Direct observation correlates NFκB cRel in B cells with activating and terminating their proliferative program

Area of Science:

• Immunology
• Molecular Biology
• Cellular Biology

Background:

• Antibody responses depend on B cell proliferation, which is regulated by affinity-dependent signals.
• B cell proliferation exhibits significant heterogeneity, with individual cells undergoing varying numbers of divisions.
• NFκB cRel is a key transcription factor required for B cell proliferation following immune stimulation.

Purpose of the Study:

• To investigate whether natural variations in NFκB cRel abundance influence the heterogeneity of B cell proliferation.
• To quantitatively analyze the relationship between cRel expression levels and B cell proliferative capacity.

Main Methods:

• Development of a fluorescent reporter (mTFP1-cRel) for real-time observation of cRel in live B cells.
• Live-cell fluorescence microscopy to track cRel distribution and B cell division.
• Mathematical modeling of the NFκB signaling network, including autoregulation and negative feedback loops.
• Analysis of mouse knockouts to validate model predictions.

Main Results:

• cRel is heterogeneously distributed in naïve B cells, with a heavy-tailed distribution favoring high expressors.
• High cRel expressors initiate proliferation faster but exhibit earlier decay in population expansion.
• Mathematical modeling and experimental data confirm that cRel heterogeneity results from a balance between positive autoregulation and negative feedback by IκBε.
• Increased cRel primes B cells for early proliferation via cMyc, but peak induction is constrained by incoherent feedforward regulation, creating a non-monotonic relationship between cRel and proliferation extent.

Conclusions:

• Natural variations in NFκB cRel abundance are a key driver of B cell proliferative heterogeneity.
• The interplay between cRel autoregulation, IκBε inhibition, and cMyc regulation shapes the quantitative dynamics of B cell expansion.
• Direct observation studies are crucial for understanding quantitative biological relationships beyond gene knockout analyses.