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V. D. dos Santos AC, Hondl N, Ramos-Garcia V, Kuligowski J, Lendl B, Ramer G. AFM-IR for Nanoscale Chemical Characterization in Life Sciences: Recent Developments and Future Directions. ACS MEASUREMENT SCIENCE AU 2023; 3:301-314. [PMID: 37868358 PMCID: PMC10588935 DOI: 10.1021/acsmeasuresciau.3c00010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/30/2023] [Accepted: 05/30/2023] [Indexed: 10/24/2023]
Abstract
Despite the ubiquitous absorption of mid-infrared (IR) radiation by virtually all molecules that belong to the major biomolecules groups (proteins, lipids, carbohydrates, nucleic acids), the application of conventional IR microscopy to the life sciences remained somewhat limited, due to the restrictions on spatial resolution imposed by the diffraction limit (in the order of several micrometers). This issue is addressed by AFM-IR, a scanning probe-based technique that allows for chemical analysis at the nanoscale with resolutions down to 10 nm and thus has the potential to contribute to the investigation of nano and microscale biological processes. In this perspective, in addition to a concise description of the working principles and operating modes of AFM-IR, we present and evaluate the latest key applications of AFM-IR to the life sciences, summarizing what the technique has to offer to this field. Furthermore, we discuss the most relevant current limitations and point out potential future developments and areas for further application for fruitful interdisciplinary collaboration.
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Affiliation(s)
| | - Nikolaus Hondl
- Institute
of Chemical Technologies and Analytics, TU Wien, Getreidemarkt 9, 1060 Vienna, Austria
| | - Victoria Ramos-Garcia
- Health
Research Institute La Fe, Avenida Fernando Abril Martorell 106, 46026 Valencia, Spain
| | - Julia Kuligowski
- Health
Research Institute La Fe, Avenida Fernando Abril Martorell 106, 46026 Valencia, Spain
| | - Bernhard Lendl
- Institute
of Chemical Technologies and Analytics, TU Wien, Getreidemarkt 9, 1060 Vienna, Austria
| | - Georg Ramer
- Institute
of Chemical Technologies and Analytics, TU Wien, Getreidemarkt 9, 1060 Vienna, Austria
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Hu G, Yan H, Xi G, Gao Z, Wu Z, Lu Z, Tu J. Nanopore sensors for single molecular protein detection: Research progress based on computer simulations. IET Nanobiotechnol 2023; 17:257-268. [PMID: 36924083 DOI: 10.1049/nbt2.12124] [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: 12/29/2022] [Revised: 02/20/2023] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
As biological macromolecules, proteins are involved in important cellular functions ranging from DNA replication and biosynthesis to metabolic signalling and environmental sensing. Protein sequencing can help understand the relationship between protein function and structure, and provide key information for disease diagnosis and new drug design. Nanopore sensors are a novel technology to achieve the goal of label-free and high-throughput protein sequencing. In recent years, nanopore-based biosensors have been widely used in the detection and analysis of biomolecules such as DNA, RNA, and proteins. At the same time, computer simulations can describe the transport of proteins through nanopores at the atomic level. This paper reviews the applications of nanopore sensors in protein sequencing over the past decade and the solutions to key problems from a computer simulation perspective, with the aim of pointing the way to the future of nanopore protein sequencing.
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Affiliation(s)
- Gang Hu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Han Yan
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Guohao Xi
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Zhuwei Gao
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Ziqing Wu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Zuhong Lu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Jing Tu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
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Akhgar CK, Nürnberger V, Nadvornik M, Ramos-Garcia V, Ten-Doménech I, Kuligowski J, Schwaighofer A, Rosenberg E, Lendl B. Fatty Acid Determination in Human Milk Using Attenuated Total Reflection Infrared Spectroscopy and Solvent-Free Lipid Separation. APPLIED SPECTROSCOPY 2022; 76:730-736. [PMID: 35119320 DOI: 10.1177/00037028211065502] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
This study introduces the first mid-infrared (IR)-based method for determining the fatty acid composition of human milk. A representative milk lipid fraction was obtained by applying a rapid and solvent-free two-step centrifugation method. Attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy was applied to record absorbance spectra of pure milk fat. The obtained spectra were compared to whole human milk transmission spectra, revealing the significantly higher degree of fatty acid-related spectral features in ATR FT-IR spectra. Partial least squares (PLS)-based multivariate regression equations were established by relating ATR FT-IR spectra to fatty acid reference concentrations, obtained with gas chromatography-mass spectrometry (GC-MS). Good predictions were achieved for the most important fatty acid sum parameters: saturated fatty acids (SAT, R2CV = 0.94), monounsaturated fatty acids (MONO, R2CV = 0.85), polyunsaturated fatty acids (PUFA, R2CV = 0.87), unsaturated fatty acids (UNSAT, R2CV = 0.91), short-chain fatty acids (SCFA, R2CV = 0.79), medium-chain fatty acids (MCFA, R2CV = 0.97), and long-chain fatty acids (LCFA, R2CV = 0.88). The PLS selectivity ratio (SR) was calculated in order to optimize and verify each individual calibration model. All mid-IR regions with high SR could be assigned to absorbances from fatty acids, indicating high validity of the obtained models.
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Affiliation(s)
- Christopher K Akhgar
- 27259Institute of Chemical Technologies and Analytics, Technische Universität Wien, Wien, Austria
| | | | - Marlene Nadvornik
- 27259Institute of Chemical Technologies and Analytics, Technische Universität Wien, Wien, Austria
| | | | | | | | - Andreas Schwaighofer
- 27259Institute of Chemical Technologies and Analytics, Technische Universität Wien, Wien, Austria
| | - Erwin Rosenberg
- 27259Institute of Chemical Technologies and Analytics, Technische Universität Wien, Wien, Austria
| | - Bernhard Lendl
- 27259Institute of Chemical Technologies and Analytics, Technische Universität Wien, Wien, Austria
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V. D. dos Santos AC, Tranchida D, Lendl B, Ramer G. Nanoscale chemical characterization of a post-consumer recycled polyolefin blend using tapping mode AFM-IR. Analyst 2022; 147:3741-3747. [DOI: 10.1039/d2an00823h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Tapping mode AFM-IR reveals the presence of contaminants, PP inclusions within the PE phase, and EPR rubber at the interphase between PP and PE in a real-world polyolefin recyclate.
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Affiliation(s)
| | | | - Bernhard Lendl
- Institute of Chemical Technologies and Analytics, TU Wien, 1060 Vienna, Austria
| | - Georg Ramer
- Institute of Chemical Technologies and Analytics, TU Wien, 1060 Vienna, Austria
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Fomitcheva-Khartchenko A, Rapsomaniki MA, Sobottka B, Schraml P, Kaigala GV. Spatial protein heterogeneity analysis in frozen tissues to evaluate tumor heterogeneity. PLoS One 2021; 16:e0259332. [PMID: 34797831 PMCID: PMC8604290 DOI: 10.1371/journal.pone.0259332] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 10/19/2021] [Indexed: 11/19/2022] Open
Abstract
A new workflow for protein-based tumor heterogeneity probing in tissues is here presented. Tumor heterogeneity is believed to be key for therapy failure and differences in prognosis in cancer patients. Comprehending tumor heterogeneity, especially at the protein level, is critical for tracking tumor evolution, and showing the presence of different phenotypical variants and their location with respect to tissue architecture. Although a variety of techniques is available for quantifying protein expression, the heterogeneity observed in the tissue is rarely addressed. The proposed method is validated in breast cancer fresh-frozen tissues derived from five patients. Protein expression is quantified on the tissue regions of interest (ROI) with a resolution of up to 100 μm in diameter. High heterogeneity values across the analyzed patients in proteins such as cytokeratin 7, β-actin and epidermal growth factor receptor (EGFR) using a Shannon entropy analysis are observed. Additionally, ROIs are clustered according to their expression levels, showing their location in the tissue section, and highlighting that similar phenotypical variants are not always located in neighboring regions. Interestingly, a patient with a phenotype related to increased aggressiveness of the tumor presents a unique protein expression pattern. In summary, a workflow for the localized extraction and protein analysis of regions of interest from frozen tissues, enabling the evaluation of tumor heterogeneity at the protein level is presented.
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Affiliation(s)
| | | | - Bettina Sobottka
- Department of Pathology and Molecular Pathology, University Hospital Zurich and University Zurich, Zurich, Switzerland
| | - Peter Schraml
- Department of Pathology and Molecular Pathology, University Hospital Zurich and University Zurich, Zurich, Switzerland
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Zeng X, Xiang Y, Liu Q, Wang L, Ma Q, Ma W, Zeng D, Yin Y, Wang D. Nanopore Technology for the Application of Protein Detection. NANOMATERIALS (BASEL, SWITZERLAND) 2021; 11:1942. [PMID: 34443773 PMCID: PMC8400292 DOI: 10.3390/nano11081942] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/23/2021] [Accepted: 07/27/2021] [Indexed: 01/19/2023]
Abstract
Protein is an important component of all the cells and tissues of the human body and is the material basis of life. Its content, sequence, and spatial structure have a great impact on proteomics and human biology. It can reflect the important information of normal or pathophysiological processes and promote the development of new diagnoses and treatment methods. However, the current techniques of proteomics for protein analysis are limited by chemical modifications, large sample sizes, or cumbersome operations. Solving this problem requires overcoming huge challenges. Nanopore single molecule detection technology overcomes this shortcoming. As a new sensing technology, it has the advantages of no labeling, high sensitivity, fast detection speed, real-time monitoring, and simple operation. It is widely used in gene sequencing, detection of peptides and proteins, markers and microorganisms, and other biomolecules and metal ions. Therefore, based on the advantages of novel nanopore single-molecule detection technology, its application to protein sequence detection and structure recognition has also been proposed and developed. In this paper, the application of nanopore single-molecule detection technology in protein detection in recent years is reviewed, and its development prospect is investigated.
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Affiliation(s)
- Xiaoqing Zeng
- Chongqing University, 174 Shazheng Street, Shapingba District, Chongqing 400044, China; (X.Z.); (Y.X.); (W.M.)
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
| | - Yang Xiang
- Chongqing University, 174 Shazheng Street, Shapingba District, Chongqing 400044, China; (X.Z.); (Y.X.); (W.M.)
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
| | - Qianshan Liu
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
| | - Liang Wang
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
| | - Qianyun Ma
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing 400054, China
| | - Wenhao Ma
- Chongqing University, 174 Shazheng Street, Shapingba District, Chongqing 400044, China; (X.Z.); (Y.X.); (W.M.)
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
| | - Delin Zeng
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
- School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yajie Yin
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
| | - Deqiang Wang
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; (Q.L.); (L.W.); (Q.M.); (D.Z.)
- Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
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Fatty Acid Prediction in Bovine Milk by Attenuated Total Reflection Infrared Spectroscopy after Solvent-Free Lipid Separation. Foods 2021; 10:foods10051054. [PMID: 34064791 PMCID: PMC8151219 DOI: 10.3390/foods10051054] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/07/2021] [Accepted: 05/10/2021] [Indexed: 11/17/2022] Open
Abstract
In the present study, a novel approach for mid-infrared (IR)-based prediction of bovine milk fatty acid composition is introduced. A rapid, solvent-free, two-step centrifugation method was applied in order to obtain representative milk fat fractions. IR spectra of pure milk lipids were recorded with attenuated total reflection Fourier-transform infrared (ATR-FT-IR) spectroscopy. Comparison to the IR transmission spectra of whole milk revealed a higher amount of significant spectral information for fatty acid analysis. Partial least squares (PLS) regression models were calculated to relate the IR spectra to gas chromatography/mass spectrometry (GC/MS) reference values, providing particularly good predictions for fatty acid sum parameters as well as for the following individual fatty acids: C10:0 (R2P = 0.99), C12:0 (R2P = 0.97), C14:0 (R2P = 0.88), C16:0 (R2P = 0.81), C18:0 (R2P = 0.93), and C18:1cis (R2P = 0.95). The IR wavenumber ranges for the individual regression models were optimized and validated by calculation of the PLS selectivity ratio. Based on a set of 45 milk samples, the obtained PLS figures of merit are significantly better than those reported in literature using whole milk transmission spectra and larger datasets. In this context, direct IR measurement of the milk fat fraction inherently eliminates covariation structures between fatty acids and total fat content, which poses a common problem in IR-based milk fat profiling. The combination of solvent-free lipid separation and ATR-FT-IR spectroscopy represents a novel approach for fast fatty acid prediction, with the potential for high-throughput application in routine lab operation.
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