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Setia A, Mehata AK, Priya V, Pawde DM, Jain D, Mahto SK, Muthu MS. Current Advances in Nanotheranostics for Molecular Imaging and Therapy of Cardiovascular Disorders. Mol Pharm 2023; 20:4922-4941. [PMID: 37699355 DOI: 10.1021/acs.molpharmaceut.3c00582] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
Cardiovascular diseases (CVDs) refer to a collection of conditions characterized by abnormalities in the cardiovascular system. They are a global problem and one of the leading causes of mortality and disability. Nanotheranostics implies to the combination of diagnostic and therapeutic capabilities inside a single nanoscale platform that has allowed for significant advancement in cardiovascular diagnosis and therapy. These advancements are being developed to improve imaging capabilities, introduce personalized therapies, and boost cardiovascular disease patient treatment outcomes. Significant progress has been achieved in the integration of imaging and therapeutic capabilities within nanocarriers. In the case of cardiovascular disease, nanoparticles provide targeted delivery of therapeutics, genetic material, photothermal, and imaging agents. Directing and monitoring the movement of these therapeutic nanoparticles may be done with pinpoint accuracy by using imaging modalities such as cardiovascular magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), photoacoustic/ultrasound, and fluorescence imaging. Recently, there has been an increasing demand of noninvasive for multimodal nanotheranostic platforms. In these platforms, various imaging technologies such as optical and magnetic resonance are integrated into a single nanoparticle. This platform helps in acquiring more accurate descriptions of cardiovascular diseases and provides clues for accurate diagnosis. Advances in surface functionalization methods have strengthened the potential application of nanotheranostics in cardiovascular diagnosis and therapy. In this Review, we have covered the potential impact of nanomedicine on CVDs. Additionally, we have discussed the recently developed various nanoparticles for CVDs imaging. Moreover, advancements in the CMR, CT, PET, ultrasound, and photoacoustic imaging for the CVDs have been discussed. We have limited our discussion to nanomaterials based clinical trials for CVDs and their patents.
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Affiliation(s)
- Aseem Setia
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
| | - Abhishesh Kumar Mehata
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
| | - Vishnu Priya
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
| | - Datta Maroti Pawde
- School of Pharmacy & Technology Management, SVKM's Narsee Monjee Institute of Management Studies (NMIMS) Deemed-to-be University, Shirpur, Dhule, Maharashtra 425405, India
| | - Dharmendra Jain
- Department of Cardiology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India
| | - Sanjeev Kumar Mahto
- School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
| | - Madaswamy S Muthu
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
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2
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Chong D, Jones NC, Schittenhelm RB, Anderson A, Casillas-Espinosa PM. Multi-omics Integration and Epilepsy: Towards a Better Understanding of Biological Mechanisms. Prog Neurobiol 2023:102480. [PMID: 37286031 DOI: 10.1016/j.pneurobio.2023.102480] [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: 02/15/2023] [Revised: 05/09/2023] [Accepted: 06/03/2023] [Indexed: 06/09/2023]
Abstract
The epilepsies are a group of complex neurological disorders characterised by recurrent seizures. Approximately 30% of patients fail to respond to anti-seizure medications, despite the recent introduction of many new drugs. The molecular processes underlying epilepsy development are not well understood and this knowledge gap impedes efforts to identify effective targets and develop novel therapies against epilepsy. Omics studies allow a comprehensive characterisation of a class of molecules. Omics-based biomarkers have led to clinically validated diagnostic and prognostic tests for personalised oncology, and more recently for non-cancer diseases. We believe that, in epilepsy, the full potential of multi-omics research is yet to be realised and we envisage that this review will serve as a guide to researchers planning to undertake omics-based mechanistic studies.
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Affiliation(s)
- Debbie Chong
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia
| | - Nigel C Jones
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia; Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia
| | - Ralf B Schittenhelm
- Monash Proteomics & Metabolomics Facility and Monash Biomedicine Discovery Institute, Monash University, Clayton, Victoria, 3800, Australia
| | - Alison Anderson
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia; Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia
| | - Pablo M Casillas-Espinosa
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia; Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia
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3
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Schnackenberg LK, Thorn DA, Barnette D, Jones EE. MALDI imaging mass spectrometry: an emerging tool in neurology. Metab Brain Dis 2022; 37:105-121. [PMID: 34347208 DOI: 10.1007/s11011-021-00797-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/11/2021] [Indexed: 12/24/2022]
Abstract
Neurological disease and disorders remain a large public health threat. Thus, research to improve early detection and/or develop more effective treatment approaches are necessary. Although there are many common techniques and imaging modalities utilized to study these diseases, existing approaches often require a label which can be costly and time consuming. Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) is a label-free, innovative and emerging technique that produces 2D ion density maps representing the distribution of an analyte(s) across a tissue section in relation to tissue histopathology. One main advantage of MALDI IMS over other imaging modalities is its ability to determine the spatial distribution of hundreds of analytes within a single imaging run, without the need for a label or any a priori knowledge. Within the field of neurology and disease there have been several impactful studies in which MALDI IMS has been utilized to better understand the cellular pathology of the disease and or severity. Furthermore, MALDI IMS has made it possible to map specific classes of analytes to regions of the brain that otherwise may have been lost using more traditional methods. This review will highlight key studies that demonstrate the potential of this technology to elucidate previously unknown phenomenon in neurological disease.
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Affiliation(s)
- Laura K Schnackenberg
- Division of Systems Biology, National Center for Toxicological Research/FDA, 3900 NCTR Rd, Jefferson, AR, USA
| | - David A Thorn
- Division of Systems Biology, National Center for Toxicological Research/FDA, 3900 NCTR Rd, Jefferson, AR, USA
| | - Dustyn Barnette
- Division of Systems Biology, National Center for Toxicological Research/FDA, 3900 NCTR Rd, Jefferson, AR, USA
| | - E Ellen Jones
- Division of Systems Biology, National Center for Toxicological Research/FDA, 3900 NCTR Rd, Jefferson, AR, USA.
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4
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Ajith A, Sthanikam Y, Banerjee S. Chemical analysis of the human brain by imaging mass spectrometry. Analyst 2021; 146:5451-5473. [PMID: 34515699 DOI: 10.1039/d1an01109j] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Analysis of the chemical makeup of the brain enables a deeper understanding of several neurological processes. Molecular imaging that deciphers the spatial distribution of neurochemicals with high specificity and sensitivity is an exciting avenue in this aspect. The past two decades have witnessed a significant surge of mass spectrometry imaging (MSI) that can simultaneously map the distribution of hundreds to thousands of biomolecules in the tissue specimen at a fairly high resolution, which is otherwise beyond the scope of other molecular imaging techniques. In this review, we have documented the evolution of MSI technologies in imaging the anatomical distribution of neurochemicals in the human brain in the context of several neuro diseases. This review also addresses the potential of MSI to be a next-generation molecular imaging technique with its promising applications in neuropathology.
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Affiliation(s)
- Akhila Ajith
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India.
| | - Yeswanth Sthanikam
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India.
| | - Shibdas Banerjee
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India.
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5
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do Canto AM, Donatti A, Geraldis JC, Godoi AB, da Rosa DC, Lopes-Cendes I. Neuroproteomics in Epilepsy: What Do We Know so Far? Front Mol Neurosci 2021; 13:604158. [PMID: 33488359 PMCID: PMC7817846 DOI: 10.3389/fnmol.2020.604158] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 12/09/2020] [Indexed: 12/12/2022] Open
Abstract
Epilepsies are chronic neurological diseases that affect approximately 2% of the world population. In addition to being one of the most frequent neurological disorders, treatment for patients with epilepsy remains a challenge, because a proportion of patients do not respond to the antiseizure medications that are currently available. This results in a severe economic and social burden for patients, families, and the healthcare system. A characteristic common to all forms of epilepsy is the occurrence of epileptic seizures that are caused by abnormal neuronal discharges, leading to a clinical manifestation that is dependent on the affected brain region. It is generally accepted that an imbalance between neuronal excitation and inhibition generates the synchronic electrical activity leading to seizures. However, it is still unclear how a normal neural circuit becomes susceptible to the generation of seizures or how epileptogenesis is induced. Herein, we review the results of recent proteomic studies applied to investigate the underlying mechanisms leading to epilepsies and how these findings may impact research and treatment for these disorders.
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Affiliation(s)
- Amanda M. do Canto
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Amanda Donatti
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Jaqueline C. Geraldis
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Alexandre B. Godoi
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Douglas C. da Rosa
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Iscia Lopes-Cendes
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
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6
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Zhang Y, Liu Y, Jia Y, Zhao Y, Ma C, Bao X, Meng X, Dou W, Wang X, Ge W. Proteomic profiling of sclerotic hippocampus revealed dysregulated packaging of vesicular neurotransmitters in temporal lobe epilepsy. Epilepsy Res 2020; 166:106412. [DOI: 10.1016/j.eplepsyres.2020.106412] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 06/17/2020] [Accepted: 06/30/2020] [Indexed: 12/31/2022]
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7
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De Bruycker K, Welle A, Hirth S, Blanksby SJ, Barner-Kowollik C. Mass spectrometry as a tool to advance polymer science. Nat Rev Chem 2020; 4:257-268. [PMID: 37127980 DOI: 10.1038/s41570-020-0168-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/31/2020] [Indexed: 12/12/2022]
Abstract
In contrast to natural polymers, which have existed for billions of years, the first well-understood synthetic polymers date back to just over one century ago. Nevertheless, this relatively short period has seen vast progress in synthetic polymer chemistry, which can now afford diverse macromolecules with varying structural complexities. To keep pace with this synthetic progress, there have been commensurate developments in analytical chemistry, where mass spectrometry has emerged as the pre-eminent technique for polymer analysis. This Perspective describes present challenges associated with the mass-spectrometric analysis of synthetic polymers, in particular the desorption, ionization and structural interrogation of high-molar-mass macromolecules, as well as strategies to lower spectral complexity. We critically evaluate recent advances in technology in the context of these challenges and suggest how to push the field beyond its current limitations. In this context, the increasingly important role of high-resolution mass spectrometry is emphasized because of its unrivalled ability to describe unique species within polymer ensembles, rather than to report the average properties of the ensemble.
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8
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Klein O, Kanter F, Kulbe H, Jank P, Denkert C, Nebrich G, Schmitt WD, Wu Z, Kunze CA, Sehouli J, Darb‐Esfahani S, Braicu I, Lellmann J, Thiele H, Taube ET. MALDI‐Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods. Proteomics Clin Appl 2018; 13:e1700181. [DOI: 10.1002/prca.201700181] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 10/31/2018] [Indexed: 12/11/2022]
Affiliation(s)
- Oliver Klein
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Berlin‐Brandenburg Center for Regenerative TherapiesCharité—Universitätsmedizin Berlin 13353 Berlin Germany
| | - Frederic Kanter
- Institute of Mathematics and Image ComputingUniversität zu Lübeck Lübeck Germany
| | - Hagen Kulbe
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Department of GynecologyCharité—Universitätsmedizin Berlin 13353 Berlin Germany
- Fraunhofer—Institute for Medical Image Computing MEVIS 23562 Lübeck Germany
| | - Paul Jank
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Institute of PathologyCharité—Universitätsmedizin Berlin 10117 Berlin Germany
| | - Carsten Denkert
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Institute of PathologyCharité—Universitätsmedizin Berlin 10117 Berlin Germany
| | - Grit Nebrich
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Berlin‐Brandenburg Center for Regenerative TherapiesCharité—Universitätsmedizin Berlin 13353 Berlin Germany
| | - Wolfgang D. Schmitt
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Institute of PathologyCharité—Universitätsmedizin Berlin 10117 Berlin Germany
| | - Zhiyang Wu
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Berlin‐Brandenburg Center for Regenerative TherapiesCharité—Universitätsmedizin Berlin 13353 Berlin Germany
| | - Catarina A. Kunze
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Institute of PathologyCharité—Universitätsmedizin Berlin 10117 Berlin Germany
| | - Jalid Sehouli
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Department of GynecologyCharité—Universitätsmedizin Berlin 13353 Berlin Germany
- Fraunhofer—Institute for Medical Image Computing MEVIS 23562 Lübeck Germany
| | - Silvia Darb‐Esfahani
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Institute of Pathology Spandau 13589 Berlin Germany
| | - Ioana Braicu
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Department of GynecologyCharité—Universitätsmedizin Berlin 13353 Berlin Germany
- Fraunhofer—Institute for Medical Image Computing MEVIS 23562 Lübeck Germany
| | - Jan Lellmann
- Institute of Mathematics and Image ComputingUniversität zu Lübeck Lübeck Germany
| | - Herbert Thiele
- Fraunhofer—Institute for Medical Image Computing MEVIS 23562 Lübeck Germany
| | - Eliane T. Taube
- Charité—Universitätsmedizin Berlincorporate member of Freie Universität BerlinHumboldt‐Universität zu BerlinBerlin Institute of Health Berlin Germany
- Institute of PathologyCharité—Universitätsmedizin Berlin 10117 Berlin Germany
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9
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Kumar K. Discrete Wavelet Transform (DWT) Assisted Partial Least Square (PLS) Analysis of Excitation-Emission Matrix Fluorescence (EEMF) Spectroscopic Data Sets: Improving the Quantification Accuracy of EEMF Technique. J Fluoresc 2018; 29:185-193. [PMID: 30488232 DOI: 10.1007/s10895-018-2327-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 11/19/2018] [Indexed: 11/25/2022]
Abstract
In the present work, it is shown that quantitative estimation efficiency of the partial least square (PLS) calibration model can be significantly improved by pre-processing the EEMF with discrete wavelet transform (DWT) analysis. The application of DWT essentially reduces the volume of data sets retaining all the analytically relevant information that subsequently helps in establishing a better correlation between the spectral and concentration data matrices. The utility of the proposed approach is successfully validated by analyzing the dilute aqueous mixtures of four fluorophores having significant spectral overlap with each other. The analytical procedure developed in the present study could be useful for analyzing the environmental, agricultural, and biological samples containing the fluorescent molecules at low concentration levels.
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Affiliation(s)
- Keshav Kumar
- Institute for Wine analysis and Beverage Research, Hochschule Geisenheim University, 65366, Geisenheim, Germany.
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10
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Xie X, Jiang Y, Yuan Y, Wang P, Li X, Chen F, Sun C, Zhao H, Zeng X, Jiang L, Zhou Y, Dan H, Feng M, Liu R, Chen Q. MALDI imaging reveals NCOA7 as a potential biomarker in oral squamous cell carcinoma arising from oral submucous fibrosis. Oncotarget 2018; 7:59987-60004. [PMID: 27509054 PMCID: PMC5312364 DOI: 10.18632/oncotarget.11046] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Accepted: 06/09/2016] [Indexed: 02/05/2023] Open
Abstract
Oral squamous cell carcinoma (OSCC) ranks among the most common cancer worldwide, and is associated with severe morbidity and high mortality. Oral submucous fibrosis (OSF), characterized by fibrosis of the mucosa of the upper digestive tract, is a pre-malignant lesion, but the molecular mechanisms underlying this malignant transformation remains to be elucidated. In this study, matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS)-based proteomic strategy was employed to profile the differentially expressed peptides/proteins between OSCC tissues and the corresponding adjacent non-cancerous OSF tissues. Sixty-five unique peptide peaks and nine proteins were identified with altered expression levels. Of them, expression of NCOA7 was found to be up-regulated in OSCC tissues by immunohistochemistry staining and western blotting, and correlated with a pan of clinicopathologic parameters, including lesion site, tumor differentiation status and lymph node metastasis. Further, we show that overexpression of NCOA7 promotes OSCC cell proliferation in either in vitro or in vivo models. Mechanistic study demonstrates that NCOA7 induces OSCC cell proliferation probably by activating aryl hydrocarbon receptor (AHR). The present study suggests that NCOA7 is a potential biomarker for early diagnosis of OSF malignant transformation, and leads to a better understanding of the molecular mechanisms responsible for OSCC development.
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Affiliation(s)
- Xiaoyan Xie
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Yuchen Jiang
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Yao Yuan
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Peiqi Wang
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Xinyi Li
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Fangman Chen
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Chongkui Sun
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Hang Zhao
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Xin Zeng
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Lu Jiang
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Yu Zhou
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Hongxia Dan
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Mingye Feng
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Rui Liu
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Qianming Chen
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
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11
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Rabe JH, A Sammour D, Schulz S, Munteanu B, Ott M, Ochs K, Hohenberger P, Marx A, Platten M, Opitz CA, Ory DS, Hopf C. Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies. Sci Rep 2018; 8:313. [PMID: 29321555 PMCID: PMC5762902 DOI: 10.1038/s41598-017-18477-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 12/12/2017] [Indexed: 12/27/2022] Open
Abstract
Multimodal imaging combines complementary platforms for spatially resolved tissue analysis that are poised for application in life science and personalized medicine. Unlike established clinical in vivo multimodality imaging, automated workflows for in-depth multimodal molecular ex vivo tissue analysis that combine the speed and ease of spectroscopic imaging with molecular details provided by mass spectrometry imaging (MSI) are lagging behind. Here, we present an integrated approach that utilizes non-destructive Fourier transform infrared (FTIR) microscopy and matrix assisted laser desorption/ionization (MALDI) MSI for analysing single-slide tissue specimen. We show that FTIR microscopy can automatically guide high-resolution MSI data acquisition and interpretation without requiring prior histopathological tissue annotation, thus circumventing potential human-annotation-bias while achieving >90% reductions of data load and acquisition time. We apply FTIR imaging as an upstream modality to improve accuracy of tissue-morphology detection and to retrieve diagnostic molecular signatures in an automated, unbiased and spatially aware manner. We show the general applicability of multimodal FTIR-guided MALDI-MSI by demonstrating precise tumor localization in mouse brain bearing glioma xenografts and in human primary gastrointestinal stromal tumors. Finally, the presented multimodal tissue analysis method allows for morphology-sensitive lipid signature retrieval from brains of mice suffering from lipidosis caused by Niemann-Pick type C disease.
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Affiliation(s)
- Jan-Hinrich Rabe
- Center for Applied Research in Applied Biomedical Mass Spectrometry (ABIMAS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
| | - Denis A Sammour
- Center for Applied Research in Applied Biomedical Mass Spectrometry (ABIMAS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
| | - Sandra Schulz
- Center for Applied Research in Applied Biomedical Mass Spectrometry (ABIMAS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
| | - Bogdan Munteanu
- Center for Applied Research in Applied Biomedical Mass Spectrometry (ABIMAS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany
| | - Martina Ott
- German Cancer Consortium (DKTK) CCU Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Katharina Ochs
- German Cancer Consortium (DKTK) CCU Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neurology and National Center of Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Peter Hohenberger
- University Medical Center Mannheim of Heidelberg University, Mannheim, Germany
| | - Alexander Marx
- University Medical Center Mannheim of Heidelberg University, Mannheim, Germany
| | - Michael Platten
- German Cancer Consortium (DKTK) CCU Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- University Medical Center Mannheim of Heidelberg University, Mannheim, Germany
| | - Christiane A Opitz
- Brain Cancer Metabolism Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neurology and National Center of Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Daniel S Ory
- Diabetic Cardiovascular Disease Center and Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, 63110, USA
| | - Carsten Hopf
- Center for Applied Research in Applied Biomedical Mass Spectrometry (ABIMAS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany.
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163, Mannheim, Germany.
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12
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Quanico J, Franck J, Wisztorski M, Salzet M, Fournier I. Integrated mass spectrometry imaging and omics workflows on the same tissue section using grid-aided, parafilm-assisted microdissection. Biochim Biophys Acta Gen Subj 2017; 1861:1702-1714. [PMID: 28300637 DOI: 10.1016/j.bbagen.2017.03.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2016] [Revised: 03/08/2017] [Accepted: 03/10/2017] [Indexed: 01/03/2023]
Abstract
BACKGROUND In spite of the number of applications describing the use of MALDI MSI, one of its major drawbacks is the limited capability of identifying multiple compound classes directly on the same tissue section. METHODS We demonstrate the use of grid-aided, parafilm-assisted microdissection to perform MALDI MS imaging and shotgun proteomics and metabolomics in a combined workflow and using only a single tissue section. The grid is generated by microspotting acid dye 25 using a piezoelectric microspotter, and this grid was used as a guide to locate regions of interest and as an aid during manual microdissection. Subjecting the dissected pieces to the modified Folch method allows to separate the metabolites from proteins. The proteins can then be subjected to digestion under controlled conditions to improve protein identification yields. RESULTS The proof of concept experiment on rat brain generated 162 and 140 metabolite assignments from three ROIs (cerebellum, hippocampus and midbrain/hypothalamus) in positive and negative modes, respectively, and 890, 1303 and 1059 unique proteins. Integrated metabolite and protein overrepresentation analysis identified pathways associated with the biological functions of each ROI, most of which were not identified when looking at the protein and metabolite lists individually. CONCLUSIONS This combined MALDI MS imaging and multi-omics approach further extends the amount of information that can be generated from single tissue sections. GENERAL SIGNIFICANCE To the best of our knowledge, this is the first report combining both imaging and multi-omics analyses in the same workflow and on the same tissue section.
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Affiliation(s)
- Jusal Quanico
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Julien Franck
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Maxence Wisztorski
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Michel Salzet
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Isabelle Fournier
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France.
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13
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A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF. Proteomes 2016; 4:proteomes4040032. [PMID: 28248242 PMCID: PMC5260965 DOI: 10.3390/proteomes4040032] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 10/04/2016] [Accepted: 10/17/2016] [Indexed: 01/08/2023] Open
Abstract
Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.
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14
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Longuespée R, Casadonte R, Kriegsmann M, Pottier C, Picard de Muller G, Delvenne P, Kriegsmann J, De Pauw E. MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology. Proteomics Clin Appl 2016; 10:701-19. [PMID: 27188927 DOI: 10.1002/prca.201500140] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 04/07/2016] [Accepted: 05/13/2016] [Indexed: 01/16/2023]
Abstract
Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.
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Affiliation(s)
- Rémi Longuespée
- Proteopath GmbH, Trier, Germany.,Mass Spectrometry Laboratory, GIGA-Research, Department of Chemistry, University of Liège, Liège, Belgium
| | | | - Mark Kriegsmann
- Institute of Pathology, University of Heidelberg, Heidelberg, Germany
| | - Charles Pottier
- Laboratory of Experimental Pathology, GIGA-Cancer, Department of Pathology, University of Liège, Liège, Belgium
| | | | - Philippe Delvenne
- Laboratory of Experimental Pathology, GIGA-Cancer, Department of Pathology, University of Liège, Liège, Belgium
| | - Jörg Kriegsmann
- Proteopath GmbH, Trier, Germany.,MVZ for Histology, Cytology and Molecular Diagnostics Trier, Trier, Germany
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, GIGA-Research, Department of Chemistry, University of Liège, Liège, Belgium
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15
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Potential of MALDI imaging for the toxicological evaluation of environmental pollutants. J Proteomics 2016; 144:133-9. [PMID: 27178109 DOI: 10.1016/j.jprot.2016.05.008] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 04/13/2016] [Accepted: 05/08/2016] [Indexed: 01/02/2023]
Abstract
Risk assessment related to the exposure of humans to chemicals released into the environment is a major concern of our modern societies. In this context, toxicology plays a crucial role to characterize the effects of this exposure on health and identify the targets of these molecules. MALDI imaging mass spectrometry (IMS) is an enabling technology for biodistribution studies of chemicals. Although the majority of published studies are presented in a pharmacological context, the concepts discussed in this review can be applied to the toxicological evaluation of chemicals released into the environment. The major asset of IMS is the simultaneous localization and identification of a parent molecule and its metabolites without labeling and without any prior knowledge. Quantification methods developed in IMS are presented with application to an environmental pollutant. IMS is effective in the localization of chemicals and endogenous species. This opens unique perspectives for the discovery of molecular alterations in metabolites and protein biomarkers that could help for a better understanding of toxicity mechanisms. Distribution studies of agrochemicals in plants by IMS can contribute to a better understanding of their mode of action and to a more effective use of these chemicals, avoiding the current concern of environmental damage.
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16
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Lahiri S, Sun N, Buck A, Imhof A, Walch A. MALDI imaging mass spectrometry as a novel tool for detecting histone modifications in clinical tissue samples. Expert Rev Proteomics 2016; 13:275-84. [DOI: 10.1586/14789450.2016.1146598] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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17
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Wijetunge CD, Saeed I, Boughton BA, Spraggins JM, Caprioli RM, Bacic A, Roessner U, Halgamuge SK. EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data. Bioinformatics 2015; 31:3198-206. [DOI: 10.1093/bioinformatics/btv356] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Accepted: 06/04/2015] [Indexed: 11/13/2022] Open
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18
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Hanrieder J, Malmberg P, Ewing AG. Spatial neuroproteomics using imaging mass spectrometry. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2015; 1854:718-31. [PMID: 25582083 DOI: 10.1016/j.bbapap.2014.12.026] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Revised: 12/11/2014] [Accepted: 12/19/2014] [Indexed: 12/12/2022]
Abstract
The nervous system constitutes arguably the most complicated and least understood cellular network in the human body. This consequently manifests itself in the fact that the molecular bases of neurodegenerative diseases remain unknown. The limited understanding of neurobiological mechanisms relates directly to the lack of appropriate bioanalytical technologies that allow highly resolved, sensitive, specific and comprehensive molecular imaging in complex biological matrices. Imaging mass spectrometry (IMS) is an emerging technique for molecular imaging. The technique is characterized by its high chemical specificity allowing comprehensive, spatial protein and peptide profiling in situ. Imaging MS represents therefore a powerful approach for investigation of spatio-temporal protein and peptide regulations in CNS derived tissue and cells. This review aims to provide a concise overview of major developments and applications concerning imaging mass spectrometry based protein and peptide profiling in neurobiological and biomedical research. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.
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Affiliation(s)
- Jörg Hanrieder
- National Center for Imaging Mass Spectrometry, University of Gothenburg and Chalmers University of Technology, Gothenburg, Sweden; Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Institute of Neuroscience and Physiology, Department Psychiatry and Neurochemistry, University of Gothenburg, Sahlgrenska University Hospital Mölndal, Mölndal, Sweden
| | - Per Malmberg
- National Center for Imaging Mass Spectrometry, University of Gothenburg and Chalmers University of Technology, Gothenburg, Sweden; Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Andrew G Ewing
- National Center for Imaging Mass Spectrometry, University of Gothenburg and Chalmers University of Technology, Gothenburg, Sweden; Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.
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19
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Crecelius AC, Schubert US, von Eggeling F. MALDI mass spectrometric imaging meets “omics”: recent advances in the fruitful marriage. Analyst 2015; 140:5806-20. [DOI: 10.1039/c5an00990a] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI MSI) is a method that allows the investigation of the molecular content of surfaces, in particular, tissues, within its morphological context.
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Affiliation(s)
- A. C. Crecelius
- Laboratory of Organic and Macromolecular Chemistry (IOMC)
- Friedrich Schiller University Jena
- 07743 Jena
- Germany
- Jena Center for Soft Matter (JCSM)
| | - U. S. Schubert
- Laboratory of Organic and Macromolecular Chemistry (IOMC)
- Friedrich Schiller University Jena
- 07743 Jena
- Germany
- Jena Center for Soft Matter (JCSM)
| | - F. von Eggeling
- Jena Center for Soft Matter (JCSM)
- Friedrich Schiller University Jena
- 07743 Jena
- Germany
- Institute of Physical Chemistry
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20
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Schwartz M, Meyer B, Wirnitzer B, Hopf C. Standardized processing of MALDI imaging raw data for enhancement of weak analyte signals in mouse models of gastric cancer and Alzheimer's disease. Anal Bioanal Chem 2014; 407:2255-64. [PMID: 25542565 DOI: 10.1007/s00216-014-8356-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2014] [Revised: 11/16/2014] [Accepted: 11/18/2014] [Indexed: 12/17/2022]
Abstract
Conventional mass spectrometry image preprocessing methods used for denoising, such as the Savitzky-Golay smoothing or discrete wavelet transformation, typically do not only remove noise but also weak signals. Recently, memory-efficient principal component analysis (PCA) in conjunction with random projections (RP) has been proposed for reversible compression and analysis of large mass spectrometry imaging datasets. It considers single-pixel spectra in their local context and consequently offers the prospect of using information from the spectra of adjacent pixels for denoising or signal enhancement. However, little systematic analysis of key RP-PCA parameters has been reported so far, and the utility and validity of this method for context-dependent enhancement of known medically or pharmacologically relevant weak analyte signals in linear-mode matrix-assisted laser desorption/ionization (MALDI) mass spectra has not been explored yet. Here, we investigate MALDI imaging datasets from mouse models of Alzheimer's disease and gastric cancer to systematically assess the importance of selecting the right number of random projections k and of principal components (PCs) L for reconstructing reproducibly denoised images after compression. We provide detailed quantitative data for comparison of RP-PCA-denoising with the Savitzky-Golay and wavelet-based denoising in these mouse models as a resource for the mass spectrometry imaging community. Most importantly, we demonstrate that RP-PCA preprocessing can enhance signals of low-intensity amyloid-β peptide isoforms such as Aβ1-26 even in sparsely distributed Alzheimer's β-amyloid plaques and that it enables enhanced imaging of multiply acetylated histone H4 isoforms in response to pharmacological histone deacetylase inhibition in vivo. We conclude that RP-PCA denoising may be a useful preprocessing step in biomarker discovery workflows.
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Affiliation(s)
- Matthias Schwartz
- Center for Applied Research in Biomedical Mass Spectrometry (ABIMAS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163, Mannheim, Germany
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21
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Ye H, Mandal R, Catherman A, Thomas PM, Kelleher NL, Ikonomidou C, Li L. Top-down proteomics with mass spectrometry imaging: a pilot study towards discovery of biomarkers for neurodevelopmental disorders. PLoS One 2014; 9:e92831. [PMID: 24710523 PMCID: PMC3978070 DOI: 10.1371/journal.pone.0092831] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Accepted: 02/27/2014] [Indexed: 11/19/2022] Open
Abstract
In the developing mammalian brain, inhibition of NMDA receptor can induce widespread neuroapoptosis, inhibit neurogenesis and cause impairment of learning and memory. Although some mechanistic insights into adverse neurological actions of these NMDA receptor antagonists exist, our understanding of the full spectrum of developmental events affected by early exposure to these chemical agents in the brain is still limited. Here we attempt to gain insights into the impact of pharmacologically induced excitatory/inhibitory imbalance in infancy on the brain proteome using mass spectrometric imaging (MSI). Our goal was to study changes in protein expression in postnatal day 10 (P10) rat brains following neonatal exposure to the NMDA receptor antagonist dizocilpine (MK801). Analysis of rat brains exposed to vehicle or MK801 and comparison of their MALDI MS images revealed differential relative abundances of several proteins. We then identified these markers such as ubiquitin, purkinje cell protein 4 (PEP-19), cytochrome c oxidase subunits and calmodulin, by a combination of reversed-phase (RP) HPLC fractionation and top-down tandem MS platform. More in-depth large scale study along with validation experiments will be carried out in the future. Overall, our findings indicate that a brief neonatal exposure to a compound that alters excitatory/inhibitory balance in the brain has a long term effect on protein expression patterns during subsequent development, highlighting the utility of MALDI-MSI as a discovery tool for potential biomarkers.
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Affiliation(s)
- Hui Ye
- State Key Laboratory of Natural Medicines, Key Lab of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, PR China
- Department of Pharmaceutical Analysis, China Pharmaceutical University, Nanjing, PR China
- School of Pharmacy, University of Wisconsin Madison, Madison, Wisconsin, United States of America
| | - Rakesh Mandal
- Department of Neurology, University of Wisconsin Madison, Madison, Wisconsin, United States of America
| | - Adam Catherman
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, United States of America
| | - Paul M. Thomas
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, United States of America
| | - Neil L. Kelleher
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, United States of America
| | - Chrysanthy Ikonomidou
- Department of Neurology, University of Wisconsin Madison, Madison, Wisconsin, United States of America
- * E-mail: (CI); (LL)
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin Madison, Madison, Wisconsin, United States of America
- Department of Chemistry, University of Wisconsin Madison, Madison, Wisconsin, United States of America
- * E-mail: (CI); (LL)
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22
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Le Faouder J, Laouirem S, Alexandrov T, Ben-Harzallah S, Léger T, Albuquerque M, Bedossa P, Paradis V. Tumoral heterogeneity of hepatic cholangiocarcinomas revealed by MALDI imaging mass spectrometry. Proteomics 2014; 14:965-72. [DOI: 10.1002/pmic.201300463] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2013] [Revised: 01/24/2014] [Accepted: 01/27/2014] [Indexed: 01/29/2023]
Affiliation(s)
- Julie Le Faouder
- Claude Bernard Institute; Paris-Diderot University; Paris France
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
| | - Samira Laouirem
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
| | - Theodore Alexandrov
- Center for Industrial Mathematics; University of Bremen; Bremen Germany
- Steinbeis Innovation Center SCiLS Research; Bremen Germany
- SCiLS GmbH; Bremen Germany
- Skaggs School of Pharmacy and Pharmaceutical Sciences; University of California San Diego; La Jolla CA USA
| | | | - Thibaut Léger
- Mass Spectrometry Facility; Jacques Monod Institute; UMR7592-CNRS; University Paris-Diderot; Paris France
| | - Miguel Albuquerque
- Pathology Department; Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
| | - Pierre Bedossa
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
- Pathology Department; Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
| | - Valérie Paradis
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
- Pathology Department; Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
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23
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Mériaux C, Franck J, Park DB, Quanico J, Kim YH, Chung CK, Park YM, Steinbusch H, Salzet M, Fournier I. Human temporal lobe epilepsy analyses by tissue proteomics. Hippocampus 2014; 24:628-42. [DOI: 10.1002/hipo.22246] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2014] [Indexed: 01/01/2023]
Affiliation(s)
- Céline Mériaux
- Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée-EA 4550, Bât SN3, 1 étage; Université de Lille 1; Villeneuve d'Ascq France
- EURON-European Graduate School of Neuroscience, Maastricht University; Maastricht The Netherlands
| | - Julien Franck
- Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée-EA 4550, Bât SN3, 1 étage; Université de Lille 1; Villeneuve d'Ascq France
- EURON-European Graduate School of Neuroscience, Maastricht University; Maastricht The Netherlands
| | - Dan Bi Park
- Division of Mass Spectrometry Research; Korea Basic Science Institute; Ochang Chungbuk Republic of Korea
- Graduate School of Analytical Science and Technology; Chungnam National University; Daejeon Republic of Korea
| | - Jusal Quanico
- Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée-EA 4550, Bât SN3, 1 étage; Université de Lille 1; Villeneuve d'Ascq France
- EURON-European Graduate School of Neuroscience, Maastricht University; Maastricht The Netherlands
| | - Young Hye Kim
- Division of Mass Spectrometry Research; Korea Basic Science Institute; Ochang Chungbuk Republic of Korea
| | - Chun Kee Chung
- Department of Neurosurgery; College of Medicine, Seoul National University; Seoul Republic of Korea
| | - Young Mok Park
- Division of Mass Spectrometry Research; Korea Basic Science Institute; Ochang Chungbuk Republic of Korea
- Graduate School of Analytical Science and Technology; Chungnam National University; Daejeon Republic of Korea
| | - Harry Steinbusch
- EURON-European Graduate School of Neuroscience, Maastricht University; Maastricht The Netherlands
- Department of Translational Neuroscience; Faculty of Health; Medicine & Life Sciences; Maastricht University; Maastricht The Netherlands
| | - Michel Salzet
- Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée-EA 4550, Bât SN3, 1 étage; Université de Lille 1; Villeneuve d'Ascq France
- EURON-European Graduate School of Neuroscience, Maastricht University; Maastricht The Netherlands
| | - Isabelle Fournier
- Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée-EA 4550, Bât SN3, 1 étage; Université de Lille 1; Villeneuve d'Ascq France
- EURON-European Graduate School of Neuroscience, Maastricht University; Maastricht The Netherlands
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24
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Pesson M, Eymin B, De La Grange P, Simon B, Corcos L. A dedicated microarray for in-depth analysis of pre-mRNA splicing events: application to the study of genes involved in the response to targeted anticancer therapies. Mol Cancer 2014; 13:9. [PMID: 24428911 PMCID: PMC3899606 DOI: 10.1186/1476-4598-13-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2013] [Accepted: 01/09/2014] [Indexed: 12/22/2022] Open
Abstract
Alternative pre-mRNA splicing (AS) widely expands proteome diversity through the combinatorial assembly of exons. The analysis of AS on a large scale, by using splice-sensitive microarrays, is a highly efficient method to detect the majority of known and predicted alternative transcripts for a given gene. The response to targeted anticancer therapies cannot easily be anticipated without prior knowledge of the expression, by the tumor, of target proteins or genes. To analyze, in depth, transcript structure and levels for genes involved in these responses, including AKT1-3, HER1-4, HIF1A, PIK3CA, PIK3R1-2, VEGFA-D and PIR, we engineered a dedicated gene chip with coverage of an average 185 probes per gene and, especially, exon-exon junction probes. As a proof of concept, we demonstrated the ability of such a chip to detect the effects of over-expressed SRSF2 RNA binding protein on the structure and abundance of mRNA products in H358 lung cancer cells conditionally over-expressing SRSF2. Major splicing changes were observed, including in HER1/EGFR pre-mRNA, which were also seen in human lung cancer samples over-expressing the SRSF2 protein. In addition, we showed that variations in HER1/EGFR pre-mRNA splicing triggered by SRSF2 overexpression in H358 cells resulted in a drop in HER1/EGFR protein level, which correlated with increased sensitivity to gefitinib, an EGFR tyrosine kinase inhibitor. We propose, therefore, that this novel tool could be especially relevant for clinical applications, with the aim to predict the response before treatment.
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Affiliation(s)
| | | | | | | | - Laurent Corcos
- UMR INSERM U1078-UBO, Equipe ECLA, Faculté de Médecine, 22 Avenue Camille Desmoulins, 29200 Brest, France.
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25
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McDonnell LA, Walch A, Stoeckli M, Corthals GL. MSiMass list: a public database of identifications for protein MALDI MS imaging. J Proteome Res 2013; 13:1138-42. [PMID: 24313301 DOI: 10.1021/pr400620y] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The clinical application of mass spectrometry imaging has developed into a sizable subdiscipline of proteomics and metabolomics because its seamless integration with pathology enables biomarkers and biomarker profiles to be determined that can aid patient and disease stratification (diagnosis, prognosis, and response to therapy). Confident identification of the discriminating peaks remains a challenge owing to the presence of nontryptic protein fragments, large mass-to-charge ratio ions that are not efficiently fragmented via tandem mass spectrometry or a high density of isobaric species. A public database of identifications has been initiated to aid the clinical development and implementation of mass spectrometry imaging. The MSiMass list database ( www.maldi-msi.org/mass ) enables users to assign identities to the peaks observed in their experiments and provides the methods by which the identifications were obtained. In contrast with existing protein databases, this list is designed as a community effort without a formal review panel. In this concept, authors can freely enter data and can comment on existing entries. In such, the database itself is an experiment on sharing knowledge, and its ability to rapidly provide quality data will be evaluated in the future.
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Affiliation(s)
- Liam A McDonnell
- Center for Proteomics and Metabolomics, Leiden University Medical Center , Albinusdreef 2, 2333 ZA Leiden, The Netherlands
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26
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Powers TW, Jones EE, Betesh LR, Romano P, Gao P, Copland JA, Mehta AS, Drake RR. Matrix assisted laser desorption ionization imaging mass spectrometry workflow for spatial profiling analysis of N-linked glycan expression in tissues. Anal Chem 2013; 85:9799-806. [PMID: 24050758 PMCID: PMC3969840 DOI: 10.1021/ac402108x] [Citation(s) in RCA: 126] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
A new matrix assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) method to spatially profile the location and distribution of multiple N-linked glycan species in tissues is described. Application of an endoglycosidase, peptide N-glycosidase F (PNGaseF), directly on tissues followed by incubation releases N-linked glycan species amenable to detection by MALDI-IMS. The method has been designed to simultaneously profile the multiple glycan species released from intracellular organelle and cell surface glycoproteins, while maintaining histopathology compatible preparation workflows. A recombinant PNGaseF enzyme was sprayed uniformly across mouse brain tissue slides, incubated for 2 h, then sprayed with 2,5-dihydroxybenzoic acid matrix for MALDI-IMS analysis. Using this basic approach, global snapshots of major cellular N-linked glycoforms were detected, including their tissue localization and distribution, structure, and relative abundance. Off-tissue extraction and modification of glycans from similarly processed tissues and further mass spectrometry or HPLC analysis was done to assign structural designations. MALDI-IMS has primarily been utilized to spatially profile proteins, lipids, drug, and small molecule metabolites in tissues, but it has not been previously applied to N-linked glycan analysis. The translatable MALDI-IMS glycan profiling workflow described herein can readily be applied to any tissue type of interest. From a clinical diagnostics perspective, the ability to differentially profile N-glycans and correlate their molecular expression to histopathological changes can offer new approaches to identifying novel disease related targets for biomarker and therapeutic applications.
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Affiliation(s)
- Thomas W. Powers
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics and MUSC Proteomics Center, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425 USA
| | - E. Ellen Jones
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics and MUSC Proteomics Center, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425 USA
| | - Lucy R. Betesh
- Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, 4500 San Pablo Road, Jacksonville, FL 32224, USA
| | - Patrick Romano
- Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, 4500 San Pablo Road, Jacksonville, FL 32224, USA
| | - Peng Gao
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics and MUSC Proteomics Center, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425 USA
| | - John A. Copland
- Drexel University College of Medicine, Department of Microbiology and Immunology and Drexel Institute for Biotechnology and Virology, 3805 Old Easton Road, Doylestown, PA 18902, USA
| | - Anand S. Mehta
- Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, 4500 San Pablo Road, Jacksonville, FL 32224, USA
| | - Richard R. Drake
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics and MUSC Proteomics Center, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425 USA
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27
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Schey KL, Anderson DM, Rose KL. Spatially-directed protein identification from tissue sections by top-down LC-MS/MS with electron transfer dissociation. Anal Chem 2013; 85:6767-74. [PMID: 23718750 DOI: 10.1021/ac400832w] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
MALDI imaging mass spectrometry (MALDI-IMS) has become a powerful tool for localizing both small molecules and intact proteins in a wide variety of tissue samples in both normal and diseased states. Identification of imaged signals in MALDI-IMS remains a bottleneck in the analysis and limits the interpretation of underlying biology of tissue specimens. In this work, spatially directed tissue microextraction of intact proteins followed by LC-MS/MS with electron transfer dissociation (ETD) was used to identify proteins from specific locations in three tissue types; ocular lens, brain, and kidney. Detection limits were such that a 1 μL extraction volume was sufficient to deliver proteins to the LC-MS/MS instrumentation with sufficient sensitivity to detect 50-100 proteins in a single experiment. Additionally, multiple modified proteins were identified; including truncated lens proteins that would be difficult to assign to an imaged mass using a bottom-up approach. Protein separation and identification are expected to improve with advances in intact protein fractionation/chromatography and advances in interpretation algorithms leading to increased depth of proteome coverage from distinct tissue locations.
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Affiliation(s)
- Kevin L Schey
- Department of Biochemistry and Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA.
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28
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Maier SK, Hahne H, Gholami AM, Balluff B, Meding S, Schoene C, Walch AK, Kuster B. Comprehensive identification of proteins from MALDI imaging. Mol Cell Proteomics 2013; 12:2901-10. [PMID: 23782541 DOI: 10.1074/mcp.m113.027599] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a generic method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics. The analyses of ten human tissues lead to the identification of 1400 abundant and soluble proteins constituting the set of proteins detectable by MALDI IMS including >90% of all IMS biomarkers reported in the literature. Top-down analysis of the matrix proteome identified 124 mostly N- and C-terminally fragmented proteins indicating considerable protein processing activity in tissues. All protein identification data from this study as well as the IMS literature has been deposited into MaTisse, a new publically available database, which we anticipate will become a valuable resource for the IMS community.
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Affiliation(s)
- Stefan K Maier
- Chair for Proteomics and Bioanalytics, Technische Universität München, Emil Erlenmeyer Forum 5, 85354 Freising, Germany
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