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

Single-cell RNA sequencing of liver fine-needle aspirates captures immune diversity in the blood and liver in chronic hepatitis B patients

Background and Aims: HBV infection is restricted to the liver, where it drives exhaustion of virus-specific T and B cells and pathogenesis through dysregulation of intrahepatic immunity. Our understanding of liver-specific events related to viral control and liver damage has relied almost solely on animal models, and we lack useable peripheral biomarkers to quantify intrahepatic immune activation beyond cytokine measurement. Our objective was to overcome the practical obstacles of liver sampling using fine-needle aspiration and develop an optimized workflow to comprehensively compare the blood and liver compartments within patients with chronic hepatitis B using single-cell RNA sequencing. Approach and Results: We developed a workflow that enabled multi-site international studies and centralized single-cell RNA sequencing. Blood and liver fine-needle aspirations were collected, and cellular and molecular captures were compared between the Seq-Well S3 picowell-based and the 10× Chromium reverse-emulsion droplet–based single-cell RNA sequencing technologies. Both technologies captured the cellular diversity of the liver, but Seq-Well S3 effectively captured neutrophils, which were absent in the 10× dataset. CD8 T cells and neutrophils displayed distinct transcriptional profiles between blood and liver. In addition, liver fine-needle aspirations captured a heterogeneous liver macrophage population. Comparison between untreated patients with chronic hepatitis B and patients treated with nucleoside analogs showed that myeloid cells were highly sensitive to environmental changes while lymphocytes displayed minimal differences. Conclusions: The ability to electively sample and intensively profile the immune landscape of the liver, and generate high-resolution data, will enable multi-site clinical studies to identify biomarkers for intrahepatic immune activity in HBV and beyond.</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

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

Microdevices for Non-Invasive Detection of Bladder Cancer

Bladder cancer holds the record for the highest lifetime cost on a per-patient basis. This is due to high recurrence rates, which necessitate invasive and costly long-term evaluation methods such as cystoscopy and imaging. Microfluidics is emerging as an important approach to contribute to initial diagnosis and follow-up, by enabling the precise manipulation of biological samples. Specifically, microdevices have been used for the isolation of cells or genetic material from blood samples, sparking significant interest as a versatile platform for non-invasive bladder cancer detection with voided urine. In this review, we revisit the methods of bladder cancer detection and describe various types of markers currently used for evaluation. We detail cutting-edge technologies and evaluate their merits in the detection, screening, and diagnosis of bladder cancer. Advantages of microscale devices over standard methods of detection, as well as their limitations, are provided. We conclude with a discussion of criteria for guiding microdevice development that could deepen our understanding of prognoses at the level of individual patients and the underlying biology of bladder cancer development. Collectively, the development and widespread application of improved microfluidic devices for bladder cancer could drive treatment breakthroughs and establish widespread, tangible outcomes on patients’ long-term survival

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