Volume 13 Issue 10
Oct.  2023
Turn off MathJax
Article Contents
Ying Hou, Hongren Yao, Jin-Ming Lin. Recent advancements in single-cell metabolic analysis for pharmacological research[J]. Journal of Pharmaceutical Analysis, 2023, 13(10): 1102-1116. doi: 10.1016/j.jpha.2023.08.014
Citation: Ying Hou, Hongren Yao, Jin-Ming Lin. Recent advancements in single-cell metabolic analysis for pharmacological research[J]. Journal of Pharmaceutical Analysis, 2023, 13(10): 1102-1116. doi: 10.1016/j.jpha.2023.08.014

Recent advancements in single-cell metabolic analysis for pharmacological research

doi: 10.1016/j.jpha.2023.08.014
Funds:

This work was supported by the National Key R&D Program of China (Grant No.: 2022YFC3400700) and the National Natural Science Foundation of China (Grant Nos.: 22034005, 81973569 and 221115402533).

  • Received Date: Jul. 11, 2023
  • Accepted Date: Aug. 18, 2023
  • Rev Recd Date: Aug. 12, 2023
  • Publish Date: Oct. 30, 2023
  • Cellular heterogeneity is crucial for understanding tissue biology and disease pathophysiology. Pharmacological research is being advanced by single-cell metabolic analysis, which offers a technique to identify variations in RNA, proteins, metabolites, and drug molecules in cells. In this review, the recent advancement of single-cell metabolic analysis techniques and their applications in drug metabolism and drug response are summarized. High-precision and controlled single-cell isolation and manipulation are provided by microfluidics-based methods, such as droplet microfluidics, microchamber, open microfluidic probe, and digital microfluidics. They are used in tandem with variety of detection techniques, including optical imaging, Raman spectroscopy, electrochemical detection, RNA sequencing, and mass spectrometry, to evaluate single-cell metabolic changes in response to drug administration. The advantages and disadvantages of different techniques are discussed along with the challenges and future directions for single-cell analysis. These techniques are employed in pharmaceutical analysis for studying drug response and resistance pathway, therapeutic targets discovery, and in vitro disease model evaluation.
  • loading
  • R. Zenobi, Single-cell metabolomics: Analytical and biological perspectives, Science 342 (2013), 1243259.
    S.J. Altschuler, L.F. Wu, Cellular heterogeneity: Do differences make a difference? Cell 141 (2010) 559-563.
    Y. Oren, M. Tsabar, M.S. Cuoco, et al., Cycling cancer persister cells arise from lineages with distinct programs, Nature 596 (2021) 576-582.
    A.M. Wheeler, C.D. Eberhard, E.P. Mosher, et al., Achieving a deeper understanding of drug metabolism and responses using single-cell technologies, Drug Metab. Dispos. 51 (2023) 350-359.
    Y. Zhang, S. Chen, F. Fan, et al., Neurotoxicity mechanism of aconitine in HT22 cells studied by microfluidic chip-mass spectrometry, J. Pharm. Anal. 13 (2023) 88-98.
    S. Ma, J. Wu, Z. Liu, et al., Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication, J. Pharm. Anal. 13 (2023) 388-402.
    T. Chen, C. Huang, Y. Wang, et al., Microfluidic methods for cell separation and subsequent analysis, Chin. Chem. Lett. 33 (2022) 1180-1192.
    X. Lin, J. Su, S. Zhou, Microfluidic chip of concentration gradient and fluid shear stress on a single cell level, Chin. Chem. Lett. 33 (2022) 3133-3138.
    Y. Jiao, L. Gao, Y. Ji, et al., Recent advances in microfluidic single-cell analysis and its applications in drug development, Trac Trends Anal. Chem. 157 (2022), 116796.
    Y. Ai, F. Zhang, C. Wang, et al., Recent progress in lab-on-a-chip for pharmaceutical analysis and pharmacological/toxicological test, Trac Trends Anal. Chem. 117 (2019) 215-230.
    Q. Zhong, X. Huang, R. Zhang, et al., Optical sensing strategies for probing single-cell secretion, ACS Sens. 7 (2022) 1779-1790.
    G.Q. Wallace, J.F. Masson, From single cells to complex tissues in applications of surface-enhanced Raman scattering, Analyst 145 (2020) 7162-7185.
    Q. Yang, X. Huang, B. Gao, et al., Advances in electrochemiluminescence for single-cell analysis, Analyst 148 (2023) 9-25.
    Y. Lei, R. Tang, J. Xu, et al., Applications of single-cell sequencing in cancer research: Progress and perspectives, J. Hematol. Oncol. 14 (2021), 91.
    M. Tajik, M. Baharfar, W.A. Donald, Single-cell mass spectrometry, Trends Biotechnol. 40 (2022) 1374-1392.
    Z. Wu, P.J. Lawrence, A. Ma, et al., Single-cell techniques and deep learning in predicting drug response, Trends Pharmacol. Sci. 41 (2020) 1050-1065.
    N. Shembekar, C. Chaipan, R. Utharala, et al., Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics, Lab Chip 16 (2016) 1314-1331.
    Y. Hou, S. Chen, Y. Zheng, et al., Droplet-based digital PCR (ddPCR) and its applications, Trac Trends Anal. Chem. 158 (2023), 116897.
    D. Xu, W. Zhang, H. Li, et al., Advances in droplet digital polymerase chain reaction on microfluidic chips, Lab Chip 23 (2023) 1258-1278.
    X. Yue, X. Fang, T. Sun, et al., Breaking through the Poisson Distribution: A compact high-efficiency droplet microfluidic system for single-bead encapsulation and digital immunoassay detection, Biosens. Bioelectron. 211 (2022), 114384.
    J. Zhong, M. Liang, Q. Tang, et al., Selectable encapsulated cell quantity in droplets via label-free electrical screening and impedance-activated sorting, Mater. Today Bio. 19 (2023), 100594.
    W. Zhang, N. Li, L. Lin, et al., Concentrating single cells in picoliter droplets for phospholipid profiling on a microfluidic system, Small 16 (2020), 1903402.
    W. Zhang, N. Li, L. Lin, et al., Metabolism-based capture and analysis of circulating tumor cells in an open space, Anal. Chem. 93 (2021) 6955-6960.
    W. Wu, S. Zhang, T. Zhang, et al., Immobilized droplet arrays in thermosetting oil for dynamic proteolytic assays of single cells, ACS Appl. Mater. Interfaces 13 (2021) 6081-6090.
    T. Xie, Q. Zhang, W. Zhang, et al., Inkjet-patterned microdroplets as individual microenvironments for adherent single cell culture, Small 18 (2022), 2270097.
    S.W. Wong, S. Lenzini, R. Bargi, et al., Controlled deposition of 3D matrices to direct single cell functions, Adv. Sci. 7 (2020), 2001066.
    B. Ha, T.J. Kim, E. Moon, et al., Flow radiocytometry using droplet optofluidics, Biosens. Bioelectron. 194 (2021), 113565.
    Y. Zhou, Z. Yu, M. Wu, et al., Single-cell sorting using integrated pneumatic valve droplet microfluidic chip, Talanta 253 (2023), 124044.
    S.N. Agnihotri, G.S. Ugolini, M.R. Sullivan, et al., Droplet microfluidics for functional temporal analysis and cell recovery on demand using microvalves: Application in immunotherapies for cancer, Lab Chip 22 (2022) 3258-3267.
    T. Khajvand, P. Huang, L. Li, et al., Interfacing droplet microfluidics with antibody barcodes for multiplexed single-cell protein secretion profiling, Lab Chip 21 (2021) 4823-4830.
    P. Radfar, L. Ding, L.R. de la Fuente, et al., Rapid metabolomic screening of cancer cells via high-throughput static droplet microfluidics, Biosens. Bioelectron. 223 (2023), 114966.
    R. Xie, Y. Liu, S. Wang, et al., Combinatorial perturbation sequencing on single cells using microwell-based droplet random pairing, Biosens. Bioelectron. 220 (2023), 114913.
    M. Zhang, Y. Zou, X. Xu, et al., Highly parallel and efficient single cell mRNA sequencing with paired picoliter chambers, Nat. Commun. 11 (2020), 2118.
    S. Lin, K. Yin, Y. Zhang, et al., Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics, Nat. Commun. 14 (2023), 1272.
    Q. Zhang, S. Feng, L. Lin, et al., Emerging open microfluidics for cell manipulation, Chem. Soc. Rev. 50 (2021) 5333-5348.
    S. Mao, W. Zhang, Q. Huang, et al., In situ scatheless cell detachment reveals correlation between adhesion strength and viability at single-cell resolution, Angew. Chem. Int. Ed. 57 (2018) 236-240.
    S. Mao, Q. Zhang, H. Li, et al., Measurement of cell-matrix adhesion at single-cell resolution for revealing the functions of biomaterials for adherent cell culture, Anal. Chem. 90 (2018) 9637-9643.
    S. Mao, Q. Zhang, H. Li, et al., Adhesion analysis of single circulating tumor cells on a base layer of endothelial cells using open microfluidics, Chem. Sci. 9 (2018) 7694-7699.
    Q. Zhang, S. Mao, W. Li, et al., Microfluidic adhesion analysis of single glioma cells for evaluating the effect of drugs, Sci. China Chem. 63 (2020) 865-870.
    Q. Zhang, S. Mao, M. Khan, et al., In situ partial treatment of single cells by laminar flow in the “open space”, Anal. Chem. 91 (2019) 1644-1650.
    Q. Zhang, S. Feng, W. Li, et al., In situ stable generation of reactive intermediates by open microfluidic probe for subcellular free radical attack and membrane labeling, Angew. Chem. Int. Ed. 60 (2021) 8483-8487.
    Q. Huang, S. Mao, M. Khan, et al., Single-cell identification by microfluidic-based in situ extracting and online mass spectrometric analysis of phospholipids expression, Chem. Sci. 11 (2020) 253-256.
    X. Yi, Q. Zhang, T. Xie, et al., Microfluidic mixer for in situ ammonia analysis of single cells in mass spectrometry, Anal. Chem. 95 (2023) 2321-2328.
    J. Lamanna, E.Y. Scott, H.S. Edwards, et al., Digital microfluidic isolation of single cells for-Omics, Nat. Commun. 11 (2020), 5632.
    Q. Zhang, X. Xu, L. Lin, et al., Cilo-seq: Highly sensitive cell-in-library-out single-cell transcriptome sequencing with digital microfluidics, Lab Chip 22 (2022) 1971-1979.
    X. Xu, L. Lin, J. Yang, et al., Simultaneous single-cell genome and transcriptome sequencing in nanoliter droplet with digital microfluidics identifying essential driving genes, Nano Today 46 (2022), 101596.
    W. Li, M. Khan, L. Lin, et al., Monitoring H2O2 on the surface of single cells with liquid crystal elastomer microspheres, Angew. Chem. Int. Ed. 59 (2020) 9282-9287.
    C. Wang, C. Wang, Y. Wu, et al., High-throughput, living single-cell, multiple secreted biomarker profiling using microfluidic chip and machine learning for tumor cell classification, Adv. Healthcare Mater. 11 (2022), 2102800.
    Q.A. Alshammari, R. Pala, N. Katzir, et al., Label-free spectral imaging to study drug distribution and metabolism in single living cells, Sci. Rep. 11 (2021), 2703.
    H. Kondo, C.D.H. Ratcliffe, S. Hooper, et al., Single-cell resolved imaging reveals intra-tumor heterogeneity in glycolysis, transitions between metabolic states, and their regulatory mechanisms, Cell Rep. 34 (2021), 108750.
    C.A. Dawson, S.N. Mueller, G.J. Lindeman, et al., Intravital microscopy of dynamic single-cell behavior in mouse mammary tissue, Nat. Protoc. 16 (2021) 1907-1935.
    A. R. Heaton, P. R. Rehani, A. Hoefges, et al., Single cell metabolic imaging of tumor and immune cells in vivo in melanoma bearing mice, Front. Oncol. 13 (2023), 1110503.
    L. Pedro, P.J. Rudewicz, Analysis of live single cells by confocal microscopy and high-resolution mass spectrometry to study drug uptake, metabolism, and drug-induced phospholipidosis, Anal. Chem. 92 (2020) 16005-16015.
    N. Altemose, A. Maslan, C. Rios-Martinez, et al., μDamID: A microfluidic approach for joint imaging and sequencing of protein-DNA interactions in single cells, Cell Syst. 11 (2020) 354-366.e9.
    A. Gerard, A. Woolfe, G. Mottet, et al., High-throughput single-cell activity-based screening and sequencing of antibodies using droplet microfluidics, Nat. Biotechnol. 38 (2020) 715-721.
    Y. Wen, J. Liu, H. He, et al., Single-cell analysis of signaling proteins provides insights into proapoptotic properties of anticancer drugs, Anal. Chem. 92 (2020) 12498-12508.
    J. Liu, H. He, D. Xie, et al., Probing low-copy-number proteins in single living cells using single-cell plasmonic immunosandwich assays, Nat. Protoc. 16 (2021) 3522-3546.
    J. Wang, K. Lin, H. Hu, et al., In vitro anticancer drug sensitivity sensing through single-cell Raman spectroscopy, Biosensors 11 (2021), 286.
    Z. Zhao, C. Chen, H. Xiong, et al., Metabolic activity phenotyping of single cells with multiplexed vibrational probes, Anal. Chem. 92 (2020) 9603-9612.
    C. Chen, Z. Zhao, N. Qian, et al., Multiplexed live-cell profiling with Raman probes, Nat. Commun. 12 (2021), 3405.
    M. Li, Y. Nawa, S. Ishida, et al., Label-free chemical imaging of cytochrome P450 activity by Raman microscopy, Commun. Biol. 5 (2022), 778.
    C.C. Hsu, J. Xu, B. Brinkhof, et al., A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons, Proc. Natl. Acad. Sci. U. S. A. 117 (2020) 18412-18423.
    X. Wang, L. Ren, Z. Diao, et al., Robust spontaneous Raman flow cytometry for single-cell metabolic phenome profiling via pDEP-DLD-RFC, Adv. Sci. 10 (2023), 2370102.
    H. Wang, Y. Ruan, L. Zhu, et al., An integrated electrochemical nanodevice for intracellular RNA collection and detection in single living cell, Angew. Chem. Int. Ed. 60 (2021) 13244-13250.
    Y. Xu, Y. Ruan, H. Wang, et al., A practical electrochemical nanotool for facile quantification of amino acids in single cell, Small 17 (2021), 2100503.
    A.N. Vaneev, P.V. Gorelkin, A.S. Garanina, et al., In vitro and in vivo electrochemical measurement of reactive oxygen species after treatment with anticancer drugs, Anal. Chem. 92 (2020) 8010-8014.
    L. Zhou, N. Kasai, H. Nakajima, et al., In situ single-cell stimulation and real-time electrochemical detection of lactate response using a microfluidic probe, Anal. Chem. 93 (2021) 8680-8686.
    E.Z. Macosko, A. Basu, R. Satija, et al., Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets, Cell 161 (2015) 1202-1214.
    L. Tian, J.S. Jabbari, R. Thijssen, et al., Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing, Genome Biol. 22 (2021), 310.
    F. Salmen, J. De Jonghe, T.S. Kaminski, et al., High-throughput total RNA sequencing in single cells using VASA-seq, Nat. Biotechnol. 40 (2022) 1780-1793.
    Q. Qiu, P. Hu, X. Qiu, et al., Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq, Nat. Meth. 17 (2020) 991-1001.
    W. Chen, O. Guillaume-Gentil, P.Y. Rainer, et al., Live-seq enables temporal transcriptomic recording of single cells, Nature 608 (2022) 733-740.
    M. Meyer, A. Paquet, M.J. Arguel, et al., Profiling the non-genetic origins of cancer drug resistance with a single-cell functional genomics approach using predictive cell dynamics, Cell Syst. 11 (2020) 367-374.e5.
    Q. Tang, L. Liu, Y. Guo, et al., Optical cell tagging for spatially resolved single-cell RNA sequencing, Angew. Chem. 134 (2022), e202113929.
    M.R. Vahid, E.L. Brown, C.B. Steen, et al., High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE, Nat. Biotechnol. (2023). https://doi.org/10.1038/s41587-41023-01697-41589.
    X. Pan, H. Yao, S. Zhang, et al., Recent progress in mass spectrometry for single-cell metabolomics, Curr. Opin. Chem. Biol. 71 (2022), 102226.
    X. Men, C. Wu, X. Zhang, et al., Tracking cellular transformation of As(III) in HepG2 cells by single-cell focusing/capillary electrophoresis coupled to ICP-MS, Anal. Chim. Acta 1226 (2022), 340268.
    S.Y. Lim, Z.E. Low, R.P.W. Tan, et al., Single-cell and bulk ICP-MS investigation of accumulation patterns of Pt-based metallodrugs in cisplatin-sensitive and-resistant cell models, Metallomics. 14 (2022), mfac085.
    Y. Meng, X. Cheng, T. Wang, et al., Micro-lensed fiber laser desorption mass spectrometry imaging reveals subcellular distribution of drugs within single cells, Angew. Chem. Int. Ed. 59 (2020) 17864-17871.
    X. Cheng, Z. Yin, L. Rong, et al., Subcellular chemical imaging of structurally similar acridine drugs by near-field laser desorption/laser postionization mass spectrometry, Nano Res. 13 (2020) 745-751.
    F. Jia, J. Wang, Y. Zhao, et al., In situ visualization of proteins in single cells by time-of-flight-secondary ion mass spectrometry coupled with genetically encoded chemical tags, Anal. Chem. 92 (2020) 15517-15525.
    A. Vegvari, J.E. Rodriguez, R.A. Zubarev, Single-cell chemical proteomics (SCCP) interrogates the timing and heterogeneity of cancer cell commitment to death, Anal. Chem. 94 (2022) 9261-9269.
    A.D. Brunner, M. Thielert, C. Vasilopoulou, et al., Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation, Mol. Syst. Biol. 18 (2022), e10798.
    G. Zhu, W. Zhang, Y. Zhao, et al., Single-cell metabolomics-based strategy for studying the mechanisms of drug action, Anal. Chem. 95 (2023) 4712-4720.
    E. Hiyama, A. Ali, S. Amer, et al., Direct lipido-metabolomics of single floating cells for analysis of circulating tumor cells by live single-cell mass spectrometry, Anal. Sci. 31 (2015) 1215-1217.
    A. Ali, Y. Abouleila, S. Amer, et al., Quantitative live single-cell mass spectrometry with spatial evaluation by three-dimensional holographic and tomographic laser microscopy, Anal. Sci. 32 (2016) 125-127.
    E. Cuypers, B.S.R. Claes, R. Biemans, et al., ‘on the spot’ digital pathology of breast cancer based on single-cell mass spectrometry imaging, Anal. Chem. 94 (2022) 6180-6190.
    S. Xu, M. Liu, Y. Bai, et al., Multi-dimensional organic mass cytometry: Simultaneous analysis of proteins and metabolites on single cells, Angew. Chem. Int. Ed. 60 (2021) 1806-1812.
    H. Takeshima, Y. Yoda, M. Wakabayashi, et al., Low-dose DNA demethylating therapy induces reprogramming of diverse cancer-related pathways at the single-cell level, Clin. Epigenet. 12 (2020) 142.
    S.R. Park, S. Namkoong, L. Friesen, et al., Single-cell transcriptome analysis of colon cancer cell response to 5-fluorouracil-induced DNA damage, Cell Rep. 32 (2020), 108077.
    N. Onoda, A. Kawabata, K. Hasegawa, et al., Spatial and single-cell transcriptome analysis reveals changes in gene expression in response to drug perturbation in rat kidney, DNA Res. 29 (2022), dsac007.
    J. Jones-Tabah, R.D. Martin, J.C. Tanny, et al., High-content single-cell Forster resonance energy transfer imaging of cultured striatal neurons reveals novel cross-talk in the regulation of nuclear signaling by protein kinase A and extracellular signal-regulated kinase 1/2, Mol. Pharmacol. 100 (2021) 526-539.
    H. Li, Y. Gao, L. Xie, et al., Prednisone reprograms the transcriptional immune cell landscape in CNS autoimmune disease, Front. Immunol. 12 (2021), 739605.
    M.C. Meinsohn, H.D. Saatcioglu, L. Wei, et al., Single-cell sequencing reveals suppressive transcriptional programs regulated by MIS/AMH in neonatal ovaries, Proc. Natl. Acad. Sci. U. S. A. 118 (2021), e2100920118.
    A. Farkkila, D.C. Gulhan, J. Casado, et al., Author Correction: Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer, Nat. Commun. 11 (2020), 2543.
    R. Zhong, Y. Zhang, D. Chen, et al., Single-cell RNA sequencing reveals cellular and molecular immune profile in a Pembrolizumab-responsive PD-L1-negative lung cancer patient, Cancer Immunol. Immunother. 70 (2021) 2261-2274.
    N. Sahu, F.C. Grandi, N. Bhutani, A single-cell mass cytometry platform to map the effects of preclinical drugs on cartilage homeostasis, JCI Insight 7 (2022), e160702.
    Y. Kashima, D. Shibahara, A. Suzuki, et al., Single-cell analyses reveal diverse mechanisms of resistance to EGFR tyrosine kinase inhibitors in lung cancer, Cancer Res. 81 (2021) 4835-4848.
    S. Taavitsainen, N. Engedal, S. Cao, et al., Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse, Nat. Commun. 12 (2021), 5307.
    Y.C. Cohen, M. Zada, S. Wang, et al., Identification of resistance pathways and therapeutic targets in relapsed multiple myeloma patients through single-cell sequencing, Nat. Med. 27 (2021) 491-503.
    J. Goveia, K. Rohlenova, F. Taverna, et al., An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates, Cancer Cell 37 (2020) 21-36.e13.
    J. Wu, Y. Xiao, J. Sun, et al., A single-cell survey of cellular hierarchy in acute myeloid leukemia, J. Hematol. Oncol. 13 (2020), 128.
    H. Zhao, Y. Gao, J. Miao, et al., Single-cell RNA-seq highlights a specific carcinoembryonic cluster in ovarian cancer, Cell Death Dis. 12 (2021), 1082.
    J. A. Taverna, C. N. Hung, D. T. Dearmond, et al., Single-cell proteomic profiling identifies combined AXL and JAK1 inhibition as a novel therapeutic strategy for lung cancer, Cancer Res. 80 (2020) 1551-1563.
    D.H. Aggen, C.R. Ager, A.Z. Obradovic, et al., Blocking IL1 beta promotes tumor regression and remodeling of the myeloid compartment in a renal cell carcinoma model: Multidimensional analyses, Clin. Cancer Res. 27 (2021) 608-621.
    J.Y. Sung, J.H. Cheong, Single cell analysis reveals reciprocal tumor-macrophage intercellular communications related with metabolic reprogramming in stem-like gastric cancer, Cells 11 (2022), 2373.
    T. Selvin, E. Fasterius, M. Jarvius, et al., Single-cell transcriptional pharmacodynamics of trifluridine in a tumor-immune model, Sci. Rep. 12 (2022), 11960.
    P.J. Lee, C.C. Ho, H. Ho, et al., Tumor microenvironment-based screening repurposes drugs targeting cancer stem cells and cancer-associated fibroblasts, Theranostics 11 (2021) 9667-9686.
    C.J. Messner, L. Babrak, G. Titolo, et al., Single cell gene expression analysis in a 3D microtissue liver model reveals cell type-specific responses to pro-fibrotic TGF-β1 stimulation, Int. J. Mol. Sci. 22 (2021), 4372.
    L.M. Smits, S. Magni, K. Kinugawa, et al., Single-cell transcriptomics reveals multiple neuronal cell types in human midbrain-specific organoids, Cell Tissue Res. 382 (2020) 463-476.
    Y. Zhao, Z. Li, Y. Zhu, et al., Single-cell transcriptome analysis uncovers intratumoral heterogeneity and underlying mechanisms for drug resistance in hepatobiliary tumor organoids, Adv. Sci. 8 (2021), 2003897.
    G. Inak, A. Rybak-Wolf, P. Lisowski, et al., Defective metabolic programming impairs early neuronal morphogenesis in neural cultures and an organoid model of Leigh syndrome, Nat. Commun. 12 (2021), 1929.
    Z. Yuan, X. Fan, J.J. Zhu, et al., Presence of complete murine viral genome sequences in patient-derived xenografts, Nat. Commun. 12 (2021), 2031.
    A. Ediriwickrema, A. Aleshin, J.G. Reiter, et al., Single-cell mutational profiling enhances the clinical evaluation of AML MRD, Blood Adv. 4 (2020) 943-952.
    O. Rozenblatt-Rosen, A. Regev, P. Oberdoerffer, et al., The human tumor atlas network: Charting tumor transitions across space and time at single-cell resolution, Cell 181 (2020) 236-249.
    M. Li, X. Zhang, K.S. Ang, et al., DISCO: A database of Deeply Integrated human Single-Cell Omics data, Nucleic Acids Res. 50 (2022) D596-D602.
    B. Van de Sande, J.S. Lee, E. Mutasa-Gottgens, et al., Applications of single-cell RNA sequencing in drug discovery and development, Nat. Rev. Drug Discov. 22 (2023) 496-520.
    Y. Cao, B. Su, X. Guo, et al., Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells, Cell 182 (2020) 73-84.e16.
    R. Qi, Q. Zou, Trends and potential of machine learning and deep learning in drug study at single-cell level, Research 6 (2023), 005.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)

    Article Metrics

    Article views (336) PDF downloads(27) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return