We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.


The Rise of Micro and Nanoflow in Proteomics

Listen with
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: 6 minutes

A key driver for the advent of proteomics was the realization that complexity is driven by protein variation. Contrary to expectation, the genome is thought to be predominantly invariant1; however, the proteome displays significant plasticity that is a product of protein complexation, post-translational modification (PTM), splicing, and both the spatial and temporal regulation of proteins.2 Proteomics is the concomitant and systematic study of numerous and diverse proteins. Given that the proteome is a readout of the changing state of cells, tissues, and therefore the organism, it underpins our understanding of both health and disease.

Nanoscale proteomics

As other technologies mature and move toward smaller sample sizes (microscale to nanoscale), proteomics must meet these emerging challenges. Nanoscale samples are defined as those containing less than 1 μg of total protein, and by extension, proteomic analysis of these samples is dubbed “nano proteomics”.3 To illustrate the difference in the micro and nanoscale sample domains, a million cells contain ~ 50000 ng of protein and a single cell 0.5 ng.4 Multiple inquiries, such as the interrogation of the cellular microenvironment5, the study of extracellular vesicles6, and rare populations of cells7, are liable to result in low volume samples. Frequently these sample-limited specimens are generated by innovative techniques such as laser capture micro-dissection (LCM)8, fluorescence-activated cell sorting (FACS)9, and miniaturized “lab-on-chip” microfluidic devices.10

Evolution of nano and microflow liquid chromatography

The capability of mass spectrometry to simultaneously identify and quantify thousands of proteins from diverse samples makes it a vital tool within the field of proteomics.11 The improvements in mass spectrometer (MS) performance over the last decade is the most pivotal factor for achieving significant increases in overall sensitivity. MS performance has incrementally improved in numerous categories. These technological advances include mass accuracy and resolving power, advanced ion optics, improved scanning speeds, dynamic range, and sensitivity.4 Liquid-phase separations, such as liquid chromatography (LC), have improved MS sensitivity by using LC columns with smaller internal diameters (ID) and reducing the volume of fluid flowing through the column.

Definition of micro and nanoflow

The miniaturization of liquid chromatography (LC) systems has been accelerated by analytical necessity. Conventional flow LC systems increasingly lack application when sample volumes are scarce, and analyte concentrations are low. There are no universally accepted definitions of the terms nano and microflow; however, it is generally accepted that microflow is performed on capillary columns with an ID of <1.0 mm, at a reduced flow rate of <100 μl/min.12,13 In nanoflow-LC chromatographic separations are performed using flow rates in the range of low nl/min.14

Microflow LC-MS

Conventional flow techniques are widely used as they offer both rapid and robust analysis. However, microflow-LC occupies a niche between conventional and nanoflow-LC, more sensitive than conventional flow, and more rugged than nanoflow. Employment of microflow LC for sensitivity improvement is achieved by performing chromatography on capillary columns with an internal diameter of <1.0 mm, at a reduced flow rate of <50 μl/min. Technical advances have driven a resurgence in the use of microflow-LC, including flow pumps that can accurately and reliably deliver the requisite LC-flow rate without splitting, and improved coupling of the microflow-LC to the mass spectrometer.12

The use of MS within the regulatory setting has been previously limited as the analytical method is not considered robust enough. Methotrexate has been historically prescribed for several autoimmune diseases such as rheumatoid arthritis, ankylosing spondylitis, and systemic lupus erythematosus.15 Methotrexate may be administered alongside newer or novel preparations. It is, therefore, vital to determine any potential drug-drug interactions. Christensen et al. have used microflow LC-MS to quantify methotrexate in plasma samples reliably. The overall precision, accuracy and ruggedness was compared with conventional high pressure liquid chromatography – mass spectrometry (HPLC–MS/MS) and this bioanalytical validation data was deemed to meet Food and Drug Administration (FDA) criteria.13

Nanoflow LC-MS

The use of nanoflow-LC for separating peptides or proteins prior to MS is widespread.16 The sensitivity achieved with nanoflow-LC is its main advantage. This is achieved by compounds entering the MS in more concentrated bands. Its improved sensitivity makes this technique particularly applicable to limited samples or low abundance analytes.17 However, there are technical challenges associated with nanoflow LC and its inherent low flow rates, this technology is used in research laboratories but may still be challenging to run routinely in settings such as clinics.18 Nanoflow is also associated with slow run times.

The sensitivity associated with Nanoflow-LC has contributed to its use in a variety of novel analytical settings that may have a sample limited input. Tissues are often heterogenous in nature, and the ability to interrogate cellular heterogeneity is vitally important, for example, microheterogeneity in tumor biology. Ultra-sensitive nanoflow-LC has been combined with FACS and bespoke nanodroplet sample preparation (nanoPOTS), enabling the identification of >700 proteins from a single HeLa cell. This proteome coverage (for a single cell) is more comprehensive than previously reported.17 This affords the possibility of investigating single cells and their microenvironment to help determine their contribution to disease progression.

Biomarker discovery is often complicated by methodological challenges, where low concentrations of analytes must be determined in a complex matrix. Poor ovarian response is typically difficult to predict. Biomarker discovery studies (conducted during IVF treatment) on follicular fluid were performed using a high‐resolution orbitrap mass spectrometer coupled to a nanoflow‐LC system. Numerous proteins were identified (1079), and three of these proteins (renin, pregnancy zone protein, and sushi repeat-containing protein (SRPX)) were identified as predictors of a poor response.19

Imaging mass spectrometry (IMS) is an emerging technique for mapping the spatial distribution of analytes (e.g., lipids) across tissue. However, various technical challenges have limited its application to proteomics. Applying these methods would have traditionally relied on labels that require prior knowledge of protein targets. Label-free LC-nanoflow proteomics has been used to analyze tissue voxels, prepared from mouse uterus prior to blastocyst implantation. This generated quantitative cell-type-specific images for more than 2000 proteins with a spatial resolution of 100 μm.20

Tooth enamel is the densest, hardest, and most mineralized human tissue. Analysis of its proteome is further complicated by the meager (<1%) presence of proteinaceous material. Amelogenin is a dimorphic and abundant tooth protein and expressed from both X and Y chromosomes. Gender may, therefore, be revealed by sequencing the gender dimorphic peptide regions. The analysis of enamel is crucial in archeological or forensic specimens where no other tissue is available and DNA may be irreparably degraded. In these circumstances, the amount of sample available may also be severely restricted. Unique peptides have been identified by acid etching single teeth and peptide identification made possible using nanoflow LC-MS. This workflow has enabled the identification of major structural enamel peptides, including amelogenin isoforms, in teeth obtained from Anglo-Saxon burials (600–900 AD).21

Given the drive toward increasingly small sample sizes, both micro and nano-LC are expected to play larger roles in research proteomics and will therefore remain fundamental to the advancement of biomedical science.


  1. Patterson SD, Aebersold RH. (2003). Proteomics: the first decade and beyond. Nature Genetics. DOI: https://doi.org/10.1038/ng1106
  2. Altelaar AFM, Munoz J, Heck AJR. (2013). Next-generation proteomics: towards an integrative view of proteome dynamics. Nature Reviews Genetics. DOI: https://doi.org/10.1038/nrg3356
  3. Wang H, Qian W-J, Mottaz HM, Clauss TRW, Anderson DJ, Moore RJ, et al. (2005). Development and evaluation of a micro- and nanoscale proteomic sample preparation method. Journal of Proteome Research. DOI: https://doi.org/10.1021/pr050160f
  4. Yi L, Piehowski PD, Shi T, Smith RD, Qian W-J. (2017). Advances in microscale separations towards nanoproteomics applications. Journal of Chromatography A. DOI: https://doi.org/10.1016/j.chroma.2017.07.055
  5. Hanash S, Schliekelman M. (2014). Proteomic profiling of the tumor microenvironment: recent insights and the search for biomarkers. Genome Medicine. DOI: https://doi.org/10.1186/gm529
  6. Bandu R, Oh JW, Kim KP. (2019). Mass spectrometry-based proteome profiling of extracellular vesicles and their roles in cancer biology. Experimental & Molecular Medicine. DOI: https://doi.org/10.1038/s12276-019-0218-2
  7. Zhu Y, Piehowski PD, Kelly RT, Qian W-J. (2018). Nanoproteomics comes of age. Expert Reviews of Proteomics. DOI: https://doi.org/10.1080/14789450.2018.1537787
  8. Clair G, Piehowski PD, Nicola T, Kitzmiller JA, Huang EL, Zink EM, et al. (2016). Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples. Scientific Reports. DOI: https://doi.org/10.1038/srep39223
  9. Gawad C, Koh W, Quake SR. (2016). Single-cell genome sequencing: current state of the science. Nature Reviews Genetics. DOI: https://doi.org/10.1038/nrg.2015.16
  10. Furlan C, Dirks RAM, Thomas PC, Jones RC, Wang J, Lynch M, et al. (2019). Miniaturised interaction proteomics on a microfluidic platform with ultra-low input requirements. Nature Communications. DOI: https://doi.org/10.1038/s41467-019-09533-y
  11. Aebersold R, Mann M. (2003). Mass spectrometry-based proteomics. Nature. DOI: https://doi.org/10.1038/nature01511
  12. Zhang J, Shou W, Ogura T, Li S, Weller H. (2019). Optimization of microflow LC–MS/MS and its utility in quantitative discovery bioanalysis. Bioanalysis. DOI: https://doi.org/10.4155/bio-2019-0076
  13. Christianson CC, Johnson CJ, Needham SR. (2013). The advantages of microflow LC–MS/MS compared with conventional HPLC–MS/MS for the analysis of methotrexate from human plasma. Bioanalysis. DOI: https://doi.org/10.4155/bio.13.73
  14. R. Cutillas P. (2005). Principles of Nanoflow Liquid Chromatography and Applications to Proteomics. Current Nanoscience. DOI: https://doi.org/10.2174/1573413052953093
  15. Cipriani P, Ruscitti P, Carubbi F, Liakouli V, Giacomelli R. (2014). Methotrexate: an old new drug in autoimmune disease. Expert Review of Clinical Immunology. DOI: https://doi.org/10.1586/1744666x.2014.962996
  16. Wilson SR, Vehus T, Berg HS, Lundanes E. (2015). Nano-LC in proteomics: recent advances and approaches. Bioanalysis. DOI: https://doi.org/10.4155/bio.15.92
  17. Zhu Y, Clair G, Chrisler WB, Shen Y, Zhao R, Shukla AK, et al. (2018). Proteomic Analysis of Single Mammalian Cells Enabled by Microfluidic Nanodroplet Sample Preparation and Ultrasensitive NanoLC-MS. Angewandte Chemie. DOI: https://doi.org/10.1002/anie.201802843
  18. Gaspari M, Cuda G. (2011). Nano LC-MS/MS: a robust setup for proteomic analysis. Methods in Molecular Biology. DOI: https://doi.org/10.1007/978-1-61779-319-6_9
  19. Oh JW, Kim SK, Cho K-C, Kim M-S, Suh CS, Lee JR, et al. (2017). Proteomic analysis of human follicular fluid in poor ovarian responders during in vitro fertilization. Proteomics. DOI: https://doi.org/10.1002/pmic.201600333
  20. Piehowski PD, Zhu Y, Bramer LM, Stratton KG, Zhao R, Orton DJ, et al. (2020). Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-μm spatial resolution. Nature Communications. DOI: https://doi.org/10.1038/s41467-019-13858-z
  21. Stewart NA, Molina GF, Issa JPM, Yates NA, Sosovicka M, Vieira AR, et al. (2016). The identification of peptides by nanoLC-MS/MS from human surface tooth enamel following a simple acid etch extraction. RSC Advances. DOI: https://doi.org/10.1039/C6RA05120K