Chronic metabolic stress drives developmental programs and loss of tissue functions in non-transformed liver that mirror tumor states and stratify survival.

Under chronic stress, cells must balance competing demands between cellular survival and tissue function. In metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD/NASH), hepatocytes cooperate with structural and immune cells to perform crucial metabolic, synthetic, and detoxification functions despite nutrient imbalances. While prior work has emphasized stress-induced drivers of cell death, the dynamic adaptations of surviving cells and their functional repercussions remain unclear. Namely, we do not know which pathways and programs define cellular responses, what regulatory factors mediate (mal)adaptations, and how this aberrant activity connects to tissue-scale dysfunction and long-term disease outcomes. Here, by applying longitudinal single-cell multi -omics to a mouse model of chronic metabolic stress and extending to human cohorts, we show that stress drives survival-linked tradeoffs and metabolic rewiring, manifesting as shifts towards development-associated states in non-transformed hepatocytes with accompanying decreases in their professional functionality. Diet-induced adaptations occur significantly prior to tumorigenesis but parallel tumorigenesis-induced phenotypes and predict worsened human cancer survival. Through the development of a multi -omic computational gene regulatory inference framework and human in vitro and mouse in vivo genetic perturbations, we validate transcriptional (RELB, SOX4) and metabolic (HMGCS2) mediators that co-regulate and couple the balance between developmental state and hepatocyte functional identity programming. Our work defines cellular features of liver adaptation to chronic stress as well as their links to long-term disease outcomes and cancer hallmarks, unifying diverse axes of cellular dysfunction around core causal mechanisms.

Tobacco smoke exposure recruits inflammatory airspace monocytes that establish permissive lung niches for Mycobacterium tuberculosis.

Tobacco smoking doubles the risk of active tuberculosis (TB) and accounts for up to 20% of all active TB cases globally. How smoking promotes lung microenvironments permissive to Mycobacterium tuberculosis (Mtb) growth remains incompletely understood. We investigated primary bronchoalveolar lavage cells from current and never smokers by performing single-cell RNA sequencing (scRNA-seq), flow cytometry, and functional assays. We observed the enrichment of immature inflammatory monocytes in the lungs of smokers compared with nonsmokers. These monocytes exhibited phenotypes consistent with recent recruitment from blood, ongoing differentiation, increased activation, and states similar to those with chronic obstructive pulmonary disease. Using integrative scRNA-seq and flow cytometry, we identified CD93 as a marker for a subset of these newly recruited smoking-associated lung monocytes and further provided evidence that the recruitment of monocytes into the lung was mediated by CCR2-binding chemokines, including CCL11. We also show that these cells exhibit elevated inflammatory responses upon exposure to Mtb and accelerated intracellular growth of Mtb compared with mature macrophages. This elevated Mtb growth could be inhibited by anti-inflammatory small molecules, providing a connection between smoking-induced pro-inflammatory states and permissiveness to Mtb growth. Our findings suggest a model in which smoking leads to the recruitment of immature inflammatory monocytes from the periphery to the lung, which results in the accumulation of these Mtb-permissive cells in the airway. This work defines how smoking may lead to increased susceptibility to Mtb and identifies host-directed therapies to reduce the burden of TB among those who smoke.

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 S 3 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 S 3 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.

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control.

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB.

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

A 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.

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

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.

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.

Magnetic Entropy as a Proposed Gating Mechanism for Magnetogenetic Ion Channels.

Magnetically sensitive ion channels would allow researchers to better study how specific brain cells affect behavior in freely moving animals; however, recent reports of "magnetogenetic" ion channels based on biogenic ferritin nanoparticles have been questioned because known biophysical mechanisms cannot explain experimental observations. Here, we reproduce a weak magnetically mediated calcium response in HEK cells expressing a previously published TRPV4-ferritin fusion protein. We find that this magnetic sensitivity is attenuated when we reduce the temperature sensitivity of the channel but not when we reduce the mechanical sensitivity of the channel, suggesting that the magnetic sensitivity of this channel is thermally mediated. As a potential mechanism for this thermally mediated magnetic response, we propose that changes in the magnetic entropy of the ferritin particle can generate heat via the magnetocaloric effect and consequently gate the associated temperature-sensitive ion channel. Unlike other forms of magnetic heating, the magnetocaloric mechanism can cool magnetic particles during demagnetization. To test this prediction, we constructed a magnetogenetic channel based on the cold-sensitive TRPM8 channel. Our observation of a magnetic response in cold-gated channels is consistent with the magnetocaloric hypothesis. Together, these new data and our proposed mechanism of action provide additional resources for understanding how ion channels could be activated by low-frequency magnetic fields.

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.