1
|
Stillger MN, Li MJ, Hönscheid P, von Neubeck C, Föll MC. Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma. Proteomics 2024; 24:e2300001. [PMID: 38402423 DOI: 10.1002/pmic.202300001] [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: 06/08/2023] [Revised: 02/10/2024] [Accepted: 02/12/2024] [Indexed: 02/26/2024]
Abstract
MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.
Collapse
Affiliation(s)
- Maren Nicole Stillger
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Mujia Jenny Li
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- Institute for Pharmaceutical Sciences, University of Freiburg, Freiburg, Germany
| | - Pia Hönscheid
- Institute of Pathology, Faculty of Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases, Partner Site Dresden, German Cancer Research Center Heidelberg, Dresden, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Cläre von Neubeck
- Department of Particle Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Melanie Christine Föll
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Khoury College of Computer Sciences, Northeastern University, Boston, USA
| |
Collapse
|
2
|
Madsen JØ, Topalian SON, Jacobsen MF, Skovby T, Gernaey KV, Myerson AS, Woodley J. Raman spectroscopy and one-dimensional convolutional neural network modeling as a real-time monitoring tool for in vitro transaminase-catalyzed synthesis of a pharmaceutically relevant amine precursor. Biotechnol Prog 2024; 40:e3444. [PMID: 38539226 DOI: 10.1002/btpr.3444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/31/2024] [Accepted: 02/04/2024] [Indexed: 06/28/2024]
Abstract
Raman spectroscopy has been used to measure the concentration of a pharmaceutically relevant model amine intermediate for positive allosteric modulators of nicotinic acetylcholine receptor in a ω-transaminase-catalyzed conversion. A model based on a one-dimensional convolutional neural network was developed to translate raw data augmented Raman spectra directly into substrate concentrations, with which the conversion from ketone to amine by ω-transaminase could be determined over time. The model showed very good predictive capabilities, with R2 values higher than 0.99 for the spectra included in the modeling and 0.964 for an independent dataset. However, the model could not extrapolate outside the concentrations specified by the model. The presented work shows the potential of Raman spectroscopy as a real-time monitoring tool for biocatalytic reactions.
Collapse
Affiliation(s)
- Julie Østerby Madsen
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | | | | | - Tommy Skovby
- Chemical Production Development, H. Lundbeck A/S, Nykøbing Sjælland, Denmark
| | - Krist V Gernaey
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Allan S Myerson
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - John Woodley
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark
| |
Collapse
|
3
|
Kim H, Oh S, Lee S, Lee KS, Park Y. Recent advances in label-free imaging and quantification techniques for the study of lipid droplets in cells. Curr Opin Cell Biol 2024; 87:102342. [PMID: 38428224 DOI: 10.1016/j.ceb.2024.102342] [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: 10/24/2023] [Revised: 01/20/2024] [Accepted: 02/01/2024] [Indexed: 03/03/2024]
Abstract
Lipid droplets (LDs), once considered mere storage depots for lipids, have gained recognition for their intricate roles in cellular processes, including metabolism, membrane trafficking, and disease states like obesity and cancer. This review explores label-free imaging techniques' applications in LD research. We discuss holotomography and vibrational spectroscopic microscopy, emphasizing their potential for studying LDs without molecular labels, and we highlight the growing integration of artificial intelligence. Clinical applications in disease diagnosis and therapy are also considered.
Collapse
Affiliation(s)
- Hyeonwoo Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Seungeun Oh
- Department of Physics, Department of Cellular Molecular Medicine, University of California, San Diego, CA 2093, USA
| | - Seongsoo Lee
- Gwangju Center, Korea Basic Science Institute (KBSI), Gwangju 61751, Republic of Korea; Department of Systems Biotechnology, Chung-Ang University Anseong-si, Gyeonggi-do 17546, Republic of Korea
| | - Kwang Suk Lee
- Department of Urology, Yonsei University College of Medicine, Gangnam Severance Hospital, Seoul 06229, Republic of Korea
| | - YongKeun Park
- Department of Physics, KAIST, Daejeon 34141, Republic of Korea; KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea; Tomocube Inc., Daejeon 34109, Republic of Korea.
| |
Collapse
|
4
|
Jensen M, Liu S, Stepula E, Martella D, Birjandi AA, Farrell‐Dillon K, Chan KLA, Parsons M, Chiappini C, Chapple SJ, Mann GE, Vercauteren T, Abbate V, Bergholt MS. Opto-Lipidomics of Tissues. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2302962. [PMID: 38145965 PMCID: PMC11005704 DOI: 10.1002/advs.202302962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 11/30/2023] [Indexed: 12/27/2023]
Abstract
Lipid metabolism and signaling play pivotal functions in biology and disease development. Despite this, currently available optical techniques are limited in their ability to directly visualize the lipidome in tissues. In this study, opto-lipidomics, a new approach to optical molecular tissue imaging is introduced. The capability of vibrational Raman spectroscopy is expanded to identify individual lipids in complex tissue matrices through correlation with desorption electrospray ionization (DESI) - mass spectrometry (MS) imaging in an integrated instrument. A computational pipeline of inter-modality analysis is established to infer lipidomic information from optical vibrational spectra. Opto-lipidomic imaging of transient cerebral ischemia-reperfusion injury in a murine model of ischemic stroke demonstrates the visualization and identification of lipids in disease with high molecular specificity using Raman scattered light. Furthermore, opto-lipidomics in a handheld fiber-optic Raman probe is deployed and demonstrates real-time classification of bulk brain tissues based on specific lipid abundances. Opto-lipidomics opens a host of new opportunities to study lipid biomarkers for diagnostics, prognostics, and novel therapeutic targets.
Collapse
Affiliation(s)
- Magnus Jensen
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| | - Shiyue Liu
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
- Institute of Pharmaceutical ScienceKing's College LondonLondonSE1 9NHUK
| | - Elzbieta Stepula
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| | - Davide Martella
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| | - Anahid A. Birjandi
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| | - Keith Farrell‐Dillon
- King's British Heart Foundation Centre of Research ExcellenceSchool of Cardiovascular and Metabolic Medicine & SciencesFaculty of Life Sciences & MedicineKing's College London150 Stamford StreetLondonSE1 9NHUK
| | | | - Maddy Parsons
- Randall Centre for Cell and Molecular BiophysicsKing's College LondonLondonSE1 1ULUK
| | - Ciro Chiappini
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| | - Sarah J. Chapple
- Institute of Pharmaceutical ScienceKing's College LondonLondonSE1 9NHUK
- King's British Heart Foundation Centre of Research ExcellenceSchool of Cardiovascular and Metabolic Medicine & SciencesFaculty of Life Sciences & MedicineKing's College London150 Stamford StreetLondonSE1 9NHUK
| | - Giovanni E. Mann
- Institute of Pharmaceutical ScienceKing's College LondonLondonSE1 9NHUK
- King's British Heart Foundation Centre of Research ExcellenceSchool of Cardiovascular and Metabolic Medicine & SciencesFaculty of Life Sciences & MedicineKing's College London150 Stamford StreetLondonSE1 9NHUK
| | - Tom Vercauteren
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonWC2R 2LSUK
| | - Vincenzo Abbate
- Department of AnalyticalEnvironmental and Forensic SciencesKing's College London150 Stamford StreetLondonSE1 9NHUK
| | - Mads S. Bergholt
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| |
Collapse
|
5
|
Dhillon AK, Sharma A, Yadav V, Singh R, Ahuja T, Barman S, Siddhanta S. Raman spectroscopy and its plasmon-enhanced counterparts: A toolbox to probe protein dynamics and aggregation. WILEY INTERDISCIPLINARY REVIEWS. NANOMEDICINE AND NANOBIOTECHNOLOGY 2024; 16:e1917. [PMID: 37518952 DOI: 10.1002/wnan.1917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 06/22/2023] [Accepted: 07/06/2023] [Indexed: 08/01/2023]
Abstract
Protein unfolding and aggregation are often correlated with numerous diseases such as Alzheimer's, Parkinson's, Huntington's, and other debilitating neurological disorders. Such adverse events consist of a plethora of competing mechanisms, particularly interactions that control the stability and cooperativity of the process. However, it remains challenging to probe the molecular mechanism of protein dynamics such as aggregation, and monitor them in real-time under physiological conditions. Recently, Raman spectroscopy and its plasmon-enhanced counterparts, such as surface-enhanced Raman spectroscopy (SERS) and tip-enhanced Raman spectroscopy (TERS), have emerged as sensitive analytical tools that have the potential to perform molecular studies of functional groups and are showing significant promise in probing events related to protein aggregation. We summarize the fundamental working principles of Raman, SERS, and TERS as nondestructive, easy-to-perform, and fast tools for probing protein dynamics and aggregation. Finally, we highlight the utility of these techniques for the analysis of vibrational spectra of aggregation of proteins from various sources such as tissues, pathogens, food, biopharmaceuticals, and lastly, biological fouling to retrieve precise chemical information, which can be potentially translated to practical applications and point-of-care (PoC) devices. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > Diagnostic Nanodevices Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.
Collapse
Affiliation(s)
| | - Arti Sharma
- Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India
| | - Vikas Yadav
- Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India
| | - Ruchi Singh
- Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India
| | - Tripti Ahuja
- Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India
| | - Sanmitra Barman
- Center for Advanced Materials and Devices (CAMD), BML Munjal University, Haryana, India
| | - Soumik Siddhanta
- Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India
| |
Collapse
|
6
|
Tang W, Li Z, Zou Y, Liao J, Li B. A multimodal pipeline for image correction and registration of mass spectrometry imaging with microscopy. Anal Chim Acta 2023; 1283:341969. [PMID: 37977791 DOI: 10.1016/j.aca.2023.341969] [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: 05/28/2023] [Revised: 10/12/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023]
Abstract
The integration of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) and histology plays a pivotal role in advancing our understanding of complex heterogeneous tissues, which provides a comprehensive description of biological tissue with both wide molecule coverage and high lateral resolution. Herein, we proposed a novel strategy for the correction and registration of MALDI MSI data with hematoxylin & eosin (H&E) staining images. To overcome the challenges of discrepancies in spatial resolution towards the unification of the two imaging modalities, a deep learning-based interpolation algorithm for MALDI MSI data was constructed, which enables spatial coherence and the following orientation matching between images. Coupled with the affine transformation (AT) and the subsequent moving least squares algorithm, the two types of images from one rat brain tissue section were aligned automatically with high accuracy. Moreover, we demonstrated the practicality of the developed pipeline by projecting it to a rat cerebral ischemia-reperfusion injury model, which would help decipher the link between molecular metabolism and pathological interpretation towards microregion. This new approach offers the chance for other types of bioimaging to boost the field of multimodal image fusion.
Collapse
Affiliation(s)
- Weiwei Tang
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Zhen Li
- School of Science, China Pharmaceutical University, Nanjing, 211198, China
| | - Yuchen Zou
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Jun Liao
- School of Science, China Pharmaceutical University, Nanjing, 211198, China.
| | - Bin Li
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
| |
Collapse
|
7
|
Holtkamp HU, Aguergaray C, Prangnell K, Pook C, Amirapu S, Grey A, Simpson C, Nieuwoudt M, Jarrett P. Raman spectroscopy and mass spectrometry identifies a unique group of epidermal lipids in active discoid lupus erythematosus. Sci Rep 2023; 13:16452. [PMID: 37777584 PMCID: PMC10542761 DOI: 10.1038/s41598-023-43331-3] [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: 05/07/2023] [Accepted: 09/22/2023] [Indexed: 10/02/2023] Open
Abstract
Discoid lupus erythematosus (DLE) is the most common form of cutaneous lupus1. It can cause permanent scarring. The pathophysiology of is not fully understood. Plasmacytoid dendritic cells are found in close association with apoptotic keratinocytes inferring close cellular signalling. Matrix Associated Laser Desorption Ionisation (MALDI) combined with Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) is an exquisitely sensitive combination to examine disease processes at the cellular and molecular level. Active areas of discoid lupus erythematosus were compared with normal perilesional skin using MALDI combined with FT-ICR-MS. A unique set of biomarkers, including epidermal lipids is identified in active discoid lupus. These were assigned as sphingomyelins, phospholipids and ceramides. Additionally, increased levels of proteins from the keratin, and small proline rich family, and aromatic amino acids (tryptophan, phenylalanine, and tyrosine) in the epidermis are observed. These techniques, applied to punch biopsies of the skin, have shown a distinctive lipid profile of active discoid lupus. This profile may indicate specific lipid signalling pathways. Lipid rich microdomains (known as lipid rafts) are involved in cell signalling and lipid abnormalities have been described with systemic lupus erythematosus which correlate with disease activity.
Collapse
Affiliation(s)
- Hannah U Holtkamp
- The Photon Factory, The University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, The University of Auckland, Auckland, New Zealand
- The Dodd Walls Centre for Photonic and Quantum Technologies, Dunedin, New Zealand
| | - Claude Aguergaray
- The Photon Factory, The University of Auckland, Auckland, New Zealand
- The Dodd Walls Centre for Photonic and Quantum Technologies, Dunedin, New Zealand
- Department of Physics, The University of Auckland, Auckland, New Zealand
| | - Kalita Prangnell
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Christopher Pook
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Satya Amirapu
- Department of Anatomy and Medical Imaging, The University of Auckland, Auckland, New Zealand
| | - Angus Grey
- Department of Physiology, The University of Auckland, Auckland, New Zealand
| | - Cather Simpson
- The Photon Factory, The University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, The University of Auckland, Auckland, New Zealand
- The Dodd Walls Centre for Photonic and Quantum Technologies, Dunedin, New Zealand
- Department of Physics, The University of Auckland, Auckland, New Zealand
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington, New Zealand
| | - Michel Nieuwoudt
- The Photon Factory, The University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, The University of Auckland, Auckland, New Zealand
- The Dodd Walls Centre for Photonic and Quantum Technologies, Dunedin, New Zealand
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington, New Zealand
| | - Paul Jarrett
- Department of Dermatology, Middlemore Hospital, Auckland, New Zealand.
- Department of Medicine, The University of Auckland, Auckland, New Zealand.
| |
Collapse
|
8
|
Darvin ME. Optical Methods for Non-Invasive Determination of Skin Penetration: Current Trends, Advances, Possibilities, Prospects, and Translation into In Vivo Human Studies. Pharmaceutics 2023; 15:2272. [PMID: 37765241 PMCID: PMC10538180 DOI: 10.3390/pharmaceutics15092272] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/19/2023] [Accepted: 08/24/2023] [Indexed: 09/29/2023] Open
Abstract
Information on the penetration depth, pathways, metabolization, storage of vehicles, active pharmaceutical ingredients (APIs), and functional cosmetic ingredients (FCIs) of topically applied formulations or contaminants (substances) in skin is of great importance for understanding their interaction with skin targets, treatment efficacy, and risk assessment-a challenging task in dermatology, cosmetology, and pharmacy. Non-invasive methods for the qualitative and quantitative visualization of substances in skin in vivo are favored and limited to optical imaging and spectroscopic methods such as fluorescence/reflectance confocal laser scanning microscopy (CLSM); two-photon tomography (2PT) combined with autofluorescence (2PT-AF), fluorescence lifetime imaging (2PT-FLIM), second-harmonic generation (SHG), coherent anti-Stokes Raman scattering (CARS), and reflectance confocal microscopy (2PT-RCM); three-photon tomography (3PT); confocal Raman micro-spectroscopy (CRM); surface-enhanced Raman scattering (SERS) micro-spectroscopy; stimulated Raman scattering (SRS) microscopy; and optical coherence tomography (OCT). This review summarizes the state of the art in the use of the CLSM, 2PT, 3PT, CRM, SERS, SRS, and OCT optical methods to study skin penetration in vivo non-invasively (302 references). The advantages, limitations, possibilities, and prospects of the reviewed optical methods are comprehensively discussed. The ex vivo studies discussed are potentially translatable into in vivo measurements. The requirements for the optical properties of substances to determine their penetration into skin by certain methods are highlighted.
Collapse
|
9
|
Shaikh R, Tafintseva V, Nippolainen E, Virtanen V, Solheim J, Zimmermann B, Saarakkala S, Töyräs J, Kohler A, Afara IO. Characterisation of Cartilage Damage via Fusing Mid-Infrared, Near-Infrared, and Raman Spectroscopic Data. J Pers Med 2023; 13:1036. [PMID: 37511649 PMCID: PMC10381453 DOI: 10.3390/jpm13071036] [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: 05/19/2023] [Revised: 06/19/2023] [Accepted: 06/22/2023] [Indexed: 07/30/2023] Open
Abstract
Mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR), and Raman spectroscopy are all well-established analytical techniques in biomedical applications. Since they provide complementary chemical information, we aimed to determine whether combining them amplifies their strengths and mitigates their weaknesses. This study investigates the feasibility of the fusion of MIR, NIR, and Raman spectroscopic data for characterising articular cartilage integrity. Osteochondral specimens from bovine patellae were subjected to mechanical and enzymatic damage, and then MIR, NIR, and Raman data were acquired from the damaged and control specimens. We assessed the capacity of individual spectroscopic methods to classify the samples into damage or control groups using Partial Least Squares Discriminant Analysis (PLS-DA). Multi-block PLS-DA was carried out to assess the potential of data fusion by combining the dataset by applying two-block (MIR and NIR, MIR and Raman, NIR and Raman) and three-block approaches (MIR, NIR, and Raman). The results of the one-block models show a higher classification accuracy for NIR (93%) and MIR (92%) than for Raman (76%) spectroscopy. In contrast, we observed the highest classification efficiency of 94% and 93% for the two-block (MIR and NIR) and three-block models, respectively. The detailed correlative analysis of the spectral features contributing to the discrimination in the three-block models adds considerably more insight into the molecular origin of cartilage damage.
Collapse
Affiliation(s)
- Rubina Shaikh
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, D07 XT95 Dublin, Ireland
| | - Valeria Tafintseva
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway
| | - Ervin Nippolainen
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Vesa Virtanen
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Johanne Solheim
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway
| | - Boris Zimmermann
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway
| | - Simo Saarakkala
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
- Research Unit of Health Sciences and Technology, University of Oulu, 90220 Oulu, Finland
| | - Juha Töyräs
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
- Science Service Center, Kuopio University Hospital, 70210 Kuopio, Finland
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisban, QLD 4072, Australia
| | - Achim Kohler
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway
| | - Isaac O Afara
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisban, QLD 4072, Australia
| |
Collapse
|
10
|
Yu H, Yang Z, Fu S, Zhang Y, Panneerselvamc R, Li B, Zhang L, Chen Z, Wang X, Li J. Intelligent convolution neural network-assisted SERS to realize highly accurate identification of six pathogenic Vibrio. Chem Commun (Camb) 2023; 59:5779-5782. [PMID: 37096554 DOI: 10.1039/d3cc01129a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
Based on label-free SERS technology, the relationship between the Raman signals of pathogenic Vibrio microorganisms and purine metabolites was analyzed in detail. A deep learning CNN model was successfully developed, achieving a high accuracy rate of 99.7% in the identification of six typical pathogenic Vibrio species within 15 minutes, providing a new method for pathogen identification.
Collapse
Affiliation(s)
- Hui Yu
- College of Materials, State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, College of Energy, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China.
| | - Zhilan Yang
- College of Materials, State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, College of Energy, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China.
| | - Shiying Fu
- College of Materials, State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, College of Energy, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China.
| | - Yuejiao Zhang
- College of Materials, State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, College of Energy, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China.
| | | | - Baoqiang Li
- State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China.
| | - Lin Zhang
- State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China.
| | - Zehui Chen
- Xiamen City Center for Disease Control and Prevention, Xiamen 361005, China.
| | - Xin Wang
- College of Materials, State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, College of Energy, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China.
| | - Jianfeng Li
- College of Materials, State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, College of Energy, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China.
| |
Collapse
|
11
|
Pena-Rodríguez E, García-Berrocoso T, Vázquez Fernández E, Otero-Espinar FJ, Abian J, Fernández-Campos F. Monitoring dexamethasone skin biodistribution with ex vivo MALDI-TOF mass spectrometry imaging and confocal Raman microscopy. Int J Pharm 2023; 636:122808. [PMID: 36889415 DOI: 10.1016/j.ijpharm.2023.122808] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 03/08/2023]
Abstract
Two of the most promising techniques in terms of ex vivo skin imaging and quantifying are confocal Raman microscopy and MALDI-TOF mass spectrometry imaging (MALDI-TOF MSI). Both techniques were set up, and the semiquantitative skin biodistribution of previously developed dexamethasone (DEX) loaded lipomers was compared using Benzalkonium chloride (BAK) as a tracer of the nanoparticles. In MALDI-TOF MSI, DEX was derivatised with GirT (DEX-GirT) and the semiquantitative biodistribution of both DEX-GirT and BAK was successfully obtained. The amount of DEX measured by confocal Raman microscopy was higher than that measured by MALDI-TOF MSI, but MALDI-TOF MSI proved to be a more suitable technique for tracing BAK. An absorption-promoting tendency of DEX loaded in lipomers versus a free-DEX solution was observed in confocal Raman microscopy. The higher spatial resolution of confocal Raman microscopy (350 nm) with respect to MALDI-TOF MSI (50 μm) allowed to observe specific skin structures like hair follicles. Nevertheless, the faster sampling rate of MALDI-TOF-MSI, permitted the analysis of larger tissue regions. In conclusion, both techniques allowed to simultaneously analyze semiquantitative data together with qualitative images of biodistribution, which is a very helpful tool when designing nanoparticles that accumulate in specific anatomical regions.
Collapse
Affiliation(s)
- Eloy Pena-Rodríguez
- Laboratory Reig Jofre, R&D Department, 08970, Sant Joan Despí, Barcelona, Spain.
| | - Teresa García-Berrocoso
- Biological and Environmental Proteomics, Institut d'Investigacions Biomèdiques de Barcelona, Consejo Superior de Investigaciones Científicas (IIBB-CSIC), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Laboratorio de Proteómica CSIC/Universitat Autònoma de Barcelona (UAB), IIBB-CSIC, Barcelona, Spain
| | - Ezequiel Vázquez Fernández
- Pharmacology, Pharmacy and Pharmaceutical Technology Department, Faculty of Pharmacy, University of Santiago de Compostela (USC), Santiago de Compostela, Spain
| | - Francisco J Otero-Espinar
- Pharmacology, Pharmacy and Pharmaceutical Technology Department, Faculty of Pharmacy, University of Santiago de Compostela (USC), Santiago de Compostela, Spain; Parqueasil Group, Health Research Institute of Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Institute of Materials (iMATUS), University of Santiago de Compostela (USC), Santiago de Compostela, Spain.
| | - Joaquin Abian
- Biological and Environmental Proteomics, Institut d'Investigacions Biomèdiques de Barcelona, Consejo Superior de Investigaciones Científicas (IIBB-CSIC), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Laboratorio de Proteómica CSIC/Universitat Autònoma de Barcelona (UAB), IIBB-CSIC, Barcelona, Spain
| | | |
Collapse
|
12
|
Rončević A, Koruga N, Soldo Koruga A, Debeljak Ž, Rončević R, Turk T, Kretić D, Rotim T, Krivdić Dupan Z, Troha D, Perić M, Šimundić T. MALDI Imaging Mass Spectrometry of High-Grade Gliomas: A Review of Recent Progress and Future Perspective. Curr Issues Mol Biol 2023; 45:838-851. [PMID: 36826000 PMCID: PMC9955680 DOI: 10.3390/cimb45020055] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/22/2022] [Accepted: 01/14/2023] [Indexed: 01/20/2023] Open
Abstract
Glioblastoma (GBM) is the most common malignancy of the brain with a relatively short median survival and high mortality. Advanced age, high socioeconomic status, exposure to ionizing radiation, and other factors have been correlated with an increased incidence of GBM, while female sex hormones, history of allergies, and frequent use of specific drugs might exert protective effects against this disease. However, none of these explain the pathogenesis of GBM. The most recent WHO classification of CNS tumors classifies neoplasms based on their histopathological and molecular characteristics. Modern laboratory techniques, such as matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry, enable the comprehensive metabolic analysis of the tissue sample. MALDI imaging is able to characterize the spatial distribution of a wide array of biomolecules in a sample, in combination with histological features, without sacrificing the tissue integrity. In this review, we first provide an overview of GBM epidemiology, risk, and protective factors, as well as the recent WHO classification of CNS tumors. We then provide an overview of mass spectrometry workflow, with a focus on MALDI imaging, and recent advances in cancer research. Finally, we conclude the review with studies of GBM that utilized MALDI imaging and offer our perspective on future research.
Collapse
Affiliation(s)
- Alen Rončević
- Department of Neurosurgery, University Hospital Center Osijek, 31000 Osijek, Croatia
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Correspondence: ; Tel.: +385-98-169-8481
| | - Nenad Koruga
- Department of Neurosurgery, University Hospital Center Osijek, 31000 Osijek, Croatia
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
| | - Anamarija Soldo Koruga
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Neurology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Željko Debeljak
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Clinical Institute of Laboratory Diagnostics, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Robert Rončević
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Diagnostic and Interventional Radiology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Tajana Turk
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Diagnostic and Interventional Radiology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Domagoj Kretić
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Diagnostic and Interventional Radiology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Tatjana Rotim
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Diagnostic and Interventional Radiology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Zdravka Krivdić Dupan
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Diagnostic and Interventional Radiology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Damir Troha
- Department of Radiology, Vinkovci General Hospital, 31000 Osijek, Croatia
| | - Marija Perić
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Clinical Cytology, University Hospital Center Osijek, 31000 Osijek, Croatia
| | - Tihana Šimundić
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Department of Nephrology, University Hospital Center Osijek, 31000 Osijek, Croatia
| |
Collapse
|
13
|
Azam KSF, Ryabchykov O, Bocklitz T. A Review on Data Fusion of Multidimensional Medical and Biomedical Data. Molecules 2022; 27:7448. [PMID: 36364272 PMCID: PMC9655963 DOI: 10.3390/molecules27217448] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/19/2022] [Accepted: 10/21/2022] [Indexed: 08/05/2024] Open
Abstract
Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis and prognosis. In this paper, we present an overview of the advances achieved over the last decades in data fusion approaches in the context of the medical and biomedical fields. We collected approaches for interpreting multiple sources of data in different combinations: image to image, image to biomarker, spectra to image, spectra to spectra, spectra to biomarker, and others. We found that the most prevalent combination is the image-to-image fusion and that most data fusion approaches were applied together with deep learning or machine learning methods.
Collapse
Affiliation(s)
- Kazi Sultana Farhana Azam
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| |
Collapse
|
14
|
Koster HJ, Guillen-Perez A, Gomez-Diaz JS, Navas-Moreno M, Birkeland AC, Carney RP. Fused Raman spectroscopic analysis of blood and saliva delivers high accuracy for head and neck cancer diagnostics. Sci Rep 2022; 12:18464. [PMID: 36323705 PMCID: PMC9630497 DOI: 10.1038/s41598-022-22197-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 10/11/2022] [Indexed: 11/25/2022] Open
Abstract
As a rapid, label-free, non-destructive analytical measurement requiring little to no sample preparation, Raman spectroscopy shows great promise for liquid biopsy cancer detection and diagnosis. We carried out Raman analysis and mass spectrometry of plasma and saliva from more than 50 subjects in a cohort of head and neck cancer patients and benign controls (e.g., patients with benign oral masses). Unsupervised data models were built to assess diagnostic performance. Raman spectra collected from either biofluid provided moderate performance to discriminate cancer samples. However, by fusing together the Raman spectra of plasma and saliva for each patient, subsequent analytical models delivered an impressive sensitivity, specificity, and accuracy of 96.3%, 85.7%, and 91.7%, respectively. We further confirmed that the metabolites driving the differences in Raman spectra for our models are among the same ones that drive mass spectrometry models, unifying the two techniques and validating the underlying ability of Raman to assess metabolite composition. This study bolsters the relevance of Raman to provide additive value by probing the unique chemical compositions across biofluid sources. Ultimately, we show that a simple data augmentation routine of fusing plasma and saliva spectra provided significantly higher clinical value than either biofluid alone, pushing forward the potential of clinical translation of Raman spectroscopy for liquid biopsy cancer diagnostics.
Collapse
Affiliation(s)
- Hanna J. Koster
- grid.27860.3b0000 0004 1936 9684Biomedical Engineering, University of California, Davis, CA USA
| | - Antonio Guillen-Perez
- grid.27860.3b0000 0004 1936 9684Electrical and Computer Engineering, University of California, Davis, CA USA
| | - Juan Sebastian Gomez-Diaz
- grid.27860.3b0000 0004 1936 9684Electrical and Computer Engineering, University of California, Davis, CA USA
| | | | - Andrew C. Birkeland
- grid.27860.3b0000 0004 1936 9684Department of Otolaryngology, University of California, CA Davis, USA
| | - Randy P. Carney
- grid.27860.3b0000 0004 1936 9684Biomedical Engineering, University of California, Davis, CA USA
| |
Collapse
|
15
|
Tolstik E, Gongalsky MB, Dierks J, Brand T, Pernecker M, Pervushin NV, Maksutova DE, Gonchar KA, Samsonova JV, Kopeina G, Sivakov V, Osminkina LA, Lorenz K. Raman and fluorescence micro-spectroscopy applied for the monitoring of sunitinib-loaded porous silicon nanocontainers in cardiac cells. Front Pharmacol 2022; 13:962763. [PMID: 36016563 PMCID: PMC9397571 DOI: 10.3389/fphar.2022.962763] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 07/05/2022] [Indexed: 11/17/2022] Open
Abstract
Nanomaterials are a central pillar in modern medicine. They are thought to optimize drug delivery, enhance therapeutic efficacy, and reduce side-effects. To foster this technology, analytical methods are needed to validate not only the localization and distribution of these nanomaterials, but also their compatibility with cells, drugs, and drug release. In the present work, we assessed nanoparticles based on porous silicon (pSiNPs) loaded with the clinically used tyrosine kinase inhibitor sunitinib for their effectiveness of drug delivery, release, and toxicity in colon cancer cells (HCT 116 cells) and cardiac myoblast cells (H9c2) using Raman micro-spectroscopy, high-resolution fluorescence microscopy, along with biological methods for toxicological effects. We produced pSiNPs with a size of about 100 nm by grinding mesoporous silicon layers. pSiNPs allowed an effective loading of sunitinib due to their high porosity. Photoluminescence properties of the nanoparticles within the visible spectrum allowed the visualization of their uptake in cardiac cells. Raman micro-spectroscopy allowed not only the detection of the uptake and distribution of pSiNPs within the cells via a characteristic silicon Raman band at about 518–520 cm−1, but also the localization of the drug based on its characteristic molecular fingerprints. Cytotoxicity studies by Western blot analyses of apoptotic marker proteins such as caspase-3, and the detection of apoptosis by subG1-positive cell fractions in HCT 116 and MTT analyses in H9c2 cells, suggest a sustained release of sunitinib from pSiNPs and delayed cytotoxicity of sunitinib in HCT 116 cells. The analyses in cardiac cells revealed that pSiNPs are well tolerated and that they may even protect from toxic effects in these cells to some extent. Analyses of the integrity of mitochondrial networks as an early indicator for apoptotic cellular effects seem to validate these observations. Our study suggests pSiNPs-based nanocontainers for efficient and safe drug delivery and Raman micro-spectroscopy as a reliable method for their detection and monitoring. Thus, the herein presented nanocontainers and analytical methods have the potential to allow an efficient advancement of nanoparticles for targeted and sustained intracellular drug release that is of need, e.g., in chronic diseases and for the prevention of cardiac toxicity.
Collapse
Affiliation(s)
- E. Tolstik
- Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., Dortmund, Germany
- *Correspondence: E. Tolstik, elen.tolstik@isas; L. A. Osminkina, ; K. Lorenz,
| | - M. B. Gongalsky
- Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia
| | - J. Dierks
- Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., Dortmund, Germany
| | - T. Brand
- Institute of Pharmacology and Toxicology, University of Würzburg, Würzburg, Germany
| | - M. Pernecker
- Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., Dortmund, Germany
| | - N. V. Pervushin
- Lomonosov Moscow State University, Faculty of Medicine, Moscow, Russia
| | - D. E. Maksutova
- Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia
| | - K. A. Gonchar
- Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia
| | - J. V. Samsonova
- Lomonosov Moscow State University, Faculty of Chemistry, Moscow, Russia
| | - G. Kopeina
- Lomonosov Moscow State University, Faculty of Medicine, Moscow, Russia
| | - V. Sivakov
- Leibniz Institute of Photonic Technology, Department Functional Interfaces, Jena, Germany
| | - L. A. Osminkina
- Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia
- Institute for Biological Instrumentation of Russian Academy of Sciences, Moscow, Russia
- *Correspondence: E. Tolstik, elen.tolstik@isas; L. A. Osminkina, ; K. Lorenz,
| | - K. Lorenz
- Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., Dortmund, Germany
- Institute of Pharmacology and Toxicology, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center, University Hospital of Würzburg, Würzburg, Germany
- *Correspondence: E. Tolstik, elen.tolstik@isas; L. A. Osminkina, ; K. Lorenz,
| |
Collapse
|
16
|
Grujcic V, Taylor GT, Foster RA. One Cell at a Time: Advances in Single-Cell Methods and Instrumentation for Discovery in Aquatic Microbiology. Front Microbiol 2022; 13:881018. [PMID: 35677911 PMCID: PMC9169044 DOI: 10.3389/fmicb.2022.881018] [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: 02/22/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Studying microbes from a single-cell perspective has become a major theme and interest within the field of aquatic microbiology. One emerging trend is the unfailing observation of heterogeneity in activity levels within microbial populations. Wherever researchers have looked, intra-population variability in biochemical composition, growth rates, and responses to varying environmental conditions has been evident and probably reflect coexisting genetically distinct strains of the same species. Such observations of heterogeneity require a shift away from bulk analytical approaches and development of new methods or adaptation of existing techniques, many of which were first pioneered in other, unrelated fields, e.g., material, physical, and biomedical sciences. Many co-opted approaches were initially optimized using model organisms. In a field with so few cultivable models, method development has been challenging but has also contributed tremendous insights, breakthroughs, and stimulated curiosity. In this perspective, we present a subset of methods that have been effectively applied to study aquatic microbes at the single-cell level. Opportunities and challenges for innovation are also discussed. We suggest future directions for aquatic microbiological research that will benefit from open access to sophisticated instruments and highly interdisciplinary collaborations.
Collapse
Affiliation(s)
- Vesna Grujcic
- Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden
| | - Gordon T Taylor
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, United States
| | - Rachel A Foster
- Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden
| |
Collapse
|
17
|
Tuck M, Grélard F, Blanc L, Desbenoit N. MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives. Front Chem 2022; 10:904688. [PMID: 35615316 PMCID: PMC9124797 DOI: 10.3389/fchem.2022.904688] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 04/14/2022] [Indexed: 01/22/2023] Open
Abstract
Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.
Collapse
|
18
|
Iakab SA, Baquer G, Lafuente M, Pina MP, Ramírez JL, Ràfols P, Correig-Blanchar X, García-Altares M. SALDI-MS and SERS Multimodal Imaging: One Nanostructured Substrate to Rule Them Both. Anal Chem 2022; 94:2785-2793. [PMID: 35102738 PMCID: PMC8851428 DOI: 10.1021/acs.analchem.1c04118] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
Imaging techniques
based on mass spectrometry or spectroscopy methods
inform in situ about the chemical composition of
biological tissues or organisms, but they are sometimes limited by
their specificity, sensitivity, or spatial resolution. Multimodal
imaging addresses these limitations by combining several imaging modalities;
however, measuring the same sample with the same preparation using
multiple imaging techniques is still uncommon due to the incompatibility
between substrates, sample preparation protocols, and data formats.
We present a multimodal imaging approach that employs a gold-coated
nanostructured silicon substrate to couple surface-assisted laser
desorption/ionization mass spectrometry (SALDI-MS) and surface-enhanced
Raman spectroscopy (SERS). Our approach integrates both imaging modalities
by using the same substrate, sample preparation, and data analysis
software on the same sample, allowing the coregistration of both images.
We transferred molecules from clean fingertips and fingertips covered
with plasticine modeling clay onto our nanostructure and analyzed
their chemical composition and distribution by SALDI-MS and SERS.
Multimodal analysis located the traces of plasticine on fingermarks
and provided chemical information on the composition of the clay.
Our multimodal approach effectively combines the advantages of mass
spectrometry and vibrational spectroscopy with the signal enhancing
abilities of our nanostructured substrate.
Collapse
Affiliation(s)
- Stefania-Alexandra Iakab
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| | - Gerard Baquer
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain
| | - Marta Lafuente
- Instituto de Nanociencia y Materiales de Aragón (INMA), CSIC-Universidad de Zaragoza, Zaragoza 50009, Spain.,Departamento de Ingeniería Química y Tecnologías del Medio Ambiente, Universidad de Zaragoza, Campus Río Ebro-Edificio I+D+i, C/Mariano Esquillor s/n, Zaragoza 50018, Spain
| | - Maria Pilar Pina
- Instituto de Nanociencia y Materiales de Aragón (INMA), CSIC-Universidad de Zaragoza, Zaragoza 50009, Spain.,Departamento de Ingeniería Química y Tecnologías del Medio Ambiente, Universidad de Zaragoza, Campus Río Ebro-Edificio I+D+i, C/Mariano Esquillor s/n, Zaragoza 50018, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN, Madrid 28029, Spain
| | - José Luis Ramírez
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain
| | - Pere Ràfols
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| | - Xavier Correig-Blanchar
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus 43204, Spain
| | - María García-Altares
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| |
Collapse
|
19
|
Balluff B, Heeren RM, Race AM. An overview of image registration for aligning mass spectrometry imaging with clinically relevant imaging modalities. J Mass Spectrom Adv Clin Lab 2022; 23:26-38. [PMID: 35156074 PMCID: PMC8821033 DOI: 10.1016/j.jmsacl.2021.12.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 12/13/2021] [Accepted: 12/15/2021] [Indexed: 01/25/2023] Open
Abstract
Mass spectrometry imaging (MSI) is a powerful molecular imaging technique. Integration with other imaging modalities is essential in clinical MSI. Image integration is performed by image registration techniques. Technical potential of image registration in MSI has not been fully exploited. Roadmap proposed to improve registration accuracy.
Mass spectrometry imaging (MSI) is used in many aspects of clinical research, including pharmacokinetics, toxicology, personalised medicine, and surgical decision-making. Maximising its potential requires the spatial integration of MSI images with imaging data from existing clinical imaging modalities, such as histology and MRI. To ensure that the information is properly integrated, all contributing images must be accurately aligned. This process is called image registration and is the focus of this review. In light of the ever-increasing spatial resolution of MSI instrumentation and a diversification of multi-modal MSI studies (e.g., spatial omics, 3D-MSI), the accuracy, versatility, and precision of image registration must increase accordingly. We review the application of image registration to align MSI data with different clinically relevant ex vivo and in vivo imaging techniques. Based on this, we identify steps in the current image registration processes where there is potential for improvement. Finally, we propose a roadmap for community efforts to address these challenges in order to increase registration quality and help MSI to fully exploit its multi-modal potential.
Collapse
|
20
|
Lee PY, Yeoh Y, Omar N, Pung YF, Lim LC, Low TY. Molecular tissue profiling by MALDI imaging: recent progress and applications in cancer research. Crit Rev Clin Lab Sci 2021; 58:513-529. [PMID: 34615421 DOI: 10.1080/10408363.2021.1942781] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Matrix-assisted laser desorption/ionization (MALDI) imaging is an emergent technology that has been increasingly adopted in cancer research. MALDI imaging is capable of providing global molecular mapping of the abundance and spatial information of biomolecules directly in the tissues without labeling. It enables the characterization of a wide spectrum of analytes, including proteins, peptides, glycans, lipids, drugs, and metabolites and is well suited for both discovery and targeted analysis. An advantage of MALDI imaging is that it maintains tissue integrity, which allows correlation with histological features. It has proven to be a valuable tool for probing tumor heterogeneity and has been increasingly applied to interrogate molecular events associated with cancer. It provides unique insights into both the molecular content and spatial details that are not accessible by other techniques, and it has allowed considerable progress in the field of cancer research. In this review, we first provide an overview of the MALDI imaging workflow and approach. We then highlight some useful applications in various niches of cancer research, followed by a discussion of the challenges, recent developments and future prospect of this technique in the field.
Collapse
Affiliation(s)
- Pey Yee Lee
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Yeelon Yeoh
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Nursyazwani Omar
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Yuh-Fen Pung
- Division of Biomedical Science, University of Nottingham Malaysia, Selangor, Malaysia
| | - Lay Cheng Lim
- Department of Life Sciences, School of Pharmacy, International Medical University (IMU), Kuala Lumpur, Malaysia
| | - Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| |
Collapse
|
21
|
Yu S, Li X, Lu W, Li H, Fu YV, Liu F. Analysis of Raman Spectra by Using Deep Learning Methods in the Identification of Marine Pathogens. Anal Chem 2021; 93:11089-11098. [PMID: 34339167 DOI: 10.1021/acs.analchem.1c00431] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
The need for efficient and accurate identification of pathogens in seafood and the environment has become increasingly urgent, given the current global pandemic. Traditional methods are not only time consuming but also lead to sample wastage. Here, we have proposed two new methods that involve Raman spectroscopy combined with a long short-term memory (LSTM) neural network and compared them with a method using a normal convolutional neural network (CNN). We used eight strains isolated from the marine organism Urechis unicinctus, including four kinds of pathogens. After the models were configured and trained, the LSTM methods that we proposed achieved average isolation-level accuracies exceeding 94%, not only meeting the requirement for identification but also indicating that the proposed methods were faster and more accurate than the normal CNN models. Finally, through a computational approach, we designed a loss function to explore the mechanism reflected by the Raman data, finding the Raman segments that most likely exhibited the characteristics of nucleic acids. These novel experimental results provide insights for developing additional deep learning methods to accurately analyze complex Raman data.
Collapse
Affiliation(s)
- Shixiang Yu
- Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China.,University of the Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Xin Li
- Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China.,University of the Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Weilai Lu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, P. R. China.,University of the Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Hanfei Li
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, P. R. China.,University of the Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yu Vincent Fu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, P. R. China.,University of the Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Fanghua Liu
- Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China.,National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, P. R. China
| |
Collapse
|
22
|
Petersen M, Yu Z, Lu X. Application of Raman Spectroscopic Methods in Food Safety: A Review. BIOSENSORS 2021; 11:187. [PMID: 34201167 PMCID: PMC8229164 DOI: 10.3390/bios11060187] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 05/31/2021] [Accepted: 06/04/2021] [Indexed: 12/15/2022]
Abstract
Food detection technologies play a vital role in ensuring food safety in the supply chains. Conventional food detection methods for biological, chemical, and physical contaminants are labor-intensive, expensive, time-consuming, and often alter the food samples. These limitations drive the need of the food industry for developing more practical food detection tools that can detect contaminants of all three classes. Raman spectroscopy can offer widespread food safety assessment in a non-destructive, ease-to-operate, sensitive, and rapid manner. Recent advances of Raman spectroscopic methods further improve the detection capabilities of food contaminants, which largely boosts its applications in food safety. In this review, we introduce the basic principles of Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), and micro-Raman spectroscopy and imaging; summarize the recent progress to detect biological, chemical, and physical hazards in foods; and discuss the limitations and future perspectives of Raman spectroscopic methods for food safety surveillance. This review is aimed to emphasize potential opportunities for applying Raman spectroscopic methods as a promising technique for food safety detection.
Collapse
Affiliation(s)
- Marlen Petersen
- Food, Nutrition and Health Program, Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada; (M.P.); (Z.Y.)
| | - Zhilong Yu
- Food, Nutrition and Health Program, Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada; (M.P.); (Z.Y.)
- Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Saint-Anne-de-Bellevue, QC H9X 3V9, Canada
| | - Xiaonan Lu
- Food, Nutrition and Health Program, Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada; (M.P.); (Z.Y.)
- Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Saint-Anne-de-Bellevue, QC H9X 3V9, Canada
| |
Collapse
|
23
|
Iakab S, Ràfols P, Correig-Blanchar X, García-Altares M. Perspective on Multimodal Imaging Techniques Coupling Mass Spectrometry and Vibrational Spectroscopy: Picturing the Best of Both Worlds. Anal Chem 2021; 93:6301-6310. [PMID: 33856207 PMCID: PMC8491157 DOI: 10.1021/acs.analchem.0c04986] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 04/07/2021] [Indexed: 01/19/2023]
Abstract
Studies on complex biological phenomena often combine two or more imaging techniques to collect high-quality comprehensive data directly in situ, preserving the biological context. Mass spectrometry imaging (MSI) and vibrational spectroscopy imaging (VSI) complement each other in terms of spatial resolution and molecular information. In the past decade, several combinations of such multimodal strategies arose in research fields as diverse as microbiology, cancer, and forensics, overcoming many challenges toward the unification of these techniques. Here we focus on presenting the advantages and challenges of multimodal imaging from the point of view of studying biological samples as well as giving a perspective on the upcoming trends regarding this topic. The latest efforts in the field are discussed, highlighting the purpose of the technique for clinical applications.
Collapse
Affiliation(s)
- Stefania
Alexandra Iakab
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| | - Pere Ràfols
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| | - Xavier Correig-Blanchar
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| | - María García-Altares
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| |
Collapse
|
24
|
Klein D, Breuch R, Reinmüller J, Engelhard C, Kaul P. Rapid detection and discrimination of food-related bacteria using IR-microspectroscopy in combination with multivariate statistical analysis. Talanta 2021; 232:122424. [PMID: 34074410 DOI: 10.1016/j.talanta.2021.122424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/30/2021] [Accepted: 04/09/2021] [Indexed: 10/21/2022]
Abstract
Spoilage microorganisms are of great concern for the food industry. While traditional culturing methods for spoilage microorganism detection are laborious and time-consuming, the development of early detection methods has gained a lot of interest in the last decades. In this work a rapid and non-destructive detection and discrimination method of eight important food-related microorganisms (Bacillus subtilis DSM 10, Bacillus coagulans DSM 1, Escherichia coli K12 DSM 498, Escherichia coli TOP10, Micrococcus luteus DSM 20030, Pseudomonas fluorescens DSM 4358, Pseudomonas fluorescens DSM 50090 and Bacillus thuringiensis israelensis DSM 5724) based on IR-microspectroscopy and chemometric evaluation was developed. Sampling was carried out directly from the surface to be tested, without the need for sample preparation such as purification, singulation, centrifugation and washing steps, as an efficient and inexpensive blotting technique using the sample carrier. IR spectra were recorded directly after the blotting from the surface of the sample carrier without any further pretreatments. A combination of data preprocessing, principal component analysis and canonical discriminant analysis was found to be suitable. The spectral range from 400 to 1750 cm-1 of the IR-microspectrosopic data was determined to be highly sensitive to the time after incubation and sample thickness, resulting in a high standard deviation. Therefore, this area was excluded from the evaluation in favor of the meaningfulness of the chemometric model and, thus, only the spectral range of specific -CH/-NH/-OH excitations (2815-3680 cm-1) was used for model development. This study showed that the differentiation of food-related microorganisms on genera, species and strain level is feasible. A leave-one-out cross-validation of the training data set showed 100% accuracy. The classification of the ungrouped test data showed with an accuracy of 94.5% that, despite the large biological variance of the analytes such as different times after incubation and the presented sampling (including its variance), a robust and meaningful model for the differentiation of food-related bacteria could be developed by data preprocessing and subsequent chemometric evaluation.
Collapse
Affiliation(s)
- Daniel Klein
- Bonn-Rhein-Sieg University of Applied Sciences, Institute of Safety and Security Research, von Liebig-Straße 20, 53359, Rheinbach, Germany.
| | - René Breuch
- Bonn-Rhein-Sieg University of Applied Sciences, Institute of Safety and Security Research, von Liebig-Straße 20, 53359, Rheinbach, Germany
| | - Jessica Reinmüller
- Bonn-Rhein-Sieg University of Applied Sciences, Institute of Safety and Security Research, von Liebig-Straße 20, 53359, Rheinbach, Germany
| | - Carsten Engelhard
- Department of Chemistry and Biology, University of Siegen, Adolf-Reichwein-Str. 2, D-57076, Germany; Center of Micro- and Nanochemistry and Engineering, University of Siegen, Adolf-Reichwein-Str. 2, D-57076, Siegen, Germany
| | - Peter Kaul
- Bonn-Rhein-Sieg University of Applied Sciences, Institute of Safety and Security Research, von Liebig-Straße 20, 53359, Rheinbach, Germany
| |
Collapse
|
25
|
Grélard F, Legland D, Fanuel M, Arnaud B, Foucat L, Rogniaux H. Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images. BMC Bioinformatics 2021; 22:56. [PMID: 33557761 PMCID: PMC7869484 DOI: 10.1186/s12859-020-03954-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 12/30/2020] [Indexed: 11/29/2022] Open
Abstract
Background Mass spectrometry imaging (MSI) is a family of acquisition techniques producing images of the distribution of molecules in a sample, without any prior tagging of the molecules. This makes it a very interesting technique for exploratory research. However, the images are difficult to analyze because the enclosed data has high dimensionality, and their content does not necessarily reflect the shape of the object of interest. Conversely, magnetic resonance imaging (MRI) scans reflect the anatomy of the tissue. MRI also provides complementary information to MSI, such as the content and distribution of water. Results We propose a new workflow to merge the information from 2D MALDI–MSI and MRI images. Our workflow can be applied to large MSI datasets in a limited amount of time. Moreover, the workflow is fully automated and based on deterministic methods which ensures the reproducibility of the results. Our methods were evaluated and compared with state-of-the-art methods. Results show that the images are combined precisely and in a time-efficient manner. Conclusion Our workflow reveals molecules which co-localize with water in biological images. It can be applied on any MSI and MRI datasets which satisfy a few conditions: same regions of the shape enclosed in the images and similar intensity distributions.
Collapse
Affiliation(s)
- Florent Grélard
- UR BIA, INRAE, 44316, Nantes, France. .,BIBS Facility, INRAE, 44316, Nantes, France.
| | - David Legland
- UR BIA, INRAE, 44316, Nantes, France.,BIBS Facility, INRAE, 44316, Nantes, France
| | - Mathieu Fanuel
- UR BIA, INRAE, 44316, Nantes, France.,BIBS Facility, INRAE, 44316, Nantes, France
| | - Bastien Arnaud
- UR BIA, INRAE, 44316, Nantes, France.,BIBS Facility, INRAE, 44316, Nantes, France
| | - Loïc Foucat
- UR BIA, INRAE, 44316, Nantes, France.,BIBS Facility, INRAE, 44316, Nantes, France
| | - Hélène Rogniaux
- UR BIA, INRAE, 44316, Nantes, France.,BIBS Facility, INRAE, 44316, Nantes, France
| |
Collapse
|
26
|
Neumann EK, Djambazova KV, Caprioli RM, Spraggins JM. Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:2401-2415. [PMID: 32886506 PMCID: PMC9278956 DOI: 10.1021/jasms.0c00232] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.
Collapse
Affiliation(s)
- Elizabeth K Neumann
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Katerina V Djambazova
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
| | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
- Department of Pharmacology, Vanderbilt University, 2220 Pierce Avenue, Nashville, Tennessee 37232, United States
- Department of Medicine, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Jeffrey M Spraggins
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
| |
Collapse
|
27
|
Tuck M, Blanc L, Touti R, Patterson NH, Van Nuffel S, Villette S, Taveau JC, Römpp A, Brunelle A, Lecomte S, Desbenoit N. Multimodal Imaging Based on Vibrational Spectroscopies and Mass Spectrometry Imaging Applied to Biological Tissue: A Multiscale and Multiomics Review. Anal Chem 2020; 93:445-477. [PMID: 33253546 DOI: 10.1021/acs.analchem.0c04595] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Michael Tuck
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| | - Landry Blanc
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| | - Rita Touti
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| | - Nathan Heath Patterson
- Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232-8575, United States
| | - Sebastiaan Van Nuffel
- Materials Research Institute, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Sandrine Villette
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| | - Jean-Christophe Taveau
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| | - Andreas Römpp
- Bioanalytical Sciences and Food Analysis, University of Bayreuth, Universitätsstraße 30, 95440 Bayreuth, Germany
| | - Alain Brunelle
- Laboratoire d'Archéologie Moléculaire et Structurale, LAMS UMR 8220, CNRS, Sorbonne Université, 4 Place Jussieu, 75005 Paris, France
| | - Sophie Lecomte
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| | - Nicolas Desbenoit
- Institut de Chimie & Biologie des Membranes & des Nano-objets, CBMN UMR 5248, CNRS, Université de Bordeaux, 1 Allée Geoffroy Saint-Hilaire, 33600 Pessac, France
| |
Collapse
|
28
|
Iakab SA, Sementé L, García-Altares M, Correig X, Ràfols P. Raman2imzML converts Raman imaging data into the standard mass spectrometry imaging format. BMC Bioinformatics 2020; 21:448. [PMID: 33036551 PMCID: PMC7547406 DOI: 10.1186/s12859-020-03789-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 09/29/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Multimodal imaging that combines mass spectrometry imaging (MSI) with Raman imaging is a rapidly developing multidisciplinary analytical method used by a growing number of research groups. Computational tools that can visualize and aid the analysis of datasets by both techniques are in demand. RESULTS Raman2imzML was developed as an open-source converter that transforms Raman imaging data into imzML, a standardized common data format created and adopted by the mass spectrometry community. We successfully converted Raman datasets to imzML and visualized Raman images using open-source software designed for MSI applications. CONCLUSION Raman2imzML enables both MSI and Raman images to be visualized using the same file format and the same software for a straightforward exploratory imaging analysis.
Collapse
Affiliation(s)
- Stefania Alexandra Iakab
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), 28029, Madrid, Spain
| | - Lluc Sementé
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain
| | - María García-Altares
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain. .,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), 28029, Madrid, Spain.
| | - Xavier Correig
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), 28029, Madrid, Spain.,Institut d'Investigació Sanitària Pere Virgili, Tarragona, Spain
| | - Pere Ràfols
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain
| |
Collapse
|
29
|
Perry WJ, Weiss A, Van de Plas R, Spraggins JM, Caprioli RM, Skaar EP. Integrated molecular imaging technologies for investigation of metals in biological systems: A brief review. Curr Opin Chem Biol 2020; 55:127-135. [PMID: 32087551 PMCID: PMC7237308 DOI: 10.1016/j.cbpa.2020.01.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 11/25/2019] [Accepted: 01/14/2020] [Indexed: 02/08/2023]
Abstract
Metals play an essential role in biological systems and are required as structural or catalytic co-factors in many proteins. Disruption of the homeostatic control and/or spatial distributions of metals can lead to disease. Imaging technologies have been developed to visualize elemental distributions across a biological sample. Measurement of elemental distributions by imaging mass spectrometry and imaging X-ray fluorescence are increasingly employed with technologies that can assess histological features and molecular compositions. Data from several modalities can be interrogated as multimodal images to correlate morphological, elemental, and molecular properties. Elemental and molecular distributions have also been axially resolved to achieve three-dimensional volumes, dramatically increasing the biological information. In this review, we provide an overview of recent developments in the field of metal imaging with an emphasis on multimodal studies in two and three dimensions. We specifically highlight studies that present technological advancements and biological applications of how metal homeostasis affects human health.
Collapse
Affiliation(s)
- William J Perry
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, 37232, USA; Department of Chemistry, Vanderbilt University, Nashville, TN, 37232, USA; Vanderbilt Institute for Infection, Immunology and Inflammation, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Andy Weiss
- Vanderbilt Institute for Infection, Immunology and Inflammation, Vanderbilt University Medical Center, Nashville, TN, 37232, USA; Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Raf Van de Plas
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, 37232, USA; Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands; Department of Biochemistry, Vanderbilt University, Nashville, TN, 37232, USA
| | - Jeffrey M Spraggins
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, 37232, USA; Department of Chemistry, Vanderbilt University, Nashville, TN, 37232, USA; Department of Biochemistry, Vanderbilt University, Nashville, TN, 37232, USA
| | - Richard M Caprioli
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, 37232, USA; Department of Chemistry, Vanderbilt University, Nashville, TN, 37232, USA; Department of Biochemistry, Vanderbilt University, Nashville, TN, 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37232, USA; Department of Pharmacology, Vanderbilt University, Nashville, TN, 37232, USA; Department of Medicine, Vanderbilt University, Nashville, TN, 37232, USA
| | - Eric P Skaar
- Vanderbilt Institute for Infection, Immunology and Inflammation, Vanderbilt University Medical Center, Nashville, TN, 37232, USA; Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
| |
Collapse
|
30
|
Bergholt MS, Serio A, Albro MB. Raman Spectroscopy: Guiding Light for the Extracellular Matrix. Front Bioeng Biotechnol 2019; 7:303. [PMID: 31737621 PMCID: PMC6839578 DOI: 10.3389/fbioe.2019.00303] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 10/16/2019] [Indexed: 12/12/2022] Open
Abstract
The extracellular matrix (ECM) consists of a complex mesh of proteins, glycoproteins, and glycosaminoglycans, and is essential for maintaining the integrity and function of biological tissues. Imaging and biomolecular characterization of the ECM is critical for understanding disease onset and for the development of novel, disease-modifying therapeutics. Recently, there has been a growing interest in the use of Raman spectroscopy to characterize the ECM. Raman spectroscopy is a label-free vibrational technique that offers unique insights into the structure and composition of tissues and cells at the molecular level. This technique can be applied across a broad range of ECM imaging applications, which encompass in vitro, ex vivo, and in vivo analysis. State-of-the-art confocal Raman microscopy imaging now enables label-free assessments of the ECM structure and composition in tissue sections with a remarkably high degree of biomolecular specificity. Further, novel fiber-optic instrumentation has opened up for clinical in vivo ECM diagnostic measurements across a range of tissue systems. A palette of advanced computational methods based on multivariate statistics, spectral unmixing, and machine learning can be applied to Raman data, allowing for the extraction of specific biochemical information of the ECM. Here, we review Raman spectroscopy techniques for ECM characterizations over a variety of exciting applications and tissue systems, including native tissue assessments (bone, cartilage, cardiovascular), regenerative medicine quality assessments, and diagnostics of disease states. We further discuss the challenges in the widespread adoption of Raman spectroscopy in biomedicine. The results of the latest discovery-driven Raman studies are summarized, illustrating the current and potential future applications of Raman spectroscopy in biomedicine.
Collapse
Affiliation(s)
- Mads S. Bergholt
- Centre for Craniofacial and Regenerative Biology, King's College London, London, United Kingdom
| | - Andrea Serio
- Centre for Craniofacial and Regenerative Biology, King's College London, London, United Kingdom
| | - Michael B. Albro
- Department of Mechanical Engineering, Boston University, Boston, MA, United States
| |
Collapse
|