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Khadem H, Mangini M, Farazpour S, De Luca AC. Correlative Raman Imaging: Development and Cancer Applications. BIOSENSORS 2024; 14:324. [PMID: 39056600 PMCID: PMC11274409 DOI: 10.3390/bios14070324] [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: 05/24/2024] [Revised: 06/26/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
Despite extensive research efforts, cancer continues to stand as one of the leading causes of death on a global scale. To gain profound insights into the intricate mechanisms underlying cancer onset and progression, it is imperative to possess methodologies that allow the study of cancer cells at the single-cell level, focusing on critical parameters such as cell morphology, metabolism, and molecular characteristics. These insights are essential for effectively discerning between healthy and cancerous cells and comprehending tumoral progression. Recent advancements in microscopy techniques have significantly advanced the study of cancer cells, with Raman microspectroscopy (RM) emerging as a particularly powerful tool. Indeed, RM can provide both biochemical and spatial details at the single-cell level without the need for labels or causing disruptions to cell integrity. Moreover, RM can be correlated with other microscopy techniques, creating a synergy that offers a spectrum of complementary insights into cancer cell morphology and biology. This review aims to explore the correlation between RM and other microscopy techniques such as confocal fluoresce microscopy (CFM), atomic force microscopy (AFM), digital holography microscopy (DHM), and mass spectrometry imaging (MSI). Each of these techniques has their own strengths, providing different perspectives and parameters about cancer cell features. The correlation between information from these various analysis methods is a valuable tool for physicians and researchers, aiding in the comprehension of cancer cell morphology and biology, unraveling mechanisms underlying cancer progression, and facilitating the development of early diagnosis and/or monitoring cancer progression.
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Affiliation(s)
- Hossein Khadem
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
| | - Maria Mangini
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
| | - Somayeh Farazpour
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
| | - Anna Chiara De Luca
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
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2
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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.
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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
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3
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Weaver AA, Jia J, Cutri AR, Madukoma CS, Vaerewyck CM, Bohn PW, Shrout JD. Alkyl quinolones mediate heterogeneous colony biofilm architecture that improves community-level survival. J Bacteriol 2024; 206:e0009524. [PMID: 38564677 PMCID: PMC11025328 DOI: 10.1128/jb.00095-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 03/11/2024] [Indexed: 04/04/2024] Open
Abstract
Bacterial communities exhibit complex self-organization that contributes to their survival. To better understand the molecules that contribute to transforming a small number of cells into a heterogeneous surface biofilm community, we studied acellular aggregates, structures seen by light microscopy in Pseudomonas aeruginosa colony biofilms using light microscopy and chemical imaging. These structures differ from cellular aggregates, cohesive clusters of cells important for biofilm formation, in that they are visually distinct from cells using light microscopy and are reliant on metabolites for assembly. To investigate how these structures benefit a biofilm community we characterized three recurrent types of acellular aggregates with distinct geometries that were each abundant in specific areas of these biofilms. Alkyl quinolones (AQs) were essential for the formation of all aggregate types with AQ signatures outside the aggregates below the limit of detection. These acellular aggregates spatially sequester AQs and differentiate the biofilm space. However, the three types of aggregates showed differing properties in their size, associated cell death, and lipid content. The largest aggregate type co-localized with spatially confined cell death that was not mediated by Pf4 bacteriophage. Biofilms lacking AQs were absent of localized cell death but exhibited increased, homogeneously distributed cell death. Thus, these AQ-rich aggregates regulate metabolite accessibility, differentiate regions of the biofilm, and promote survival in biofilms.IMPORTANCEPseudomonas aeruginosa is an opportunistic pathogen with the ability to cause infection in the immune-compromised. It is well established that P. aeruginosa biofilms exhibit resilience that includes decreased susceptibility to antimicrobial treatment. This work examines the self-assembled heterogeneity in biofilm communities studying acellular aggregates, regions of condensed matter requiring alkyl quinolones (AQs). AQs are important to both virulence and biofilm formation. Aggregate structures described here spatially regulate the accessibility of these AQs, differentiate regions of the biofilm community, and despite their association with autolysis, correlate with improved P. aeruginosa colony biofilm survival.
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Affiliation(s)
- Abigail A. Weaver
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - Jin Jia
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| | - Allison R. Cutri
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| | - Chinedu S. Madukoma
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - Catherine M. Vaerewyck
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - Paul W. Bohn
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, USA
| | - Joshua D. Shrout
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA
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4
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Chen LC, Lee C, Hsu CC. Towards developing a matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) compatible tissue expansion protocol. Anal Chim Acta 2024; 1297:342345. [PMID: 38438227 DOI: 10.1016/j.aca.2024.342345] [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: 09/19/2023] [Revised: 01/05/2024] [Accepted: 02/04/2024] [Indexed: 03/06/2024]
Abstract
Mass spectrometry imaging (MSI) visualizes spatial distribution of molecules in a biological tissue. However, compared with traditional microscopy-based imaging, conventional MSI is limited to its spatial resolution, resulting in difficulties in identifying detailed tissue morphological characters, such as lesion boundary or nanoscale structures. On the other hand, expansion microscopy, a tissue expansion method widely used in optical imaging to improve morphological details, has great potential to solve insufficient spatial resolution in mass spectrometry imaging (MSI). However, expansion microscopy was not originally designed for MSI, resulting in problems while combining expansion microscopy and MSI such as expanded sample fragility, vacuum stability and molecule loss during sample preparation. In this research we developed a MALDI MSI compatible expansion protocol by adjusting sample preparation methods during tissue expansion, successfully combining expansion microscopy with MSI. After tissue expansion the expanded sample can be readily applied to MALDI MSI sample preparation and further data acquisition. The MALDI MSI compatible expansion protocol has great potential to be widely applied in MALDI MSI sample preparation to facilitate improvement of MSI spatial resolution.
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Affiliation(s)
- Li-Cyun Chen
- Department of Chemistry, National Taiwan University, No.1, Sec. 4, Roosevelt Road, Taipei City, 106319, Taiwan.
| | - Chuping Lee
- Department of Chemistry, National Chung Hsing University, No.145, Xingda Rd., South Dist., Taichung City, 40227, Taiwan.
| | - Cheng-Chih Hsu
- Department of Chemistry, National Taiwan University, No.1, Sec. 4, Roosevelt Road, Taipei City, 106319, Taiwan.
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5
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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.
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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
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6
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Belsey NA, Dexter A, Vorng JL, Tsikritsis D, Nikula CJ, Murta T, Tiddia MV, Zhang J, Gurdak E, Trindade GF, Gilmore IS, Page L, Roper CS, Guy RH, Bettex MB. Visualisation of drug distribution in skin using correlative optical spectroscopy and mass spectrometry imaging. J Control Release 2023; 364:79-89. [PMID: 37858627 DOI: 10.1016/j.jconrel.2023.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/05/2023] [Accepted: 10/16/2023] [Indexed: 10/21/2023]
Abstract
A correlative methodology for label-free chemical imaging of soft tissue has been developed, combining non-linear optical spectroscopies and mass spectrometry to achieve sub-micron spatial resolution and critically improved drug detection sensitivity. The approach was applied to visualise the kinetics of drug reservoir formation within human skin following in vitro topical treatment with a commercial diclofenac gel. Non-destructive optical spectroscopic techniques, namely stimulated Raman scattering, second harmonic generation and two photon fluorescence microscopies, were used to provide chemical and structural contrast. The same tissue sections were subsequently analysed by secondary ion mass spectrometry, which offered higher sensitivity for diclofenac detection throughout the epidermis and dermis. A method was developed to combine the optical and mass spectrometric datasets using image registration techniques. The label-free, high-resolution visualisation of tissue structure coupled with sensitive chemical detection offers a powerful method for drug biodistribution studies in the skin that impact directly on topical pharmaceutical product development.
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Affiliation(s)
- Natalie A Belsey
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK; School of Chemistry & Chemical Engineering, University of Surrey, Guildford GU2 7XH, UK.
| | - Alex Dexter
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Jean-Luc Vorng
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Dimitrios Tsikritsis
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Chelsea J Nikula
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Teresa Murta
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Maria-Vitalia Tiddia
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Junting Zhang
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Elzbieta Gurdak
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Gustavo F Trindade
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Ian S Gilmore
- Chemical & Biological Sciences Department, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Leanne Page
- Charles River Laboratories Edinburgh Ltd, Tranent, East Lothian EH33 2NE, UK
| | - Clive S Roper
- Charles River Laboratories Edinburgh Ltd, Tranent, East Lothian EH33 2NE, UK; Roper Toxicology Consulting Limited, Edinburgh EH3 6AD, UK
| | - Richard H Guy
- Department of Life Sciences, University of Bath, BA2 7AY, UK
| | - Mila Boncheva Bettex
- Haleon CH SARL, Route de l'Etraz 2, Case postale 1279, 1260 Nyon 1, Switzerland.
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7
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Yang E, Kim JH, Tressler CM, Shen XE, Brown DR, Johnson CC, Hahm TH, Barman I, Glunde K. RaMALDI: Enabling simultaneous Raman and MALDI imaging of the same tissue section. Biosens Bioelectron 2023; 239:115597. [PMID: 37597501 PMCID: PMC10544780 DOI: 10.1016/j.bios.2023.115597] [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: 06/05/2023] [Revised: 08/02/2023] [Accepted: 08/11/2023] [Indexed: 08/21/2023]
Abstract
Multimodal tissue imaging techniques that integrate two complementary modalities are powerful discovery tools for unraveling biological processes and identifying biomarkers of disease. Combining Raman spectroscopic imaging (RSI) and matrix-assisted laser-desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain fused images with the advantages of both modalities has the potential of providing spatially resolved, sensitive, specific biomolecular information, but has so far involved two separate sample preparations, or even consecutive tissue sections for RSI and MALDI MSI, resulting in images with inherent disparities. We have developed RaMALDI, a streamlined, integrated, multimodal imaging workflow of RSI and MALDI MSI, performed on a single tissue section with one sample preparation protocol. We show that RaMALDI imaging of various tissues effectively integrates molecular information acquired from both RSI and MALDI MSI of the same sample, which will drive discoveries in cell biology, biomedicine, and pathology, and advance tissue diagnostics.
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Affiliation(s)
- Ethan Yang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Jeong Hee Kim
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Caitlin M Tressler
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Xinyi Elaine Shen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Dalton R Brown
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Cole C Johnson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Tae-Hun Hahm
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Ishan Barman
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
| | - Kristine Glunde
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Departments of Oncology and Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
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8
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Avard RC, Broad ML, Zandkarimi F, Devanny AJ, Hammer JL, Yu K, Guzman A, Kaufman LJ. DISC-3D: dual-hydrogel system enhances optical imaging and enables correlative mass spectrometry imaging of invading multicellular tumor spheroids. Sci Rep 2023; 13:12383. [PMID: 37524722 PMCID: PMC10390472 DOI: 10.1038/s41598-023-38699-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 07/13/2023] [Indexed: 08/02/2023] Open
Abstract
Multicellular tumor spheroids embedded in collagen I matrices are common in vitro systems for the study of solid tumors that reflect the physiological environment and complexities of the in vivo environment. While collagen I environments are physiologically relevant and permissive of cell invasion, studying spheroids in such hydrogels presents challenges to key analytical assays and to a wide array of imaging modalities. While this is largely due to the thickness of the 3D hydrogels that in other samples can typically be overcome by sectioning, because of their highly porous nature, collagen I hydrogels are very challenging to section, especially in a manner that preserves the hydrogel network including cell invasion patterns. Here, we describe a novel method for preparing and cryosectioning invasive spheroids in a two-component (collagen I and gelatin) matrix, a technique we term dual-hydrogel in vitro spheroid cryosectioning of three-dimensional samples (DISC-3D). DISC-3D does not require cell fixation, preserves the architecture of invasive spheroids and their surroundings, eliminates imaging challenges, and allows for use of techniques that have infrequently been applied in three-dimensional spheroid analysis, including super-resolution microscopy and mass spectrometry imaging.
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Affiliation(s)
- Rachel C Avard
- Department of Chemistry, Columbia University, New York, NY, 10027, USA
| | - Megan L Broad
- Department of Chemistry, Columbia University, New York, NY, 10027, USA
- Department of Chemistry, Cardiff University, Cardiff, CF10 3AT, Wales, UK
| | | | | | - Joseph L Hammer
- Department of Chemistry, Columbia University, New York, NY, 10027, USA
| | - Karen Yu
- Department of Chemistry, Columbia University, New York, NY, 10027, USA
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Asja Guzman
- Department of Biological Sciences, Columbia University, New York, NY, 10027, USA
| | - Laura J Kaufman
- Department of Chemistry, Columbia University, New York, NY, 10027, USA.
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Guo L, Zhu J, Wang K, Cheng KK, Xu J, Dong L, Xu X, Chen C, Shah M, Peng Z, Wang J, Cai Z, Dong J. Multimodal Image Fusion Offers Better Spatial Resolution for Mass Spectrometry Imaging. Anal Chem 2023. [PMID: 37296503 DOI: 10.1021/acs.analchem.3c02002] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
High-resolution reconstruction has attracted increasing research interest in mass spectrometry imaging (MSI), but it remains a challenging ill-posed problem. In the present study, we proposed a deep learning model to fuse multimodal images to enhance the spatial resolution of MSI data, namely, DeepFERE. Hematoxylin and eosin (H&E) stain microscopy imaging was used to pose constraints in the process of high-resolution reconstruction to alleviate the ill-posedness. A novel model architecture was designed to achieve multi-task optimization by incorporating multi-modal image registration and fusion in a mutually reinforced framework. Experimental results demonstrated that the proposed DeepFERE model is able to produce high-resolution reconstruction images with rich chemical information and a detailed structure on both visual inspection and quantitative evaluation. In addition, our method was found to be able to improve the delimitation of the boundary between cancerous and para-cancerous regions in the MSI image. Furthermore, the reconstruction of low-resolution spatial transcriptomics data demonstrated that the developed DeepFERE model may find wider applications in biomedical fields.
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Affiliation(s)
- Lei Guo
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Jinyu Zhu
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Keqi Wang
- Institute of Big Data Science and Industry, Shanxi University, Taiyuan 030006, China
| | - Kian-Kai Cheng
- Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor 81310, Malaysia
| | - Jingjing Xu
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Liheng Dong
- School of Computing and Data Science, Xiamen University Malaysia, Sepang 43600, Malaysia
| | - Xiangnan Xu
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
| | - Can Chen
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, China
| | - Mudassir Shah
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Zhangxiao Peng
- Department of Molecular Oncology, Eastern Hepatobiliary Surgery Hospital & National Centre for Liver Cancer, Navy Military Medical University, Shanghai 200438, China
| | - Jianing Wang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Jiyang Dong
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
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10
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Liu J, Hu W, Han Y, Nie H. Recent advances in mass spectrometry imaging of single cells. Anal Bioanal Chem 2023:10.1007/s00216-023-04774-9. [PMID: 37269305 DOI: 10.1007/s00216-023-04774-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/18/2023] [Accepted: 05/23/2023] [Indexed: 06/05/2023]
Abstract
Mass spectrometry imaging (MSI) is a sensitive, specific, label-free imaging analysis technique that can simultaneously obtain the spatial distribution, relative content, and structural information of hundreds of biomolecules in cells and tissues, such as lipids, small drug molecules, peptides, proteins, and other compounds. The study of molecular mapping of single cells can reveal major scientific issues such as the activity pattern of living organisms, disease pathogenesis, drug-targeted therapy, and cellular heterogeneity. Applying MSI technology to the molecular mapping of single cells can provide new insights and ideas for the study of single-cell metabolomics. This review aims to provide an informative resource for those in the MSI community who are interested in single-cell imaging. Particularly, we discuss advances in imaging schemes and sample preparation, instrumentation improvements, data processing and analysis, and 3D MSI over the past few years that have allowed MSI to emerge as a powerful technique in the molecular imaging of single cells. Also, we highlight some of the most cutting-edge studies in single-cell MSI, demonstrating the future potential of single-cell MSI. Visualizing molecular distribution at the single-cell or even sub-cellular level can provide us with richer cell information, which strongly contributes to advancing research fields such as biomedicine, life sciences, pharmacodynamic testing, and metabolomics. At the end of the review, we summarize the current development of single-cell MSI technology and look into the future of this technology.
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Affiliation(s)
- Jikun Liu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, 102249, China
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
- Analytical Instrumental Center, Peking University, Beijing, 100871, China
| | - Wenya Hu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, 102249, China
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
- Analytical Instrumental Center, Peking University, Beijing, 100871, China
| | - Yehua Han
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, 102249, China.
| | - Honggang Nie
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
- Analytical Instrumental Center, Peking University, Beijing, 100871, China.
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11
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Woodhouse N, Majer J, Marshall P, Hood S, Notingher I. Quantification of Drugs in Brain and Liver Mimetic Tissue Models Using Raman Spectroscopy. APPLIED SPECTROSCOPY 2023; 77:246-260. [PMID: 36320126 PMCID: PMC10034474 DOI: 10.1177/00037028221139494] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
Quantitative analysis of drug delivery with in biological systems is an integral challenge in drug development. Analytical techniques are important for assessing both drug target delivery, target action, and drug toxicology. Using mimetic tissue models, we have investigated the efficacy of Raman spectroscopy in quantitative detection of alkyne group and deuterated drugs in rat brain and rat liver tissue models. Lasers with 671 nm and 785 nm wavelengths were assessed for their feasibility in this application due to opposing relative benefits and disadvantages. Thin tissue sections have been tested as a practical means of reducing autofluorescent background by minimizing out-of-focus tissue and therefore maximizing photobleaching rates. Alkyne-tagged drugs were quantitatively measured at 18 ± 5 μg/g drug/tissue mass ratio in rat brain and at 34 ± 6 μg/g in rat liver. Quantification calibration curves were generated for a range of concentrations from 0-500 μg/g. These results show the potential of Raman spectroscopy as a diffraction-limited spatially resolved imaging technique for assessing drug delivery in tissue applications.
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Affiliation(s)
- Nathan Woodhouse
- School of Physics and Astronomy,
University
of Nottingham, Nottingham, UK
| | | | | | | | - Ioan Notingher
- School of Physics and Astronomy,
University
of Nottingham, Nottingham, UK
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12
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Liu H, Pan Y, Xiong C, Han J, Wang X, Chen J, Nie Z. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) for in situ analysis of endogenous small molecules in biological samples. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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13
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Hu H, Laskin J. Emerging Computational Methods in Mass Spectrometry Imaging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2203339. [PMID: 36253139 PMCID: PMC9731724 DOI: 10.1002/advs.202203339] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/17/2022] [Indexed: 05/10/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.
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Affiliation(s)
- Hang Hu
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
| | - Julia Laskin
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
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14
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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.
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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
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15
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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: 3] [Impact Index Per Article: 1.5] [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.
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16
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Müller WH, Verdin A, De Pauw E, Malherbe C, Eppe G. Surface-assisted laser desorption/ionization mass spectrometry imaging: A review. MASS SPECTROMETRY REVIEWS 2022; 41:373-420. [PMID: 33174287 PMCID: PMC9292874 DOI: 10.1002/mas.21670] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 05/04/2023]
Abstract
In the last decades, surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) has attracted increasing interest due to its unique capabilities, achievable through the nanostructured substrates used to promote the analyte desorption/ionization. While the most widely recognized asset of SALDI-MS is the untargeted analysis of small molecules, this technique also offers the possibility of targeted approaches. In particular, the implementation of SALDI-MS imaging (SALDI-MSI), which is the focus of this review, opens up new opportunities. After a brief discussion of the nomenclature and the fundamental mechanisms associated with this technique, which are still highly controversial, the analytical strategies to perform SALDI-MSI are extensively discussed. Emphasis is placed on the sample preparation but also on the selection of the nanosubstrate (in terms of chemical composition and morphology) as well as its functionalization possibilities for the selective analysis of specific compounds in targeted approaches. Subsequently, some selected applications of SALDI-MSI in various fields (i.e., biomedical, biological, environmental, and forensic) are presented. The strengths and the remaining limitations of SALDI-MSI are finally summarized in the conclusion and some perspectives of this technique, which has a bright future, are proposed in this section.
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Affiliation(s)
- Wendy H. Müller
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Alexandre Verdin
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Cedric Malherbe
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Gauthier Eppe
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
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17
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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.
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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
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18
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Capturing the third dimension in drug discovery: Spatially-resolved tools for interrogation of complex 3D cell models. Biotechnol Adv 2021; 55:107883. [PMID: 34875362 DOI: 10.1016/j.biotechadv.2021.107883] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 11/22/2021] [Accepted: 11/30/2021] [Indexed: 02/07/2023]
Abstract
Advanced three-dimensional (3D) cell models have proven to be capable of depicting architectural and microenvironmental features of several tissues. By providing data of higher physiological and pathophysiological relevance, 3D cell models have been contributing to a better understanding of human development, pathology onset and progression mechanisms, as well as for 3D cell-based assays for drug discovery. Nonetheless, the characterization and interrogation of these tissue-like structures pose major challenges on the conventional analytical methods, pushing the development of spatially-resolved technologies. Herein, we review recent advances and pioneering technologies suitable for the interrogation of multicellular 3D models, while capable of retaining biological spatial information. We focused on imaging technologies and omics tools, namely transcriptomics, proteomics and metabolomics. The advantages and shortcomings of these novel methodologies are discussed, alongside the opportunities to intertwine data from the different tools.
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19
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Do H, Madukoma CS, Sundaresan V, Shrout JD, Hoffman AJ, Bohn PW. Spatiotemporal distribution of chemical signatures exhibited by Myxococcus xanthus in response to metabolic conditions. Anal Bioanal Chem 2021; 414:1691-1698. [PMID: 34850244 DOI: 10.1007/s00216-021-03795-6] [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: 07/26/2021] [Revised: 11/16/2021] [Accepted: 11/18/2021] [Indexed: 11/25/2022]
Abstract
Myxococcus xanthus is a common soil bacterium with a complex life cycle, which is known for production of secondary metabolites. However, little is known about the effects of nutrient availability on M. xanthus metabolite production. In this study, we utilize confocal Raman microscopy (CRM) to examine the spatiotemporal distribution of chemical signatures secreted by M. xanthus and their response to varied nutrient availability. Ten distinct spectral features are observed by CRM from M. xanthus grown on nutrient-rich medium. However, when M. xanthus is constrained to grow under nutrient-limited conditions, by starving it of casitone, it develops fruiting bodies, and the accompanying Raman microspectra are dramatically altered. The reduced metabolic state engendered by the absence of casitone in the medium is associated with reduced, or completely eliminated, features at 1140 cm-1, 1560 cm-1, and 1648 cm-1. In their place, a feature at 1537 cm-1 is observed, this feature being tentatively assigned to a transitional phase important for cellular adaptation to varying environmental conditions. In addition, correlating principal component analysis heat maps with optical images illustrates how fruiting bodies in the center co-exist with motile cells at the colony edge. While the metabolites responsible for these Raman features are not completely identified, three M. xanthus peaks at 1004, 1151, and 1510 cm-1 are consistent with the production of lycopene. Thus, a combination of CRM imaging and PCA enables the spatial mapping of spectral signatures of secreted factors from M. xanthus and their correlation with metabolic conditions.
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Affiliation(s)
- Hyein Do
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Chinedu S Madukoma
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Vignesh Sundaresan
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Joshua D Shrout
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA.,Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Anthony J Hoffman
- Department of Electrical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Paul W Bohn
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, 46556, USA. .,Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
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20
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Cao T, Weaver AA, Baek S, Jia J, Shrout JD, Bohn PW. Depth distributions of signaling molecules in Pseudomonas aeruginosa biofilms mapped by confocal Raman microscopy. J Chem Phys 2021; 154:204201. [PMID: 34241187 DOI: 10.1063/5.0052785] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Pseudomonas aeruginosa is an opportunistic human pathogen implicated in both acute and chronic diseases, which resists antibiotic treatment, in part by forming physical and chemical barriers such as biofilms. Here, we explore the use of confocal Raman imaging to characterize the three-dimensional (3D) spatial distribution of alkyl quinolones (AQs) in P. aeruginosa biofilms by reconstructing depth profiles from hyperspectral Raman data. AQs are important to quorum sensing (QS), virulence, and other actions of P. aeruginosa. Three-dimensional distributions of three different AQs (PQS, HQNO, and HHQ) were observed to have a significant depth, suggesting 3D anisotropic shapes-sheet-like rectangular solids for HQNO and extended cylinders for PQS. Similar to observations from 2D imaging studies, spectral features characteristic of AQs (HQNO or PQS) and the amide I vibration from peptide-containing species were found to correlate with the PQS cylinders typically located at the tips of the HQNO rectangular solids. In the QS-deficient mutant lasIrhlI, a small globular component was observed, whose highly localized nature and similarity in size to a P. aeruginosa cell suggest that the feature arises from HHQ localized in the vicinity of the cell from which it was secreted. The difference in the shapes and sizes of the aggregates of the three AQs in wild-type and mutant P. aeruginosa is likely related to the difference in the cellular response to growth conditions, environmental stress, metabolic levels, or other structural and biochemical variations inside biofilms. This study provides a new route to characterizing the 3D structure of biofilms and shows the potential of confocal Raman imaging to elucidate the nature of heterogeneous biofilms in all three spatial dimensions. These capabilities should be applicable as a tool in studies of infectious diseases.
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Affiliation(s)
- Tianyuan Cao
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Abigail A Weaver
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Seol Baek
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Jin Jia
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Joshua D Shrout
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Paul W Bohn
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
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21
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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.
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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
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22
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Pieters VM, Co IL, Wu NC, McGuigan AP. Applications of Omics Technologies for Three-Dimensional In Vitro Disease Models. Tissue Eng Part C Methods 2021; 27:183-199. [PMID: 33406987 DOI: 10.1089/ten.tec.2020.0300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, multiomics, and integrated modalities, have greatly contributed to our understanding of various diseases by enabling researchers to probe the molecular wiring of cellular systems in a high-throughput and precise manner. With the development of tissue-engineered three-dimensional (3D) in vitro disease models, such as organoids and spheroids, there is potential of integrating omics technologies with 3D disease models to elucidate the complex links between genotype and phenotype. These 3D disease models have been used to model cancer, infectious disease, toxicity, neurological disorders, and others. In this review, we provide an overview of omics technologies, highlight current and emerging studies, discuss the associated experimental design considerations, barriers and challenges of omics technologies, and provide an outlook on the future applications of omics technologies with 3D models. Overall, this review aims to provide a valuable resource for tissue engineers seeking to leverage omics technologies for diving deeper into biological discovery. Impact statement With the emergence of three-dimensional (3D) in vitro disease models, tissue engineers are increasingly interested to investigate these systems to address biological questions related to disease mechanism, drug target discovery, therapy resistance, and more. Omics technologies are a powerful and high-throughput approach, but their application for 3D disease models is not maximally utilized. This review illustrates the achievements and potential of using omics technologies to leverage the full potential of 3D in vitro disease models. This will improve the quality of such models, advance our understanding of disease, and contribute to therapy development.
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Affiliation(s)
- Vera M Pieters
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Ileana L Co
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Nila C Wu
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Alison P McGuigan
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada.,Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
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23
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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
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24
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Abstract
Mass spectrometry imaging (MSI) is a label-free molecular imaging technique allowing an untargeted detection of a broad range of biomolecules and xenobiotics. MSI enables imaging of the spatial distribution of proteins, peptides, lipids and metabolites from a wide range of samples. To date, this technique is commonly applied to tissue sections in cancer diagnostics and biomarker development, but also molecular histology in general. Advances in the methodology and bioinformatics improved the resolution of MS images below the single cell level and increased the flexibility of the workflow. However, MSI-based research in virology is just starting to gain momentum and its full potential has not been exploited yet. In this review, we discuss the main applications of MSI in virology. We review important aspects of matrix-assisted laser desorption/ionization (MALDI) MSI, the most widely used MSI technique in virology. In addition, we summarize relevant literature on MSI studies that aim to unravel virus-host interactions and virus pathogenesis, to elucidate antiviral drug kinetics and to improve current viral disease diagnostics. Collectively, these studies strongly improve our general understanding of virus-induced changes in the proteome, metabolome and metabolite distribution in host tissues of humans, animals and plants upon infection. Furthermore, latest MSI research provided important insights into the drug distribution and distribution kinetics, especially in antiretroviral research. Finally, MSI-based investigations of oncogenic viruses greatly increased our knowledge on tumor mass signatures and facilitated the identification of cancer biomarkers.
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Affiliation(s)
- Luca D Bertzbach
- Institute of Virology, Freie Universität Berlin, Berlin, Germany
| | | | - Axel Karger
- Institute of Molecular Virology and Cell Biology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
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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.
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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
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Blutke A, Sun N, Xu Z, Buck A, Harrison L, Schriever SC, Pfluger PT, Wiles D, Kunzke T, Huber K, Schlegel J, Aichler M, Feuchtinger A, Matiasek K, Hauck SM, Walch A. Light sheet fluorescence microscopy guided MALDI-imaging mass spectrometry of cleared tissue samples. Sci Rep 2020; 10:14461. [PMID: 32879402 PMCID: PMC7468256 DOI: 10.1038/s41598-020-71465-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 08/10/2020] [Indexed: 02/08/2023] Open
Abstract
Light sheet fluorescence microscopy (LSFM) of optically cleared biological samples represents a powerful tool to analyze the 3-dimensional morphology of tissues and organs. Multimodal combinations of LSFM with additional analyses of the identical sample help to limit the consumption of restricted specimen and reduce inter-sample variation. Here, we demonstrate the proof-of-concept that LSFM of cleared brain tissue samples can be combined with Matrix Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging (MALDI-MSI) for detection and quantification of proteins. Samples of freshly dissected murine brain and of archived formalin-fixed paraffin-embedded (FFPE) human brain tissue were cleared (3DISCO). Tissue regions of interest were defined by LSFM and excised, (re)-embedded in paraffin, and sectioned. Mouse sections were coated with sinapinic acid matrix. Human brain sections were pre-digested with trypsin and coated with α-cyano-4-hydroxycinnamic acid matrix. Subsequently, sections were subjected to MALDI-time-of-flight (TOF)-MSI in mass ranges between 0.8 to 4 kDa (human tissue sections), or 2.5–25 kDa (mouse tissue sections) with a lateral resolution of 50 µm. Protein- and peptide-identities corresponding to acquired MALDI-MSI spectra were confirmed by parallel liquid chromatography tandem mass spectrometry (LC–MS/MS) analysis. The spatial abundance- and intensity-patterns of established marker proteins detected by MALDI-MSI were also confirmed by immunohistochemistry.
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Affiliation(s)
- Andreas Blutke
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Zhihao Xu
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Luke Harrison
- Research Unit Neurobiology of Diabetes, Helmholtz Zentrum München, 85764, Neuherberg, Germany.,Institute for Diabetes and Obesity, Helmholtz Zentrum München, 85764, Neuherberg, Germany.,German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany.,Division of Metabolic Diseases, Technische Universität München, 80333, Munich, Germany
| | - Sonja C Schriever
- Research Unit Neurobiology of Diabetes, Helmholtz Zentrum München, 85764, Neuherberg, Germany.,Institute for Diabetes and Obesity, Helmholtz Zentrum München, 85764, Neuherberg, Germany.,German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany
| | - Paul T Pfluger
- Research Unit Neurobiology of Diabetes, Helmholtz Zentrum München, 85764, Neuherberg, Germany.,Institute for Diabetes and Obesity, Helmholtz Zentrum München, 85764, Neuherberg, Germany.,German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany
| | | | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Katharina Huber
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Jürgen Schlegel
- Institute for Pathology, Department of Neuropathology, Technische Universität München, 80333, Munich, Germany
| | - Michaela Aichler
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany.
| | - Kaspar Matiasek
- Institute for Veterinary Pathology at the Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, 80539, Munich, Germany
| | - Stefanie M Hauck
- Research Unit for Protein Science, Helmholtz Zentrum München, 85764, Neuherberg, Germany
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München, 8576, Neuherberg, Germany
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27
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Spatiotemporal Distribution of Pseudomonas aeruginosa Alkyl Quinolones under Metabolic and Competitive Stress. mSphere 2020; 5:5/4/e00426-20. [PMID: 32699119 PMCID: PMC7376503 DOI: 10.1128/msphere.00426-20] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Alkyl quinolones (AQs), including Pseudomonas quinolone signal (PQS), made by the opportunistic pathogen Pseudomonas aeruginosa have been associated with both population density and stress. The regulation of AQ production is known to be complex, and the stimuli that modulate AQ responses are not fully clear. Here, we have used hyperspectral Raman chemical imaging to examine the temporal and spatial profiles of AQs exhibited by P. aeruginosa under several potentially stressful conditions. We found that metabolic stress, effected by carbon limitation, or competition stress, effected by proximity to other species, resulted in accelerated PQS production. This competition effect did not require cell-to-cell interaction, as evidenced by the fact that the addition of supernatants from either Escherichia coli or Staphylococcus aureus led to early appearance of PQS. Lastly, the fact that these modulations were observed for PQS but not for all AQs suggests a high level of complexity in AQ regulation that remains to be discerned. Pseudomonas aeruginosa is an opportunistic human pathogen important to diseases such as cystic fibrosis. P. aeruginosa has multiple quorum-sensing (QS) systems, one of which utilizes the signaling molecule 2-heptyl-3-hydroxy-4-quinolone (Pseudomonas quinolone signal [PQS]). Here, we use hyperspectral Raman imaging to elucidate the spatiotemporal PQS distributions that determine how P. aeruginosa regulates surface colonization and its response to both metabolic stress and competition from other bacterial strains. These chemical imaging experiments illustrate the strong link between environmental challenges, such as metabolic stress caused by nutritional limitations or the presence of another bacterial species, and PQS signaling. Metabolic stress elicits a complex response in which limited nutrients induce the bacteria to produce PQS earlier, but the bacteria may also pause PQS production entirely if the nutrient concentration is too low. Separately, coculturing P. aeruginosa in the proximity of another bacterial species, or its culture supernatant, results in earlier production of PQS. However, these differences in PQS appearance are not observed for all alkyl quinolones (AQs) measured; the spatiotemporal response of 2-heptyl-4-hydroxyquinoline N-oxide (HQNO) is highly uniform for most conditions. These insights on the spatiotemporal distributions of quinolones provide additional perspective on the behavior of P. aeruginosa in response to different environmental cues. IMPORTANCE Alkyl quinolones (AQs), including Pseudomonas quinolone signal (PQS), made by the opportunistic pathogen Pseudomonas aeruginosa have been associated with both population density and stress. The regulation of AQ production is known to be complex, and the stimuli that modulate AQ responses are not fully clear. Here, we have used hyperspectral Raman chemical imaging to examine the temporal and spatial profiles of AQs exhibited by P. aeruginosa under several potentially stressful conditions. We found that metabolic stress, effected by carbon limitation, or competition stress, effected by proximity to other species, resulted in accelerated PQS production. This competition effect did not require cell-to-cell interaction, as evidenced by the fact that the addition of supernatants from either Escherichia coli or Staphylococcus aureus led to early appearance of PQS. Lastly, the fact that these modulations were observed for PQS but not for all AQs suggests a high level of complexity in AQ regulation that remains to be discerned.
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Race AM, Rae A, Vorng JL, Havelund R, Dexter A, Kumar N, Steven RT, Passarelli MK, Tyler BJ, Bunch J, Gilmore IS. Correlative Hyperspectral Imaging Using a Dimensionality-Reduction-Based Image Fusion Method. Anal Chem 2020; 92:10979-10988. [DOI: 10.1021/acs.analchem.9b05055] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Alan M. Race
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Alasdair Rae
- Surface Technology Group, National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Jean-Luc Vorng
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Rasmus Havelund
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Alex Dexter
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Naresh Kumar
- Surface Technology Group, National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Rory T. Steven
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Melissa K. Passarelli
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
| | - Bonnie J. Tyler
- Physikalisches Institut, Westfälische Wilhelms-Universität Münster, Wilhelm-Klemm-Straße 10, Münster 48149, Germany
| | - Josephine Bunch
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, U.K
- ,The Rosalind Franklin Institute, Harwell Campus, Didcot OX11 0FA, U.K
| | - Ian S. Gilmore
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K
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Xie P, Zhao C, Liang X, Huang W, Chen Y, Cai Z. Preparation of Frozen Sections of Multicellular Tumor Spheroids Coated with Ice for Mass Spectrometry Imaging. Anal Chem 2020; 92:7413-7418. [PMID: 32374161 DOI: 10.1021/acs.analchem.9b05812] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Increasing studies have utilized mass spectrometry imaging (MSI) that is a label-free tool to investigate drug penetration and drug biotransformation in multicellular tumor spheroids (MCTS). Currently, the gelatin-assisted sectioning method is widely used to prepare frozen sections of MCTS for MSI. However, owing to the limited transparency of frozen gelatin, MCTS with diameters less than 500 μm that closely mimic solid tumors are difficult to be detected when cryosectioning. In order to identify the presence of MCTS, hematoxylin and eosin staining for frozen sections and dye pretreatment for MCTS were employed in previous works, which either increased the analytical time and cost in sample preparation or caused signal suppression in sample analysis. Herein, a new sectioning method was developed to prepare MCTS frozen sections. MCTS was coated with ice to ensure good visibility for small-size MCTS. The optimal cutting temperature compound was added around the ice block to assist the formation of frozen sections. A precast frozen mold was prepared to allow the acquisition of complete MCTS frozen sections. The developed method was applied to investigate lipid distribution in MCTS by using matrix-assisted laser desorption/ionization MSI. Compared to the gelatin-assisted sectioning method, our method did not cause signal suppression and analyte delocalization. Thus, this method provides an easy, universal, and innovative strategy to prepare MCTS frozen sections for further MSI analysis. Besides, we applied our method to investigate the penetration of bisphenol A in MCTS.
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Affiliation(s)
- Peisi Xie
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, People's Republic of China
| | - Chao Zhao
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, People's Republic of China
| | - Xiaoping Liang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, People's Republic of China.,School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, People's Republic of China
| | - Wei Huang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, People's Republic of China
| | - Yanyan Chen
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, People's Republic of China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, People's Republic of China
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30
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Palubeckaitė I, Crooks L, Smith DP, Cole LM, Bram H, Le Maitre C, Clench MR, Cross NA. Mass spectrometry imaging of endogenous metabolites in response to doxorubicin in a novel 3D osteosarcoma cell culture model. JOURNAL OF MASS SPECTROMETRY : JMS 2020; 55:e4461. [PMID: 31654532 DOI: 10.1002/jms.4461] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 09/27/2019] [Accepted: 10/17/2019] [Indexed: 06/10/2023]
Abstract
Three-dimensional (3D) cell culture is a rapidly emerging field, which mimics some of the physiological conditions of human tissues. In cancer biology, it is considered a useful tool in predicting in vivo chemotherapy responses, compared with conventional two-dimensional (2D) cell culture. We have developed a novel 3D cell culture model of osteosarcoma composed of aggregated proliferative tumour spheroids, which shows regions of tumour heterogeneity formed by aggregated spheroids of polyclonal tumour cells. Aggregated spheroids show local necrotic and apoptotic regions and have sizes suitable for the study of spatial distribution of metabolites by mass spectrometry imaging (MSI). We have used this model to perform a proof-of-principle study showing a heterogeneous distribution of endogenous metabolites that colocalise with the necrotic core and apoptotic regions in this model. Cytotoxic chemotherapy (doxorubicin) responses were significantly attenuated in our 3D cell culture model compared with those of standard cell culture, as determined by resazurin assay, despite sufficient doxorubicin diffusion demonstrated by localisation throughout the 3D constructs. Finally, changes to the distribution of endogenous metabolites in response to doxorubicin were readily detected by MSI. Principal component analysis identified 50 metabolites which differed most in their abundance between treatment groups, and of these, 10 were identified by both in-software t test and mixed-effects analysis of variance (ANOVA). Subsequent independent MSIs of identified species were consistent with principle component analysis findings. This proof-of-principle study shows for the first time that chemotherapy-induced changes in metabolite abundance and distribution may be determined in 3D cell culture by MSI, highlighting this method as a potentially useful tool in the elucidation of chemotherapy responses as an alternative to in vivo testing.
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Affiliation(s)
- Ieva Palubeckaitė
- Department of Pathology, Leiden University Medical Center, PO Box 9600, 2300, RC, Leiden, The Netherlands
| | - Lucy Crooks
- Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
| | - David P Smith
- Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
| | - Laura M Cole
- Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
| | - Heijs Bram
- Center for Proteomics and Metabolomics, Leiden University Medical Center, PO Box 9600, 2300, RC, Leiden, The Netherlands
| | - Christine Le Maitre
- Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
| | - Malcolm R Clench
- Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
| | - Neil A Cross
- Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
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31
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Unraveling a self-assembling mechanism of isomeric aminothiophenol on Ag dendrite by correlated SERS and matrix-free LDI-MS. Anal Bioanal Chem 2019; 411:8081-8089. [DOI: 10.1007/s00216-019-02187-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/25/2019] [Accepted: 10/02/2019] [Indexed: 12/22/2022]
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Machálková M, Pavlatovská B, Michálek J, Pruška A, Štěpka K, Nečasová T, Radaszkiewicz KA, Kozubek M, Šmarda J, Preisler J, Navrátilová J. Drug Penetration Analysis in 3D Cell Cultures Using Fiducial-Based Semiautomatic Coregistration of MALDI MSI and Immunofluorescence Images. Anal Chem 2019; 91:13475-13484. [DOI: 10.1021/acs.analchem.9b02462] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Markéta Machálková
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Barbora Pavlatovská
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Adam Pruška
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Karel Štěpka
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Tereza Nečasová
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Katarzyna Anna Radaszkiewicz
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Jan Šmarda
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jan Preisler
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jarmila Navrátilová
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
- Center for Biological and Cellular Engineering, International Clinical Research Center, St. Anne’s University Hospital, Pekařská 53, 656 91 Brno, Czech Republic
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Tucker LH, Hamm GR, Sargeant RJE, Goodwin RJA, Mackay CL, Campbell CJ, Clarke DJ. Untargeted Metabolite Mapping in 3D Cell Culture Models Using High Spectral Resolution FT-ICR Mass Spectrometry Imaging. Anal Chem 2019; 91:9522-9529. [DOI: 10.1021/acs.analchem.9b00661] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Lulu H. Tucker
- EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh EH9 3FJ, United Kingdom
| | - Gregory R. Hamm
- Pathology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Rebecca J. E. Sargeant
- Pathology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Richard J. A. Goodwin
- Pathology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - C. Logan Mackay
- EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh EH9 3FJ, United Kingdom
| | - Colin J. Campbell
- EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh EH9 3FJ, United Kingdom
| | - David J. Clarke
- EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh EH9 3FJ, United Kingdom
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Do H, Kwon SR, Fu K, Morales-Soto N, Shrout JD, Bohn PW. Electrochemical Surface-Enhanced Raman Spectroscopy of Pyocyanin Secreted by Pseudomonas aeruginosa Communities. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2019; 35:7043-7049. [PMID: 31042392 PMCID: PMC8006532 DOI: 10.1021/acs.langmuir.9b00184] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Pyocyanin (PYO) is one of many toxins secreted by the opportunistic human pathogenic bacterium Pseudomonas aeruginosa. Direct detection of PYO in biofilms is crucial because PYO can provide important information about infection-related virulence mechanisms in P. aeruginosa. Because PYO is both redox-active and Raman-active, we seek to simultaneously acquire both spectroscopic and redox state information about PYO. The combination of surface-enhanced Raman spectroscopy (SERS) and voltammetry is used here to provide insights into the molecular redox behavior of PYO while controlling the SERS and electrochemical (EC) response of PYO with external stimuli, such as pH and applied potential. Furthermore, PYO secretion from biofilms of different P. aeruginosa strains is compared. Both SERS spectra and EC behavior are observed to change with pH, and several pH-dependent bands are identified in the SERS spectra, which can potentially be used to probe the local environment. Comparison of the voltammetric behavior of wild-type and a PYO-deficient mutant unequivocally identifies PYO as a major component of the secretome. Spectroelectrochemical studies of the PYO standard reveal decreasing SERS intensities of PYO bands under reducing conditions. Extending these experiments to pellicle biofilms shows similar behavior with applied potential, and SERS imaging indicates that secreted PYO is localized in regions approximately the size of P. aeruginosa cells. The in situ spectroelectrochemical biofilm characterization approach developed here suggests that EC-SERS monitoring of secreted molecules can be used diagnostically and correlated with the progress of infection.
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Affiliation(s)
- Hyein Do
- Department of Chemistry and Biochemistry,
University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Seung-Ryong Kwon
- Department of Chemical and Biomolecular
Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United
States
| | - Kaiyu Fu
- Department of Chemistry and Biochemistry,
University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Nydia Morales-Soto
- Department of Civil and Environmental
Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana
46556, United States
| | - Joshua D. Shrout
- Department of Civil and Environmental
Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana
46556, United States
- Department of Biological Sciences, University of
Notre Dame, Notre Dame, Indiana 46556, United States
| | - Paul W. Bohn
- Department of Chemistry and Biochemistry,
University of Notre Dame, Notre Dame, Indiana 46556, United States
- Department of Chemical and Biomolecular
Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United
States
- Corresponding Author
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35
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Mass Spectrometry Imaging and Integration with Other Imaging Modalities for Greater Molecular Understanding of Biological Tissues. Mol Imaging Biol 2019; 20:888-901. [PMID: 30167993 PMCID: PMC6244545 DOI: 10.1007/s11307-018-1267-y] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Over the last two decades, mass spectrometry imaging (MSI) has been increasingly employed to investigate the spatial distribution of a wide variety of molecules in complex biological samples. MSI has demonstrated its potential in numerous applications from drug discovery, disease state evaluation through proteomic and/or metabolomic studies. Significant technological and methodological advancements have addressed natural limitations of the techniques, i.e., increased spatial resolution, increased detection sensitivity especially for large molecules, higher throughput analysis and data management. One of the next major evolutions of MSI is linked to the introduction of imaging mass cytometry (IMC). IMC is a multiplexed method for tissue phenotyping, imaging signalling pathway or cell marker assessment, at sub-cellular resolution (1 μm). It uses MSI to simultaneously detect and quantify up to 30 different antibodies within a tissue section. The combination of MSI with other molecular imaging techniques can also provide highly relevant complementary information to explore new scientific fields. Traditionally, classical histology (especially haematoxylin and eosin–stained sections) is overlaid with molecular profiles obtained by MSI. Thus, MSI-based molecular histology provides a snapshot of a tissue microenvironment and enables the correlation of drugs, metabolites, lipids, peptides or proteins with histological/pathological features or tissue substructures. Recently, many examples combining MSI with other imaging modalities such as fluorescence, confocal Raman spectroscopy and MRI have emerged. For instance, brain pathophysiology has been studied using both MRI and MSI, establishing correlations between in and ex vivo molecular imaging techniques. Endogenous metabolite and small peptide modulation were evaluated depending on disease state. Here, we review advanced ‘hot topics’ in MSI development and explore the combination of MSI with established molecular imaging techniques to improve our understanding of biological and pathophysiological processes.
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36
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Lasch P, Noda I. Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra. APPLIED SPECTROSCOPY 2019; 73:359-379. [PMID: 30488717 DOI: 10.1177/0003702818819880] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The last two decades have seen tremendous progress in the application of two-dimensional correlation spectroscopy (2D-COS) as a versatile analysis method for data series obtained using a large variety of different spectroscopic modalities, including infrared (IR) and Raman spectroscopy. The analysis technique is applicable to a series of spectra recorded under the influence of an external sample perturbation. Two-dimensional COS analysis is not only helpful to decipher correlations, which may exist between distinct spectral features, but can also be utilized to obtain the sequence of individual spectral changes. The focus of this review article is on the application of 2D-COS for analyzing spatially resolved data with special emphasis on hyperspectral imaging (HSI) study. In this review, we briefly introduce the fundamentals of the generalized 2D-COS analysis approach, discuss specific points of 2D-COS application to spatially resolved spectra and demonstrate essential aspects of data pre-processing for 2D-COS analysis of spatially resolved spectra. Based on illustrative examples, we show that 2D-COS is useful for spectral band assignment in HSI applications and demonstrate its utility for detecting subtle correlations between spectra features, or between features from different imaging modalities in the case of heterospectral (multimodal) HSI. Furthermore, a short overview on existing 2D-COS software tools is provided. It is hoped that this article represents not only a useful guideline for 2D-COS analyses of spatially resolved hyperspectral data but supports also further dissemination of the 2D-COS analysis method as a whole.
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Affiliation(s)
- Peter Lasch
- 1 Robert Koch-Institute, ZBS6-Proteomics and Spectroscopy, Berlin, Germany
| | - Isao Noda
- 2 Department of Materials Science and Engineering, University of Delaware, Newark, DE, USA
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37
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Morales-Soto N, Cao T, Baig NF, Kramer KM, Bohn PW, Shrout JD. Surface-Growing Communities of Pseudomonas aeruginosa Exhibit Distinct Alkyl Quinolone Signatures. Microbiol Insights 2018; 11:1178636118817738. [PMID: 30573968 PMCID: PMC6295745 DOI: 10.1177/1178636118817738] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 11/06/2018] [Indexed: 12/24/2022] Open
Abstract
A cascade of events leads to the development of microbial biofilm communities that are thought to be responsible for over 80% of infections in humans. However, not all surface-growing bacteria reside in a stationary biofilm state. Here, we have employed confocal Raman microscopy to analyze and compare variations in the alkyl quinolone (AQ) family of molecules during the transition between surface-attached motile-swarming and stationary biofilm communities. The AQs have been established previously as important to Pseudomonas aeruginosa biofilms, interspecies competition, and virulence. The AQ Pseudomonas quinolone signal (PQS) is also a known quorum-sensing signal. We detail spatial identification of AQ, PQS, and 2-alkyl-4-hydroxyquinoline N-oxide (AQNO) metabolites in both swarm and biofilm communities. We find that AQNO metabolites are abundant signatures in active swarming communities.
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Affiliation(s)
- Nydia Morales-Soto
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, IN, USA.,Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
| | - Tianyuan Cao
- Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, IN, USA
| | - Nameera F Baig
- Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, IN, USA
| | - Kristen M Kramer
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, IN, USA.,Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | - Paul W Bohn
- Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, IN, USA.,Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, USA.,Advanced Diagnostics & Therapeutics, University of Notre Dame, Notre Dame, IN, USA
| | - Joshua D Shrout
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, IN, USA.,Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.,Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA.,Advanced Diagnostics & Therapeutics, University of Notre Dame, Notre Dame, IN, USA
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38
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Ryabchykov O, Popp J, Bocklitz T. Fusion of MALDI Spectrometric Imaging and Raman Spectroscopic Data for the Analysis of Biological Samples. Front Chem 2018; 6:257. [PMID: 30062092 PMCID: PMC6055053 DOI: 10.3389/fchem.2018.00257] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 06/08/2018] [Indexed: 01/03/2023] Open
Abstract
Despite of a large number of imaging techniques for the characterization of biological samples, no universal one has been reported yet. In this work, a data fusion approach was investigated for combining Raman spectroscopic data with matrix-assisted laser desorption/ionization (MALDI) mass spectrometric data. It betters the image analysis of biological samples because Raman and MALDI information can be complementary to each other. While MALDI spectrometry yields detailed information regarding the lipid content, Raman spectroscopy provides valuable information about the overall chemical composition of the sample. The combination of Raman spectroscopic and MALDI spectrometric imaging data helps distinguishing different regions within the sample with a higher precision than would be possible by using either technique. We demonstrate that a data weighting step within the data fusion is necessary to reveal additional spectral features. The selected weighting approach was evaluated by examining the proportions of variance within the data explained by the first principal components of a principal component analysis (PCA) and visualizing the PCA results for each data type and combined data. In summary, the presented data fusion approach provides a concrete guideline on how to combine Raman spectroscopic and MALDI spectrometric imaging data for biological analysis.
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Affiliation(s)
- Oleg Ryabchykov
- Spectroscopy and Imaging Research Department, Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
| | - Juergen Popp
- Spectroscopy and Imaging Research Department, Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
| | - Thomas Bocklitz
- Spectroscopy and Imaging Research Department, Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
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39
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Liu X, Flinders C, Mumenthaler SM, Hummon AB. MALDI Mass Spectrometry Imaging for Evaluation of Therapeutics in Colorectal Tumor Organoids. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2018; 29:516-526. [PMID: 29209911 PMCID: PMC5839975 DOI: 10.1007/s13361-017-1851-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 10/16/2017] [Accepted: 11/13/2017] [Indexed: 05/03/2023]
Abstract
Patient-derived colorectal tumor organoids (CTOs) closely recapitulate the complex morphological, phenotypic, and genetic features observed in in vivo tumors. Therefore, evaluation of drug distribution and metabolism in this model system can provide valuable information to predict the clinical outcome of a therapeutic response in individual patients. In this report, we applied matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to examine the spatial distribution of the drug irinotecan and its metabolites in CTOs from two patients. Irinotecan is a prodrug and is often prescribed as part of therapeutic regimes for patients with advanced colorectal cancer. Irinotecan shows a time-dependent and concentration-dependent permeability and metabolism in the CTOs. More interestingly, the active metabolite SN-38 does not co-localize well with the parent drug irinotecan and the inactive metabolite SN-38G. The phenotypic effect of irinotecan metabolism was also confirmed by a viability study showing significantly reduced proliferation in the drug treated CTOs. MALDI-MSI can be used to investigate various pharmaceutical compounds in CTOs derived from different patients. By analyzing multiple CTOs from a patient, this method could be used to predict patient-specific drug responses and help to improve personalized dosing regimens. Graphical Abstract ᅟ.
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Affiliation(s)
- Xin Liu
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, 140 McCourtney Hall, Notre Dame, IN, 46556, USA
| | - Colin Flinders
- Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, 2250 Alcazar Street, CSC 240, Los Angeles, CA, 90033, USA
| | - Shannon M Mumenthaler
- Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, 2250 Alcazar Street, CSC 240, Los Angeles, CA, 90033, USA
| | - Amanda B Hummon
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, 140 McCourtney Hall, Notre Dame, IN, 46556, USA.
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40
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Bergholt MS, Serio A, McKenzie JS, Boyd A, Soares RF, Tillner J, Chiappini C, Wu V, Dannhorn A, Takats Z, Williams A, Stevens MM. Correlated Heterospectral Lipidomics for Biomolecular Profiling of Remyelination in Multiple Sclerosis. ACS CENTRAL SCIENCE 2018; 4:39-51. [PMID: 29392175 PMCID: PMC5785772 DOI: 10.1021/acscentsci.7b00367] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2017] [Indexed: 05/22/2023]
Abstract
Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL) approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS), and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models.
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Affiliation(s)
- Mads S. Bergholt
- Department
of Materials, Imperial College London, London SW7 2AZ, United Kingdom
- Department
of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom
- Institute
of Biomedical Engineering, Imperial College
London, London SW7 2AZ, United Kingdom
| | - Andrea Serio
- Department
of Materials, Imperial College London, London SW7 2AZ, United Kingdom
- Department
of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom
- Institute
of Biomedical Engineering, Imperial College
London, London SW7 2AZ, United Kingdom
| | - James S. McKenzie
- Computational
and Systems Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Amanda Boyd
- MRC
Centre for Regenerative Medicine, University
of Edinburgh, Edinburgh EH16 4UU, United Kingdom
| | - Renata F. Soares
- Computational
and Systems Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Jocelyn Tillner
- Computational
and Systems Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Ciro Chiappini
- Department
of Materials, Imperial College London, London SW7 2AZ, United Kingdom
- Department
of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom
- Institute
of Biomedical Engineering, Imperial College
London, London SW7 2AZ, United Kingdom
| | - Vincen Wu
- Computational
and Systems Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Andreas Dannhorn
- Computational
and Systems Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Zoltan Takats
- Computational
and Systems Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Anna Williams
- MRC
Centre for Regenerative Medicine, University
of Edinburgh, Edinburgh EH16 4UU, United Kingdom
| | - Molly M. Stevens
- Department
of Materials, Imperial College London, London SW7 2AZ, United Kingdom
- Department
of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom
- Institute
of Biomedical Engineering, Imperial College
London, London SW7 2AZ, United Kingdom
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41
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Rae Buchberger A, DeLaney K, Johnson J, Li L. Mass Spectrometry Imaging: A Review of Emerging Advancements and Future Insights. Anal Chem 2018; 90:240-265. [PMID: 29155564 PMCID: PMC5959842 DOI: 10.1021/acs.analchem.7b04733] [Citation(s) in RCA: 561] [Impact Index Per Article: 93.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Amanda Rae Buchberger
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Kellen DeLaney
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Jillian Johnson
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
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42
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Prentice BM, Caprioli RM, Vuiblet V. Label-free molecular imaging of the kidney. Kidney Int 2017; 92:580-598. [PMID: 28750926 PMCID: PMC6193761 DOI: 10.1016/j.kint.2017.03.052] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 03/27/2017] [Accepted: 03/28/2017] [Indexed: 12/25/2022]
Abstract
In this review, we will highlight technologies that enable scientists to study the molecular characteristics of tissues and/or cells without the need for antibodies or other labeling techniques. Specifically, we will focus on matrix-assisted laser desorption/ionization imaging mass spectrometry, infrared spectroscopy, and Raman spectroscopy.
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Affiliation(s)
- Boone M Prentice
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA; Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA; Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA; Departments of Pharmacology and Medicine, Vanderbilt University, Nashville, Tennessee, USA; Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA.
| | - Vincent Vuiblet
- Biophotonic Laboratory, UMR CNRS 7369 URCA, Reims, France; Nephropathology, Department of Biopathology Laboratory, CHU de Reims, Reims, France; Nephrology and Renal Transplantation department, CHU de Reims, Reims, France.
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43
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Polisetti S, Baig NF, Morales-Soto N, Shrout JD, Bohn PW. Spatial Mapping of Pyocyanin in Pseudomonas Aeruginosa Bacterial Communities Using Surface Enhanced Raman Scattering. APPLIED SPECTROSCOPY 2017; 71:215-223. [PMID: 27354400 PMCID: PMC5475280 DOI: 10.1177/0003702816654167] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Surface enhanced Raman spectroscopy (SERS) imaging was used in conjunction with principal component analysis (PCA) for the in situ spatiotemporal mapping of the virulence factor pyocyanin in communities of the pathogenic bacterium Pseudomonas aeruginosa. The combination of SERS imaging and PCA analysis provides a robust method for the characterization of heterogeneous biological systems while circumventing issues associated with interference from sample autofluorescence and low reproducibility of SERS signals. The production of pyocyanin is found to depend both on the growth carbon source and on the specific strain of P. aeruginosa studied. A cystic fibrosis lung isolate strain of P. aeruginosa synthesizes and secretes pyocyanin when grown with glucose and glutamate, while the laboratory strain exhibits detectable production of pyocyanin only when grown with glutamate as the source of carbon. Pyocyanin production in the laboratory strain grown with glucose was below the limit of detection of SERS. In addition, the combination of SERS imaging and PCA can elucidate subtle differences in the molecular composition of biofilms. PCA loading plots from the clinical isolate exhibit features corresponding to vibrational bands of carbohydrates, which represent the mucoid biofilm matrix specific to that isolate, features that are not seen in the PCA loading plots of the laboratory strain.
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Affiliation(s)
- Sneha Polisetti
- 1 Department of Chemical and Biomolecular Engineering, University of Notre Dame, USA
| | - Nameera F Baig
- 2 Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, USA
| | - Nydia Morales-Soto
- 3 Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, USA
- 4 Eck Institute for Global Health, University of Notre Dame, USA
| | - Joshua D Shrout
- 3 Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, USA
- 4 Eck Institute for Global Health, University of Notre Dame, USA
- 5 Department of Biological Sciences, University of Notre Dame, USA
| | - Paul W Bohn
- 1 Department of Chemical and Biomolecular Engineering, University of Notre Dame, USA
- 2 Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, USA
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44
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Abstract
Over the last decade mass spectrometry imaging (MSI) has been integrated in to many areas of drug discovery and development. It can have significant impact in oncology drug discovery as it allows efficacy and safety of compounds to be assessed against the backdrop of the complex tumour microenvironment. We will discuss the roles of MSI in investigating compound and metabolite biodistribution and defining pharmacokinetic -pharmacodynamic relationships, analysis that is applicable to all drug discovery projects. We will then look more specifically at how MSI can be used to understand tumour metabolism and other applications specific to oncology research. This will all be described alongside the challenges of applying MSI to industry research with increased use of metrology for MSI.
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45
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Yue X, Lukowski JK, Weaver EM, Skube SB, Hummon AB. Quantitative Proteomic and Phosphoproteomic Comparison of 2D and 3D Colon Cancer Cell Culture Models. J Proteome Res 2016; 15:4265-4276. [PMID: 27696853 DOI: 10.1021/acs.jproteome.6b00342] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Cell cultures are widely used model systems. Some immortalized cell lines can be grown in either two-dimensional (2D) adherent monolayers or in three-dimensional (3D) multicellular aggregates, or spheroids. Here, the quantitative proteome and phosphoproteome of colon carcinoma HT29 cells cultures in 2D monolayers and 3D spheroids were compared with a stable isotope labeling of amino acids (SILAC) labeling strategy. Two biological replicates from each sample were examined, and notable differences in both the proteome and the phosphoproteome were determined by nanoliquid chromatography tandem mass spectrometry (LC-MS/MS) to assess how growth configuration affects molecular expression. A total of 5867 protein groups, including 2523 phosphoprotein groups and 8733 phosphopeptides were identified in the samples. The Gene Ontology analysis revealed enriched GO terms in the 3D samples for RNA binding, nucleic acid binding, enzyme binding, cytoskeletal protein binding, and histone binding for their molecular functions (MF) and in the process of cell cycle, cytoskeleton organization, and DNA metabolic process for the biological process (BP). The KEGG pathway analysis indicated that 3D cultures are enriched for oxidative phosphorylation pathways, metabolic pathways, peroxisome pathways, and biosynthesis of amino acids. In contrast, analysis of the phosphoproteomes indicated that 3D cultures have decreased phosphorylation correlating with slower growth rates and lower cell-to-extracellular matrix interactions. In sum, these results provide quantitative assessments of the effects on the proteome and phosphoproteome of culturing cells in 2D versus 3D cell culture configurations.
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Affiliation(s)
- Xiaoshan Yue
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame , 251 Nieuwland Science Hall, Notre Dame, Indiana 46556, United States
| | - Jessica K Lukowski
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame , 251 Nieuwland Science Hall, Notre Dame, Indiana 46556, United States
| | - Eric M Weaver
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame , 251 Nieuwland Science Hall, Notre Dame, Indiana 46556, United States
| | - Susan B Skube
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame , 251 Nieuwland Science Hall, Notre Dame, Indiana 46556, United States
| | - Amanda B Hummon
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame , 251 Nieuwland Science Hall, Notre Dame, Indiana 46556, United States
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Race AM, Palmer AD, Dexter A, Steven RT, Styles IB, Bunch J. SpectralAnalysis: Software for the Masses. Anal Chem 2016; 88:9451-9458. [DOI: 10.1021/acs.analchem.6b01643] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Alan M. Race
- National
Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, TW11 0LW, United Kingdom
- PSIBS
Doctoral Training Centre, School of Chemistry, University of Birmingham, Birmingham, B15 2TT, United Kingdom
| | - Andrew D. Palmer
- PSIBS
Doctoral Training Centre, School of Chemistry, University of Birmingham, Birmingham, B15 2TT, United Kingdom
- European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, 69117, Germany
| | - Alex Dexter
- National
Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, TW11 0LW, United Kingdom
- PSIBS
Doctoral Training Centre, School of Chemistry, University of Birmingham, Birmingham, B15 2TT, United Kingdom
| | - Rory T. Steven
- National
Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, TW11 0LW, United Kingdom
| | - Iain B. Styles
- PSIBS
Doctoral Training Centre, School of Chemistry, University of Birmingham, Birmingham, B15 2TT, United Kingdom
- School
of Computer Science, University of Birmingham, Birmingham, B15 2TT, United Kingdom
| | - Josephine Bunch
- National
Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, TW11 0LW, United Kingdom
- School
of Pharmacy, University of Nottingham, Nottingham, NG7 2RD, United Kingdom
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47
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Baig N, Polisetti S, Morales-Soto N, Dunham SJB, Sweedler JV, Shrout JD, Bohn PW. Label-free molecular imaging of bacterial communities of the opportunistic pathogen Pseudomonas aeruginosa. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2016; 9930:993004. [PMID: 29670306 PMCID: PMC5901720 DOI: 10.1117/12.2236695] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Biofilms, such as those formed by the opportunistic human pathogen Pseudomonas aeruginosa are complex, matrix enclosed, and surface-associated communities of cells. Bacteria that are part of a biofilm community are much more resistant to antibiotics and the host immune response than their free-floating counterparts. P. aeruginosa biofilms are associated with persistent and chronic infections in diseases such as cystic fibrosis and HIV-AIDS. P. aeruginosa synthesizes and secretes signaling molecules such as the Pseudomonas quinolone signal (PQS) which are implicated in quorum sensing (QS), where bacteria regulate gene expression based on population density. Processes such as biofilms formation and virulence are regulated by QS. This manuscript describes the powerful molecular imaging capabilities of confocal Raman microscopy (CRM) and surface enhanced Raman spectroscopy (SERS) in conjunction with multivariate statistical tools such as principal component analysis (PCA) for studying the spatiotemporal distribution of signaling molecules, secondary metabolites and virulence factors in biofilm communities of P. aeruginosa. Our observations reveal that the laboratory strain PAO1C synthesizes and secretes 2-alkyl-4-hydroxyquinoline N-oxides and 2-alkyl-4-hydroxyquinolones in high abundance, while the isogenic acyl homoserine lactone QS-deficient mutant (ΔlasIΔrhlI) strain produces predominantly 2-alkyl-quinolones during biofilm formation. This study underscores the use of CRM, along with traditional biological tools such as genetics, for studying the behavior of microbial communities at the molecular level.
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Affiliation(s)
- Nameera Baig
- Department of Chemistry & Biochemistry and Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Sneha Polisetti
- Department of Chemistry & Biochemistry and Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Nydia Morales-Soto
- Department of Civil and Environmental Engineering and Earth Sciences and Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
- Eck Institute for Global Health, University of Notre Dame, USA
| | - Sage J B Dunham
- Department of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jonathan V Sweedler
- Department of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Joshua D Shrout
- Department of Civil and Environmental Engineering and Earth Sciences and Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
- Eck Institute for Global Health, University of Notre Dame, USA
| | - Paul W Bohn
- Department of Chemistry & Biochemistry and Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
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48
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Polisetti S, Bible AN, Morrell-Falvey JL, Bohn PW. Raman chemical imaging of the rhizosphere bacterium Pantoea sp. YR343 and its co-culture with Arabidopsis thaliana. Analyst 2016; 141:2175-82. [PMID: 26948490 DOI: 10.1039/c6an00080k] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Chemical imaging of plant-bacteria co-cultures makes it possible to characterize bacterial populations and behaviors and their interactions with proximal organisms, under conditions closest to the environment in the rhizosphere. Here Raman micro-spectroscopy and confocal Raman imaging are used as minimally invasive probes to study the rhizosphere bacterial isolate, Pantoea sp. YR343, and its co-culture with model plant Arabidopsis thaliana by combining enhanced Raman spectroscopies with electron microscopy and principal component analysis (PCA). The presence of carotenoid pigments in the wild type Pantoea sp. YR343 was characterized using resonance Raman scattering, which was also used to confirm successful disruption of the crtB gene in an engineered carotenoid mutant strain. Other components of the Pantoea sp. YR343 cells were imaged in the presence of resonantly enhanced pigments using a combination of surface enhanced Raman imaging and PCA. Pantoea sp. YR343 cells decorated with Ag colloid synthesized ex situ gave spectra dominated by carotenoid scattering, whereas colloids synthesized in situ produced spectral signatures characteristic of flavins in the cell membrane. Scanning electron microscopy (SEM) of whole cells and transmission electron microscopy (TEM) images of thinly sliced cross-sections were used to assess structural integrity of the coated cells and to establish the origin of spectral signatures based on the position of Ag nanoparticles in the cells. Raman imaging was also used to characterize senescent green Arabidopsis thaliana plant roots inoculated with Pantoea sp. YR343, and PCA was used to distinguish spectral contributions from plant and bacterial cells, thereby establishing the potential of Raman imaging to visualize the distribution of rhizobacteria on plant roots.
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Affiliation(s)
- Sneha Polisetti
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
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Bocklitz TW, Guo S, Ryabchykov O, Vogler N, Popp J. Raman Based Molecular Imaging and Analytics: A Magic Bullet for Biomedical Applications!? Anal Chem 2015; 88:133-51. [DOI: 10.1021/acs.analchem.5b04665] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Thomas W. Bocklitz
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology (IPHT), Albert-Einstein-Strasse 9, 07745 Jena, Germany
| | - Shuxia Guo
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology (IPHT), Albert-Einstein-Strasse 9, 07745 Jena, Germany
- InfectoGnostics
Forschungscampus Jena e.V., Zentrum für Angewandte Forschung, Philosophenweg 7, 07743 Jena, Germany
| | - Oleg Ryabchykov
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology (IPHT), Albert-Einstein-Strasse 9, 07745 Jena, Germany
- InfectoGnostics
Forschungscampus Jena e.V., Zentrum für Angewandte Forschung, Philosophenweg 7, 07743 Jena, Germany
| | - Nadine Vogler
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology (IPHT), Albert-Einstein-Strasse 9, 07745 Jena, Germany
- InfectoGnostics
Forschungscampus Jena e.V., Zentrum für Angewandte Forschung, Philosophenweg 7, 07743 Jena, Germany
| | - Jürgen Popp
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology (IPHT), Albert-Einstein-Strasse 9, 07745 Jena, Germany
- InfectoGnostics
Forschungscampus Jena e.V., Zentrum für Angewandte Forschung, Philosophenweg 7, 07743 Jena, Germany
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Liu X, Hummon AB. Mass spectrometry imaging of therapeutics from animal models to three-dimensional cell cultures. Anal Chem 2015; 87:9508-19. [PMID: 26084404 PMCID: PMC4766864 DOI: 10.1021/acs.analchem.5b00419] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Mass spectrometry imaging (MSI) is a powerful label-free technique for the investigation of the spatial distribution of molecules at complex surfaces and has been widely used in the pharmaceutical sciences to understand the distribution of different drugs and their metabolites in various biological samples, ranging from cell-based models to tissues. Here, we review the current applications of MSI for drug studies in animal models, followed by a discussion of the novel advances of MSI in three-dimensional (3D) cell cultures for accurate, efficient, and high-throughput analyses to evaluate therapeutics.
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Affiliation(s)
- Xin Liu
- Department of Chemistry and Biochemistry, Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN 46556, USA
| | - Amanda B. Hummon
- Department of Chemistry and Biochemistry, Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN 46556, USA
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