Research

16 pages, 3774 KiB

Open AccessArticle

Probing the Drug Dynamics of Chemotherapeutics Using Metasurface-Enhanced Infrared Reflection Spectroscopy of Live Cells

by Po-Ting Shen, Steven H. Huang, Zhouyang Huang, Justin J. Wilson and Gennady Shvets

Cells 2022, 11(10), 1600; https://doi.org/10.3390/cells11101600 - 10 May 2022

Cited by 5 | Viewed by 2437

Abstract

Infrared spectroscopy has drawn considerable interest in biological applications, but the measurement of live cells is impeded by the attenuation of infrared light in water. Metasurface-enhanced infrared reflection spectroscopy (MEIRS) had been shown to mitigate the problem, enhance the cellular infrared signal through [...] Read more.

Infrared spectroscopy has drawn considerable interest in biological applications, but the measurement of live cells is impeded by the attenuation of infrared light in water. Metasurface-enhanced infrared reflection spectroscopy (MEIRS) had been shown to mitigate the problem, enhance the cellular infrared signal through surface-enhanced infrared absorption, and encode the cellular vibrational signatures in the reflectance spectrum at the same time. In this study, we used MEIRS to study the dynamic response of live cancer cells to a newly developed chemotherapeutic metal complex with distinct modes of action (MoAs): tricarbonyl rhenium isonitrile polypyridyl (TRIP). MEIRS measurements demonstrated that administering TRIP resulted in long-term (several hours) reduction in protein, lipid, and overall refractive index signals, and in short-term (tens of minutes) increase in these signals, consistent with the induction of endoplasmic reticulum stress. The unique tricarbonyl IR signature of TRIP in the bioorthogonal spectral window was monitored in real time, and was used as an infrared tag to detect the precise drug delivery time that was shown to be closely correlated with the onset of the phenotypic response. These results demonstrate that MEIRS is an effective label-free real-time cellular assay capable of detecting and interpreting the early phenotypic responses of cells to IR-tagged chemotherapeutics. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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13 pages, 2192 KiB

Open AccessArticle

Combining Pharmacokinetics and Vibrational Spectroscopy: MCR-ALS Hard-and-Soft Modelling of Drug Uptake In Vitro Using Tailored Kinetic Constraints

by David Pérez-Guaita, Guillermo Quintás, Zeineb Farhane, Romá Tauler and Hugh J. Byrne

Cells 2022, 11(9), 1555; https://doi.org/10.3390/cells11091555 - 05 May 2022

Cited by 4 | Viewed by 2117

Abstract

Raman microspectroscopy is a label-free technique which is very suited for the investigation of pharmacokinetics of cellular uptake, mechanisms of interaction, and efficacies of drugs in vitro. However, the complexity of the spectra makes the identification of spectral patterns associated with the drug [...] Read more.

Raman microspectroscopy is a label-free technique which is very suited for the investigation of pharmacokinetics of cellular uptake, mechanisms of interaction, and efficacies of drugs in vitro. However, the complexity of the spectra makes the identification of spectral patterns associated with the drug and subsequent cellular responses difficult. Indeed, multivariate methods that relate spectral features to the inoculation time do not normally take into account the kinetics involved, and important theoretical information which could assist in the elucidation of the relevant spectral signatures is excluded. Here, we propose the integration of kinetic equations in the modelling of drug uptake and subsequent cellular responses using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and tailored kinetic constraints, based on a system of ordinary differential equations. Advantages of and challenges to the methodology were evaluated using simulated Raman spectral data sets and real Raman spectra acquired from A549 and Calu-1 human lung cells inoculated with doxorubicin, in vitro. The results suggest a dependency of the outcome on the system of equations used, and the importance of the temporal resolution of the data set to enable the use of complex equations. Nevertheless, the use of tailored kinetic constraints during MCR-ALS allowed a more comprehensive modelling of the system, enabling the elucidation of not only the time-dependent concentration profiles and spectral features of the drug binding and cellular responses, but also an accurate computation of the kinetic constants. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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20 pages, 11806 KiB

Open AccessArticle

Illuminating Host-Parasite Interaction at the Cellular and Subcellular Levels with Infrared Microspectroscopy

by Hany M. Elsheikha, Alaa T. Al-Sandaqchi, Mohammad S. R. Harun, Francesca Winterton, Ali Altharawi, Nashwa A. Elsaied, Carl W. Stevenson, William MacNaughtan, John G. M. Mina, Paul W. Denny, Gianfelice Cinque and Ka Lung Andrew Chan

Cells 2022, 11(5), 811; https://doi.org/10.3390/cells11050811 - 25 Feb 2022

Cited by 1 | Viewed by 2731

Abstract

Toxoplasma gondii (T. gondii) is an opportunistic protozoan that can cause brain infection and other serious health consequences in immuno-compromised individuals. This parasite has a remarkable ability to cross biological barriers and exploit the host cell microenvironment to support its own [...] Read more.

Toxoplasma gondii (T. gondii) is an opportunistic protozoan that can cause brain infection and other serious health consequences in immuno-compromised individuals. This parasite has a remarkable ability to cross biological barriers and exploit the host cell microenvironment to support its own survival and growth. Recent advances in label-free spectroscopic imaging techniques have made it possible to study biological systems at a high spatial resolution. In this study, we used conventional Fourier-transform infrared (FTIR) microspectroscopy and synchrotron-based FTIR microspectroscopy to analyze the chemical changes that are associated with infection of human brain microvascular endothelial cells (hBMECs) by T. gondii (RH) tachyzoites. Both FTIR microspectroscopic methods showed utility in revealing the chemical alterations in the infected hBMECs. Using a ZnS hemisphere device, to increase the numerical aperture, and the synchrotron source to increase the brightness, we obtained spatially resolved spectra from within a single cell. The spectra extracted from the nucleus and cytosol containing the tachyzoites were clearly distinguished. RNA sequencing analysis of T. gondii-infected and uninfected hBMECs revealed significant changes in the expression of host cell genes and pathways in response to T. gondii infection. These FTIR spectroscopic and transcriptomic findings provide significant insight into the molecular changes that occur in hBMECs during T. gondii infection. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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20 pages, 18394 KiB

Open AccessArticle

Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Discriminates the Elderly with a Low and High Percentage of Pathogenic CD4+ T Cells

by Rian Ka Praja, Molin Wongwattanakul, Patcharaporn Tippayawat, Wisitsak Phoksawat, Amonrat Jumnainsong, Kanda Sornkayasit and Chanvit Leelayuwat

Cells 2022, 11(3), 458; https://doi.org/10.3390/cells11030458 - 28 Jan 2022

Cited by 8 | Viewed by 3360

Abstract

In the aging process, the presence of interleukin (IL)-17-producing CD4+CD28-NKG2D+T cells (called pathogenic CD4+ T cells) is strongly associated with inflammation and the development of various diseases. Thus, their presence needs to be monitored. The emergence of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) [...] Read more.

In the aging process, the presence of interleukin (IL)-17-producing CD4+CD28-NKG2D+T cells (called pathogenic CD4+ T cells) is strongly associated with inflammation and the development of various diseases. Thus, their presence needs to be monitored. The emergence of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy empowered with machine learning is a breakthrough in the field of medical diagnostics. This study aimed to discriminate between the elderly with a low percentage (LP; ≤3%) and a high percentage (HP; ≥6%) of pathogenic CD4+CD28-NKG2D+IL17+ T cells by utilizing ATR-FTIR coupled with machine learning algorithms. ATR spectra of serum, exosome, and HDL from both groups were explored in this study. Only exosome spectra in the 1700–1500 cm⁻¹ region exhibited possible discrimination for the LP and HP groups based on principal component analysis (PCA). Furthermore, partial least square-discriminant analysis (PLS-DA) could differentiate both groups using the 1700–1500 cm⁻¹ region of exosome ATR spectra with 64% accuracy, 69% sensitivity, and 61% specificity. To obtain better classification performance, several spectral models were then established using advanced machine learning algorithms, including J48 decision tree, support vector machine (SVM), random forest (RF), and neural network (NN). Herein, NN was considered to be the best model with an accuracy of 100%, sensitivity of 100%, and specificity of 100% using serum spectra in the region of 1800–900 cm⁻¹. Exosome spectra in the 1700–1500 and combined 3000–2800 and 1800–900 cm⁻¹ regions using the NN algorithm gave the same accuracy performance of 95% with a variation in sensitivity and specificity. HDL spectra with the NN algorithm also showed excellent test performance in the 1800–900 cm⁻¹ region with 97% accuracy, 100% sensitivity, and 95% specificity. This study demonstrates that ATR-FTIR coupled with machine learning algorithms can be used to study immunosenescence. Furthermore, this approach can possibly be applied to monitor the presence of pathogenic CD4+ T cells in the elderly. Due to the limited number of samples used in this study, it is necessary to conduct a large-scale study to obtain more robust classification models and to assess the true clinical diagnostic performance. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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15 pages, 5120 KiB

Open AccessArticle

Nano-Infrared Imaging of Primary Neurons

by Raul O. Freitas, Adrian Cernescu, Anders Engdahl, Agnes Paulus, João E. Levandoski, Isak Martinsson, Elke Hebisch, Christophe Sandt, Gunnar Keppler Gouras, Christelle N. Prinz, Tomas Deierborg, Ferenc Borondics and Oxana Klementieva

Cells 2021, 10(10), 2559; https://doi.org/10.3390/cells10102559 - 27 Sep 2021

Cited by 13 | Viewed by 3700

Abstract

Alzheimer’s disease (AD) accounts for about 70% of neurodegenerative diseases and is a cause of cognitive decline and death for one-third of seniors. AD is currently underdiagnosed, and it cannot be effectively prevented. Aggregation of amyloid-β (Aβ) proteins has been linked to the [...] Read more.

Alzheimer’s disease (AD) accounts for about 70% of neurodegenerative diseases and is a cause of cognitive decline and death for one-third of seniors. AD is currently underdiagnosed, and it cannot be effectively prevented. Aggregation of amyloid-β (Aβ) proteins has been linked to the development of AD, and it has been established that, under pathological conditions, Aβ proteins undergo structural changes to form β-sheet structures that are considered neurotoxic. Numerous intensive in vitro studies have provided detailed information about amyloid polymorphs; however, little is known on how amyloid β-sheet-enriched aggregates can cause neurotoxicity in relevant settings. We used scattering-type scanning near-field optical microscopy (s-SNOM) to study amyloid structures at the nanoscale, in individual neurons. Specifically, we show that in well-validated systems, s-SNOM can detect amyloid β-sheet structures with nanometer spatial resolution in individual neurons. This is a proof-of-concept study to demonstrate that s-SNOM can be used to detect Aβ-sheet structures on cell surfaces at the nanoscale. Furthermore, this study is intended to raise neurobiologists’ awareness of the potential of s-SNOM as a tool for analyzing amyloid β-sheet structures at the nanoscale in neurons without the need for immunolabeling. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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11 pages, 1561 KiB

Open AccessArticle

DNA Fingerprint Analysis of Raman Spectra Captures Global Genomic Alterations in Imatinib-Resistant Chronic Myeloid Leukemia: A Potential Single Assay for Screening Imatinib Resistance

by Rahul Mojidra, Arti Hole, Keita Iwasaki, Hemanth Noothalapati, Tatsuyuki Yamamoto, Murali Krishna C and Rukmini Govekar

Cells 2021, 10(10), 2506; https://doi.org/10.3390/cells10102506 - 22 Sep 2021

Cited by 3 | Viewed by 3068

Abstract

Monitoring the development of resistance to the tyrosine kinase inhibitor (TKI) imatinib in chronic myeloid leukemia (CML) patients in the initial chronic phase (CP) is crucial for limiting the progression of unresponsive patients to terminal phase of blast crisis (BC). This study for [...] Read more.

Monitoring the development of resistance to the tyrosine kinase inhibitor (TKI) imatinib in chronic myeloid leukemia (CML) patients in the initial chronic phase (CP) is crucial for limiting the progression of unresponsive patients to terminal phase of blast crisis (BC). This study for the first time demonstrates the potential of Raman spectroscopy to sense the resistant phenotype. Currently recommended resistance screening strategy include detection of BCR-ABL1 transcripts, kinase domain mutations, complex chromosomal abnormalities and BCR-ABL1 gene amplification. The techniques used for these tests are expensive, technologically demanding and have limited availability in resource-poor countries. In India, this could be a reason for more patients reporting to clinics with advanced disease. A single method which can identify resistant cells irrespective of the underlying mechanism would be a practical screening strategy. During our analysis of imatinib-sensitive and -resistant K562 cells, by array comparative genomic hybridization (aCGH), copy number variations specific to resistant cells were detected. aCGH is technologically demanding, expensive and therefore not suitable to serve as a single economic test. We therefore explored whether DNA finger-print analysis of Raman hyperspectral data could capture these alterations in the genome, and demonstrated that it could indeed segregate imatinib-sensitive and -resistant cells. Raman spectroscopy, due to availability of portable instruments, ease of spectrum acquisition and possibility of centralized analysis of transmitted data, qualifies as a preliminary screening tool in resource-poor countries for imatinib resistance in CML. This study provides a proof of principle for a single assay for monitoring resistance to imatinib, available for scrutiny in clinics. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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10 pages, 1495 KiB

Open AccessArticle

Quasar: Easy Machine Learning for Biospectroscopy

by Marko Toplak, Stuart T. Read, Christophe Sandt and Ferenc Borondics

Cells 2021, 10(9), 2300; https://doi.org/10.3390/cells10092300 - 03 Sep 2021

Cited by 49 | Viewed by 5064

Abstract

Data volumes collected in many scientific fields have long exceeded the capacity of human comprehension. This is especially true in biomedical research where multiple replicates and techniques are required to conduct reliable studies. Ever-increasing data rates from new instruments compound our dependence on [...] Read more.

Data volumes collected in many scientific fields have long exceeded the capacity of human comprehension. This is especially true in biomedical research where multiple replicates and techniques are required to conduct reliable studies. Ever-increasing data rates from new instruments compound our dependence on statistics to make sense of the numbers. The currently available data analysis tools lack user-friendliness, various capabilities or ease of access. Problem-specific software or scripts freely available in supplementary materials or research lab websites are often highly specialized, no longer functional, or simply too hard to use. Commercial software limits access and reproducibility, and is often unable to follow quickly changing, cutting-edge research demands. Finally, as machine learning techniques penetrate data analysis pipelines of the natural sciences, we see the growing demand for user-friendly and flexible tools to fuse machine learning with spectroscopy datasets. In our opinion, open-source software with strong community engagement is the way forward. To counter these problems, we develop Quasar, an open-source and user-friendly software, as a solution to these challenges. Here, we present case studies to highlight some Quasar features analyzing infrared spectroscopy data using various machine learning techniques. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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17 pages, 2473 KiB

Open AccessArticle

Cytotoxic Effects of 5-Azacytidine on Primary Tumour Cells and Cancer Stem Cells from Oral Squamous Cell Carcinoma: An In Vitro FTIRM Analysis

by Valentina Notarstefano, Alessia Belloni, Simona Sabbatini, Chiara Pro, Giulia Orilisi, Riccardo Monterubbianesi, Vincenzo Tosco, Hugh J. Byrne, Lisa Vaccari and Elisabetta Giorgini

Cells 2021, 10(8), 2127; https://doi.org/10.3390/cells10082127 - 19 Aug 2021

Cited by 17 | Viewed by 2533

Abstract

In the present study, the cytotoxic effects of 5-azacytidine on primary Oral Squamous Cell Carcinoma cells (OSCCs) from human biopsies, and on Cancer Stem Cells (CSCs) from the same samples, were investigated by an in vitro Fourier Transform InfraRed Microscospectroscopy (FTIRM) approach coupled [...] Read more.

In the present study, the cytotoxic effects of 5-azacytidine on primary Oral Squamous Cell Carcinoma cells (OSCCs) from human biopsies, and on Cancer Stem Cells (CSCs) from the same samples, were investigated by an in vitro Fourier Transform InfraRed Microscospectroscopy (FTIRM) approach coupled with multivariate analysis. OSCC is an aggressive tumoral lesion of the epithelium, accounting for ~90% of all oral cancers. It is usually diagnosed in advanced stages, and this causes a poor prognosis with low success rates of surgical, as well as radiation and chemotherapy treatments. OSCC is frequently characterised by recurrence after chemotherapy and by the development of a refractoriness to some employed drugs, which is probably ascribable to the presence of CSCs niches, responsible for cancer growth, chemoresistance and metastasis. The spectral information from FTIRM was correlated with the outcomes of cytotoxicity tests and image-based cytometry, and specific spectral signatures attributable to 5-azacytidine treatment were identified, allowing us to hypothesise the demethylation of DNA and, hence, an increase in the transcriptional activity, together with a conformational transition of DNA, and a triggering of cell death by an apoptosis mechanism. Moreover, a different mechanism of action between OSSC and CSC cells was highlighted, probably due to possible differences between OSCCs and CSCs response. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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18 pages, 3510 KiB

Open AccessArticle

The Impact of Preprocessing Methods for a Successful Prostate Cell Lines Discrimination Using Partial Least Squares Regression and Discriminant Analysis Based on Fourier Transform Infrared Imaging

by Danuta Liberda, Ewa Pięta, Katarzyna Pogoda, Natalia Piergies, Maciej Roman, Paulina Koziol, Tomasz P. Wrobel, Czeslawa Paluszkiewicz and Wojciech M. Kwiatek

Cells 2021, 10(4), 953; https://doi.org/10.3390/cells10040953 - 20 Apr 2021

Cited by 5 | Viewed by 2605

Abstract

Fourier transform infrared spectroscopy (FT-IR) is widely used in the analysis of the chemical composition of biological materials and has the potential to reveal new aspects of the molecular basis of diseases, including different types of cancer. The potential of FT-IR in cancer [...] Read more.

Fourier transform infrared spectroscopy (FT-IR) is widely used in the analysis of the chemical composition of biological materials and has the potential to reveal new aspects of the molecular basis of diseases, including different types of cancer. The potential of FT-IR in cancer research lies in its capability of monitoring the biochemical status of cells, which undergo malignant transformation and further examination of spectral features that differentiate normal and cancerous ones using proper mathematical approaches. Such examination can be performed with the use of chemometric tools, such as partial least squares discriminant analysis (PLS-DA) classification and partial least squares regression (PLSR), and proper application of preprocessing methods and their correct sequence is crucial for success. Here, we performed a comparison of several state-of-the-art methods commonly used in infrared biospectroscopy (denoising, baseline correction, and normalization) with the addition of methods not previously used in infrared biospectroscopy classification problems: Mie extinction extended multiplicative signal correction, Eiler’s smoothing, and probabilistic quotient normalization. We compared all of these approaches and their effect on the data structure, classification, and regression capability on experimental FT-IR spectra collected from five different prostate normal and cancerous cell lines. Additionally, we tested the influence of added spectral noise. Overall, we concluded that in the case of the data analyzed here, the biggest impact on data structure and performance of PLS-DA and PLSR was caused by the baseline correction; therefore, much attention should be given, especially to this step of data preprocessing. Full article

(This article belongs to the Special Issue Cellular and Subcellular Analysis Using Vibrational Spectroscopy)

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