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Lim B, Ratcliff J, Nawrot DA, Yu Y, Sanghani HR, Hsu CC, Peto L, Evans S, Hodgson SH, Skeva A, Adam M, Panopoulou M, Zois CE, Poncin K, Vasudevan SR, Dai S, Ren S, Chang H, Cui Z, Simmonds P, Huang WE, Andersson MI. Clinical validation of optimised RT-LAMP for the diagnosis of SARS-CoV-2 infection. Sci Rep 2021; 11:16193. [PMID: 34376716 PMCID: PMC8355225 DOI: 10.1038/s41598-021-95607-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 07/21/2021] [Indexed: 12/23/2022] Open
Abstract
We have optimised a reverse transcription-loop-mediated isothermal amplification (RT-LAMP) assay for the detection of SARS-CoV-2 from extracted RNA for clinical application. We improved the stability and reliability of the RT-LAMP assay by the addition of a temperature-dependent switch oligonucleotide to reduce self- or off-target amplification. We then developed freeze-dried master mix for single step RT-LAMP reaction, simplifying the operation for end users and improving long-term storage and transportation. The assay can detect as low as 13 copies of SARS-CoV2 RNA per reaction (25-μL). Cross reactivity with other human coronaviruses was not observed. We have applied the new RT-LAMP assay for testing clinical extracted RNA samples extracted from swabs of 72 patients in the UK and 126 samples from Greece and demonstrated the overall sensitivity of 90.2% (95% CI 83.8-94.7%) and specificity of 92.4% (95% CI 83.2-97.5%). Among 115 positive samples which Ct values were less than 34, the RT-LAMP assay was able to detect 110 of them with 95.6% sensitivity. The specificity was 100% when RNA elution used RNase-free water. The outcome of RT-LAMP can be reported by both colorimetric detection and quantifiable fluorescent reading. Objective measures with a digitized reading data flow would allow for the sharing of results for local or national surveillance.
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Affiliation(s)
- Boon Lim
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK
| | - Jeremy Ratcliff
- Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 3SY, UK
| | - Dorota A Nawrot
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, UK
| | - Yejiong Yu
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK
| | | | - Chia-Chen Hsu
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK
| | - Leon Peto
- Department of Microbiology, Oxford University NHS Foundation Trust, Oxford, UK
| | - Simon Evans
- Department of Microbiology, Oxford University NHS Foundation Trust, Oxford, UK
| | - Susanne H Hodgson
- Department of Microbiology, Oxford University NHS Foundation Trust, Oxford, UK
- Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Aikaterini Skeva
- Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupoli, Greece
| | - Maria Adam
- Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupoli, Greece
| | - Maria Panopoulou
- Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupoli, Greece
| | - Christos E Zois
- Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupoli, Greece
| | - Katy Poncin
- Sir William Dunn School of Pathology, University of Oxford, Oxford, UK
| | - Sridhar R Vasudevan
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, UK
| | - Siqi Dai
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK
| | - Shuai Ren
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK
| | - Hong Chang
- Oxford Suzhou Centre for Advanced Research (OSCAR), University of Oxford, Suzhou, China
| | - Zhanfeng Cui
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK
- Oxford Suzhou Centre for Advanced Research (OSCAR), University of Oxford, Suzhou, China
| | - Peter Simmonds
- Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 3SY, UK
| | - Wei E Huang
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK.
- Oxford Suzhou Centre for Advanced Research (OSCAR), University of Oxford, Suzhou, China.
| | - Monique I Andersson
- Department of Microbiology, Oxford University NHS Foundation Trust, Oxford, UK.
- Nuffield Division of Clinical Laboratory Science, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
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Gonzalez-Pujana A, de Lázaro I, Vining KH, Santos-Vizcaino E, Igartua M, Hernandez RM, Mooney DJ. 3D encapsulation and inflammatory licensing of mesenchymal stromal cells alter the expression of common reference genes used in real-time RT-qPCR. Biomater Sci 2020; 8:6741-6753. [PMID: 33136110 DOI: 10.1039/d0bm01562h] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Human mesenchymal stromal cells (hMSCs) hold great promise in the treatment of inflammatory and immune diseases, due to their immunomodulatory capacity. Their therapeutic activity is often assessed measuring levels of expression of immunomodulatory genes such as indoleamine 2,3-dioxygenase 1 (IDO1) and real-time RT-qPCR is most predominantly the method of choice due to its high sensitivity and relative simplicity. Currently, multiple strategies are explored to promote hMSC-mediated immunomodulation, overlooking the effects they pose in the expression of genes commonly used as internal calibrators in real-time RT-qPCR analyses. However, variations in their expression could introduce significant errors in the evaluation of the therapeutic potential of hMSCs. This work investigates, for the first time, how some of these strategies - 3D encapsulation, the mechanical properties of the 3D matrix and inflammatory licensing - influence the expression of common reference genes in hMSCs. Both 3D encapsulation and inflammatory licensing alter significantly the expression of β-actin (ACTB) and Ubiquitin C (UBC), respectively. Using them as normalization factors leads to an erroneous assessment of IDO1 mRNA levels, therefore resulting in over or underestimation of the therapeutic potential of hMSCs. In contrast, the range of mechanical properties of the matrix encapsulating the cells did not significantly affect the expression of any of the reference genes studied. Moreover, we identify RPS13 and RPL30 as reference genes of choice under these particular experimental conditions. These results demonstrate the vital importance of validating the expression of reference genes to correctly assess the therapeutic potential of hMSCs by real-time RT-qPCR.
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Affiliation(s)
- Ainhoa Gonzalez-Pujana
- NanoBioCel Research Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain.
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A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons. Proc Natl Acad Sci U S A 2020; 117:18412-18423. [PMID: 32694205 PMCID: PMC7414136 DOI: 10.1073/pnas.2001906117] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
We developed a label-free and noninvasive single-cell Raman microspectroscopy (SCRM)-based platform to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). Through large-scale Raman spectral analysis, we can distinguish hiPSCs and hiPSC-derived neural cells using their intrinsic biochemical profile. We identified glycogen as a Raman biomarker for neuronal differentiation and validated the results using conventional glycogen detection assays. The parameters obtained from SCRM were processed by a novel machine learning method based on t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, enabling highly accurate and robust cell classification. The platform and the proposed biomarker should also be applicable to other cell types and can shed light on developmental biology and glycogen metabolism disorders. Stem cells with the capability to self-renew and differentiate into multiple cell derivatives provide platforms for drug screening and promising treatment options for a wide variety of neural diseases. Nevertheless, clinical applications of stem cells have been hindered partly owing to a lack of standardized techniques to characterize cell molecular profiles noninvasively and comprehensively. Here, we demonstrate that a label-free and noninvasive single-cell Raman microspectroscopy (SCRM) platform was able to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). By analyzing the intrinsic biochemical profiles of single cells at a large scale (8,774 Raman spectra in total), iPSCs and iPSC-derived neural cells can be distinguished by their intrinsic phenotypic Raman spectra. We identified a Raman biomarker from glycogen to distinguish iPSCs from their neural derivatives, and the result was verified by the conventional glycogen detection assays. Further analysis with a machine learning classification model, utilizing t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, clearly categorized hiPSCs in different developmental stages with 97.5% accuracy. The present study demonstrates the capability of the SCRM-based platform to monitor cell development using high content screening with a noninvasive and label-free approach. This platform as well as our identified biomarker could be extensible to other cell types and can potentially have a high impact on neural stem cell therapy.
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Brinkhof B, Zhang B, Cui Z, Ye H, Wang H. ALCAM (CD166) as a gene expression marker for human mesenchymal stromal cell characterisation. Gene X 2020; 763S:100031. [PMID: 32550557 PMCID: PMC7285916 DOI: 10.1016/j.gene.2020.100031] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 03/08/2020] [Indexed: 02/06/2023] Open
Abstract
Background Human mesenchymal stromal cells (MSCs) phenotypically share their positive expression of the International Society for Cell and Gene Therapy (ISCT) markers CD73, CD90 and CD105 with fibroblasts. Fibroblasts are often co-isolated as an unwanted by-product from biopsy and they can rapidly overgrow the MSCs in culture. Indeed, many other surface markers have been proposed, though no unique MSC specific marker has been identified yet. Quantitative PCR (qPCR) is a precise, efficient and rapid method for gene expression analysis. To identify a marker suitable for accurate MSC characterisation, qPCR was exploited. Methods and results Two commercially obtained bone marrow (BM) derived MSCs and an hTERT immortalised BM-MSC line (MSC-TERT) have been cultured for different days and at different oxygen levels before RNA extraction. Together with RNA samples previous extracted from umbilical cord derived MSCs and MSC-TERT cells cultured in 2D or 3D, this heterogeneous sample set was quantitatively analysed for the expression levels of 18 candidate MSC marker genes. The expression levels in MSCs were compared with the expression levels in fibroblasts to verify the differentiation capability of these genes between MSCs and fibroblasts. None of the ISCT markers could differentiate between fibroblasts and MSCs. A total of six other genes (ALCAM, CLIC1, EDIL3, EPHA2, NECTIN2, and TMEM47) were identified as possible biomarkers for accurate identification of MSCs. Conclusion Justified by considerations on expression level, reliability and specificity, Activated-Leukocyte Cell Adhesion Molecule (ALCAM) was the best candidate for improving the biomarker set of MSC identification.
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Key Words
- (q)PCR, (quantitative) polymerase chain reaction
- AD, adipose
- AF, Amniotic Fluid
- ALCAM, Activated-Leukocyte Cell Adhesion Molecule
- Activated-leukocyte cell adhesion molecule
- BM, bone marrow
- BSG, Basigin
- Biomarker
- CD, cluster of differentiation
- CLIC1, chloride intracellular channel 1
- CLIC4, chloride intracellular channel 4
- Cq, Quantification cycle
- DF, Dermal Fibroblasts
- DP, Dental Pulp
- EDIL3, EGF like repeats and discoidin domains 3
- ENG, Endoglin
- EPHA2, EPH receptor A2
- ER, Endoplasmatic Reticulum
- FACS, Fluorescence Assisted Cell Sorting
- FN1, Fibronectin 1
- IGFBP7, insulin like growth factor binding protein 7
- ISCT, International Society for Cell and Gene Therapy
- ITGA1, integrin subunit alpha 1
- LAMP1, lysosomal associated membrane protein 1
- LRRC59, leucine rich repeat containing 59
- MCAM, melanoma cell adhesion molecule
- MM, Multiple Myeloma
- MPC, Mesenchymal Progenitor Cell
- MSC
- MSC, Mesenchymal Stromal Cells
- NECTIN2, nectin cell adhesion molecule 2
- NK, Natural Killer
- NT5E, 5′-nucleotidase ecto
- OS, Osteosarcoma
- PL, Placenta
- PPIA, peptidylprolyl isomerase A
- PUM1, pumilio RNA binding family member 1
- RM, Regenerative Medicine
- RNA
- RNA-seq, RNA sequencing
- RT, Reverse Transcriptase
- Regenerative medicine
- SEM, Standard Error of the Mean
- TBP, TATA-box binding protein
- TCF, Tissue Culture Plate
- TE, Tissue Engineering
- TFRC, transferrin receptor
- THY1, Thy-1 cell surface antigen
- TLN1, Talin 1
- TMEM47, transmembrane protein 47
- UC, umbilical cord
- YWHAZ, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta
- cDNA, DNA complementary to RNA
- qPCR
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Affiliation(s)
- Bas Brinkhof
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Bo Zhang
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Zhanfeng Cui
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Hua Ye
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Hui Wang
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom.,Oxford Suzhou Centre for Advanced Research, Suzhou Industrial Park, Jiangsu 215123, China
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Nguyen LTB, Odeleye AOO, Chui CY, Baudequin T, Cui Z, Ye H. Development of thermo-responsive polycaprolactone macrocarriers conjugated with Poly(N-isopropyl acrylamide) for cell culture. Sci Rep 2019; 9:3477. [PMID: 30837639 PMCID: PMC6401373 DOI: 10.1038/s41598-019-40242-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 02/12/2019] [Indexed: 01/20/2023] Open
Abstract
Poly(N-isopropyl acrylamide) (PNIPAAm) is a well-known 'smart' material responding to external stimuli such as temperature. PNIPAAm was successfully conjugated to polycaprolactone (PCL) bead surfaces through amidation reaction. Functionalization steps were characterized and confirmed by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy and Energy Dispersion Spectroscopy. PNIPAAm-conjugated PCL allowed human dermal fibroblast cells (HDF) and mesenchymal stem cells (MSC) to adhere, spread, and grow successfully. By reducing the temperature to 30 °C, more than 70% of HDF were detached from PNIPAAm-conjugated PCL macrocarriers with 85% viability. The cell detachment ratio by trypsin treatment was slightly higher than that induced by reduced temperature, however, cell detachment from PNIPAAm-conjugated macrocarriers by lowering the temperature significantly reduced cell death and increased both cell viability and the recovery potential of the detached cells. HDF attachment and detachment were also observed by Live-Dead staining and phase contrast imaging. The expression of extracellular matrix proteins such as Laminin and Fibronectin was also affected by the trypsinization process but not by the reduced temperature process. Taken together, our results showed that thermo-responsive macrocarriers could be a promising alternative method for the non-invasive detachment of cells, in particular for tissue engineering, clinical applications and the use of bioreactors.
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Affiliation(s)
- Linh T B Nguyen
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, UK
| | - Akinlolu O O Odeleye
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, UK
- Adaptimmune Limited, 60 Jubilee Avenue, Milton Park, Abingdon, OX14 4RX, UK
| | - Chih-Yao Chui
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, UK
| | - Timothée Baudequin
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, UK
| | - Zhanfeng Cui
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, UK
| | - Hua Ye
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, UK.
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