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Chen YL, Feng M, Zhu X, Zheng Z. Lanthanide complexes with an azo-dye chromophore ligand: syntheses, crystal structures, and near-infrared luminescence by long-wavelength excitation. Dalton Trans 2024; 53:7350-7357. [PMID: 38616717 DOI: 10.1039/d4dt00577e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Near-infrared (NIR) emissive probes are becoming increasingly popular in biological sensing and imaging due to the advantages of non-invasiveness and deep tissue-penetrating ability. Herein, a series of complexes of trivalent lanthanide ions (Ln = Yb, Er, and Gd) with the commercially available azo dye chromophore 2R (Na2H2C2R) as ligand and featuring respectively H2O and dimethylsulfoxide (DMSO) as ancillary ligands have been prepared. Formulated as [Ln2(HC2R)2(H2O)10]·8H2O (1-3, Ln = Yb, Er, Gd) and [Ln2(HC2R)2(DMSO)10]·2DMSO (4-6, Ln = Yb, Er, Gd), their structures have been determined by single-crystal X-ray diffraction studies. Photophysical property studies revealed NIR emissions of the DMSO complexes characteristic of Yb(III) and Er(III), effectively sensitized by the dye ligand arising mainly from the π-π* transition of the chromophore. The long-wavelength excitation of the complexes, covering the whole visible-light range and extending into the NIR region, portends the potential applications of such complexes for flexible bioimaging and sensing.
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Affiliation(s)
- Yun-Long Chen
- School of Chemistry and Life Science, Changchun University of Technology, Changchun, 130012, China.
- Department of Chemistry, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Min Feng
- Department of Chemistry, Southern University of Science and Technology, Shenzhen, 518055, China.
- Key University Laboratory of Rare Earth Chemistry of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Xiaofei Zhu
- School of Chemistry and Life Science, Changchun University of Technology, Changchun, 130012, China.
| | - Zhiping Zheng
- Department of Chemistry, Southern University of Science and Technology, Shenzhen, 518055, China.
- Key University Laboratory of Rare Earth Chemistry of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
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Mersch SA, Bergman S, Sheets ED, Boersma AJ, Heikal AA. Two-photon excited-state dynamics of mEGFP-linker-mScarlet-I crowding biosensor in controlled environments. Phys Chem Chem Phys 2024; 26:3927-3940. [PMID: 38231116 DOI: 10.1039/d3cp04733d] [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: 01/18/2024]
Abstract
Macromolecular crowding affects many cellular processes such as diffusion, biochemical reaction kinetics, protein-protein interactions, and protein folding. Mapping the heterogeneous, dynamic crowding in living cells or tissues requires genetically encoded, site-specific, crowding sensors that are compatible with quantitative, noninvasive fluorescence micro-spectroscopy. Here, we carried out time-resolved 2P-fluorescence measurements of a new mEGFP-linker-mScarlet-I macromolecular crowding construct (GE2.3) to characterize its environmental sensitivity in biomimetic crowded solutions (Ficoll-70, 0-300 g L-1) via Förster resonance energy transfer (FRET) analysis. The 2P-fluorescence lifetime of the donor (mEGFP) was measured under magic-angle polarization, in the presence (intact) and absence (enzymatically cleaved) of the acceptor (mScarlet-I), as a function of the Ficoll-70 concentration. The FRET efficiency was used to quantify the sensitivity of GE2.3 to macromolecular crowding and to determine the environmental dependence of the mEGFP-mScarlet-I distance. We also carried out time-resolved 2P-fluorescence depolarization anisotropy to examine both macromolecular crowding and linker flexibility effects on GE2.3 rotational dynamics within the context of the Stokes-Einstein model as compared with theoretical predictions based on its molecular weight. These time-resolved 2P-fluorescence depolarization measurements and conformational population analyses of GE2.3 were also used to estimate the free energy gain upon the structural collapse in crowded environment. Our results further the development of a rational engineering design for bioenvironmental sensors without the interference of cellular autofluorescence. Additionally, these results in well-defined environments will inform our future in vivo studies of genetically encoded GE2.3 towards the mapping of the crowded intracellular environment under different physiological conditions.
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Affiliation(s)
- Sarah A Mersch
- Department of Chemistry and Biochemistry, Swenson College of Science and Engineering, University of Minnesota Duluth, Duluth, MN 55812, USA.
| | - Sarah Bergman
- Department of Chemistry and Biochemistry, Swenson College of Science and Engineering, University of Minnesota Duluth, Duluth, MN 55812, USA.
| | - Erin D Sheets
- Department of Chemistry and Biochemistry, Swenson College of Science and Engineering, University of Minnesota Duluth, Duluth, MN 55812, USA.
| | - Arnold J Boersma
- Cellular Protein Chemistry, Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Ahmed A Heikal
- Department of Chemistry and Biochemistry, Swenson College of Science and Engineering, University of Minnesota Duluth, Duluth, MN 55812, USA.
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Wu X, Li JR, Fu Y, Chen DY, Nie H, Tang ZP. From static to dynamic: live observation of the support system after ischemic stroke by two photon-excited fluorescence laser-scanning microscopy. Neural Regen Res 2023; 18:2093-2107. [PMID: 37056116 PMCID: PMC10328295 DOI: 10.4103/1673-5374.369099] [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: 10/14/2022] [Revised: 12/21/2022] [Accepted: 01/13/2023] [Indexed: 02/17/2023] Open
Abstract
Ischemic stroke is one of the most common causes of mortality and disability worldwide. However, treatment efficacy and the progress of research remain unsatisfactory. As the critical support system and essential components in neurovascular units, glial cells and blood vessels (including the blood-brain barrier) together maintain an optimal microenvironment for neuronal function. They provide nutrients, regulate neuronal excitability, and prevent harmful substances from entering brain tissue. The highly dynamic networks of this support system play an essential role in ischemic stroke through processes including brain homeostasis, supporting neuronal function, and reacting to injuries. However, most studies have focused on postmortem animals, which inevitably lack critical information about the dynamic changes that occur after ischemic stroke. Therefore, a high-precision technique for research in living animals is urgently needed. Two-photon fluorescence laser-scanning microscopy is a powerful imaging technique that can facilitate live imaging at high spatiotemporal resolutions. Two-photon fluorescence laser-scanning microscopy can provide images of the whole-cortex vascular 3D structure, information on multicellular component interactions, and provide images of structure and function in the cranial window. This technique shifts the existing research paradigm from static to dynamic, from flat to stereoscopic, and from single-cell function to multicellular intercommunication, thus providing direct and reliable evidence to identify the pathophysiological mechanisms following ischemic stroke in an intact brain. In this review, we discuss exciting findings from research on the support system after ischemic stroke using two-photon fluorescence laser-scanning microscopy, highlighting the importance of dynamic observations of cellular behavior and interactions in the networks of the brain's support systems. We show the excellent application prospects and advantages of two-photon fluorescence laser-scanning microscopy and predict future research developments and directions in the study of ischemic stroke.
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Affiliation(s)
- Xuan Wu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Jia-Rui Li
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Yu Fu
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Dan-Yang Chen
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Hao Nie
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Zhou-Ping Tang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
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Zhan H, Chen S, Gao F, Wang G, Chen SD, Xi G, Yuan HY, Li X, Liu WY, Byrne CD, Targher G, Chen MY, Yang YF, Chen J, Fan Z, Sun X, Cai G, Zheng MH, Zhuo S. AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD. Aliment Pharmacol Ther 2023; 58:573-584. [PMID: 37403450 DOI: 10.1111/apt.17635] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/05/2023] [Accepted: 06/23/2023] [Indexed: 07/06/2023]
Abstract
BACKGROUND Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) is a powerful tool for label-free two-dimensional and three-dimensional tissue visualisation that shows promise in liver fibrosis assessment. AIM To investigate combining multi-photon microscopy (MPM) and deep learning techniques to develop and validate a new automated quantitative histological classification tool, named AutoFibroNet (Automated Liver Fibrosis Grading Network), for accurately staging liver fibrosis in MAFLD. METHODS AutoFibroNet was developed in a training cohort that consisted of 203 Chinese adults with biopsy-confirmed MAFLD. Three deep learning models (VGG16, ResNet34, and MobileNet V3) were used to train pre-processed images and test data sets. Multi-layer perceptrons were used to fuse data (deep learning features, clinical features, and manual features) to build a joint model. This model was then validated in two further independent cohorts. RESULTS AutoFibroNet showed good discrimination in the training set. For F0, F1, F2 and F3-4 fibrosis stages, the area under the receiver operating characteristic curves (AUROC) of AutoFibroNet were 1.00, 0.99, 0.98 and 0.98. The AUROCs of F0, F1, F2 and F3-4 fibrosis stages for AutoFibroNet in the two validation cohorts were 0.99, 0.83, 0.80 and 0.90 and 1.00, 0.83, 0.80 and 0.94, respectively, showing a good discriminatory ability in different cohorts. CONCLUSION AutoFibroNet is an automated quantitative tool that accurately identifies histological stages of liver fibrosis in Chinese individuals with MAFLD.
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Affiliation(s)
- Huiling Zhan
- School of Science, Jimei University, Xiamen, China
| | - Siyu Chen
- College of Computer Engineering, Jimei University, Xiamen, China
| | - Feng Gao
- Department of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | | | - Sui-Dan Chen
- Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Gangqin Xi
- School of Science, Jimei University, Xiamen, China
| | - Hai-Yang Yuan
- MAFLD Research Center, Department of Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaolu Li
- School of Science, Jimei University, Xiamen, China
| | - Wen-Yue Liu
- Department of Endocrinology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Christopher D Byrne
- Southampton National Institute for Health and Care Research, Biomedical Research Centre, University Hospital Southampton and University of Southampton, Southampton General Hospital, Southampton, UK
| | - Giovanni Targher
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Verona, Verona, Italy
| | - Miao-Yang Chen
- Department of Liver Diseases, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, China
| | - Yong-Feng Yang
- Department of Liver Diseases, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, China
| | - Jun Chen
- Department of Pathology, The Affiliated Drum Tower Hospital of Nanjing University, Medical School, Nanjing, China
| | - Zhiwen Fan
- Department of Pathology, The Affiliated Drum Tower Hospital of Nanjing University, Medical School, Nanjing, China
| | - Xitai Sun
- Department of Metabolic and Bariatric Surgery, The Affiliated Drum Tower Hospital of Nanjing University, Medical School, Nanjing, China
| | - Guorong Cai
- College of Computer Engineering, Jimei University, Xiamen, China
| | - Ming-Hua Zheng
- MAFLD Research Center, Department of Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- Institute of Hepatology, Wenzhou Medical University, Wenzhou, China
- Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou, China
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Liang H, Ma Z, Wang Z, Zhong P, Li R, Jiang H, Zong X, Zhong C, Liu X, Liu P, Liu J, Zhu H, Liu R, Ding Y. Structural Insights into the Binding of Red Fluorescent Protein mCherry-Specific Nanobodies. Int J Mol Sci 2023; 24:ijms24086952. [PMID: 37108116 PMCID: PMC10138814 DOI: 10.3390/ijms24086952] [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: 03/09/2023] [Revised: 03/31/2023] [Accepted: 04/06/2023] [Indexed: 04/29/2023] Open
Abstract
Red fluorescent proteins (RFPs) have broad applications in life science research, and the manipulation of RFPs using nanobodies can expand their potential uses. However, the structural information available for nanobodies that bind with RFPs is still insufficient. In this study, we cloned, expressed, purified, and crystallized complexes formed by mCherry with LaM1, LaM3, and LaM8. Then, we analyzed the biochemical properties of the complexes using mass spectrometry (MS), fluorescence-detected size exclusion chromatography (FSEC), isothermal titration calorimetry (ITC), and bio-layer interferometry (BLI) technology. We determined the crystal structure of mCherry-LaM1, mCherry-LaM3, and mCherry-LaM8, with resolutions of 2.05 Å, 3.29 Å, and 1.31 Å, respectively. In this study, we systematically compared various parameters of several LaM series nanobodies, including LaM1, LaM3, and LaM8, with previously reported data on LaM2, LaM4, and LaM6, specifically examining their structural information. After designing multivalent tandem LaM1-LaM8 and LaM8-LaM4 nanobodies based on structural information, we characterized their properties, revealing their higher affinity and specificity to mCherry. Our research provides novel structural insights that could aid in understanding nanobodies targeting a specific target protein. This could provide a starting point for developing enhanced mCherry manipulation tools.
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Affiliation(s)
- Hui Liang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Zhiqiang Ma
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Ziying Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Peiyu Zhong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Ran Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - He Jiang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xin Zong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Chao Zhong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xihuan Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Peng Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Jiayuan Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Haoran Zhu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Rui Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Yu Ding
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China
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