Date: Friday, October 10, 2025
Time: 3:00 – 4:00 PM
Room: McGovern Auditorium, Whitehead Institute
CSB Ph.D. Candidate: Diep H. Nguyen
Supervisor: Pulin Li (Biology)
TDC Members:
Professors Sebastian Lourido (MIT Biology), Harikesh Wong ( MIT Biology), and Ramnik Xavier (Broad Institute/ Massachusetts General Hospital-External Member)
Title: Design Principles of Innate Immune Sensing
Abstract:
Life is a study in contrasts between randomness and determinism: from the chaos of biomolecular interactions to precise coordination of immunity. When dealing with diverse immunogenic stimuli, robust yet tunable immune responses are required for the survival of the organisms. How the immune system balances host protection and collateral damage at the onset of innate immune sensing while resolving biological noise remains an open question.
In the first part of this thesis, I discovered a tissue-scale strategy that uses stochasticity to assess threats via pattern-recognition receptor (PRR), by characterizing the probability of detecting influenza infection among different cell types in the lung using single-molecule imaging and spatial transcriptomics. Notably, this probability is lowest in the outermost epithelia and highest in the inner stroma. Such cell-type-specific probabilities of threat-sensing emerge from the spatially graded PRR expression across tissue compartments. Selectively increasing PRR expression in lung epithelia in vivo exacerbated tissue damage upon non-infectious challenge, revealing the importance of dampening the sensitivity of barrier epithelia. These results highlight a spatially tiered strategy based on stochasticity to tolerate epithelia-restricted threats, and yet enable progressively potent immune responses as threats invade deeper into the tissue.
In the second part, I investigated the molecular events underlying the fractional control of PRR pathways. Using super-resolution and multiplexed microscopy, I provided the first in vivo demonstration and quantification of high-order assembly of adaptor proteins and kinases, representing active signaling centers downstream of activated receptors. The formation of these signaling centers depends on both PRR level and pathogen load. Stochastic simulations of receptor binding to viral RNA showed that multi-step linear binding reaction converts noisy protein level into functional ultrasensitivity at the single-cell level and fractional control at the population level. Perturbing the distribution of receptors precisely tuned the fraction of activated cells in an infected population and revealed an unexpected optimal range of receptor level where tunability is maximized.
By bridging large biological scales, from single molecules to single cells to tissues, and integrating different data modalities, including quantitative imaging, spatial transcriptomics, mouse models, and mathematical modelling, this thesis offers a novel in vivo demonstration of the cause, regulation, and functional consequence of stochasticity in innate immune sensing. Furthermore, the work reveals an emergent regulation of innate immune sensing that requires coordination of distinct tissue compartments, further expanding the conceptual framework of spatially patterned innate immunity.