France
| | - Luisa Metral
- MARBEC, Univ Montpellier, Ifremer, IRD, CNRS, Sète, France
| | - Jérôme Bourjea
- MARBEC, Univ Montpellier, Ifremer, IRD, CNRS, Sète, France
| | - Fabrice Bertile
- Université de Strasbourg, CNRS, IPHC UMR 7178, 23 rue du Loess, 67037, Strasbourg Cedex 2, France; Infrastructure Nationale de Protéomique ProFI, FR2048 CNRS, CEA, Strasbourg, 67087, France
| | - Quentin Schull
- MARBEC, Univ Montpellier, Ifremer, IRD, CNRS, Sète, France
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Varrone M, Tavernari D, Santamaria-Martínez A, Walsh LA, Ciriello G. CellCharter reveals spatial cell niches associated with tissue remodeling and cell plasticity. Nat Genet 2024; 56:74-84. [PMID: 38066188 DOI: 10.1038/s41588-023-01588-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 10/23/2023] [Indexed: 12/20/2023]
Abstract
Tissues are organized in cellular niches, the composition and interactions of which can be investigated using spatial omics technologies. However, systematic analyses of tissue composition are challenged by the scale and diversity of the data. Here we present CellCharter, an algorithmic framework to identify, characterize, and compare cellular niches in spatially resolved datasets. CellCharter outperformed existing approaches and effectively identified cellular niches across datasets generated using different technologies, and comprising hundreds of samples and millions of cells. In multiple human lung cancer cohorts, CellCharter uncovered a cellular niche composed of tumor-associated neutrophil and cancer cells expressing markers of hypoxia and cell migration. This cancer cell state was spatially segregated from more proliferative tumor cell clusters and was associated with tumor-associated neutrophil infiltration and poor prognosis in independent patient cohorts. Overall, CellCharter enables systematic analyses across data types and technologies to decode the link between spatial tissue architectures and cell plasticity.
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Affiliation(s)
- Marco Varrone
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Cancer Center Léman, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Daniele Tavernari
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Cancer Center Léman, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Swiss Institute for Experimental Cancer Research, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Albert Santamaria-Martínez
- Swiss Cancer Center Léman, Lausanne, Switzerland
- Swiss Institute for Experimental Cancer Research, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Logan A Walsh
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Giovanni Ciriello
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Swiss Cancer Center Léman, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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Chen Y, Yang S, Yu K, Zhang J, Wu M, Zheng Y, Zhu Y, Dai J, Wang C, Zhu X, Dai Y, Sun Y, Wu T, Wang S. Spatial omics: An innovative frontier in aging research. Ageing Res Rev 2024; 93:102158. [PMID: 38056503 DOI: 10.1016/j.arr.2023.102158] [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: 08/28/2023] [Revised: 11/25/2023] [Accepted: 12/01/2023] [Indexed: 12/08/2023]
Abstract
Disentangling the impact of aging on health and disease has become critical as population aging progresses rapidly. Studying aging at the molecular level is complicated by the diverse aging profiles and dynamics. However, the examination of cellular states within aging tissues in situ is hampered by the lack of high-resolution spatial data. Emerging spatial omics technologies facilitate molecular and spatial analysis of tissues, providing direct access to precise information on various functional regions and serving as a favorable tool for unraveling the heterogeneity of aging. In this review, we summarize the recent advances in spatial omics application in multi-organ aging research, which has enhanced the understanding of aging mechanisms from multiple standpoints. We also discuss the main challenges in spatial omics research to date, the opportunities for further developing the technology, and the potential applications of spatial omics in aging and aging-related diseases.
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Affiliation(s)
- Ying Chen
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Shuhao Yang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Kaixu Yu
- Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinjin Zhang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Meng Wu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Yongqiang Zheng
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Centre, Sun Yat-sen University, Guangzhou, China
| | - Yun Zhu
- Department of Internal Medicine, Southern Illinois University School of Medicine, 801 N. Rutledge, P.O. Box 19628, Springfield, IL 62702, USA
| | - Jun Dai
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Chunyan Wang
- College of Science & Engineering Jinan University, Guangzhou, China
| | - Xiaoran Zhu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Yun Dai
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China
| | - Yunhong Sun
- Hubei Key Laboratory of Food Nutrition and Safety, MOE Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tong Wu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China.
| | - Shixuan Wang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, China; Ministry of Education, Key Laboratory of Cancer Invasion and Metastasis, Wuhan, China.
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48
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Truong T, Sanchez-Avila X, Webber KGI, Johnston SM, Kelly RT. Efficient and Sensitive Sample Preparation, Separations, and Data Acquisition for Label-Free Single-Cell Proteomics. Methods Mol Biol 2024; 2817:67-84. [PMID: 38907148 DOI: 10.1007/978-1-0716-3934-4_7] [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] [Indexed: 06/23/2024]
Abstract
We describe a sensitive and efficient workflow for label-free single-cell proteomics that spans sample preparation, liquid chromatography separations, and mass spectrometry data acquisition. The Tecan Uno Single Cell Dispenser provides rapid cell isolation and nanoliter-volume reagent dispensing within 384-well PCR plates. A newly developed sample processing workflow achieves cell lysis, protein denaturation, and digestion in 1 h with a single reagent dispensing step. Low-flow liquid chromatography coupled with wide-window data-dependent acquisition results in the quantification of nearly 3000 proteins per cell using an Orbitrap Exploris 480 mass spectrometer. This approach greatly broadens accessibility to sensitive single-cell proteome profiling for nonspecialist laboratories.
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Affiliation(s)
- Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Ximena Sanchez-Avila
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA.
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49
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Demicco M, Liu XZ, Leithner K, Fendt SM. Metabolic heterogeneity in cancer. Nat Metab 2024; 6:18-38. [PMID: 38267631 DOI: 10.1038/s42255-023-00963-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/06/2023] [Indexed: 01/26/2024]
Abstract
Cancer cells rewire their metabolism to survive during cancer progression. In this context, tumour metabolic heterogeneity arises and develops in response to diverse environmental factors. This metabolic heterogeneity contributes to cancer aggressiveness and impacts therapeutic opportunities. In recent years, technical advances allowed direct characterisation of metabolic heterogeneity in tumours. In addition to the metabolic heterogeneity observed in primary tumours, metabolic heterogeneity temporally evolves along with tumour progression. In this Review, we summarize the mechanisms of environment-induced metabolic heterogeneity. In addition, we discuss how cancer metabolism and the key metabolites and enzymes temporally and functionally evolve during the metastatic cascade and treatment.
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Affiliation(s)
- Margherita Demicco
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Xiao-Zheng Liu
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Katharina Leithner
- Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium.
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium.
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50
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Bejarano DA, Schlitzer A. Unveiling Macrophage Heterogeneity and Their Spatial Distribution Using Multiplexed Tissue Imaging. Methods Mol Biol 2024; 2713:281-296. [PMID: 37639130 DOI: 10.1007/978-1-0716-3437-0_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
Macrophages display a high degree of phenotypic diversity and plasticity, which is influenced by their location within the tissue microenvironment. Co-Detection by Indexing (CODEX), a multiplexed imaging technique, allows the simultaneous detection of multiple membrane and cellular markers that enable the accurate identification of tissue-resident hematopoietic and non-hematopoietic cells, while conferring spatial information at a single-cell level. Here we describe the use of CODEX to visualize the phenotypic and spatial heterogeneity of murine tissue-resident macrophages in several organs, and a pipeline to characterize their cellular microenvironments and interactions.
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Affiliation(s)
| | - Andreas Schlitzer
- Quantitative Systems Biology, LIMES Institute, University of Bonn, Bonn, Germany.
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