Cellular Decision Making by Non-Integrative Processing of TLR Inputs

Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs) that converge on the nuclear factor κB (NF-κB) pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term “non-integrative” processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback

Noise Induces Hopping between NF-kappa B Entrainment Modes

Oscillations and noise drive many processes in biology, but how both affect the activity of the transcription factor nuclear factor κB (NF-κB) is not understood. Here, we observe that when NF-κB oscillations are entrained by periodic tumor necrosis factor (TNF) inputs in experiments, NF-κB exhibits jumps between frequency modes, a phenomenon we call “cellular mode-hopping.” By comparing stochastic simulations of NF-κB oscillations to deterministic simulations conducted inside and outside the chaotic regime of parameter space, we show that noise facilitates mode-hopping in all regimes. However, when the deterministic system is driven by chaotic dynamics, hops between modes are erratic and short-lived, whereas in experiments, the system spends several periods in one entrainment mode before hopping and rarely visits more than two modes. The experimental behavior matches our simulations of noise-induced mode-hopping outside the chaotic regime. We suggest that mode-hopping is a mechanism by which different NF-κB-dependent genes under frequency control can be expressed at different times.ISSN:2405-472

IR Sensitive Photorefractive Polymers, The First Updateable Holographic 3D Display

This work presents recent advances in the development of infra-red sensitive photorefractive polymers, and updateable near real-time holographic 3D displays based on photorefractive polymers. Theoretical and experimental techniques used for design, fabrication and characterization of photorefractive polymers are outlined. Materials development and technical advances that made possible the use of photorefractive polymers for infra-red free-space optical communications, and 3D holographic displays are presented.Photorefractive polymers are dynamic holographic materials that allow recording of highly efficient reversible holograms. The longest operation wavelength for a photorefractive polymer before this study has been 950nm, far shorter than 1550nm, the wavelength of choice for optical communications and medical imaging. The polymers shown here were sensitized using two-photon absorption, a third order nonlinear effect, beyond the linear absorption spectrum of organic dyes, and reach 40% diffraction efficiency with a 35ms response time at this wavelength. As a consequence of two-photon absorption sensitization they exhibit non-destructive readout, which is an important advantage for applications that require high signal-to-noise ratios.Holographic 3D displays provide highly realistic images without the need for special eyewear, making them valuable tools for applications that require "situational awareness" such as medical, industrial and military imaging. Current commercially available holographic 3D displays employ photopolymers that lack image updating capability, resulting in their restricted use and high cost per 3D image. The holographic 3D display shown here employs photorefractive polymers with nearly 100% diffraction efficiency and fast writing time, hours of image persistence, rapid erasure and large area, a combination of properties that has not been shown before. The 3D display is based on stereography and utilizes world's largest photorefractive devices (4x4 inch in size). It can be recorded within a few minutes, viewed for several hours without the need for refreshing and can be completely erased and updated with new images when desired, thusly comprising the first updateable holographic 3D display with memory, suitable for practical use.Dissertation originally available; restricted by author's request in 2016; author changed his mind and made available again 15-Feb-2016 / Kimberl

Ultra-multiplexed analysis of single-cell dynamics reveals logic rules in differentiation

Dynamical control of cellular microenvironments is highly desirable to study complex processes such as stem cell differentiation and immune signaling. We present an ultra-multiplexed microfluidic system for high-throughput single-cell analysis in precisely defined dynamic signaling environments. Our system delivers combinatorial and time-varying signals to 1500 independently programmable culture chambers in week-long live-cell experiments by performing nearly 106 pipetting steps, where single cells, two-dimensional (2D) populations, or 3D neurospheres are chemically stimulated andtracked. Using our system and statistical analysis, we investigatedthe signaling landscape of neural stem cell differentiation and discovered "cellular logic rules" that revealed the critical role of signal timing and sequence in cell fate decisions. We find synergistic and antagonistic signal interactions and show that differentiation pathways are highly redundant. Our system allows dissection of hidden aspects of cellular dynamics and enables accelerated biological discovery

The Immune-Metabolic Basis of Effector Memory CD4+ T Cell Function under Hypoxic Conditions

Effector memory (EM) CD4(+) T cells recirculate between normoxic blood and hypoxic tissues to screen for cognate Ag. How mitochondria of these cells, shuttling between normoxia and hypoxia, maintain bioenergetic efficiency and stably uphold antiapoptotic features is unknown. In this study, we found that human EM CD4(+) T cells had greater spare respiratory capacity (SRC) than did naive counterparts, which was immediately accessed under hypoxia. Consequently, hypoxic EM cells maintained ATP levels, survived and migrated better than did hypoxic naive cells, and hypoxia did not impair their capacity to produce IFN-gamma. EM CD4(+) T cells also had more abundant cytosolic GAPDH and increased glycolytic reserve. In contrast to SRC, glycolytic reserve was not tapped under hypoxic conditions, and, under hypoxia, glucose metabolism contributed similarly to ATP production in naive and EM cells. However, both under normoxic and hypoxic conditions, glucose was critical for EM CD4(+) T cell survival. Mechanistically, in the absence of glycolysis, mitochondrial membrane potential (DeltaPsim) of EM cells declined and intrinsic apoptosis was triggered. Restoring pyruvate levels, the end product of glycolysis, preserved DeltaPsim and prevented apoptosis. Furthermore, reconstitution of reactive oxygen species (ROS), whose production depends on DeltaPsim, also rescued viability, whereas scavenging mitochondrial ROS exacerbated apoptosis. Rapid access of SRC in hypoxia, linked with built-in, oxygen-resistant glycolytic reserve that functionally insulates DeltaPsim and mitochondrial ROS production from oxygen tension changes, provides an immune-metabolic basis supporting survival, migration, and function of EM CD4(+) T cells in normoxic and hypoxic conditions

COVIDomic:A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification, allows to analyze the presence of the most common microbial organisms, their antibiotic resistance, the severity of the infection and the set of the most probable geographical locations from which the studied strain could have originated. The online platform integrates a user friendly interface which allows easy visualization of the results. We envision this tool will not only have immediate implications for management of the ongoing COVID-19 pandemic, but will also improve our readiness to respond to other infectious outbreaks