An immune cell atlas reveals the dynamics of human macrophage specification during prenatal development.

Macrophages are heterogeneous and play critical roles in development and disease, but their diversity, function, and specification remain inadequately understood during human development. We generated a single-cell RNA sequencing map of the dynamics of human macrophage specification from PCW 4-26 across 19 tissues. We identified a microglia-like population and a proangiogenic population in 15 macrophage subtypes. Microglia-like cells, molecularly and morphologically similar to microglia in the CNS, are present in the fetal epidermis, testicle, and heart. They are the major immune population in the early epidermis, exhibit a polarized distribution along the dorsal-lateral-ventral axis, and interact with neural crest cells, modulating their differentiation along the melanocyte lineage. Through spatial and differentiation trajectory analysis, we also showed that proangiogenic macrophages are perivascular across fetal organs and likely yolk-sac-derived as microglia. Our study provides a comprehensive map of the heterogeneity and developmental dynamics of human macrophages and unravels their diverse functions during development.

LGR5 expressing skin fibroblasts define a major cellular hub perturbed in scleroderma.

Systemic sclerosis (scleroderma, SSc) is an incurable autoimmune disease with high morbidity and mortality rates. Here, we conducted a population-scale single-cell genomic analysis of skin and blood samples of 56 healthy controls and 97 SSc patients at different stages of the disease. We found immune compartment dysfunction only in a specific subtype of diffuse SSc patients but global dysregulation of the stromal compartment, particularly in a previously undefined subset of LGR5+-scleroderma-associated fibroblasts (ScAFs). ScAFs are perturbed morphologically and molecularly in SSc patients. Single-cell multiome profiling of stromal cells revealed ScAF-specific markers, pathways, regulatory elements, and transcription factors underlining disease development. Systematic analysis of these molecular features with clinical metadata associates specific ScAF targets with disease pathogenesis and SSc clinical traits. Our high-resolution atlas of the sclerodermatous skin spectrum will enable a paradigm shift in the understanding of SSc disease and facilitate the development of biomarkers and therapeutic strategies.

Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer.

Cell function and activity are regulated through integration of signaling, epigenetic, transcriptional, and metabolic pathways. Here, we introduce INs-seq, an integrated technology for massively parallel recording of single-cell RNA sequencing (scRNA-seq) and intracellular protein activity. We demonstrate the broad utility of INs-seq for discovering new immune subsets by profiling different intracellular signatures of immune signaling, transcription factor combinations, and metabolic activity. Comprehensive mapping of Arginase 1-expressing cells within tumor models, a metabolic immune signature of suppressive activity, discovers novel Arg1+ Trem2+ regulatory myeloid (Mreg) cells and identifies markers, metabolic activity, and pathways associated with these cells. Genetic ablation of Trem2 in mice inhibits accumulation of intra-tumoral Mreg cells, leading to a marked decrease in dysfunctional CD8+ T cells and reduced tumor growth. This study establishes INs-seq as a broadly applicable technology for elucidating integrated transcriptional and intra-cellular maps and identifies the molecular signature of myeloid suppressive cells in tumors.

25-Hydroxycholesterol regulates lysosome AMP kinase activation and metabolic reprogramming to educate immunosuppressive macrophages.

Macrophages are critical to turn noninflamed "cold tumors" into inflamed "hot tumors". Emerging evidence indicates abnormal cholesterol metabolites in the tumor microenvironment (TME) with unclear function. Here, we uncovered the inducible expression of cholesterol-25-hydroxylase (Ch25h) by interleukin-4 (IL-4) and interleukin-13 (IL-13) via the transcription factor STAT6, causing 25-hydroxycholesterol (25HC) accumulation. scRNA-seq analysis confirmed that CH25Hhi subsets were enriched in immunosuppressive macrophage subsets and correlated to lower survival rates in pan-cancers. Targeting CH25H abrogated macrophage immunosuppressive function to enhance infiltrating T cell numbers and activation, which synergized with anti-PD-1 to improve anti-tumor efficacy. Mechanically, lysosome-accumulated 25HC competed with cholesterol for GPR155 binding to inhibit the kinase mTORC1, leading to AMPKα activation and metabolic reprogramming. AMPKα also phosphorylated STAT6 Ser564 to enhance STAT6 activation and ARG1 production. Together, we propose CH25H as an immunometabolic checkpoint, which manipulates macrophage fate to reshape CD8+ T cell surveillance and anti-tumor response.

Modeling Rett Syndrome Using TALEN-Edited MECP2 Mutant Cynomolgus Monkeys.

Gene-editing technologies have made it feasible to create nonhuman primate models for human genetic disorders. Here, we report detailed genotypes and phenotypes of TALEN-edited MECP2 mutant cynomolgus monkeys serving as a model for a neurodevelopmental disorder, Rett syndrome (RTT), which is caused by loss-of-function mutations in the human MECP2 gene. Male mutant monkeys were embryonic lethal, reiterating that RTT is a disease of females. Through a battery of behavioral analyses, including primate-unique eye-tracking tests, in combination with brain imaging via MRI, we found a series of physiological, behavioral, and structural abnormalities resembling clinical manifestations of RTT. Moreover, blood transcriptome profiling revealed that mutant monkeys resembled RTT patients in immune gene dysregulation. Taken together, the stark similarity in phenotype and/or endophenotype between monkeys and patients suggested that gene-edited RTT founder monkeys would be of value for disease mechanistic studies as well as development of potential therapeutic interventions for RTT.

ß-Glucan Reverses the Epigenetic State of LPS-Induced Immunological Tolerance.

Innate immune memory is the phenomenon whereby innate immune cells such as monocytes or macrophages undergo functional reprogramming after exposure to microbial components such as lipopolysaccharide (LPS). We apply an integrated epigenomic approach to characterize the molecular events involved in LPS-induced tolerance in a time-dependent manner. Mechanistically, LPS-treated monocytes fail to accumulate active histone marks at promoter and enhancers of genes in the lipid metabolism and phagocytic pathways. Transcriptional inactivity in response to a second LPS exposure in tolerized macrophages is accompanied by failure to deposit active histone marks at promoters of tolerized genes. In contrast, ß-glucan partially reverses the LPS-induced tolerance in vitro. Importantly, ex vivo ß-glucan treatment of monocytes from volunteers with experimental endotoxemia re-instates their capacity for cytokine production. Tolerance is reversed at the level of distal element histone modification and transcriptional reactivation of otherwise unresponsive genes. VIDEO ABSTRACT.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.

Multi-tissue single-cell analysis deconstructs the complex programs of mouse natural killer and type 1 innate lymphoid cells in tissues and circulation.

Natural killer (NK) cells and type 1 innate lymphoid cells (ILC1s) are heterogenous innate lymphocytes broadly defined in mice as Lin-NK1.1+NKp46+ cells that express the transcription factor T-BET and produce interferon-γ. The ILC1 definition primarily stems from studies on liver and small intestinal populations. However, NK1.1+NKp46+ cells in the salivary glands, uterus, adipose, and other tissues exhibit nonuniform programs that differ from those of liver or intestinal ILC1s or NK cells. Here, we performed single-cell RNA sequencing on murine NK1.1+NKp46+ cells from blood, spleen, various tissues, and solid tumors. We identified gene expression programs of tissue-specific ILC1s, tissue-specific NK cells, and non-tissue-specific populations in blood, spleen, and other tissues largely corresponding to circulating cells. Moreover, we found that circulating NK cell programs were reshaped in tumor-bearing mice. Core programs of circulating and tumor NK cells paralleled conserved human NK cells signatures, advancing our understanding of the human NK-ILC1 spectrum.

Inhaled SARS-CoV-2 vaccine for single-dose dry powder aerosol immunization.

The COVID-19 pandemic has fostered major advances in vaccination technologies1-4; however, there are urgent needs for vaccines that induce mucosal immune responses and for single-dose, non-invasive administration4-6. Here we develop an inhalable, single-dose, dry powder aerosol SARS-CoV-2 vaccine that induces potent systemic and mucosal immune responses. The vaccine encapsulates assembled nanoparticles comprising proteinaceous cholera toxin B subunits displaying the SARS-CoV-2 RBD antigen within microcapsules of optimal aerodynamic size, and this unique nano-micro coupled structure supports efficient alveoli delivery, sustained antigen release and antigen-presenting cell uptake, which are favourable features for the induction of immune responses. Moreover, this vaccine induces strong production of IgG and IgA, as well as a local T cell response, collectively conferring effective protection against SARS-CoV-2 in mice, hamsters and nonhuman primates. Finally, we also demonstrate a mosaic iteration of the vaccine that co-displays ancestral and Omicron antigens, extending the breadth of antibody response against co-circulating strains and transmission of the Omicron variant. These findings support the use of this inhaled vaccine as a promising multivalent platform for fighting COVID-19 and other respiratory infectious diseases.

A mitochondrial EglN1-AMPKα axis drives breast cancer progression by enhancing metabolic adaptation to hypoxic stress.

Mitochondria play essential roles in cancer cell adaptation to hypoxia, but the underlying mechanisms remain elusive. Through mitochondrial proteomic profiling, we here find that the prolyl hydroxylase EglN1 (PHD2) accumulates on mitochondria under hypoxia. EglN1 substrate-binding region in the ß2ß3 loop is responsible for its mitochondrial translocation and contributes to breast tumor growth. Furthermore, we identify AMP-activated protein kinase alpha (AMPKα) as an EglN1 substrate on mitochondria. The EglN1-AMPKα interaction is essential for their mutual mitochondrial translocation. After EglN1 prolyl-hydroxylates AMPKα under normoxia, they rapidly dissociate following prolyl-hydroxylation, leading to their immediate release from mitochondria. In contrast, hypoxia results in constant EglN1-AMPKα interaction and their accumulation on mitochondria, leading to the formation of a Ca2+ /calmodulin-dependent protein kinase 2 (CaMKK2)-EglN1-AMPKα complex to activate AMPKα phosphorylation, ensuring metabolic homeostasis and breast tumor growth. Our findings identify EglN1 as an oxygen-sensitive metabolic checkpoint signaling hypoxic stress to mitochondria through its ß2ß3 loop region, suggesting a potential therapeutic target for breast cancer.

MYC Recruits SPT5 to RNA Polymerase II to Promote Processive Transcription Elongation.

The MYC oncoprotein binds to promoter-proximal regions of virtually all transcribed genes and enhances RNA polymerase II (Pol II) function, but its precise mode of action is poorly understood. Using mass spectrometry of both MYC and Pol II complexes, we show here that MYC controls the assembly of Pol II with a small set of transcription elongation factors that includes SPT5, a subunit of the elongation factor DSIF. MYC directly binds SPT5, recruits SPT5 to promoters, and enables the CDK7-dependent transfer of SPT5 onto Pol II. Consistent with known functions of SPT5, MYC is required for fast and processive transcription elongation. Intriguingly, the high levels of MYC that are expressed in tumors sequester SPT5 into non-functional complexes, thereby decreasing the expression of growth-suppressive genes. Altogether, these results argue that MYC controls the productive assembly of processive Pol II elongation complexes and provide insight into how oncogenic levels of MYC permit uncontrolled cellular growth.

Accelerated biological aging six decades after prenatal famine exposure.

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N = 951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944 to 1945, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

Single-molecule characterization of Sen1 translocation properties provides insights into eukaryotic factor-dependent transcription termination.

Sen1 is an essential helicase for factor-dependent transcription termination in Saccharomyces cerevisiae, whose molecular-motor mechanism has not been well addressed. Here, we use single-molecule experimentation to better understand the molecular-motor determinants of its action on RNA polymerase II (Pol II) complex. We quantify Sen1 translocation activity on single-stranded DNA (ssDNA), finding elevated translocation rates, high levels of processivity and ATP affinities. Upon deleting the N- and C-terminal domains, or further deleting different parts of the prong subdomain, which is an essential element for transcription termination, Sen1 displays changes in its translocation properties, such as slightly reduced translocation processivities, enhanced translocation rates and statistically identical ATP affinities. Although these parameters fulfil the requirements for Sen1 translocating along the RNA transcript to catch up with a stalled Pol II complex, we observe significant reductions in the termination efficiencies as well as the factions of the formation of the previously described topological intermediate prior to termination, suggesting that the prong may preserve an interaction with Pol II complex during factor-dependent termination. Our results underscore a more detailed rho-like mechanism of Sen1 and a critical interaction between Sen1 and Pol II complex for factor-dependent transcription termination in eukaryotes.

PlantPAD: a platform for large-scale image phenomics analysis of disease in plant science.

Plant disease, a huge burden, can cause yield loss of up to 100% and thus reduce food security. Actually, smart diagnosing diseases with plant phenomics is crucial for recovering the most yield loss, which usually requires sufficient image information. Hence, phenomics is being pursued as an independent discipline to enable the development of high-throughput phenotyping for plant disease. However, we often face challenges in sharing large-scale image data due to incompatibilities in formats and descriptions provided by different communities, limiting multidisciplinary research exploration. To this end, we build a Plant Phenomics Analysis of Disease (PlantPAD) platform with large-scale information on disease. Our platform contains 421 314 images, 63 crops and 310 diseases. Compared to other databases, PlantPAD has extensive, well-annotated image data and in-depth disease information, and offers pre-trained deep-learning models for accurate plant disease diagnosis. PlantPAD supports various valuable applications across multiple disciplines, including intelligent disease diagnosis, disease education and efficient disease detection and control. Through three applications of PlantPAD, we show the easy-to-use and convenient functions. PlantPAD is mainly oriented towards biologists, computer scientists, plant pathologists, farm managers and pesticide scientists, which may easily explore multidisciplinary research to fight against plant diseases. PlantPAD is freely available at http://plantpad.samlab.cn.

Sulfated oligosaccharide activates endothelial Notch for inducing macrophage-associated arteriogenesis to treat ischemic diseases.

Ischemic diseases lead to considerable morbidity and mortality, yet conventional clinical treatment strategies for therapeutic angiogenesis fall short of being impactful. Despite the potential of biomaterials to deliver pro-angiogenic molecules at the infarct site to induce angiogenesis, their efficacy has been impeded by aberrant vascular activation and off-target circulation. Here, we present a semisynthetic low-molecular sulfated chitosan oligosaccharide (SCOS) that efficiently induces therapeutic arteriogenesis with a spontaneous generation of collateral circulation and blood reperfusion in rodent models of hind limb ischemia and myocardial infarction. SCOS elicits anti-inflammatory macrophages' (Mφs') differentiation into perivascular Mφs, which in turn directs artery formation via a cell-to-cell communication rather than secretory factor regulation. SCOS-mediated arteriogenesis requires a canonical Notch signaling pathway in Mφs via the glycosylation of protein O-glucosyltransferases 2, which results in promoting arterial differentiation and tissue repair in ischemia. Thus, this highly bioactive oligosaccharide can be harnessed to direct efficiently therapeutic arteriogenesis and perfusion for the treatment of ischemic diseases.

ATOH8 binds SMAD3 to induce cellular senescence and prevent Ras-driven malignant transformation.

The process of oncogene-induced senescence (OIS) and the conversion between OIS and malignant transformation during carcinogenesis is poorly understood. Here, we show that following overactivation of oncogene Ras in lung epithelial cells, high-level transforming growth factor ß1 (TGF-ß1)-activated SMAD3, but not SMAD2 or SMAD4, plays a determinant role in inducing cellular senescence independent of the p53/p16/p15 senescence pathways. Importantly, SMAD3 binds a potential tumor suppressor ATOH8 to form a transcriptional complex that directly represses a series of cell cycle-promoting genes and consequently causes senescence in lung epithelial cells. Interestingly, the prosenescent SMAD3 converts to being oncogenic and essentially facilitates oncogenic Ras-driven malignant transformation. Furthermore, depleting Atoh8 rapidly accelerates oncogenic Ras-driven lung tumorigenesis, and lung cancers driven by mutant Ras and Atoh8 loss, but not by mutant Ras only, are sensitive to treatment of a specific SMAD3 inhibitor. Moreover, hypermethylation of the ATOH8 gene can be found in approximately 12% of clinical lung cancer cases. Together, our findings demonstrate not only epithelial cellular senescence directed by a potential tumor suppressor-controlled transcriptional program but also an important interplay between the prosenescent and transforming effects of TGF-ß/SMAD3, potentially laying a foundation for developing early detection and anticancer strategies.

Structural insights into the transcription activation mechanism of the global regulator GlnR from actinobacteria.

In actinobacteria, an OmpR/PhoB subfamily protein called GlnR acts as an orphan response regulator and globally coordinates the expression of genes responsible for nitrogen, carbon, and phosphate metabolism in actinobacteria. Although many researchers have attempted to elucidate the mechanisms of GlnR-dependent transcription activation, progress is impeded by lacking of an overall structure of GlnR-dependent transcription activation complex (GlnR-TAC). Here, we report a co-crystal structure of the C-terminal DNA-binding domain of GlnR (GlnR_DBD) in complex with its regulatory cis-element DNA and a cryo-EM structure of GlnR-TAC which comprises Mycobacterium tuberculosis RNA polymerase, GlnR, and a promoter containing four well-characterized conserved GlnR binding sites. These structures illustrate how four GlnR protomers coordinate to engage promoter DNA in a head-to-tail manner, with four N-terminal receiver domains of GlnR (GlnR-RECs) bridging GlnR_DBDs and the RNAP core enzyme. Structural analysis also unravels that GlnR-TAC is stabilized by complex protein-protein interactions between GlnR and the conserved ß flap, σAR4, αCTD, and αNTD domains of RNAP, which are further confirmed by our biochemical assays. Taken together, these results reveal a global transcription activation mechanism for the master regulator GlnR and other OmpR/PhoB subfamily proteins and present a unique mode of bacterial transcription regulation.

MKMR: a multi-kernel machine regression model to predict health outcomes using human microbiome data.

Studies have found that human microbiome is associated with and predictive of human health and diseases. Many statistical methods developed for microbiome data focus on different distance metrics that can capture various information in microbiomes. Prediction models were also developed for microbiome data, including deep learning methods with convolutional neural networks that consider both taxa abundance profiles and taxonomic relationships among microbial taxa from a phylogenetic tree. Studies have also suggested that a health outcome could associate with multiple forms of microbiome profiles. In addition to the abundance of some taxa that are associated with a health outcome, the presence/absence of some taxa is also associated with and predictive of the same health outcome. Moreover, associated taxa may be close to each other on a phylogenetic tree or spread apart on a phylogenetic tree. No prediction models currently exist that use multiple forms of microbiome-outcome associations. To address this, we propose a multi-kernel machine regression (MKMR) method that is able to capture various types of microbiome signals when doing predictions. MKMR utilizes multiple forms of microbiome signals through multiple kernels being transformed from multiple distance metrics for microbiomes and learn an optimal conic combination of these kernels, with kernel weights helping us understand contributions of individual microbiome signal types. Simulation studies suggest a much-improved prediction performance over competing methods with mixture of microbiome signals. Real data applicants to predict multiple health outcomes using throat and gut microbiome data also suggest a better prediction of MKMR than that of competing methods.

scFed: federated learning for cell type classification with scRNA-seq.

The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and complexity in biological tissues. However, the nature of large, sparse scRNA-seq datasets and privacy regulations present challenges for efficient cell identification. Federated learning provides a solution, allowing efficient and private data use. Here, we introduce scFed, a unified federated learning framework that allows for benchmarking of four classification algorithms without violating data privacy, including single-cell-specific and general-purpose classifiers. We evaluated scFed using eight publicly available scRNA-seq datasets with diverse sizes, species and technologies, assessing its performance via intra-dataset and inter-dataset experimental setups. We find that scFed performs well on a variety of datasets with competitive accuracy to centralized models. Though Transformer-based model excels in centralized training, its performance slightly lags behind single-cell-specific model within the scFed framework, coupled with a notable time complexity concern. Our study not only helps select suitable cell identification methods but also highlights federated learning's potential for privacy-preserving, collaborative biomedical research.

MARPPI: boosting prediction of protein-protein interactions with multi-scale architecture residual network.

Protein-protein interactions (PPIs) are a major component of the cellular biochemical reaction network. Rich sequence information and machine learning techniques reduce the dependence of exploring PPIs on wet experiments, which are costly and time-consuming. This paper proposes a PPI prediction model, multi-scale architecture residual network for PPIs (MARPPI), based on dual-channel and multi-feature. Multi-feature leverages Res2vec to obtain the association information between residues, and utilizes pseudo amino acid composition, autocorrelation descriptors and multivariate mutual information to achieve the amino acid composition and order information, physicochemical properties and information entropy, respectively. Dual channel utilizes multi-scale architecture improved ResNet network which extracts protein sequence features to reduce protein feature loss. Compared with other advanced methods, MARPPI achieves 96.03%, 99.01% and 91.80% accuracy in the intraspecific datasets of Saccharomyces cerevisiae, Human and Helicobacter pylori, respectively. The accuracy on the two interspecific datasets of Human-Bacillus anthracis and Human-Yersinia pestis is 97.29%, and 95.30%, respectively. In addition, results on specific datasets of disease (neurodegenerative and metabolic disorders) demonstrate the ability to detect hidden interactions. To better illustrate the performance of MARPPI, evaluations on independent datasets and PPIs network suggest that MARPPI can be used to predict cross-species interactions. The above shows that MARPPI can be regarded as a concise, efficient and accurate tool for PPI datasets.