Revealing protein-protein interactions at the transcriptome scale by sequencing.

We describe PROPER-seq (protein-protein interaction sequencing) to map protein-protein interactions (PPIs) en masse. PROPER-seq first converts transcriptomes of input cells into RNA-barcoded protein libraries, in which all interacting protein pairs are captured through nucleotide barcode ligation, recorded as chimeric DNA sequences, and decoded at once by sequencing and mapping. We applied PROPER-seq to human embryonic kidney cells, T lymphocytes, and endothelial cells and identified 210,518 human PPIs (collected in the PROPER v.1.0 database). Among these, 1,365 and 2,480 PPIs are supported by published co-immunoprecipitation (coIP) and affinity purification-mass spectrometry (AP-MS) data, 17,638 PPIs are predicted by the prePPI algorithm without previous experimental validation, and 100 PPIs overlap human synthetic lethal gene pairs. In addition, four previously uncharacterized interaction partners with poly(ADP-ribose) polymerase 1 (PARP1) (a critical protein in DNA repair) known as XPO1, MATR3, IPO5, and LEO1 are validated in vivo. PROPER-seq presents a time-effective technology to map PPIs at the transcriptome scale, and PROPER v.1.0 provides a rich resource for studying PPIs.

Constructing Directional Electrostatic Potential Difference via Gradient Nitrogen Doping for Efficient Oxygen Reduction Reaction.

Nitrogen doping has been recognized as an important strategy to enhance the oxygen reduction reaction (ORR) activity of carbon-encapsulated transition metal catalysts (TM@C). However, previous reports on nitrogen doping have tended to result in a random distribution of nitrogen atoms, which leads to disordered electrostatic potential differences on the surface of carbon layers, limiting further control over the materials' electronic structure. Herein, a gradient nitrogen doping strategy to prepare nitrogen-deficient graphene and nitrogen-rich carbon nanotubes encapsulated cobalt nanoparticles catalysts (Co@CNTs@NG) is proposed. The unique gradient nitrogen doping leads to a gradual increase in the electrostatic potential of the carbon layer from the nitrogen-rich region to the nitrogen-deficient region, facilitating the directed electron transfer within these layers and ultimately optimizing the charge distribution of the material. Therefore, this strategy effectively regulates the density of state and work function of the material, further optimizing the adsorption of oxygen-containing intermediates and enhancing ORR activity. Theoretical and experimental results show that under controlled gradient nitrogen doping, Co@CNTs@NG exhibits significantly ORR performance (Eonset = 0.96 V, E1/2 = 0.86 V). At the same time, Co@CNTs@NG also displays excellent performance as a cathode material for Zn-air batteries, with peak power density of 132.65 mA cm-2 and open-circuit voltage (OCV) of 1.51 V. This work provides an effective gradient nitrogen doping strategy to optimize the ORR performance.

Extracellular RNA in a single droplet of human serum reflects physiologic and disease states.

Extracellular RNAs (exRNAs) are present in human serum. It remains unclear to what extent these circulating exRNAs may reflect human physiologic and disease states. Here, we developed SILVER-seq (Small Input Liquid Volume Extracellular RNA Sequencing) to efficiently sequence both integral and fragmented exRNAs from a small droplet (5 µL to 7 µL) of liquid biopsy. We calibrated SILVER-seq in reference to other RNA sequencing methods based on milliliters of input serum and quantified droplet-to-droplet and donor-to-donor variations. We carried out SILVER-seq on more than 150 serum droplets from male and female donors ranging from 18 y to 48 y of age. SILVER-seq detected exRNAs from more than a quarter of the human genes, including small RNAs and fragments of mRNAs and long noncoding RNAs (lncRNAs). The detected exRNAs included those derived from genes with tissue (e.g., brain)-specific expression. The exRNA expression levels separated the male and female samples and were correlated with chronological age. Noncancer and breast cancer donors exhibited pronounced differences, whereas donors with or without cancer recurrence exhibited moderate differences in exRNA expression patterns. Even without using differentially expressed exRNAs as features, nearly all cancer and noncancer samples and a large portion of the recurrence and nonrecurrence samples could be correctly classified by exRNA expression values. These data suggest the potential of using exRNAs in a single droplet of serum for liquid biopsy-based diagnostics.

Suppression of Endothelial AGO1 Promotes Adipose Tissue Browning and Improves Metabolic Dysfunction.

BACKGROUND: Metabolic disorders such as obesity and diabetes mellitus can cause dysfunction of endothelial cells (ECs) and vascular rarefaction in adipose tissues. However, the modulatory role of ECs in adipose tissue function is not fully understood. Other than vascular endothelial growth factor-vascular endothelial growth factor receptor-mediated angiogenic signaling, little is known about the EC-derived signals in adipose tissue regulation. We previously identified Argonaute 1 (AGO1; a key component of microRNA-induced silencing complex) as a crucial regulator in hypoxia-induced angiogenesis. In this study, we intend to determine the AGO1-mediated EC transcriptome, the functional importance of AGO1-regulated endothelial function in vivo, and the relevance to adipose tissue function and obesity. METHODS: We generated and subjected mice with EC-AGO1 deletion (EC-AGO1-knockout [KO]) and their wild-type littermates to a fast food-mimicking, high-fat high-sucrose diet and profiled the metabolic phenotypes. We used crosslinking immunoprecipitation- and RNA-sequencing to identify the AGO1-mediated mechanisms underlying the observed metabolic phenotype of EC-AGO1-KO. We further leveraged cell cultures and mouse models to validate the functional importance of the identified molecular pathway, for which the translational relevance was explored using human endothelium isolated from healthy donors and donors with obesity/type 2 diabetes mellitus. RESULTS: We identified an antiobesity phenotype of EC-AGO1-KO, evident by lower body weight and body fat, improved insulin sensitivity, and enhanced energy expenditure. At the organ level, we observed the most significant phenotype in the subcutaneous and brown adipose tissues of KO mice, with greater vascularity and enhanced browning and thermogenesis. Mechanistically, EC-AGO1 suppression results in inhibition of thrombospondin-1 (THBS1/TSP1), an antiangiogenic and proinflammatory cytokine that promotes insulin resistance. In EC-AGO1-KO mice, overexpression of TSP1 substantially attenuated the beneficial phenotype. In human endothelium isolated from donors with obesity or type 2 diabetes mellitus, AGO1 and THBS1 are expressed at higher levels than the healthy controls, supporting a pathological role of this pathway. CONCLUSIONS: Our study suggests a novel mechanism by which ECs, through the AGO1-TSP1 pathway, control vascularization and function of adipose tissues, insulin sensitivity, and whole-body metabolic state.

Composition Tuning of Semi-Open Cell Carriers via Phase Freeze-Shrink Self-Molding.

Extracellular matrix (ECM)-mimicking microsized cell carriers featuring a semi-isolated chamber facilitate the study of cellular heterogeneity as well as intercellular communication. However, the semiopen shaping of the designated gel mixture remains unattainable with current methods. We report an oil-phase freeze-shrink self-molding mechanism for generating size- and composition-tunable cradle-shaped microgels (microcradles) from water-in-oil droplets. The universality of this shape transition principle is demonstrated with six types of polysaccharides dispersed in a poly(ethylene glycol) diacrylate (PEGDA) or methacrylate gelatin (GelMA) matrix. By doping the microcradles with the major ECM component, hyaluronic acid sodium, we demonstrate a label-free selective culture of CD44 receptor-rich cells and the formation of cell spheroids within 3 days. This cryo-induced cradle-shaping strategy enables the functionalization of microcarriers for selective cell culture, thereby allowing them to be used for intercellular communication, drug delivery, and the construction of structural units for osteogenesis and 3D printing.

Genome-Wide Mapping of RNA-Protein Associations via Sequencing.

RNA-protein interactions are crucial for regulating gene expression and cellular functions, with their dysregulation potentially impacting disease progression. Systematically mapping these interactions is resource-intensive due to the vast number of potential RNA and protein interactions. Here, we introduce PRIM-seq (Protein-RNA Interaction Mapping by sequencing), a method for the concurrent de novo identification of RNA-binding proteins (RBPs) and the elucidation of their associated RNAs. PRIM-seq works by converting each RNA-protein pair into a unique chimeric DNA sequence, which is then decoded through DNA sequencing. Applied to two human cell types, PRIM-seq generated a comprehensive human RNA-protein association network (HuRPA), consisting of more than 350,000 RNA-proteins pairs involving approximately 7,000 RNAs and 11,000 proteins. The data revealed an enrichment of previously reported RBPs and RNA-protein interactions within HuRPA. We also identified LINC00339 as a protein-associating non-coding RNA and PHGDH as an RNA-associating protein. Notably, PHGDH interacts with BECN1 and ATF4 mRNAs, suppressing their protein expression and consequently inhibiting autophagy, apoptosis, and neurite outgrowth while promoting cell proliferation. PRIM-seq offers a powerful tool for discovering RBPs and RNA-protein associations, contributing to more comprehensive functional genome annotations.

Regulation of nuclear transcription by mitochondrial RNA in endothelial cells.

Chromatin-associated RNAs (caRNAs) form a relatively poorly recognized layer of the epigenome. The caRNAs reported to date are transcribed from the nuclear genome. Here, leveraging a recently developed assay for detection of caRNAs and their genomic association, we report that mitochondrial RNAs (mtRNAs) are attached to the nuclear genome and constitute a subset of caRNA, thus termed mt-caRNA. In four human cell types analyzed, mt-caRNAs preferentially attach to promoter regions. In human endothelial cells (ECs), the level of mt-caRNA-promoter attachment changes in response to environmental stress that mimics diabetes. Suppression of a non-coding mt-caRNA in ECs attenuates stress-induced nascent RNA transcription from the nuclear genome, including that of critical genes regulating cell adhesion, and abolishes stress-induced monocyte adhesion, a hallmark of dysfunctional ECs. Finally, we report increased nuclear localization of multiple mtRNAs in the ECs of human diabetic donors, suggesting many mtRNA translocate to the nucleus in a cell stress and disease-dependent manner. These data nominate mt-caRNAs as messenger molecules responsible for mitochondrial-nuclear communication and connect the immediate product of mitochondrial transcription with the transcriptional regulation of the nuclear genome.

Tuning the Coordination Environment of Carbon-Based Single-Atom Catalysts via Doping with Multiple Heteroatoms and Their Applications in Electrocatalysis.

Carbon-based single-atom catalysts (SACs) are considered to be a perfect platform for studying the structure-activity relationship of different reactions due to the adjustability of their coordination environment. Multi-heteroatom doping has been demonstrated as an effective strategy for tuning the coordination environment of carbon-based SACs and enhancing catalytic performance in electrochemical reactions. Herein, recently developed strategies for multi-heteroatom doping, focusing on the regulation of single-atom active sites by heteroatoms in different coordination shells, are summarized. In addition, the correlation between the coordination environment and the catalytic activity of carbon-based SACs are investigated through representative experiments and theoretical calculations for various electrochemical reactions. Finally, concerning certain shortcomings of the current strategies of doping multi-heteroatoms, some suggestions are put forward to promote the development of carbon-based SACs in the field of electrocatalysis.

Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells.

The interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.

Miniaturized soft centrifugal pumps with magnetic levitation for fluid handling.

Centrifugal pumps are essential mechanical components for liquid delivery in many biomedical systems whose miniaturization can promote innovative disease treatment approaches. However, centrifugal pumps are predominately constructed by rigid and bulky components. Here, we combine the soft materials and flexible electronics to achieve soft magnetic levitation micropumps (SMLMs) that are only 1.9 to 12.8 grams in weight. The SMLMs that rotate at a rotation speed of 1000 revolutions per min to pump liquids with various viscosities ranging from 1 to 6 centipoise can be used in assisting dialysis, blood circulation, and skin temperature control because of excellent biocompatibility with no organ damage. The development of SMLMs not only demonstrates the possibility to replace rigid rotating structures with soft materials for handling large volumes of fluids but also indicates the potential for fully flexible artificial organs that may revolutionize health care and improve the well-being of patients.

Avoiding common pitfalls when clustering biological data.

Clustering is an unsupervised learning method, which groups data points based on similarity, and is used to reveal the underlying structure of data. This computational approach is essential to understanding and visualizing the complex data that are acquired in high-throughput multidimensional biological experiments. Clustering enables researchers to make biological inferences for further experiments. Although a powerful technique, inappropriate application can lead biological researchers to waste resources and time in experimental follow-up. We review common pitfalls identified from the published molecular biology literature and present methods to avoid them. Commonly encountered pitfalls relate to the high-dimensional nature of biological data from high-throughput experiments, the failure to consider more than one clustering method for a given problem, and the difficulty in determining whether clustering has produced meaningful results. We present concrete examples of problems and solutions (clustering results) in the form of toy problems and real biological data for these issues. We also discuss ensemble clustering as an easy-to-implement method that enables the exploration of multiple clustering solutions and improves robustness of clustering solutions. Increased awareness of common clustering pitfalls will help researchers avoid overinterpreting or misinterpreting the results and missing valuable insights when clustering biological data.