Prior knowledge-guided multilevel graph neural network for tumor risk prediction and interpretation via multi-omics data integration.

The interrelation and complementary nature of multi-omics data can provide valuable insights into the intricate molecular mechanisms underlying diseases. However, challenges such as limited sample size, high data dimensionality and differences in omics modalities pose significant obstacles to fully harnessing the potential of these data. The prior knowledge such as gene regulatory network and pathway information harbors useful gene-gene interaction and gene functional module information. To effectively integrate multi-omics data and make full use of the prior knowledge, here, we propose a Multilevel-graph neural network (GNN): a hierarchically designed deep learning algorithm that sequentially leverages multi-omics data, gene regulatory networks and pathway information to extract features and enhance accuracy in predicting survival risk. Our method achieved better accuracy compared with existing methods. Furthermore, key factors nonlinearly associated with the tumor pathogenesis are prioritized by employing two interpretation algorithms (i.e. GNN-Explainer and IGscore) for neural networks, at gene and pathway level, respectively. The top genes and pathways exhibit strong associations with disease in survival analyses, many of which such as SEC61G and CYP27B1 are previously reported in the literature.

Plasticity of intragraft alloreactive T cell clones in human gut correlates with transplant outcomes.

The site of transition between tissue-resident memory (TRM) and circulating phenotypes of T cells is unknown. We integrated clonotype, alloreactivity, and gene expression profiles of graft-repopulating recipient T cells in the intestinal mucosa at the single-cell level after human intestinal transplantation. Host-versus-graft (HvG)-reactive T cells were mainly distributed to TRM, effector T (Teff)/TRM, and T follicular helper compartments. RNA velocity analysis demonstrated a trajectory from TRM to Teff/TRM clusters in association with rejection. By integrating pre- and post-transplantation (Tx) mixed lymphocyte reaction-determined alloreactive repertoires, we observed that pre-existing HvG-reactive T cells that demonstrated tolerance in the circulation were dominated by TRM profiles in quiescent allografts. Putative de novo HvG-reactive clones showed a transcriptional profile skewed to cytotoxic effectors in rejecting grafts. Inferred protein regulon network analysis revealed upstream regulators that accounted for the effector and tolerant T cell states. We demonstrate Teff/TRM interchangeability for individual T cell clones with known (allo)recognition in the human gut, providing novel insight into TRM biology.

Single-cell transcriptomic characterization of sheep conceptus elongation and implantation.

Bidirectional communication between the developing conceptus and endometrium is essential for pregnancy recognition and establishment in ruminants. We dissect the transcriptomic dynamics of sheep conceptus and corresponding endometrium at pre- and peri-implantation stages using single-cell RNA sequencing. Spherical blastocysts contain five cell types, with 68.62% trophectoderm cells. Strikingly, elongated conceptuses differentiate into 17 cell types, indicating dramatic cell fate specifications. Cell-type-specific gene expression delineates the features of distinctive trophectoderm lineages and indicates that the transition from polar trophectoderm to trophoblast increases interferon-tau expression and likely drives elongation initiation. We identify 13 endometrium-derived cell types and elucidate their molecular responses to conceptus development. Integrated analyses uncover multiple paired transcripts mediating the dialogues between extraembryonic membrane and endometrium, including IGF2-IGF1R, FGF19-FGFR1, NPY-NPY1R, PROS1-AXL, and ADGRE5-CD55. These data provide insight into the molecular regulation of conceptus elongation and represent a valuable resource for functional investigations of pre- and peri-implantation ruminant development.

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas.

Spatial transcriptomics can be used to capture cellular spatial organization and has facilitated new insights into different biological contexts, including developmental biology, cancer, and neuroscience. However, its wide application is still hindered by its technical challenges and immature data analysis methods. Allen Brain Atlas (ABA) provides a great source for spatial gene expression throughout the mouse brain at various developmental stages with in situ hybridization image data. To the best of our knowledge, the portal developed to access spatial expression data is not very useful to biologists. Here, we developed a toolkit to collect and preprocess expression data from the ABA and allow a friendlier query to visualize the spatial distribution of genes of interest, characterize the spatial heterogeneity of the brain, and register cells from single-cell transcriptomics data to fine anatomical brain regions via machine learning methods with high accuracy. AllenDigger will be very helpful to the community in precise spatial gene expression queries and add extra spatial information to further interpret the scRNA-seq data in a cost-effective manner.

Molecular and cellular evolution of the amygdala across species analyzed by single-nucleus transcriptome profiling.

The amygdala, or an amygdala-like structure, is found in the brains of all vertebrates and plays a critical role in survival and reproduction. However, the cellular architecture of the amygdala and how it has evolved remain elusive. Here, we generated single-nucleus RNA-sequencing data for more than 200,000 cells in the amygdala of humans, macaques, mice, and chickens. Abundant neuronal cell types from different amygdala subnuclei were identified in all datasets. Cross-species analysis revealed that inhibitory neurons and inhibitory neuron-enriched subnuclei of the amygdala were well-conserved in cellular composition and marker gene expression, whereas excitatory neuron-enriched subnuclei were relatively divergent. Furthermore, LAMP5+ interneurons were much more abundant in primates, while DRD2+ inhibitory neurons and LAMP5+SATB2+ excitatory neurons were dominant in the human central amygdalar nucleus (CEA) and basolateral amygdalar complex (BLA), respectively. We also identified CEA-like neurons and their species-specific distribution patterns in chickens. This study highlights the extreme cell-type diversity in the amygdala and reveals the conservation and divergence of cell types and gene expression patterns across species that may contribute to species-specific adaptations.

Single-nucleus transcriptomic profiling of multiple organs in a rhesus macaque model of SARS-CoV-2 infection.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes diverse clinical manifestations and tissue injuries in multiple organs. However, cellular and molecular understanding of SARS-CoV-2 infection-associated pathology and immune defense features in different organs remains incomplete. Here, we profiled approximately 77 000 single-nucleus transcriptomes of the lung, liver, kidney, and cerebral cortex in rhesus macaques ( Macaca mulatta) infected with SARS-CoV-2 and healthy controls. Integrated analysis of the multi-organ dataset suggested that the liver harbored the strongest global transcriptional alterations. We observed prominent impairment in lung epithelial cells, especially in AT2 and ciliated cells, and evident signs of fibrosis in fibroblasts. These lung injury characteristics are similar to those reported in patients with coronavirus disease 2019 (COVID-19). Furthermore, we found suppressed MHC class I/II molecular activity in the lung, inflammatory response in the liver, and activation of the kynurenine pathway, which induced the development of an immunosuppressive microenvironment. Analysis of the kidney dataset highlighted tropism of tubule cells to SARS-CoV-2, and we found membranous nephropathy (an autoimmune disease) caused by podocyte dysregulation. In addition, we identified the pathological states of astrocytes and oligodendrocytes in the cerebral cortex, providing molecular insights into COVID-19-related neurological implications. Overall, our multi-organ single-nucleus transcriptomic survey of SARS-CoV-2-infected rhesus macaques broadens our understanding of disease features and antiviral immune defects caused by SARS-CoV-2 infection, which may facilitate the development of therapeutic interventions for COVID-19.

Deciphering the spatial-temporal transcriptional landscape of human hypothalamus development.

The hypothalamus comprises various nuclei and neuronal subpopulations that control fundamental homeostasis and behaviors. However, spatiotemporal molecular characterization of hypothalamus development in humans is largely unexplored. Here, we revealed spatiotemporal transcriptome profiles and cell-type characteristics of human hypothalamus development and illustrated the molecular diversity of neural progenitors and the cell-fate decision, which is programmed by a combination of transcription factors. Different neuronal and glial fates are sequentially produced and showed spatial developmental asynchrony. Moreover, human hypothalamic gliogenesis occurs at an earlier stage of gestation and displays distinctive transcription profiles compared with those in mouse. Notably, early oligodendrocyte cells in humans exhibit different gene patterns and interact with neuronal cells to regulate neuronal maturation by Wnt, Hippo, and integrin signals. Overall, our study provides a comprehensive molecular landscape of human hypothalamus development at early- and mid-embryonic stages and a foundation for understanding its spatial and functional complexity.

COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

Pore engineering of graphene aerogels for vanadium redox flow batteries.

The all-vanadium redox flow battery is considered to be a dispersive and non-perennial energy source due to its grid reliability, high efficiency, standalone modular design, and excellent cycling stability. However, the large vanadium ionic size and relatively high viscosity lead to poor compatibility with most carbon-based microporous electrodes, resulting in sluggish mass diffusion and unsatisfied capacitance retention. Herein, a novel cross-coupled porous graphene aerogel is proposed via the NaNO3-template pore engineering strategy. The microscopic observations and N2 adsorption-desorption isotherms validate the successful regulation of the surface area and porous structure, with the addition of different porogen contents (6.25-25 g L-1). The vanadium redox flow battery delivers a specific capacity of 163.4 mA h g-1 (5.6 A h L-1) at a current density of 25 mA cm-2, surpassing most previously reported batteries with a similar reactor volume. This method holds great promise for the better design and preparation of porous electrodes, and potential suitable applications.

Comprehensive analyses of B-cell compartments across the human body reveal novel subsets and a gut-resident memory phenotype.

Although human B cells have been extensively studied, most reports have used peripheral blood as a source. Here, we used a unique tissue resource derived from healthy organ donors to deeply characterize human B-cell compartments across multiple tissues and donors. These datasets revealed that B cells in the blood are not in homeostasis with compartments in other tissues. We found striking donor-to-donor variability in the frequencies and isotype of CD27+ memory B cells (MBCs). A comprehensive antibody-based screen revealed markers of MBC and allowed identification of novel MBC subsets with distinct functions defined according to surface expression of CD69 and CD45RB. We defined a tissue-resident MBC phenotype that was predominant in the gut but absent in blood. RNA-sequencing of MBC subsets from multiple tissues revealed a tissue-resident MBC gene signature as well as gut- and spleen-specific signatures. Overall, these studies provide novel insights into the nature and function of human B-cell compartments across multiple tissues.

Tissue Determinants of Human NK Cell Development, Function, and Residence.

Immune responses in diverse tissue sites are critical for protective immunity and homeostasis. Here, we investigate how tissue localization regulates the development and function of human natural killer (NK) cells, innate lymphocytes important for anti-viral and tumor immunity. Integrating high-dimensional analysis of NK cells from blood, lymphoid organs, and mucosal tissue sites from 60 individuals, we identify tissue-specific patterns of NK cell subset distribution, maturation, and function maintained across age and between individuals. Mature and terminally differentiated NK cells with enhanced effector function predominate in blood, bone marrow, spleen, and lungs and exhibit shared transcriptional programs across sites. By contrast, precursor and immature NK cells with reduced effector capacity populate lymph nodes and intestines and exhibit tissue-resident signatures and site-specific adaptations. Together, our results reveal anatomic control of NK cell development and maintenance as tissue-resident populations, whereas mature, terminally differentiated subsets mediate immunosurveillance through diverse peripheral sites. VIDEO ABSTRACT.

Single cell RNA-Seq reveals pre-cDCs fate determined by transcription factor combinatorial dose.

BACKGROUND: Classic dendritic cells (cDCs) play a central role in the immune system by processing and presenting antigens to activate T cells, and consist of two major subsets: CD141+ cDC (cDC1) and CD1c+ cDC (cDC2). A population of migratory precursor cells, the pre-cDCs, is the immediate precursors to both cDC subsets. Previous studies showed that there were two pre-committed pre-cDC subpopulations. However, the key molecular drivers of pre-commitment in human pre-cDCs were not investigated. RESULTS: To identify the key molecular drivers for pre-commitment in human pre-cDCs, we performed single cell RNA sequencing (RNA-Seq) of two cDC subsets and pre-cDCs, and bulk RNA-Seq of pre-cDCs and cDCs from human peripheral blood. We found that pre-DC subpopulations cannot be separated by either variable genes within pre-cDCs or differentially expressed genes between cDC1 and cDC2. In contrast, they were separated by 16 transcription factors that are themselves differentially expressed or have regulated targets enriched in the differentially expressed genes between bulk cDC1 and cDC2, with one subpopulation close to cDC1 and the other close to cDC2. More importantly, these two pre-cDC sub-populations are correlated with ratio of IRF8 to IRF4 expression level more than their individual expression level. We also verified these findings using three recently published datasets. CONCLUSIONS: In this study, we demonstrate that single cell transcriptome profiling can reveal pre-cDCs differentiation map, and our results suggest the concept that combinatorial dose of transcription factors determines cell differentiation fate.

High Dimensional Functionomic Analysis of Human Hematopoietic Stem and Progenitor Cells at a Single Cell Level.

The ability to conduct investigation of cellular transcription, signaling, and function at the single-cell level has opened opportunities to examine heterogeneous populations at unprecedented resolutions. Although methods have been developed to evaluate high-dimensional transcriptomic and proteomic data (relating to cellular mRNA and protein), there has not been a method to evaluate corresponding high-dimensional functionomic data (relating to cellular functions) from single cells. Here, we present a protocol to quantitatively measure the differentiation potentials of single human hematopoietic stem and progenitor cells, and then cluster the cells according to these measurements. High dimensional functionomic analysis of cell potential allows cell function to be linked to molecular mechanisms within the same progenitor population.

Human Tissue-Resident Memory T Cells Are Defined by Core Transcriptional and Functional Signatures in Lymphoid and Mucosal Sites.

Tissue-resident memory T cells (TRMs) in mice mediate optimal protective immunity to infection and vaccination, while in humans, the existence and properties of TRMs remain unclear. Here, we use a unique human tissue resource to determine whether human tissue memory T cells constitute a distinct subset in diverse mucosal and lymphoid tissues. We identify a core transcriptional profile within the CD69+ subset of memory CD4+ and CD8+ T cells in lung and spleen that is distinct from that of CD69- TEM cells in tissues and circulation and defines human TRMs based on homology to the transcriptional profile of mouse CD8+ TRMs. Human TRMs in diverse sites exhibit increased expression of adhesion and inhibitory molecules, produce both pro-inflammatory and regulatory cytokines, and have reduced turnover compared with circulating TEM, suggesting unique adaptations for in situ immunity. Together, our results provide a unifying signature for human TRM and a blueprint for designing tissue-targeted immunotherapies.

Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors.

The origin and specification of human dendritic cells (DCs) have not been investigated at the clonal level. Through the use of clonal assays, combined with statistical computation, to quantify the yield of granulocytes, monocytes, lymphocytes and three subsets of DCs from single human CD34+ progenitor cells, we found that specification to the DC lineage occurred in parallel with specification of hematopoietic stem cells (HSCs) to the myeloid and lymphoid lineages. This started as a lineage bias defined by specific transcriptional programs that correlated with the combinatorial 'dose' of the transcription factors IRF8 and PU.1, which was transmitted to most progeny cells and was reinforced by upregulation of IRF8 expression driven by the hematopoietic cytokine FLT3L during cell division. We propose a model in which specification to the DC lineage is driven by parallel and inheritable transcriptional programs in HSCs and is reinforced over cell division by recursive interactions between transcriptional programs and extrinsic signals.

Loss of RNA expression and allele-specific expression associated with congenital heart disease.

Congenital heart disease (CHD), a prevalent birth defect occurring in 1% of newborns, likely results from aberrant expression of cardiac developmental genes. Mutations in a variety of cardiac transcription factors, developmental signalling molecules and molecules that modify chromatin cause at least 20% of disease, but most CHD remains unexplained. We employ RNAseq analyses to assess allele-specific expression (ASE) and biallelic loss-of-expression (LOE) in 172 tissue samples from 144 surgically repaired CHD subjects. Here we show that only 5% of known imprinted genes with paternal allele silencing are monoallelic versus 56% with paternal allele expression-this cardiac-specific phenomenon seems unrelated to CHD. Further, compared with control subjects, CHD subjects have a significant burden of both LOE genes and ASE events associated with altered gene expression. These studies identify FGFBP2, LBH, RBFOX2, SGSM1 and ZBTB16 as candidate CHD genes because of significantly altered transcriptional expression.

A New Hidden Markov Model for Protein Quality Assessment Using Compatibility Between Protein Sequence and Structure.

Protein structure Quality Assessment (QA) is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure QA. In this work, we developed a new Hidden Markov Model (HMM) to assess the compatibility of protein sequence and structure for capturing their complex relationship. More specifically, the emission of the HMM consists of protein local structures in angular space, secondary structures, and sequence profiles. This model has two capabilities: (1) encoding local structure of each position by jointly considering sequence and structure information, and (2) assigning a global score to estimate the overall quality of a predicted structure, as well as local scores to assess the quality of specific regions of a structure, which provides useful guidance for targeted structure refinement. We compared the HMM model to state-of-art single structure quality assessment methods OPUSCA, DFIRE, GOAP, and RW in protein structure selection. Computational results showed our new score HMM.Z can achieve better overall selection performance on the benchmark datasets.

Detecting protein conformational changes in interactions via scaling known structures.

Conformational changes frequently occur when proteins interact with other proteins. How to detect such changes in silico is a major problem. Existing methods for docking with conformational changes remain time-consuming, and they solve only a small portion of protein complexes accurately. This work presents a more accurate method (FlexDoBi) for docking with conformational changes. FlexDoBi generates the possible conformational changes of the interface residues that transform the proteins from their unbound states to bound states. Based on the generated conformational changes, multidimensional scaling is performed to construct candidates for the bound structure. We develop a new energy item for determining the orientation of docking subunits and selecting of plausible conformational changes. Experimental results illustrate that FlexDoBi achieves better results. On 20 complexes, we obtained an average iRMSD of 1.55Å, which compares favorably with the average iRMSD of 1.94Å for FiberDock. Compared to ZDOCK, our results are of 0.27Å less in average iRMSD of the medium difficulty group.