A photoconversion model for full spectral programming and multiplexing of optogeneticﾠsystems

Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength‐ and intensity‐dependent photoconversion, signaling, and output gene expression for our two previously engineered light‐sensing Escherichia coli two‐component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open‐source “Light Plate Apparatus” device. In principle, the parameterized model should predict the gene expression response to any time‐varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross‐reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision‐making pathways integrate multiple input signals

A photoconversion model for full spectral programming and multiplexing of optogenetic systems

Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength‐ and intensity‐dependent photoconversion, signaling, and output gene expression for our two previously engineered light‐sensing Escherichia coli two‐component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open‐source “Light Plate Apparatus” device. In principle, the parameterized model should predict the gene expression response to any time‐varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross‐reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision‐making pathways integrate multiple input signals

A photoconversion model for full spectral programming and multiplexing of optogenetic systems

Abstract Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength‐ and intensity‐dependent photoconversion, signaling, and output gene expression for our two previously engineered light‐sensing Escherichia coli two‐component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open‐source “Light Plate Apparatus” device. In principle, the parameterized model should predict the gene expression response to any time‐varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross‐reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision‐making pathways integrate multiple input signals

Hydra vulgaris shows stable responses to thermal stimulation despite large changes in the number of neurons

Summary: Many animals that lose neural tissue to injury or disease can maintain behavioral repertoires by regenerating new neurons or reorganizing existing neural circuits. However, most neuroscience small model organisms lack this high degree of neural plasticity. We show that Hydra vulgaris can maintain stable sensory-motor behaviors despite 2-fold changes in neuron count, due to naturally occurring size variation or surgical resection. Specifically, we find that both behavioral and neural responses to rapid temperature changes are maintained following these perturbations. We further describe possible mechanisms for the observed neural activity and argue that Hydra's radial symmetry may allow it to maintain stable behaviors when changes in the numbers of neurons do not selectively eliminate any specific neuronal cell type. These results suggest that Hydra provides a powerful model for studying how animals maintain stable sensory-motor responses within dynamic neural circuits and may lead to the development of general principles for injury-tolerant neural architectures

High-fat diet-activated fatty acid oxidation mediates intestinal stemness and tumorigenicity

Obesity is an established risk factor for cancer in many tissues. In the mammalian intestine, a pro-obesity high-fat diet (HFD) promotes regeneration and tumorigenesis by enhancing intestinal stem cell (ISC) numbers, proliferation, and function. Although PPAR (peroxisome proliferator-activated receptor) nuclear receptor activity has been proposed to facilitate these effects, their exact role is unclear. Here we find that, in loss-of-function in vivo models, PPARα and PPARδ contribute to the HFD response in ISCs. Mechanistically, both PPARs do so by robustly inducing a downstream fatty acid oxidation (FAO) metabolic program. Pharmacologic and genetic disruption of CPT1A (the rate-controlling enzyme of mitochondrial FAO) blunts the HFD phenotype in ISCs. Furthermore, inhibition of CPT1A dampens the pro-tumorigenic consequences of a HFD on early tumor incidence and progression. These findings demonstrate that inhibition of a HFD-activated FAO program creates a therapeutic opportunity to counter the effects of a HFD on ISCs and intestinal tumorigenesis

Live cell tagging tracking and isolation for spatial transcriptomics using photoactivatable cell dyes

AbstractA cell’s phenotype and function are influenced by dynamic interactions with its microenvironment. To examine cellular spatiotemporal activity, we developed SPACECAT—Spatially PhotoActivatable Color Encoded Cell Address Tags—to annotate, track, and isolate cells while preserving viability. In SPACECAT, samples are stained with photocaged fluorescent molecules, and cells are labeled by uncaging those molecules with user-patterned near-UV light. SPACECAT offers single-cell precision and temporal stability across diverse cell and tissue types. Illustratively, we target crypt-like regions in patient-derived intestinal organoids to enrich for stem-like and actively mitotic cells, matching literature expectations. Moreover, we apply SPACECAT to ex vivo tissue sections from four healthy organs and an autochthonous lung tumor model. Lastly, we provide a computational framework to identify spatially-biased transcriptome patterns and enriched phenotypes. This minimally perturbative and broadly applicable method links cellular spatiotemporal and/or behavioral phenotypes with diverse downstream assays, enabling insights into the connections between tissue microenvironments and (dys)function.</jats:p

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.

There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection