Our Partnership aims to extend the multiparameter capabilities of flow cytometry by measuring Raman spectra from individual cells in flow. We are developing nanoparticle surface enhanced Raman scattering (SERS) tags, a new generation of spectral flow cytometers that can measure high resolution Raman spectra from individual cells, and software for Raman flow cytometry data analysis. The Partnership is applying these problems in multiplexed and highly multi-parameter cell analysis.


Surface Enhanced Raman Scattering (SERS) Tags

We are developing metal nanoparticle-based SERS tags that exhibit distinctive spectral fingerprints that allow for a high degree of spectral multiplexing. Starting with gold or silver nanospheres, nanoshells, or nanorods whose size and shape are tuned to produce a localized surface plasmon resonance at an excitation wave length of interest,  we incorporate Raman-active compounds that confers a unique spectral fingerprint, and then encapsulate it in a polymer layer that can be functionalized with antibodies or other targeting molecules. More than ten distinct SERS tags have been developed thus far, with brightness optimized to allow detection with sub-millisecond measurement times.


Raman Flow Cytometers

We have developed the first Raman flow cytometers, custom instruments that can collect the full Raman spectra from single cells or other particles in 100 microseconds or less. We have also adapted commercial flow cytometer to enable Raman spectral measurements, and have recently developed a family of dual mode flow cytometers that can measure fluorescence signals and Raman spectra simultaneously from individual particles in flow. Current efforts are directed toward developing a Raman-activated cell sorting system.

BRP Intruments_res

Spectral Flow Cytometry Software

We have developed algorithms and software to facilitate the visualization and analysis of of Raman spectral flow cytometry data. FCS Express Spectral is a custom-developed software package that supports the display and analysis of spectral flow cytometry data. In additional to displaying spectra from individual cells and populations of cells, and performing basic arithmetic operations on spectral data, is supports the display of derived parameters generated by spectral unmixing algorithms. These spectral unmixing procedures have been developed in MatLab and feature a user friendly interface and flexibility to support a variety of experimental designs.

BRP Software_res


We are using these reagents, instruments, and software to pursue a applications is immunology and cell biology that require higher levels or multiplexed/multiparameter analysis than is possible using conventional fluorescence flow cytometer. These include applications in cell signaling, antigen-specific immune responses and high throughput screening.


Scintillon Institute 

Stanford University 

DeNovo Software 

Darkling Instruments 


National Institute of Biomedical Imaging and Bioengineering 



1.  Mulligan, S.K., J.A. Spier, I. Razinkov, A. Cheng, J. Crum, T. Jain, E. Duggan, E. Liu, J.P. Nolan, B. Carragher, C.S. Potter (2015) Multiplexed TEM specimen preparation and analysis of plasmonic nanoparticles. Microscopy and Microanalysis (in press).

2.   Stoner, S.A., E. Duggan, D. Condello, A. Guerrero, J.R. Turk, P. Narayanan, J.P. Nolan (2015) High sensitivity analysis of membrane vesicles. Cytometry (in press).

3.   Nolan, J.P. (2015) Flow cytometry of extracellular vesicles: pitfalls and prospects. Current Protocols in Cytometry (in press).

4.   Zhu, S., M. Ling, S. Wang, C. Chen, L. Wang, W. Hang, J.P. Nolan, L. Wu, X. Yan (2014) Light-scattering detection below the level of single fluorescent molecules for high-resolution characterization of functional nanoparticles. ACS Nano 8: 10998-11006.

5.   Nolan, J.P., E. Duggan, D Condello (2014) Optimization of SERS tag intensity, binding footprint, and emittance. Journal of Bioconjugate Chemistry 25: 1233–1242

6.   Nima, Z.A., M. Mahmood, Y. Xu, T. Mustafa, F. Watanabe, D.A. Nedoskin, M.A. Juratli, T. Fahmi, E.I. Galanzha,J.P. Nolan, A.Basnakian, V.P. Zharov, A.S. Biris (2014) Circulating cancer cell identification by functionalized silver-gold nanorods with super-enhanced SERS and photothermal resonances. Scientific Reports 4:4752.

7.   Liu, E., J.P. Nolan (2014) Surface Enhanced Raman Scattering (SERS) Image Cytometry for High Content Screening in Advanced Fluorescence Microscopy Techniques (PM Conn, ed), Elsevier.

8.   Nolan, J.P., S.A. Stoner (2013) A Trigger Channel Threshold Artifact in Nanoparticle Analysis.Cytometry Part A, 83A: 301-305.

9.   Nolan, J.P. and D. Condello (2013) Spectral flow cytometry. Current Protocols in Cytometry, 1.27.1-1.27.13.

10. Nolan, J.P., D. Condello, E. Duggan, M. Naivar, D. Novo (2013) Visible and Near Infrared Fluorescence Spectral Flow Cytometry.Cytometry Part A, 83A: 253-264.

11. Hoffman, R.A., L. Wang, M. Bigos, J.P. Nolan (2012) NIST/ISAC standardization study: Variability in assignment of intensity values to fluorescence standard beads and in cross calibration of standard beads to hard dyed beads Cytometry, 81:785-96.

12. Nolan, J.P., E. Duggan, E Liu, D. Condello, I. Dave, S.A. Stoner (2012) Single cell analysis using surface enhanced Raman scattering (SERS) tags.Methods, 57:272-9.

13. Pérez-Pineiro, R.; Correa-Duarte, M. A.; Salgueirino, V.; Alvarez-Puebla, R. A., (2011) SERS assisted ultra-fast peptidic screening: a new tool for drug discovery. Nanoscale

14. Nolan, J. P.; Sebba, D. S., (2011) Surface Enhanced Raman Scattering (SERS) Cytometry. Methods in Cell Biology, 102, 515.

15. Naivar, M. A.; Wilder, M. E.; Habbersett, R. C.; Woods, T. A.; Sebba, D. S.; Nolan, J. P.; Graves, S. W., (2009) Development of small and inexpensive digital data acquisition systems using a microcontroller‐based approach. Cytometry Part A, 75, 979-989.

16. Sebba, D. S.; Watson, D. A.; Nolan, J. P., (2009) High throughput single nanoparticle spectroscopy. ACS nano, 3, 1477-1484.

17. Watson, D. A.; Gaskill, D. F.; Brown, L. O.; Doorn, S. K.; Nolan, J. P., (2009) Spectral measurements of large particles by flow cytometry. Cytometry Part A, 75, 460-464.

18. Blais, D. R.; varez-Puebla, R. A.; Bravo-Vasquez, J. P.; Fenniri, H.; Pezacki, J. P., (2008) Multiplex pathogen detection based on spatially addressable microarrays of barcoded resins. Biotechnol.J., 3, 948-953.

19. Brown, L. O.; Doorn, S. K., (2008) A controlled and reproducible pathway to dye-tagged, encapsulated silver nanoparticles as substrates for SERS multiplexing. Langmuir, 24, 2277-2280.

20. Brown, L. O.; Doorn, S. K., (2008) Optimization of the Preparation of Glass-Coated, Dye-Tagged Metal Nanoparticles as SERS Substrates. Langmuir, 24, 2178-2185.

21. Watson, D. A.; Brown, L. O.; Gaskill, D. F.; Naivar, M.; Graves, S. W.; Doorn, S. K.; Nolan, J. P.,(2008) A flow cytometer for the measurement of Raman spectra. Cytometry A, 73, 119-128.

22. Farah, A. A.; Bravo‐Vasquez, J. P.; Alvarez‐Puebla, R. A.; Cho, J. Y.; Fenniri, H., (2009) Robust Au–PEG/PS Microbeads as Optically Stable Platforms for SERS. Small, 5, 1283-1286.

23. Farah, A. A.; Alvarez-Puebla, R. A.; Fenniri, H., (2008) Chemically stable silver nanoparticle-crosslinked polymer microspheres. J.Colloid Interface Sci., 319, 572-576.

24. Chen, J.; Zhou, J.; Bae, W.; Sanders, C. K.; Nolan, J. P.; Cai, H., (2008) A yEGFP-based reporter system for high-throughput yeast two-hybrid assay by flow cytometry. Cytometry A, 73, 312-320.

25. Nolan, J. P.; Yang, L., (2007) The flow of cytometry into systems biology. Briefings in Functional Genomics and Proteomics, In press.

26. Nolan, J. P.; Mandy, F., (2006) Multiplexed and microparticle-based analyses: quantitative tools for the large-scale analysis of biological systems. Cytometry A, 69, 318-325.

27. Nolan, J. P.; Yang, L.; van der Heyde, H. C., (2007) Reagents and instruments and for multiplexed analysis using microparticles. Current Protocols in Cytometry.

28. Yan, X.; Zhong, W.; Tang, A.; Schielke, E. G.; Hang, W.; Nolan, J. P., (2005) Multiplexed flow cytometric immunoassay for influenza virus detection and differentiation. Anal.Chem., 77, 7673-7678.

29. Gramaglia, I.; Sobolewski, P.; Meays, D.; Contreras, R.; Nolan, J. P.; Frangos, J. A.; Intaglietta, M.; van der Heyde, H. C., (2006) Low nitric oxide bioavailability contributes to the genesis of experimental cerebral malaria. Nat Med, 12, 1417-1422.

30. Van der Heyde, H. C.; Nolan, J.; Combes, V.; Gramaglia, I.; Grau, G. E., (2006) A unified hypothesis for the genesis of cerebral malaria: sequestration, inflammation and hemostasis leading to microcirculatory dysfunction. Trends in Parasitology, 22, 503-508.

31. Gramaglia, I.; Sahlin, H.; Nolan, J. P.; Frangos, J. A.; Intaglietta, M.; van der Heyde, H. C., (2005) Cell- rather than antibody-mediated immunity leads to the development of profound thrombocytopenia during experimental Plasmodium berghei malaria. J.Immunol., 175, 7699-7707.

32. Yang, L.; Nolan, J. P., (2007) High-throughput screening and characterization of clones selected from phage display libraries. Cytometry A, 71, 625-631.

33. Raez, J.; Blais, D. R.; Zhang, Y.; varez-Puebla, R. A.; Bravo-Vasquez, J. P.; Pezacki, J. P.; Fenniri, H., (2007) Spectroscopically encoded microspheres for antigen biosensing. Langmuir, 23, 6482-6485.

34. Fenniri, H.; Terreau, O.; Chun, S.; Oh, S. J.; Finney, W. F.; Morris, M. D., (2006) Classification of spectroscopically encoded resins by Raman mapping and infrared hyperspectral imaging. ;J Comb.Chem, 8, 192-198.

35. Chun, S.; Xu, J.; Cheng, J.; Ding, L.; Winograd, N.; Fenniri, H., (2006) Spectroscopically encoded resins for high throughput imaging time-of-flight secondary ion mass spectrometry. J Comb.Chem, 8, 18-25.

36. Van der Heyde, H. C.; Burns, J. M.; Weidanz, W. P.; Horn, J.; Gramaglia, I.; Nolan, J. P., (2007 Analysis of antigen-specific antibodies and their isotypes in experimental malaria. Cytometry A, 71, 242-250.

37. Naivar, M.; Parson, J. D.; Wilder, M. E.; Habbersett, R. C.; Edwards, B. S.; Sklar, L. A.; Nolan, J. P.; Graves, S. W.; Martin, J. C.; Jett, J. H.; Freyer, J. P., (2007) Open reconfigurable cytometric acquisition system:ORCAS. Cytometry, 71A, 915-924.

38. Goddard, G.; Martin, J. C.; Naivar, M.; Goodwin, P. M.; Graves, S. W.; Habbersett, R.; Nolan, J. P.; Jett, J. H., (2006) Single particle high resolution spectral analysis flow cytometry. Cytometry A, 69, 842-851.