TIR domains as two-tiered enzymes to activate plant immunity.

Plant immune receptors often contain TIR domains, which can oligomerize to form active enzyme complexes in response to pathogen infections. In this issue of Cell, Yu and colleagues discover that some plant TIR domains possess a novel 2',3'-cAMP/cGMP synthetase activity that cleaves double-stranded RNA/DNA, triggering cell death during plant immune responses.

ILC1s control leukemia stem cell fate and limit development of AML.

Type I innate lymphoid cells (ILC1s) are critical regulators of inflammation and immunity in mammalian tissues. However, their function in cancer is mostly undefined. Here, we show that a high density of ILC1s induces leukemia stem cell (LSC) apoptosis in mice. At a lower density, ILC1s prevent LSCs from differentiating into leukemia progenitors and promote their differentiation into non-leukemic cells, thus blocking the production of terminal myeloid blasts. All of these effects, which require ILC1s to produce interferon-γ after cell-cell contact with LSCs, converge to suppress leukemogenesis in vivo. Conversely, the antileukemia potential of ILC1s wanes when JAK-STAT or PI3K-AKT signaling is inhibited. The relevant antileukemic properties of ILC1s are also functional in healthy individuals and impaired in individuals with acute myeloid leukemia (AML). Collectively, these findings identify ILC1s as anticancer immune cells that might be suitable for AML immunotherapy and provide a potential strategy to treat AML and prevent relapse of the disease.

High-speed low-light in vivo two-photon voltage imaging of large neuronal populations.

Monitoring spiking activity across large neuronal populations at behaviorally relevant timescales is critical for understanding neural circuit function. Unlike calcium imaging, voltage imaging requires kilohertz sampling rates that reduce fluorescence detection to near shot-noise levels. High-photon flux excitation can overcome photon-limited shot noise, but photobleaching and photodamage restrict the number and duration of simultaneously imaged neurons. We investigated an alternative approach aimed at low two-photon flux, which is voltage imaging below the shot-noise limit. This framework involved developing positive-going voltage indicators with improved spike detection (SpikeyGi and SpikeyGi2); a two-photon microscope ('SMURF') for kilohertz frame rate imaging across a 0.4 mm × 0.4 mm field of view; and a self-supervised denoising algorithm (DeepVID) for inferring fluorescence from shot-noise-limited signals. Through these combined advances, we achieved simultaneous high-speed deep-tissue imaging of more than 100 densely labeled neurons over 1 hour in awake behaving mice. This demonstrates a scalable approach for voltage imaging across increasing neuronal populations.

Analysis of sex-biased gene expression in a Eurasian admixed population.

Sex-biased gene expression differs across human populations; however, the underlying genetic basis and molecular mechanisms remain largely unknown. Here, we explore the influence of ancestry on sex differences in the human transcriptome and its genetic effects on a Eurasian admixed population: Uyghurs living in Xinjiang (XJU), by analyzing whole-genome sequencing data and transcriptome data of 90 XJU and 40 unrelated Han Chinese individuals. We identified 302 sex-biased expressed genes and 174 sex-biased cis-expression quantitative loci (sb-cis-eQTLs) in XJU, which were enriched in innate immune-related functions, indicating sex differences in immunity. Notably, approximately one-quarter of the sb-cis-eQTLs showed a strong correlation with ancestry composition; i.e. populations of similar ancestry tended to show similar patterns of sex-biased gene expression. Our analysis further suggested that genetic admixture induced a moderate degree of sex-biased gene expression. Interestingly, analysis of chromosome interactions revealed that the X chromosome acted on autosomal immunity-associated genes, partially explaining the sex-biased phenotypic differences. Our work extends the knowledge of sex-biased gene expression from the perspective of genetic admixture and bridges the gap in the exploration of sex-biased phenotypes shaped by autosome and X-chromosome interactions. Notably, we demonstrated that sex chromosomes cannot fully explain sex differentiation in immune-related phenotypes.

A MAP kinase cascade broadly regulates the lifestyle of Sclerotinia sclerotiorum and can be targeted by HIGS for disease control.

Sclerotinia sclerotiorum causes white mold or stem rot in a wide range of economically important plants, bringing significant yield losses worldwide. Control of this pathogen is difficult as its resting structure sclerotia can survive in soil for years, and no Resistance genes have been identified in S. sclerotiorum hosts. Host-induced gene silencing (HIGS) has shown promising effects in controlling many fungal pathogens, including S. sclerotiorum. However, better molecular genetic understanding of signaling pathways involved in its development and pathogenicity is needed to provide effective HIGS gene targets. Here, by employing a forward genetic screen, we characterized an evolutionarily conserved mitogen-activated protein kinase (MAPK) cascade in S. sclerotiorum, consisting of SsSte50-SsSte11-SsSte7-Smk1, which controls mycelial growth, sclerotia development, compound appressoria formation, virulence, and hyphal fusion. Moreover, disruption of the putative downstream transcription factor SsSte12 led to normal sclerotia but deformed appressoria and attenuated host penetration, as well as impaired apothecia formation, suggestive of diverged regulation downstream of the MAPK cascade. Most importantly, targeting SsSte50 using host-expressed double-stranded RNA resulted in largely reduced virulence of S. sclerotiorum on both Nicotiana benthamiana leaves and transgenic Arabidopsis thaliana plants. Therefore, this MAPK signaling cascade is generally needed for its growth, development, and pathogenesis and can serve as ideal HIGS targets for mitigating economic damages caused by S. sclerotiorum infection.

Potent NKT cell ligands overcome SARS-CoV-2 immune evasion to mitigate viral pathogenesis in mouse models.

One of the major pathogenesis mechanisms of SARS-CoV-2 is its potent suppression of innate immunity, including blocking the production of type I interferons. However, it is unknown whether and how the virus interacts with different innate-like T cells, including NKT, MAIT and γδ T cells. Here we reported that upon SARS-CoV-2 infection, invariant NKT (iNKT) cells rapidly trafficked to infected lung tissues from the periphery. We discovered that the envelope (E) protein of SARS-CoV-2 efficiently down-regulated the cell surface expression of the antigen-presenting molecule, CD1d, to suppress the function of iNKT cells. E protein is a small membrane protein and a viroporin that plays important roles in virion packaging and envelopment during viral morphogenesis. We showed that the transmembrane domain of E protein was responsible for suppressing CD1d expression by specifically reducing the level of mature, post-ER forms of CD1d, suggesting that it suppressed the trafficking of CD1d proteins and led to their degradation. Point mutations demonstrated that the putative ion channel function was required for suppression of CD1d expression and inhibition of the ion channel function using small chemicals rescued the CD1d expression. Importantly, we discovered that among seven human coronaviruses, only E proteins from highly pathogenic coronaviruses including SARS-CoV-2, SARS-CoV and MERS suppressed CD1d expression, whereas the E proteins of human common cold coronaviruses, HCoV-OC43, HCoV-229E, HCoV-NL63 and HCoV-HKU1, did not. These results suggested that E protein-mediated evasion of NKT cell function was likely an important pathogenesis factor, enhancing the virulence of these highly pathogenic coronaviruses. Remarkably, activation of iNKT cells with their glycolipid ligands, both prophylactically and therapeutically, overcame the putative viral immune evasion, significantly mitigated viral pathogenesis and improved host survival in mice. Our results suggested a novel NKT cell-based anti-SARS-CoV-2 therapeutic approach.

NCPbook: A comprehensive database of noncanonical peptides.

Noncanonical peptides (NCPs) are a class of peptides generated from regions previously thought of as noncoding, such as introns, 5' UTRs, 3' UTRs, and intergenic regions. In recent years, the significance and diverse functions of NCPs have come to light, yet a systematic and comprehensive NCP database remains absent. Here, we developed NCPbook (https://ncp.wiki/ncpbook/), a database of evidence-supported NCPs, which aims to provide a resource for efficient exploration, analysis, and manipulation of NCPs. NCPbook incorporates data from diverse public databases and scientific literature. The current version of NCPbook includes 180,676 NCPs across 29 different species, evidenced by MS, ribosome profiling, or molecular experiments. These NCPs are distributed across kingdoms, comprising 123,408 from 14 plant species, 56,999 from 7 animal species, and 269 from 8 microbial species. Furthermore, NCPbook encompasses 9,166 functionally characterized NCPs playing important roles in immunity, stress resistance, growth, and development. Equipped with a user-friendly interface, NCPbook allows users to search, browse, visualize, and retrieve data, making it an indispensable platform for researching NCPs in various plant, animal, and microbial species.

The N-terminally truncated helper NLR NRG1C antagonizes immunity mediated by its full-length neighbors NRG1A and NRG1B.

Both plants and animals utilize nucleotide-binding leucine-rich repeat immune receptors (NLRs) to perceive the presence of pathogen-derived molecules and induce immune responses. NLR genes are far more abundant and diverse in vascular plants than in animals. Truncated NLRs, which lack one or more of the canonical domains, are also commonly encoded in plant genomes. However, little is known about their functions, especially the N-terminally truncated ones. Here, we show that the Arabidopsis thaliana N-terminally truncated helper NLR (hNLR) gene N REQUIREMENT GENE1 (NRG1C) is highly induced upon pathogen infection and in autoimmune mutants. The immune response and cell death conferred by some Toll/interleukin-1 receptor-type NLRs (TNLs) were compromised in Arabidopsis NRG1C overexpression lines. Detailed genetic analysis revealed that NRG1C antagonizes the immunity mediated by its full-length neighbors NRG1A and NRG1B. Biochemical tests suggested that NRG1C might interfere with the EDS1-SAG101 complex, which functions in immunity signaling together with NRG1A/1B. Interestingly, Brassicaceae NRG1Cs are functionally exchangeable and that the Nicotiana benthamiana N-terminally truncated hNLR NRG2 also antagonizes NRG1 activity. Together, our study uncovers an unexpected negative role of N-terminally truncated hNLRs in immunity in different plant species.

ITIH4 reversed the effects of thrombin on VSMCs stiffness via JNK and ERK signaling pathway.

Vascular smooth muscle cell (VSMCs) is one of the important cell types in artery. VSMCs stiffening may regulate vascular stiffness and contribute to the development of vulnerable plaques. Thrombin, an enzyme in coagulation system, is involved in pathological processes of atherosclerosis. Inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) plays an important role in regulating inflammation and may have cardiovascular protective effect. Therefore, the elucidation of the mechanisms underlying ITIH4-mediated VSMCs stiffening helps to provide new ideas and potential targets for the diagnosis and treatment of atherosclerosis. In this study, we used specific ITIH4 expression vector and siRNA methods to transfect VSMCs. Our results found that ITIH4 expression increased VSMCs stiffness, meanwhile, ITIH4 siRNA decreased VSMCs stiffness. ITIH4 increased acetylated α-tubulin and inhibited ERK1/2 and JNK, but not P38 MAPK. ERK inhibitor (PD98059) or JNK inhibitor (SP600125) treatment increased acetylated α-tubulin expression and cell stiffness in VSMCs. ITIH4 was downregulated by thrombin treatment, ITIH4 partly reversed the effect of thrombin on acetylated α-tubulin and VSMCs stiffness. These results indicated that ITIH4 regulated acetylated α-tubulin expression in VSMCs and was against the effects of thrombin on VSMCs stiffness. JNK and ERK signaling pathways were proved to participate in this process.

Metabolic control of BRISC-SHMT2 assembly regulates immune signalling.

Serine hydroxymethyltransferase 2 (SHMT2) regulates one-carbon transfer reactions that are essential for amino acid and nucleotide metabolism, and uses pyridoxal-5'-phosphate (PLP) as a cofactor. Apo SHMT2 exists as a dimer with unknown functions, whereas PLP binding stabilizes the active tetrameric state. SHMT2 also promotes inflammatory cytokine signalling by interacting with the deubiquitylating BRCC36 isopeptidase complex (BRISC), although it is unclear whether this function relates to metabolism. Here we present the cryo-electron microscopy structure of the human BRISC-SHMT2 complex at a resolution of 3.8 Å. BRISC is a U-shaped dimer of four subunits, and SHMT2 sterically blocks the BRCC36 active site and inhibits deubiquitylase activity. Only the inactive SHMT2 dimer-and not the active PLP-bound tetramer-binds and inhibits BRISC. Mutations in BRISC that disrupt SHMT2 binding impair type I interferon signalling in response to inflammatory stimuli. Intracellular levels of PLP regulate the interaction between BRISC and SHMT2, as well as inflammatory cytokine responses. These data reveal a mechanism in which metabolites regulate deubiquitylase activity and inflammatory signalling.

Electrochemical versus Photoelectrochemical Water Oxidation Kinetics on Bismuth Vanadate (Photo)anodes.

This study reports a comparison of the kinetics of electrochemical (EC) versus photoelectrochemical (PEC) water oxidation on bismuth vanadate (BiVO4) photoanodes. Plots of current density versus surface hole density, determined from operando optical absorption analyses under EC and PEC conditions, are found to be indistinguishable. We thus conclude that EC water oxidation is driven by the Zener effect tunneling electrons from the valence to conduction band under strong bias, with the kinetics of both EC and PEC water oxidation being determined by the density of accumulated surface valence band holes. We further demonstrate that our combined optical absorption/current density analyses enable an operando quantification of the BiVO4 photovoltage as a function of light intensity.

Facet-Engineered BiVO4 Photocatalysts for Water Oxidation: Lifetime Gain Versus Energetic Loss.

A limiting factor to the efficiency of water Oxygen Evolution Reaction (OER) in metal oxide nanoparticle photocatalysts is the rapid recombination of holes and electrons. Facet-engineering can effectively improve charge separation and, consequently, OER efficiency. However, the kinetics behind this improvement remain poorly understood. This study utilizes photoinduced absorption spectroscopy to investigate the charge yield and kinetics in facet-engineered BiVO4 (F-BiVO4) compared to a non-faceted sample (NF-BiVO4) under operando conditions. A significant influence of preillumination on hole accumulation is observed, linked to the saturation and, thus, passivation of deep and inactive hole traps on the BiVO4 surface. In DI-water, F-BiVO4 shows a 10-fold increase in charge accumulation (∼5 mΔOD) compared to NF-BiVO4 (∼0.5 mΔOD), indicating improved charge separation and stabilization. With the addition of Fe(NO3)3, an efficient electron acceptor, F-BiVO4 demonstrates a 30-fold increase in the accumulation of long-lived holes (∼45 mΔOD), compared to NF-BiVO4 (∼1.5 mΔOD) and an increased half-time, from 2 to 10 s. Based on a simple kinetic model, this increase in hole accumulation suggests that facet-engineering causes at least a 50-100 meV increase in band bending in BiVO4 particles, thereby stabilizing surface holes. This energetic stabilization/loss results in a retardation of OER relative to NF-BiVO4. This slower catalysis is, however, offset by the observed increase in density and lifetime of photoaccumulated holes. Overall, this work quantifies how surface faceting can impact the kinetics of long-lived charge accumulation on metal oxide photocatalysts, highlighting the trade-off between lifetime gain and energetic loss critical to optimizing photocatalytic efficiency.

Plant E3 ligases SNIPER1 and SNIPER2 broadly regulate the homeostasis of sensor NLR immune receptors.

In both plants and animals, nucleotide-binding leucine-rich repeat (NLR) immune receptors perceive pathogen-derived molecules to trigger immunity. Global NLR homeostasis must be tightly controlled to ensure sufficient and timely immune output while avoiding aberrant activation, the mechanisms of which are largely unclear. In a previous reverse genetic screen, we identified two novel E3 ligases, SNIPER1 and its homolog SNIPER2, both of which broadly control the levels of NLR immune receptors in Arabidopsis. Protein levels of sensor NLRs (sNLRs) are inversely correlated with SNIPER1 amount and the interactions between SNIPER1 and sNLRs seem to be through the common nucleotide-binding (NB) domains of sNLRs. In support, SNIPER1 can ubiquitinate the NB domains of multiple sNLRs in vitro. Our study thus reveals a novel process of global turnover of sNLRs by two master E3 ligases for immediate attenuation of immune output to effectively avoid autoimmunity. Such unique mechanism can be utilized in the future for engineering broad-spectrum resistance in crops to fend off pathogens that damage our food supply.

Robust single-shot 3D fluorescence imaging in scattering media with a simulator-trained neural network.

Imaging through scattering is a pervasive and difficult problem in many biological applications. The high background and the exponentially attenuated target signals due to scattering fundamentally limits the imaging depth of fluorescence microscopy. Light-field systems are favorable for high-speed volumetric imaging, but the 2D-to-3D reconstruction is fundamentally ill-posed, and scattering exacerbates the condition of the inverse problem. Here, we develop a scattering simulator that models low-contrast target signals buried in heterogeneous strong background. We then train a deep neural network solely on synthetic data to descatter and reconstruct a 3D volume from a single-shot light-field measurement with low signal-to-background ratio (SBR). We apply this network to our previously developed computational miniature mesoscope and demonstrate the robustness of our deep learning algorithm on scattering phantoms with different scattering conditions. The network can robustly reconstruct emitters in 3D with a 2D measurement of SBR as low as 1.05 and as deep as a scattering length. We analyze fundamental tradeoffs based on network design factors and out-of-distribution data that affect the deep learning model's generalizability to real experimental data. Broadly, we believe that our simulator-based deep learning approach can be applied to a wide range of imaging through scattering techniques where experimental paired training data is lacking.

Cell classification with phase-imaging meta-sensors.

The development of photonic technologies for machine learning is a promising avenue toward reducing the computational cost of image classification tasks. Here we investigate a convolutional neural network (CNN) where the first layer is replaced by an image sensor array consisting of recently developed angle-sensitive metasurface photodetectors. This array can visualize transparent phase objects directly by recording multiple anisotropic edge-enhanced images, analogous to the feature maps computed by the first convolutional layer of a CNN. The resulting classification performance is evaluated for a realistic task (the identification of transparent cancer cells from seven different lines) through computational-imaging simulations based on the measured angular characteristics of prototype devices. Our results show that this hybrid optoelectronic network can provide accurate classification (>90%) similar to its fully digital baseline CNN but with an order-of-magnitude reduction in the number of calculations.

Genetic and molecular correlates of cortical thickness alterations in adults with obsessive-compulsive disorder: a transcription-neuroimaging association analysis.

BACKGROUND: Although numerous neuroimaging studies have depicted neural alterations in individuals with obsessive-compulsive disorder (OCD), a psychiatric disorder characterized by intrusive cognitions and repetitive behaviors, the molecular mechanisms connecting brain structural changes and gene expression remain poorly understood. METHODS: This study combined the Allen Human Brain Atlas dataset with neuroimaging data from the Meta-Analysis (ENIGMA) consortium and independent cohorts. Later, partial least squares regression and enrichment analysis were performed to probe the correlation between transcription and cortical thickness variation among adults with OCD. RESULTS: The cortical map of case-control differences in cortical thickness was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms preferentially expressed across different cell types and cortical layers. These genes were specifically expressed in brain tissue, spanning all cortical developmental stages. Protein-protein interaction analysis revealed that these genes coded a network of proteins encompassing various highly interactive hubs. CONCLUSIONS: The study findings bridge the gap between neural structure and transcriptome data in OCD, fostering an integrative understanding of the potential biological mechanisms.

RUNX1 promotes proliferation and migration in non-small cell lung cancer cell lines via the mTOR pathway.

RUNX1, a member of the RUNX family of metazoan transcription factors, participates in the regulation of differentiation, proliferation, and other processes involved in growth and development. It also functions in the occurrence and development of tumors. However, the role and mechanism of action of RUNX1 in non-small cell lung cancer (NSCLC) are not yet clear. We used a bioinformatics approach as well as in vitro and in vivo assays to evaluate the role of RUNX1 in NSCLC as the molecular mechanisms underlying its effects. Using the TCGA, GEO, GEPIA (Gene Expression Profiling Interactive Analysis), and Kaplan-Meier databases, we screened the differentially expressed genes (DEGs) and found that RUNX1 was highly expressed in lung cancer and was associated with a poor prognosis. Immunohistochemical staining based on tissue chips from 110 samples showed that the expression of RUNX1 in lung cancer tissues was higher than that in adjacent normal tissues and was positively correlated with lymph node metastasis and TNM staging. In vitro experiments, we found that RUNX1 overexpression promoted cell proliferation and migration functions and affected downstream functional proteins by regulating the activity of the mTOR pathway, as confirmed by an analysis using the mTOR pathway inhibitor rapamycin. In addition, RUNX1 affected PD-L1 expression via the mTOR pathway. These results indicate that RUNX1 is a potential therapeutic target for NSCLC.

M2 macrophage-derived exosomes carry miR-142-3p to restore the differentiation balance of irradiated BMMSCs by targeting TGF-ß1.

Radiotherapy is essential to cancer treatment, while it inevitably injures surrounding normal tissues, and bone tissue is one of the most common sites prone to irradiation. Bone marrow mesenchymal stem cells (BMMSCs) are sensitive to irradiation and the irradiated dysfunction of BMMSCs may be closely related to irradiation-induced bone damage. Macropahges play important role in regulating stem cell function, bone metabolic balance and irradiation response, but the effects of macrophages on irradiated BMMSCs are still unclear. This study aimed to investigate the role of macrophages and macrophage-derived exosomes in restoring irradiated BMMSCs function. The effects of macrophage conditioned medium (CM) and macrophage-derived exosomes on osteogenic and fibrogenic differentiation capacities of irradiated BMMSCs were detected. The key microribonucleic acids (miRNAs) and targeted proteins in exosomes were also determined. The results showed that irradiation significantly inhibited the proliferation of BMMSCs, and caused differentiation imbalance of BMMSCs, with decreased osteogenic differentiation and increased fibrogenic differentiation. M2 macrophage-derived exosomes (M2D-exos) inhibited the fibrogenic differentiation and promoted the osteogenic differentiation of irradiated BMMSCs. We identified that miR-142-3p was significantly overexpressed in M2D-exos and irradiated BMMSCs treated with M2D-exos. After inhibition of miR-142-3p in M2 macrophage, the effects of M2D-exos on irradiated BMMSCs differentiation were eliminated. Furthermore, transforming growth factor beta 1 (TGF-ß1), as a direct target of miR-142-3p, was significantly decreased in irradiated BMMSCs treated with M2D-exos. This study indicated that M2D-exos could carry miR-142-3p to restore the differentiation balance of irradiated BMMSCs by targeting TGF-ß1. These findings pave a new way for promising and cell-free method to treat irradiation-induced bone damage.

Object detection: A novel AI technology for the diagnosis of hepatocyte ballooning.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has reached epidemic proportions worldwide and is the most frequent cause of chronic liver disease in developed countries. Within the spectrum of liver disease in MAFLD, steatohepatitis is a progressive form of liver disease and hepatocyte ballooning (HB) is a cardinal pathological feature of steatohepatitis. The accurate and reproducible diagnosis of HB is therefore critical for the early detection and treatment of steatohepatitis. Currently, a diagnosis of HB relies on pathological examination by expert pathologists, which may be a time-consuming and subjective process. Hence, there has been interest in developing automated methods for diagnosing HB. This narrative review briefly discusses the development of artificial intelligence (AI) technology for diagnosing fatty liver disease pathology over the last 30 years and provides an overview of the current research status of AI algorithms for the identification of HB, including published articles on traditional machine learning algorithms and deep learning algorithms. This narrative review also provides a summary of object detection algorithms, including the principles, historical developments, and applications in the medical image analysis. The potential benefits of object detection algorithms for HB diagnosis (specifically those combined with a transformer architecture) are discussed, along with the future directions of object detection algorithms in HB diagnosis and the potential applications of generative AI on transformer architecture in this field. In conclusion, object detection algorithms have huge potential for the identification of HB and could make the diagnosis of MAFLD more accurate and efficient in the near future.