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High-Content Quantification of Single-Cell Immune Dynamics.

Junkin M, Kaestli AJ, Cheng Z, Jordi C, Albayrak C, Hoffmann A, Tay S - Cell Rep (2016)

Bottom Line: Characterizing dynamic input-output relationships in single cells is crucial for understanding and modeling cellular systems.We developed an automated microfluidic system that delivers precisely defined dynamical inputs to individual living cells and simultaneously measures key immune parameters dynamically.Our system combines nanoliter immunoassays, microfluidic input generation, and time-lapse microscopy, enabling study of previously untestable aspects of immunity by measuring time-dependent cytokine secretion and transcription factor activity from single cells stimulated with dynamic inflammatory inputs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland.

No MeSH data available.


Relationship between NF-κB and TNF Secretion Recapitulated by a Mathematical Model of the Mechanisms Governing NF-κB Activation and TNF Production(A) A table cross-correlating, qualitatively, nuclear NF-κB activation and TNF secretion. Cells with a NF-κB peak during LPS stimulation greater than baseline NF-κB level by 2 SDs are categorized as NF-κB+. Other cells are categorized as NF-κB−. Cells with a measured TNF peak larger than 5% of maximum measured TNF in the whole population are defined as TNF+; others are categorized as TNF−.(B) Quantitative cross-correlation (by Pearson coefficient) between the magnitude of observed NF-κB peak values with observed TNF release peaks.(C) The modified Caldwell et al. (2014) model to simulate LPS pulse induced TNF secretion at the single-cell level. Extrinsic noise was added by sampling key kinetic parameters from gamma distributions as in Cheng et al. (2015).(D) Model predictions of active TRIF, nuclear NF-κB, and secreted TNF dynamics in 500 single cells, with red lines showing mean behavior. Simulated secretion profiles agree well with the measured single-cell TNF secretion time courses.(E) The model simulations indicate that, qualitatively, NF-κB positivity (NF-κB+) correlates better to TNF positivity (TNF+) than TRIF positivity (TRIF+). Many cells categorized as TRIF− may produce TNF above the detectable level.(F) The model simulations indicate that TNF peak magnitude is not quantitatively correlated (by Pearson coefficient) to nuclear NF-κB peak magnitude but is quantitatively correlated to peak TRIF values.
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fig6: Relationship between NF-κB and TNF Secretion Recapitulated by a Mathematical Model of the Mechanisms Governing NF-κB Activation and TNF Production(A) A table cross-correlating, qualitatively, nuclear NF-κB activation and TNF secretion. Cells with a NF-κB peak during LPS stimulation greater than baseline NF-κB level by 2 SDs are categorized as NF-κB+. Other cells are categorized as NF-κB−. Cells with a measured TNF peak larger than 5% of maximum measured TNF in the whole population are defined as TNF+; others are categorized as TNF−.(B) Quantitative cross-correlation (by Pearson coefficient) between the magnitude of observed NF-κB peak values with observed TNF release peaks.(C) The modified Caldwell et al. (2014) model to simulate LPS pulse induced TNF secretion at the single-cell level. Extrinsic noise was added by sampling key kinetic parameters from gamma distributions as in Cheng et al. (2015).(D) Model predictions of active TRIF, nuclear NF-κB, and secreted TNF dynamics in 500 single cells, with red lines showing mean behavior. Simulated secretion profiles agree well with the measured single-cell TNF secretion time courses.(E) The model simulations indicate that, qualitatively, NF-κB positivity (NF-κB+) correlates better to TNF positivity (TNF+) than TRIF positivity (TRIF+). Many cells categorized as TRIF− may produce TNF above the detectable level.(F) The model simulations indicate that TNF peak magnitude is not quantitatively correlated (by Pearson coefficient) to nuclear NF-κB peak magnitude but is quantitatively correlated to peak TRIF values.

Mentions: The observed TNF release by single cells displays a heterogeneous and dynamic immune secretory response to pathogenic input. Although NF-κB activation and TNF secretion were qualitatively correlated (Figure 6A), considering their amplitudes quantitatively revealed no correlation (Pearson correlation r = −0.06; Figure 6B). To understand mechanisms of the observed TNF release profiles and understand why NF-κB activation and TNF secretion showed so little correlation, we undertook computational modeling of the kinetic interplay of mechanisms controlling not only TNF mRNA synthesis but also mRNA processing and half-life control, translation to TNF pro-protein, protein maturation, and secretion (Caldwell et al., 2014, Cheng et al., 2015, Werner et al., 2005).


High-Content Quantification of Single-Cell Immune Dynamics.

Junkin M, Kaestli AJ, Cheng Z, Jordi C, Albayrak C, Hoffmann A, Tay S - Cell Rep (2016)

Relationship between NF-κB and TNF Secretion Recapitulated by a Mathematical Model of the Mechanisms Governing NF-κB Activation and TNF Production(A) A table cross-correlating, qualitatively, nuclear NF-κB activation and TNF secretion. Cells with a NF-κB peak during LPS stimulation greater than baseline NF-κB level by 2 SDs are categorized as NF-κB+. Other cells are categorized as NF-κB−. Cells with a measured TNF peak larger than 5% of maximum measured TNF in the whole population are defined as TNF+; others are categorized as TNF−.(B) Quantitative cross-correlation (by Pearson coefficient) between the magnitude of observed NF-κB peak values with observed TNF release peaks.(C) The modified Caldwell et al. (2014) model to simulate LPS pulse induced TNF secretion at the single-cell level. Extrinsic noise was added by sampling key kinetic parameters from gamma distributions as in Cheng et al. (2015).(D) Model predictions of active TRIF, nuclear NF-κB, and secreted TNF dynamics in 500 single cells, with red lines showing mean behavior. Simulated secretion profiles agree well with the measured single-cell TNF secretion time courses.(E) The model simulations indicate that, qualitatively, NF-κB positivity (NF-κB+) correlates better to TNF positivity (TNF+) than TRIF positivity (TRIF+). Many cells categorized as TRIF− may produce TNF above the detectable level.(F) The model simulations indicate that TNF peak magnitude is not quantitatively correlated (by Pearson coefficient) to nuclear NF-κB peak magnitude but is quantitatively correlated to peak TRIF values.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

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fig6: Relationship between NF-κB and TNF Secretion Recapitulated by a Mathematical Model of the Mechanisms Governing NF-κB Activation and TNF Production(A) A table cross-correlating, qualitatively, nuclear NF-κB activation and TNF secretion. Cells with a NF-κB peak during LPS stimulation greater than baseline NF-κB level by 2 SDs are categorized as NF-κB+. Other cells are categorized as NF-κB−. Cells with a measured TNF peak larger than 5% of maximum measured TNF in the whole population are defined as TNF+; others are categorized as TNF−.(B) Quantitative cross-correlation (by Pearson coefficient) between the magnitude of observed NF-κB peak values with observed TNF release peaks.(C) The modified Caldwell et al. (2014) model to simulate LPS pulse induced TNF secretion at the single-cell level. Extrinsic noise was added by sampling key kinetic parameters from gamma distributions as in Cheng et al. (2015).(D) Model predictions of active TRIF, nuclear NF-κB, and secreted TNF dynamics in 500 single cells, with red lines showing mean behavior. Simulated secretion profiles agree well with the measured single-cell TNF secretion time courses.(E) The model simulations indicate that, qualitatively, NF-κB positivity (NF-κB+) correlates better to TNF positivity (TNF+) than TRIF positivity (TRIF+). Many cells categorized as TRIF− may produce TNF above the detectable level.(F) The model simulations indicate that TNF peak magnitude is not quantitatively correlated (by Pearson coefficient) to nuclear NF-κB peak magnitude but is quantitatively correlated to peak TRIF values.
Mentions: The observed TNF release by single cells displays a heterogeneous and dynamic immune secretory response to pathogenic input. Although NF-κB activation and TNF secretion were qualitatively correlated (Figure 6A), considering their amplitudes quantitatively revealed no correlation (Pearson correlation r = −0.06; Figure 6B). To understand mechanisms of the observed TNF release profiles and understand why NF-κB activation and TNF secretion showed so little correlation, we undertook computational modeling of the kinetic interplay of mechanisms controlling not only TNF mRNA synthesis but also mRNA processing and half-life control, translation to TNF pro-protein, protein maturation, and secretion (Caldwell et al., 2014, Cheng et al., 2015, Werner et al., 2005).

Bottom Line: Characterizing dynamic input-output relationships in single cells is crucial for understanding and modeling cellular systems.We developed an automated microfluidic system that delivers precisely defined dynamical inputs to individual living cells and simultaneously measures key immune parameters dynamically.Our system combines nanoliter immunoassays, microfluidic input generation, and time-lapse microscopy, enabling study of previously untestable aspects of immunity by measuring time-dependent cytokine secretion and transcription factor activity from single cells stimulated with dynamic inflammatory inputs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland.

No MeSH data available.