Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Leukocyte function assessed via serial microlitre sampling of peripheral blood from sepsis patients correlates with disease severity

Abstract

Dysregulated leukocyte responses underlie the pathobiology of sepsis, which is a leading cause of death. However, measures of leukocyte function are not routinely available in clinical care. Here we report the development and testing of an inertial microfluidic system for the label-free isolation and downstream functional assessment of leukocytes from 50 μl of peripheral blood. We used the system to assess leukocyte phenotype and function in serial samples from 18 hospitalized patients with sepsis and 10 healthy subjects. The sepsis samples had significantly higher levels of CD16dim and CD16 neutrophils and CD16+ ‘intermediate’ monocytes, as well as significantly lower levels of neutrophil-elastase release, O2 production and phagolysosome formation. Repeated sampling of sepsis patients over 7 days showed that leukocyte activation (measured by isodielectric separation) and leukocyte phenotype and function were significantly more predictive of the clinical course than complete-blood-count parameters. We conclude that the serial assessment of leukocyte function in microlitre blood volumes is feasible and that it provides significantly more prognostic information than leukocyte counting.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Closed-loop inertial microfluidic separation of leukocytes from whole blood.
Fig. 2: Neutrophil subsets and function in sepsis and healthy patients.
Fig. 3: IDS of activated from non-activated human PMNs.
Fig. 4: Monocyte subsets in sepsis and healthy patients.
Fig. 5: Principal component analyses for routine CBC measures, clinical severity and leukocyte phenotype and function in sepsis and healthy patients.
Fig. 6: Correlation between PMN responses and measures of clinical severity during sepsis.

Similar content being viewed by others

Data availability

The data supporting the results in this study are available in the Article and Supplementary Information. The raw patient data are available from the authors, subject to approval from the Institutional Review Board of Partner’s Healthcare.

Code availability

The custom code used in this study is available at https://github.com/bdlevylab/BDLevy-Lab.

References

  1. Delano, M. J. & Ward, P. A. Sepsis-induced immune dysfunction: can immune therapies reduce mortality? J. Clin. Invest. 126, 23–31 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Angus, D. C. & van der Poll, T. Severe sepsis and septic shock. N. Engl. J. Med. 369, 840–851 (2013).

    Article  CAS  PubMed  Google Scholar 

  3. Serhan, C. N. Pro-resolving lipid mediators are leads for resolution physiology. Nature 510, 92–101 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Majno, G. & Joris, I. Cells, Tissues, and Disease 2nd edn (Oxford University Press, 2004).

  5. Spite, M. et al. Resolvin D2 is a potent regulator of leukocytes and controls microbial sepsis. Nature 461, 1287–1291 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Singer, M. et al. The Third International Consensus definitions for sepsis and septic shock (Sepsis-3). J. Am. Med. Assoc. 315, 801–810 (2016).

    Article  CAS  Google Scholar 

  7. Rhee, C. et al. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014. J. Am. Med. Assoc. 318, 1241–1249 (2017).

    Article  Google Scholar 

  8. Buchegger, P. & Preininger, C. Point-of-care chip for diagnosis of sepsis: joining biomarker quantification and bacterial class identification. Biomed. Tech. https://doi.org/10.1515/bmt-2013-4146 (2013).

  9. Hassan, U. et al. A point-of-care microfluidic biochip for quantification of CD64 expression from whole blood for sepsis stratification. Nat. Commun. 8, 15949 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kemmler, M., Sauer, U., Schleicher, E., Preininger, E. & Brandenburg, A. Biochip point-of-care device for sepsis diagnostics. Sens. Actuat. B 192, 205–215 (2014).

    Article  CAS  Google Scholar 

  11. Reddy, B. et al. Point-of-care sensors for the management of sepsis. Nat. Biomed. Eng. 2, 640–648 (2018).

    Article  PubMed  Google Scholar 

  12. Zhang, Y. et al. Detection of sepsis in patient blood samples using CD64 expression in a microfluidic cell separation device. Analyst 143, 241–249 (2017).

    Article  PubMed  Google Scholar 

  13. Zhang, Y. et al. Multiparameter affinity microchip for early sepsis diagnosis based on CD64 and CD69 expression and cell capture. Anal. Chem. 90, 7204–7211 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Zhou, Y. et al. Detection of culture-negative sepsis in clinical blood samples using a microfluidic assay for combined CD64 and CD69 cell capture. Anal. Chim. Acta 1062, 110–117 (2019).

    Article  CAS  PubMed  Google Scholar 

  15. Ellett, F. et al. Diagnosis of sepsis from a drop of blood by measurement of spontaneous neutrophil motility in a microfluidic assay. Nat. Biomed. Eng. 2, 207–214 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Vincent, J. L. et al. Anemia and blood transfusion in critically ill patients. J. Am. Med. Assoc. 288, 1499–1507 (2002).

    Article  Google Scholar 

  17. Ryu, H.et al. Label-free neutrophil enrichment from patient-derived airway secretion using closed-loop inertial microfluidics. J. Vis. Exp. https://doi.org/10.3791/57673 (2018).

  18. Wu, L., Guan, G., Hou, H. W., Bhagat, A. A. & Han, J. Separation of leukocytes from blood using spiral channel with trapezoid cross-section. Anal. Chem. 84, 9324–9331 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Ryu, H. et al. Patient-derived airway secretion dissociation technique to isolate and concentrate immune cells using closed-loop inertial microfluidics. Anal. Chem. 89, 5549–5556 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Amini, H., Lee, W. & Di Carlo, D. Inertial microfluidic physics. Lab Chip 14, 2739–2761 (2014).

    Article  CAS  PubMed  Google Scholar 

  21. Di Carlo, D. Inertial microfluidics. Lab Chip 9, 3038–3046 (2009).

    Article  PubMed  CAS  Google Scholar 

  22. Prieto, J. L. et al. Monitoring sepsis using electrical cell profiling. Lab Chip 16, 4333–4340 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Gonzalez, I. et al. A label free disposable device for rapid isolation of rare tumor cells from blood by ultrasounds. Micromachines 9, 129 (2018).

    Article  PubMed Central  Google Scholar 

  24. Li, P. et al. Acoustic separation of circulating tumor cells. Proc. Natl Acad. Sci. USA 112, 4970–4975 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Mach, A. J. & Di Carlo, D. Continuous scalable blood filtration device using inertial microfluidics. Biotechnol. Bioeng. 107, 302–311 (2010).

    Article  CAS  PubMed  Google Scholar 

  26. Nivedita, N. & Papautsky, I. Continuous separation of blood cells in spiral microfluidic devices. Biomicrofluidics 7, 54101 (2013).

    Article  PubMed  CAS  Google Scholar 

  27. Smith, A. J. et al. Rapid cell separation with minimal manipulation for autologous cell therapies. Sci. Rep. 7, 41872 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ai, Y., Sanders, C. K. & Marrone, B. L. Separation of Escherichia coli bacteria from peripheral blood mononuclear cells using standing surface acoustic waves. Anal. Chem. 85, 9126–9134 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wu, M. et al. Isolation of exosomes from whole blood by integrating acoustics and microfluidics. Proc. Natl Acad. Sci. USA 114, 10584–10589 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Vykoukal, J., Vykoukal, D. M., Freyberg, S., Alt, E. U. & Gascoyne, P. R. Enrichment of putative stem cells from adipose tissue using dielectrophoretic field-flow fractionation. Lab Chip 8, 1386–1393 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Vahey, M. D., Quiros Pesudo, L., Svensson, J. P., Samson, L. D. & Voldman, J. Microfluidic genome-wide profiling of intrinsic electrical properties in Saccharomyces cerevisiae. Lab Chip 13, 2754–2763 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Di Carlo, D., Irimia, D., Tompkins, R. G. & Toner, M. Continuous inertial focusing, ordering, and separation of particles in microchannels. Proc. Natl Acad. Sci. USA 104, 18892–18897 (2007).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  33. Nivedita, N., Ligrani, P. & Papautsky, I. Dean flow dynamics in low-aspect ratio spiral microchannels. Sci. Rep. 7, 44072 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Wang, X. & Papautsky, I. Size-based microfluidic multimodal microparticle sorter. Lab Chip 15, 1350–1359 (2015).

    Article  CAS  PubMed  Google Scholar 

  35. Hou, H. W. et al. Isolation and retrieval of circulating tumor cells using centrifugal forces. Sci. Rep. 3, 1259 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Khoo, B. L. et al. Clinical validation of an ultra high-throughput spiral microfluidics for the detection and enrichment of viable circulating tumor cells. PLoS ONE 9, e99409 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Warkiani, M. E. et al. Slanted spiral microfluidics for the ultra-fast, label-free isolation of circulating tumor cells. Lab Chip 14, 128–137 (2014).

    Article  CAS  PubMed  Google Scholar 

  38. Warkiani, M. E. et al. An ultra-high-throughput spiral microfluidic biochip for the enrichment of circulating tumor cells. Analyst 139, 3245–3255 (2014).

    Article  CAS  PubMed  Google Scholar 

  39. Warkiani, M. E. et al. Ultra-fast, label-free isolation of circulating tumor cells from blood using spiral microfluidics. Nat. Protoc. 11, 134–148 (2016).

    Article  CAS  PubMed  Google Scholar 

  40. Yin, L. et al. Microfluidic label-free selection of mesenchymal stem cell subpopulation during culture expansion extends the chondrogenic potential in vitro. Lab Chip 18, 878–889 (2018).

    Article  CAS  PubMed  Google Scholar 

  41. Choi, K. et al. Negative selection by spiral inertial microfluidics improves viral recovery and sequencing from blood. Anal. Chem. 90, 4657–4662 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hou, H. W., Bhattacharyya, R. P., Hung, D. T. & Han, J. Direct detection and drug-resistance profiling of bacteremias using inertial microfluidics. Lab Chip 15, 2297–2307 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Abdulla, A., Liu, W., Gholamipour-Shirazi, A., Sun, J. & Ding, X. High-throughput isolation of circulating tumor cells using cascaded inertial focusing microfluidic channel. Anal. Chem. 90, 4397–4405 (2018).

    Article  CAS  PubMed  Google Scholar 

  44. Nivedita, N., Garg, N., Lee, A. P. & Papautsky, I. A high throughput microfluidic platform for size-selective enrichment of cell populations in tissue and blood samples. Analyst 142, 2558–2569 (2017).

    Article  CAS  PubMed  Google Scholar 

  45. Shen, X. F., Cao, K., Jiang, J. P., Guan, W. X. & Du, J. F. Neutrophil dysregulation during sepsis: an overview and update. J. Cell. Mol. Med. 21, 1687–1697 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Solomkin, J. S., Cotta, L. A., Brodt, J. K. & Hurst, J. M. Regulation of neutrophil superoxide production in sepsis. Arch. Surg. 120, 93–98 (1985).

    Article  CAS  PubMed  Google Scholar 

  47. Pillay, J. et al. A subset of neutrophils in human systemic inflammation inhibits T cell responses through Mac-1. J. Clin. Invest. 122, 327–336 (2012).

    Article  CAS  PubMed  Google Scholar 

  48. Lollike, K. & Lindau, M. Membrane capacitance techniques to monitor granule exocytosis in neutrophils. J. Immunol. Methods 232, 111–120 (1999).

    Article  CAS  PubMed  Google Scholar 

  49. Griffith, A. W. & Cooper, J. M. Single-cell measurements of human neutrophil activation using electrorotation. Anal. Chem. 70, 2607–2612 (1998).

    Article  CAS  PubMed  Google Scholar 

  50. Holmes, D. et al. Leukocyte analysis and differentiation using high speed microfluidic single cell impedance cytometry. Lab Chip 9, 2881–2889 (2009).

    Article  CAS  PubMed  Google Scholar 

  51. Ziegler-Heitbrock, L. Monocyte subsets in man and other species. Cell. Immunol. 289, 135–139 (2014).

    Article  CAS  PubMed  Google Scholar 

  52. Abdulnour, R. E. et al. Early intravascular events are associated with development of acute respiratory distress syndrome. A substudy of the LIPS-A clinical trial. Am. J. Respir. Crit. Care Med. 197, 1575–1585 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Patel, A. A. et al. The fate and lifespan of human monocyte subsets in steady state and systemic inflammation. J. Exp. Med. 214, 1913–1923 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Zawada, A. M. et al. SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset. Blood 118, e50–e61 (2011).

    Article  CAS  PubMed  Google Scholar 

  55. Pierrakos, C. & Vincent, J. L. Sepsis biomarkers: a review. Crit. Care 14, R15 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Villani, A. C. et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science 356, eaah4573 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Seymour, C. W. Assessment of clinical criteria for sepsis. JAMA 315, 762 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Dolinay, T. et al. Inflammasome-regulated cytokines are critical mediators of acute lung injury. Am. J. Respir. Crit. Care Med. 185, 1225–1234 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Fredenburgh, L. E. et al. A phase I trial of low-dose inhaled carbon monoxide in sepsis-induced ARDS. JCI Insight 3, e124039 (2018).

    Article  PubMed Central  Google Scholar 

  60. Barnig, C. et al. Lipoxin A4 regulates natural killer cell and type 2 innate lymphoid cell activation in asthma. Sci. Transl. Med. 5, 174ra126 (2013).

    Article  CAS  Google Scholar 

  61. Neutrophil Elastase Activity Assay Kit. Cayman Chemical https://www.caymanchem.com/product/600610/neutrophil-elastase-activity-assay-kit (2019).

Download references

Acknowledgements

The authors acknowledge the contributions of G. Zhu, L. A. Cosimi and additional members of the Brigham and Women’s Registry of Critical Illness (including L. Fredenburgh, P. Dieffenbach, S. Ash and J. Englert). The work was supported by grant nos. U24-AI118656 (B.D.L., J.V.), K08-HL130540 (R.E.A.) and K12-HD047349 (M.G.D).

Author information

Authors and Affiliations

Authors

Contributions

B.J., H.R. and D.-H.L. contributed equally to this study. J.H., J.V. and B.D.L. coconceived the study. B.J., H.R., D.-H.L., R.E.A., B.D.E., M.G.D., J.L., R.M.B., N.K., J.H., J.V. and B.D.L. designed the experiments and interpreted the results. B.J., D.-H.L., R.E.A., B.D.E, J.L., J.V. and B.D.L. performed and analysed the functional biological experiments. H.R. and J.H. designed and performed experiments using the inertial microfluidic system. A.H., M.P.-V., M.E.B. and R.M.B. provided blood samples and clinical data from patients with sepsis. The manuscript was written by B.J., H.R., D.-H.L., R.E.A., B.D.E., M.G.D., J.L., N.K., R.M.B., J.H., J.V. and B.D.L.

Corresponding author

Correspondence to Bruce D. Levy.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jundi, B., Ryu, H., Lee, DH. et al. Leukocyte function assessed via serial microlitre sampling of peripheral blood from sepsis patients correlates with disease severity. Nat Biomed Eng 3, 961–973 (2019). https://doi.org/10.1038/s41551-019-0473-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41551-019-0473-5

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing