Skip to main content

Advertisement

Springer Nature Link
Log in

N,S-Decorated graphenes modified with 2,3,7,8,12,13,17,18-octaethyl-21H,23H-porphine manganese(III) chloride-based 3D needle stochastic sensors for enantioanalysis of arginine: a key factor in the metabolomics and early detection of gastric cancer

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

Arginine has an important role in the metabolomics of gastric cancer. Two 3D enantioselective needle stochastic sensors based on the physical immobilization of 2,3,7,8,12,13,17,18-octaethyl-21H,23H-porphine manganese(III) chloride (solution, 10−3 mol L−1) in graphene paste matrices decorated with N and S atoms were designed, characterized and validated for the enantioanalysis of arginine in whole blood and tissue samples. The signature values obtained for the enantiomers of arginine confirmed that the stochastic sensors are enantioselective. The lowest limit of quantification obtained for both enantiomers of arginine was 1 fmol L−1, while sensitivity of up to 1011 s−1 mol−1 L was recorded for the stochastic sensors. High recoveries were obtained for the determination of one enantiomer in the presence of the other one; moreover, very good correlation was found between the results obtained with the two 3D enantioselective needle stochastic sensors.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  1. Jing F, Hu X, Cao Y, Xu M, Wang Y, Jing Y, Hu X, Gao Y, Zhu Z. Discriminating gastric cancer and gastric ulcer using human plasma amino acid metabolic profile. IUBMB Life. 2018;70:553–62.

    Article  CAS  Google Scholar 

  2. Lind DS. Arginine and cancer. J Nutr. 2004;134:2837S–41.

    Article  CAS  Google Scholar 

  3. Liu J, Lin S, Li Z, Zhou L, Yan X, Xue Y, Meng L, Lu J, Suo B, Jian W. Free amino acid profiling of gastric juice as a method for discovering potential biomarkers of early gastric cancer. Int J Clin Exp Pathol. 2018;11:2323–36.

    PubMed  PubMed Central  Google Scholar 

  4. Kögl F, Erxleben H. Zur ätiologie der malignen tumoren. Zeitschrift fűr Physiologische Chemie. 1939;258:57–95.

    Article  Google Scholar 

  5. Bastings JJAJ, van Eijk HM, Damink SWO, Rensen SS. d-amino Acids in Health and Disease: A Focus on Cancer. Nutrients. 2019;11:2205.

    Article  CAS  Google Scholar 

  6. Ilie-Mihai RM, Stefan-van Staden RI, Magerusan L, Coros M, Pruneanu S. Enantioanalysis of tryptophan in whole blood samples using stochastic sensors—A screening test for gastric cancer. Chirality. 2020;32:215–22.

    Article  CAS  Google Scholar 

  7. Bogea IM, Stefan-van Staden RI, Gheorghe DC, Ilie-Mihai RM. Enantioanalysis of Aspartic Acid Using 3D Stochastic Sensors. Anal Lett. 2022;55:8592.

    Article  Google Scholar 

  8. Stefan-van Staden RI, Ilie-Mihai RM, Magerusan L, Coros M, Pruneanu S. Enantioanalysis of glutamine—a key factor in establishing the metabolomics process in gastric cancer. Anal Bioanal Chem. 2020;412:3199–207.

    Article  CAS  Google Scholar 

  9. Wei Z, Liu X, Cheng C, Yu W, Yi P. Metabolism of Amino Acids in Cancer. Frontiers Cell. Dev Biol. 2021;8:603837. https://doi.org/10.3389/fcell.2020.603837.

    Article  Google Scholar 

  10. Glass RE, Goode AW, Houghton BJ, Rowell LW. Plasma arginine in cancer of the gastrointestinal tract: effect of surgical treatment. Gut. 1986;27:8448.

    Article  Google Scholar 

  11. Al-Koussa H, El Mais N, Maalouf H, Abi-Habib R, El-Sibai. Arginine deprivation: a potential therapeutic for cancer cell metastasis? A review. M. Cancer Cell Int. 2020;20:150.

    Article  CAS  Google Scholar 

  12. Rodriguez PC, Quiceno DG, Ochoa AC. L-arginine availability regulates T-lymphocyte cell-cycle progression. Blood. 2007;109:1568–73.

    Article  CAS  Google Scholar 

  13. Scolaro LM, Castriciano M, Romeo A, Patané A, Cefali E, Allegrini M. Aggregation behaviour of Protoporphyrin IX in aqueous solutions: clear evidence of vesicle formation. J Phys Chem B. 2002;106:2453–9.

    Article  CAS  Google Scholar 

  14. Coros M, Pruneanu S, Stefan-van Staden RI. Review—Recent Progress in the Graphene-Based Electrochemical Sensors and Biosensors. J Electrochem Soc. 2020;167:037528.

    Article  CAS  Google Scholar 

  15. Pogacean F, Socaci C, Pruneanu SM, Biris AR, Coros M, Magerusan L, Katona G, Turcu R, Borodi G. Graphene based nanomaterials as chemical sensors for hydrogen peroxide—a comparison study of their intrinsic peroxidase catalytic behavior. Sensors Actuators B Chem. 2015;213:474–83.

    Article  CAS  Google Scholar 

  16. Udayabhaskar R, Mangalaraja RV, Pandiyarajan T, Karthikeyan B, Mansilla HD, Contreras D. Spectroscopic investigation on graphene-copper nanocomposites with strong UV emission and high catalytic activity. Carbon. 2017;124:256–62.

    Article  CAS  Google Scholar 

  17. Stasyuk N, Smutok O, Gayda G, Koval’chuk Y, Gonchar M. A new bi-enzyme potentiometric sensor for arginine analysis based on recombinant human arginase I and commercial urease. J Mater Sci Eng A. 2011;1:819–27.

    Google Scholar 

  18. Stasyuk N, Smutok O, Gayda G, Vus B, Gonchar M, Koval’chuk Y. Bi-enzyme l-arginine-selective amperometric biosensor based on ammonium-sensing polyaniline-modified electrode. Biosens Bioelectron. 2012;37:46–52.

    Article  CAS  Google Scholar 

  19. Stasyuka NY, Gaydaa GZ, Gonchar MV. l-Arginine-selective microbial amperometric sensor based on recombinant yeast cells over-producing human liver arginase I. Sensors Actuators B. 2014;204:515–21.

    Article  Google Scholar 

  20. Nikolelis DP, Hadjiioannou TP. Construction of an arginine enzyme electrode and determination of arginine in biological materials. Anal Chim Acta. 1983;147:33–9.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors are grateful to Alexandra Cioriţă for the SEM investigation of graphene samples and to Alexandru Turza for recording the XRD pattern of the samples.

Funding

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI–UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0006, within PNCDI III.

Author information

Authors and Affiliations

  1. Laboratory of Electrochemistry and PATLAB, National Institute of Research for Electrochemistry and Condensed Matter, 202 Splaiul Independentei Str., 060021, Bucharest-6, Romania

    Raluca-Ioana Stefan-van Staden, Mihaela Iuliana Bogea, Ruxandra-Maria Ilie-Mihai & Damaris-Cristina Gheorghe

  2. Faculty of Applied Chemistry and Material Science, Politehnica University of Bucharest, Bucharest, Romania

    Raluca-Ioana Stefan-van Staden & Mihaela Iuliana Bogea

  3. Pharmaceutical and Medicinal Chemistry Department, The Pharmaceutical and Drug Industries Research Division, National Research Centre, Cairo, Dokki, 12311, Egypt

    Hassan Y. Aboul-Enein

  4. National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103, Donat Street, Cluj Napoca, Romania

    Maria Coros & Stela Maria Pruneanu

Authors
  1. Raluca-Ioana Stefan-van Staden
    View author publications

    Search author on:PubMed Google Scholar

  2. Mihaela Iuliana Bogea
    View author publications

    Search author on:PubMed Google Scholar

  3. Ruxandra-Maria Ilie-Mihai
    View author publications

    Search author on:PubMed Google Scholar

  4. Damaris-Cristina Gheorghe
    View author publications

    Search author on:PubMed Google Scholar

  5. Hassan Y. Aboul-Enein
    View author publications

    Search author on:PubMed Google Scholar

  6. Maria Coros
    View author publications

    Search author on:PubMed Google Scholar

  7. Stela Maria Pruneanu
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Raluca-Ioana Stefan-van Staden.

Ethics declarations

Ethics approval

Ethics committee approval no. 75/2015 obtained from the Hospital of Targu Mures

Source of biological material

Biological samples of whole blood and gastric tumor tissues were obtained from the Hospital of Targu Mures within the project PN-III-P4-ID-PCCF-2016-0006.

Conflicts of interest

The authors declare no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Stefan-van Staden, RI., Bogea, M.I., Ilie-Mihai, RM. et al. N,S-Decorated graphenes modified with 2,3,7,8,12,13,17,18-octaethyl-21H,23H-porphine manganese(III) chloride-based 3D needle stochastic sensors for enantioanalysis of arginine: a key factor in the metabolomics and early detection of gastric cancer. Anal Bioanal Chem 414, 6521–6530 (2022). https://doi.org/10.1007/s00216-022-04209-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-022-04209-x

Keywords

Profiles

  1. Ruxandra-Maria Ilie-Mihai View author profile
  2. Damaris-Cristina Gheorghe View author profile
  3. Hassan Y. Aboul-Enein View author profile