Multi-organ proteomic landscape of COVID-19 autopsies.

The molecular pathology of multi-organ injuries in COVID-19 patients remains unclear, preventing effective therapeutics development. Here, we report a proteomic analysis of 144 autopsy samples from seven organs in 19 COVID-19 patients. We quantified 11,394 proteins in these samples, in which 5,336 were perturbed in the COVID-19 patients compared to controls. Our data showed that cathepsin L1, rather than ACE2, was significantly upregulated in the lung from the COVID-19 patients. Systemic hyperinflammation and dysregulation of glucose and fatty acid metabolism were detected in multiple organs. We also observed dysregulation of key factors involved in hypoxia, angiogenesis, blood coagulation, and fibrosis in multiple organs from the COVID-19 patients. Evidence for testicular injuries includes reduced Leydig cells, suppressed cholesterol biosynthesis, and sperm mobility. In summary, this study depicts a multi-organ proteomic landscape of COVID-19 autopsies that furthers our understanding of the biological basis of COVID-19 pathology.

Neuroimmune cardiovascular interfaces control atherosclerosis.

Atherosclerotic plaques develop in the inner intimal layer of arteries and can cause heart attacks and strokes1. As plaques lack innervation, the effects of neuronal control on atherosclerosis remain unclear. However, the immune system responds to plaques by forming leukocyte infiltrates in the outer connective tissue coat of arteries (the adventitia)2-6. Here, because the peripheral nervous system uses the adventitia as its principal conduit to reach distant targets7-9, we postulated that the peripheral nervous system may directly interact with diseased arteries. Unexpectedly, widespread neuroimmune cardiovascular interfaces (NICIs) arose in mouse and human atherosclerosis-diseased adventitia segments showed expanded axon networks, including growth cones at axon endings near immune cells and media smooth muscle cells. Mouse NICIs established a structural artery-brain circuit (ABC): abdominal adventitia nociceptive afferents10-14 entered the central nervous system through spinal cord T6-T13 dorsal root ganglia and were traced to higher brain regions, including the parabrachial and central amygdala neurons; and sympathetic efferent neurons projected from medullary and hypothalamic neurons to the adventitia through spinal intermediolateral neurons and both coeliac and sympathetic chain ganglia. Moreover, ABC peripheral nervous system components were activated: splenic sympathetic and coeliac vagus nerve activities increased in parallel to disease progression, whereas coeliac ganglionectomy led to the disintegration of adventitial NICIs, reduced disease progression and enhanced plaque stability. Thus, the peripheral nervous system uses NICIs to assemble a structural ABC, and therapeutic intervention in the ABC attenuates atherosclerosis.

Molecular basis of locus-specific H3K9 methylation catalyzed by SUVH6 in plants.

Dimethylated histone H3 Lys9 (H3K9me2) is a conserved heterochromatic mark catalyzed by SUPPRESSOR OF VARIEGATION 3-9 HOMOLOG (SUVH) methyltransferases in plants. However, the mechanism underlying the locus specificity of SUVH enzymes has long been elusive. Here, we show that a conserved N-terminal motif is essential for SUVH6-mediated H3K9me2 deposition in planta. The SUVH6 N-terminal peptide can be recognized by the bromo-adjacent homology (BAH) domain of the RNA- and chromatin-binding protein ANTI-SILENCING 1 (ASI1), which has been shown to function in a complex to confer gene expression regulation. Structural data indicate that a classic aromatic cage of ASI1-BAH domain specifically recognizes an arginine residue of SUVH6 through extensive hydrogen bonding interactions. A classic aromatic cage of ASI1 specifically recognizes an arginine residue of SUVH6 through extensive cation-π interactions, playing a key role in recognition. The SUVH6-ASI1 module confers locus-specific H3K9me2 deposition at most SUVH6 target loci and gives rise to distinct regulation of gene expression depending on the target loci, either conferring transcriptional silencing or posttranscriptional processing of mRNA. More importantly, such mechanism is conserved in multiple plant species, indicating a coordinated evolutionary process between SUVH6 and ASI1. In summary, our findings uncover a conserved mechanism for the locus specificity of H3K9 methylation in planta. These findings provide mechanistic insights into the delicate regulation of H3K9 methylation homeostasis in plants.

MPCLCDA: predicting circRNA-disease associations by using automatically selected meta-path and contrastive learning.

Circular RNA (circRNA) is closely associated with human diseases. Accordingly, identifying the associations between human diseases and circRNA can help in disease prevention, diagnosis and treatment. Traditional methods are time consuming and laborious. Meanwhile, computational models can effectively predict potential circRNA-disease associations (CDAs), but are restricted by limited data, resulting in data with high dimension and imbalance. In this study, we propose a model based on automatically selected meta-path and contrastive learning, called the MPCLCDA model. First, the model constructs a new heterogeneous network based on circRNA similarity, disease similarity and known association, via automatically selected meta-path and obtains the low-dimensional fusion features of nodes via graph convolutional networks. Then, contrastive learning is used to optimize the fusion features further, and obtain the node features that make the distinction between positive and negative samples more evident. Finally, circRNA-disease scores are predicted through a multilayer perceptron. The proposed method is compared with advanced methods on four datasets. The average area under the receiver operating characteristic curve, area under the precision-recall curve and F1 score under 5-fold cross-validation reached 0.9752, 0.9831 and 0.9745, respectively. Simultaneously, case studies on human diseases further prove the predictive ability and application value of this method.

NSRGRN: a network structure refinement method for gene regulatory network inference.

The elucidation of gene regulatory networks (GRNs) is one of the central challenges of systems biology, which is crucial for understanding pathogenesis and curing diseases. Various computational methods have been developed for GRN inference, but identifying redundant regulation remains a fundamental problem. Although considering topological properties and edge importance measures simultaneously can identify and reduce redundant regulations, how to address their respective weaknesses whilst leveraging their strengths is a critical problem faced by researchers. Here, we propose a network structure refinement method for GRN (NSRGRN) that effectively combines the topological properties and edge importance measures during GRN inference. NSRGRN has two major parts. The first part constructs a preliminary ranking list of gene regulations to avoid starting the GRN inference from a directed complete graph. The second part develops a novel network structure refinement (NSR) algorithm to refine the network structure from local and global topology perspectives. Specifically, the Conditional Mutual Information with Directionality and network motifs are applied to optimise the local topology, and the lower and upper networks are used to balance the bilateral relationship between the local topology's optimisation and the global topology's maintenance. NSRGRN is compared with six state-of-the-art methods on three datasets (26 networks in total), and it shows the best all-round performance. Furthermore, when acting as a post-processing step, the NSR algorithm can improve the results of other methods in most datasets.

Deciphering a crucial dimeric interface governing Norrin dimerization and the pathogenesis of familial exudative vitreoretinopathy.

Familial exudative vitreoretinopathy (FEVR) is a hereditary eye disease that could cause blindness. It has been established that Norrin forms dimers to activate ß-catenin signaling, yet the core interface for Norrin dimerization and the precise mechanism by which Norrin dimerization contributes to the pathogenesis of FEVR remain elusive. Here, we report an NDP variant, c.265T>C (p.Phe89Leu), that interrupted ß-catenin signaling by disrupting Norrin dimerization. Structural and functional analysis revealed that the Phe-89 of one Norrin monomer interacts with Pro-98, Ser-101, Arg-121, and Ile-123 of another, forming two core symmetrical dimerization interfaces that are pivotal for the formation of a "hand-by-arm" dimer. Intriguingly, we proved that one of the two core symmetrical interfaces is sufficient for dimerization and activation of ß-catenin signaling, with a substantial contribution from the Phe-89/Pro-98 interaction. Further functional analysis revealed that the disruption of both dimeric interfaces eliminates potential binding sites for LRP5, which could be partially restored by over-expression of TSPAN12. In conclusion, our findings unveil a core dimerization interface that regulates Norrin/LRP5 interaction, highlighting the essential role of Norrin dimerization on ß-catenin signaling and providing potential therapeutic avenues for the treatment of FEVR.

The solution structure of the ADAR2 dsRBM-RNA complex reveals a sequence-specific readout of the minor groove.

Sequence-dependent recognition of dsDNA-binding proteins is well understood, yet sequence-specific recognition of dsRNA by proteins remains largely unknown, despite their importance in RNA maturation pathways. Adenosine deaminases that act on RNA (ADARs) recode genomic information by the site-selective deamination of adenosine. Here, we report the solution structure of the ADAR2 double-stranded RNA-binding motifs (dsRBMs) bound to a stem-loop pre-mRNA encoding the R/G editing site of GluR-2. The structure provides a molecular basis for how dsRBMs recognize the shape, and also more surprisingly, the sequence of the dsRNA. The unexpected direct readout of the RNA primary sequence by dsRBMs is achieved via the minor groove of the dsRNA and this recognition is critical for both editing and binding affinity at the R/G site of GluR-2. More generally, our findings suggest a solution to the sequence-specific paradox faced by many dsRBM-containing proteins that are involved in post-transcriptional regulation of gene expression.

Metabolic reprogramming directed by super-enhancers in tumors: An emerging landscape.

Metabolic reprogramming is an essential hallmark of tumors, and metabolic abnormalities are strongly associated with the malignant phenotype of tumor cells. This is closely related to transcriptional dysregulation. Super-enhancers are extremely active cis-regulatory regions in the genome, and can amalgamate a complex set of transcriptional regulatory components that are crucial for establishing tumor cell identity, promoting tumorigenesis, and enhancing aggressiveness. In addition, alterations in metabolic signaling pathways are often accompanied by changes in super-enhancers. Presently, there is a surge in interest in the potential pathogenesis of various tumors through the transcriptional regulation of super-enhancers and oncogenic mutations in super-enhancers. In this review, we summarize the functions of super-enhancers, oncogenic signaling pathways, and tumor metabolic reprogramming. In particular, we focus on the role of the super-enhancer in tumor metabolism and its impact on metabolic reprogramming. This review also discusses the prospects and directions in the field of super-enhancer and metabolic reprogramming.

Proteome Landscapes of Human Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma.

Liver cancer is among the top leading causes of cancer mortality worldwide. Particularly, hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (CCA) have been extensively investigated from the aspect of tumor biology. However, a comprehensive and systematic understanding of the molecular characteristics of HCC and CCA remains absent. Here, we characterized the proteome landscapes of HCC and CCA using the data-independent acquisition (DIA) mass spectrometry (MS) method. By comparing the quantitative proteomes of HCC and CCA, we found several differences between the two cancer types. In particular, we found an abnormal lipid metabolism in HCC and activated extracellular matrix-related pathways in CCA. We next developed a three-protein classifier to distinguish CCA from HCC, achieving an area under the curve (AUC) of 0.92, and an accuracy of 90% in an independent validation cohort of 51 patients. The distinct molecular characteristics of HCC and CCA presented in this study provide new insights into the tumor biology of these two major important primary liver cancers. Our findings may help develop more efficient diagnostic approaches and new targeted drug treatments.

FerrDb V2: update of the manually curated database of ferroptosis regulators and ferroptosis-disease associations.

Ferroptosis is a mode of regulated cell death characterized by iron-dependent accumulation of lipid peroxidation. It is closely linked to the pathophysiological processes in many diseases. Since our publication of the first ferroptosis database in 2020 (FerrDb V1), many new findings have been published. To keep up with the rapid progress in ferroptosis research and to provide timely and high-quality data, here we present the successor, FerrDb V2. It contains 1001 ferroptosis regulators and 143 ferroptosis-disease associations manually curated from 3288 articles. Specifically, there are 621 gene regulators, of which 264 are drivers, 238 are suppressors, 9 are markers, and 110 are unclassified genes; and there are 380 substance regulators, with 201 inducers and 179 inhibitors. Compared to FerrDb V1, curated articles increase by >300%, ferroptosis regulators increase by 175%, and ferroptosis-disease associations increase by 50.5%. Circular RNA and pseudogene are novel regulators in FerrDb V2, and the percentage of non-coding RNA increases from 7.3% to 13.6%. External gene-related data were integrated, enabling thought-provoking and gene-oriented analysis in FerrDb V2. In conclusion, FerrDb V2 will help to acquire deeper insights into ferroptosis. FerrDb V2 is freely accessible at http://www.zhounan.org/ferrdb/.