Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling
Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and co...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lv, Jian [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery - Borgès Da Silva, Virginie ELSEVIER, 2018, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:351 ; year:2022 ; day:15 ; month:01 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.snb.2021.130877 |
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| 520 | |a Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. | ||
| 520 | |a Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. | ||
| 650 | 7 | |a Proteins |2 Elsevier | |
| 650 | 7 | |a Sialic acid |2 Elsevier | |
| 650 | 7 | |a Fluorescence imaging |2 Elsevier | |
| 650 | 7 | |a SERS labelling |2 Elsevier | |
| 700 | 1 | |a Chang, Shuai |4 oth | |
| 700 | 1 | |a Wang, Xiaoyuan |4 oth | |
| 700 | 1 | |a Zhou, Zerui |4 oth | |
| 700 | 1 | |a Chen, Binbin |4 oth | |
| 700 | 1 | |a Qian, Ruocan |4 oth | |
| 700 | 1 | |a Li, Dawei |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Borgès Da Silva, Virginie ELSEVIER |t Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery |d 2018 |g Amsterdam [u.a.] |w (DE-627)ELV001079875 |
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10.1016/j.snb.2021.130877 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001580.pica (DE-627)ELV055847501 (ELSEVIER)S0925-4005(21)01445-3 DE-627 ger DE-627 rakwb eng 610 VZ 44.91 bkl Lv, Jian verfasserin aut Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Proteins Elsevier Sialic acid Elsevier Fluorescence imaging Elsevier SERS labelling Elsevier Chang, Shuai oth Wang, Xiaoyuan oth Zhou, Zerui oth Chen, Binbin oth Qian, Ruocan oth Li, Dawei oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:351 year:2022 day:15 month:01 pages:0 https://doi.org/10.1016/j.snb.2021.130877 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 351 2022 15 0115 0 |
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10.1016/j.snb.2021.130877 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001580.pica (DE-627)ELV055847501 (ELSEVIER)S0925-4005(21)01445-3 DE-627 ger DE-627 rakwb eng 610 VZ 44.91 bkl Lv, Jian verfasserin aut Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Proteins Elsevier Sialic acid Elsevier Fluorescence imaging Elsevier SERS labelling Elsevier Chang, Shuai oth Wang, Xiaoyuan oth Zhou, Zerui oth Chen, Binbin oth Qian, Ruocan oth Li, Dawei oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:351 year:2022 day:15 month:01 pages:0 https://doi.org/10.1016/j.snb.2021.130877 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 351 2022 15 0115 0 |
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10.1016/j.snb.2021.130877 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001580.pica (DE-627)ELV055847501 (ELSEVIER)S0925-4005(21)01445-3 DE-627 ger DE-627 rakwb eng 610 VZ 44.91 bkl Lv, Jian verfasserin aut Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Proteins Elsevier Sialic acid Elsevier Fluorescence imaging Elsevier SERS labelling Elsevier Chang, Shuai oth Wang, Xiaoyuan oth Zhou, Zerui oth Chen, Binbin oth Qian, Ruocan oth Li, Dawei oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:351 year:2022 day:15 month:01 pages:0 https://doi.org/10.1016/j.snb.2021.130877 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 351 2022 15 0115 0 |
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10.1016/j.snb.2021.130877 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001580.pica (DE-627)ELV055847501 (ELSEVIER)S0925-4005(21)01445-3 DE-627 ger DE-627 rakwb eng 610 VZ 44.91 bkl Lv, Jian verfasserin aut Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Proteins Elsevier Sialic acid Elsevier Fluorescence imaging Elsevier SERS labelling Elsevier Chang, Shuai oth Wang, Xiaoyuan oth Zhou, Zerui oth Chen, Binbin oth Qian, Ruocan oth Li, Dawei oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:351 year:2022 day:15 month:01 pages:0 https://doi.org/10.1016/j.snb.2021.130877 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 351 2022 15 0115 0 |
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10.1016/j.snb.2021.130877 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001580.pica (DE-627)ELV055847501 (ELSEVIER)S0925-4005(21)01445-3 DE-627 ger DE-627 rakwb eng 610 VZ 44.91 bkl Lv, Jian verfasserin aut Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. Proteins Elsevier Sialic acid Elsevier Fluorescence imaging Elsevier SERS labelling Elsevier Chang, Shuai oth Wang, Xiaoyuan oth Zhou, Zerui oth Chen, Binbin oth Qian, Ruocan oth Li, Dawei oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:351 year:2022 day:15 month:01 pages:0 https://doi.org/10.1016/j.snb.2021.130877 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 351 2022 15 0115 0 |
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However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. 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live-cell profiling of membrane sialic acids by fluorescence imaging combined with sers labelling |
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Live-cell profiling of membrane sialic acids by fluorescence imaging combined with SERS labelling |
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Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. |
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Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. |
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Detecting cell-surface sialic acids (SAs) is essential for cancer research, as accumulating evidence indicates that SA overexpression is closely related to unusual biopathways, such as tumorigenesis. However, it remains challenging to detect and classify membrane SAs. Here, a highly efficient and convenient two-step tagging strategy is described for live-cell profiling of membrane sialic acids with fluorescence imaging and SERS labelling. The fluorescence of SA-linked dyes indicates the SA distribution, whereas the Raman signals recognize the SA-linked proteins marked by aptamer modified SERS probes. Using the tumor markers MUC-1 and TNC as the model proteins, SAs can be partitioned into distinct space domains via Flu/SERS information on living cell membrane. Importantly, we find that SAs are highly expressed near MUC-1 and TNC on the surface of cancer cells, with subtle differences existing among various carcinoma cell lines, enabling classification of various types of cells. Together, our strategy provides a robust and versatile platform for highly detailed analysis of cell surface saccharide profiles and that it has great potential for optical biosensing and molecular diagnosis. |
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