Single Nucleus Total RNA Sequencing of Formalin-Fixed Paraffin-Embedded Gliomas.

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.

Single-cell transcriptomics across 2,534 microbial species reveals functional heterogeneity in the rumen microbiome.

Deciphering the activity of individual microbes within complex communities and environments remains a challenge. Here we describe the development of microbiome single-cell transcriptomics using droplet-based single-cell RNA sequencing and pangenome-based computational analysis to characterize the functional heterogeneity of the rumen microbiome. We generated a microbial genome database (the Bovine Gastro Microbial Genome Map) as a functional reference map for the construction of a single-cell transcriptomic atlas of the rumen microbiome. The atlas includes 174,531 microbial cells and 2,534 species, of which 172 are core active species grouped into 12 functional clusters. We detected single-cell-level functional roles, including a key role for Basfia succiniciproducens in the carbohydrate metabolic niche of the rumen microbiome. Furthermore, we explored functional heterogeneity and reveal metabolic niche trajectories driven by biofilm formation pathway genes within B. succiniciproducens. Our results provide a resource for studying the rumen microbiome and illustrate the diverse functions of individual microbial cells that drive their ecological niche stability or adaptation within the ecosystem.

Efficacy and safety of the Chinese herbal medicine Bu-Shen-Huo-Xue granule for the treatment of coronary heart disease: study protocol for a multicenter, randomized, double-blinded, placebo-controlled clinical trial.

Background: Coronary heart disease (CHD) is representative of cardiovascular disease and the leading cause of death in humans. Previous studies have shown that kidney disease is associated with CHD, and current treatment options that can improve both cardiac and renal functions still have some limitations. The traditional Chinese medicine Bu-Shen-Huo-Xue granule (BSHXG) can promote blood rheology, inhibit platelet agglutination, and improve heart and kidney functions. Methods: This is a multicenter, randomized, double-blind, placebo-controlled clinical trial. A total of 210 participants will be randomized to the intervention group and the placebo group. The Guang'anmen Hospital of China Academy of Chinese Medical Sciences is the leading center, and the Affiliated Hospital of Shandong University of Chinese Medicine and the First Affiliated Hospital of Guangzhou University of Chinese Medicine are the participating units. In addition to conventional pharmacotherapy for angina, the intervention group will receive BSHXG while the placebo group will receive BSHXG placebo. All participants will receive 2 months of treatment with 6 months of follow-up. The primary outcome is the efficacy of angina pectoris symptoms in CHD. Secondary outcomes are nitroglycerin arrest, ECG efficacy, Seattle Angina Questionnaire score, serology indicators, assessment of safety, and cardiovascular endpoint events. The transcriptome and metabolome will be used to screen biomarkers for diagnosis and efficacy evaluation. Discussion: This study aimed to evaluate the efficacy and safety of Bu-Shen-Huo-Xue granule in the treatment of coronary heart disease, and to evaluate the benefits to patients with coronary heart disease from both cardiac and renal indicators. Trial registration: This trial is approved by the Ethical Review Committee of the Guang'anmen Hospital China Academy of Chinese Medical Sciences with the number 2022-224-KY-01, and has been registered on the Chinese Clinical Trials Registry with the number ChiCTR2300070977 on 27 April 2023.

Biological functions and biomedical applications of extracellular vesicles derived from blood cells.

There is a growing interest in using extracellular vesicles (EVs) for therapeutic applications. EVs are composed of cytoplasmic proteins and nucleic acids and an external lipid bilayer containing transmembrane proteins on their surfaces. EVs can alter the state of the target cells by interacting with the receptor ligand of the target cell or by being internalised by the target cell. Blood cells are the primary source of EVs, and 1 µL of plasma contains approximately 1.5 × 107 EVs. Owing to their easy acquisition and the avoidance of cell amplification in vitro, using blood cells as a source of therapeutic EVs has promising clinical application prospects. This review summarises the characteristics and biological functions of EVs derived from different blood cell types (platelets, erythrocytes, and leukocytes) and analyses the prospects and challenges of using them for clinical therapeutic applications. In summary, blood cell-derived EVs can regulate different cell types such as immune cells (macrophages, T cells, and dendritic cells), stem cells, and somatic cells, and play a role in intercellular communication, immune regulation, and cell proliferation. Overall, blood cell-derived EVs have the potential for use in vascular diseases, inflammatory diseases, degenerative diseases, and injuries. To promote the clinical translation of blood cell-derived EVs, researchers need to perform further studies on EVs in terms of scalable and reproducible isolation technology, quality control, safety, stability and storage, regulatory issues, cost-effectiveness, and long-term efficacy.

High-throughput single-microbe RNA sequencing reveals adaptive state heterogeneity and host-phage activity associations in human gut microbiome.

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications in health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve comprehensive understanding of complex microbial communities together with their hosts is therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive responses states among species in Prevotella and Roseburia genus and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated the smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-word situations and promises new perspectives in the understanding of human microbiomes.

Association between dietary live microbe intake and Life's Essential 8 in US adults: a cross-sectional study of NHANES 2005-2018.

Background: Assessing the impact of dietary live microbe intake on health outcomes has gained increasing interest. This study aimed to elucidate the relationship between dietary live microbe intake and Life's Essential 8 (LE8) scores, a metric for cardiovascular health (CVH), in the U.S. adult population. Methods: We analyzed data from 10,531 adult participants of the National Health and Nutrition Examination Survey (NHANES) spanning 2005-2018. Participants were stratified into low, medium, and high intake groups of dietary live microbe based on Marco's classification system. We employed weighted logistic and linear regression analyses, along with subgroup, interaction effect, and sensitivity analyses. Additionally, Restricted Cubic Splines (RCS) were used to explore the dose-response relationship between food intake and CVH in different groups. Results: Compared to the low live microbe intake group, the medium and high live microbe intake groups had significantly higher LE8, with ß coefficients of 2.75 (95% CI: 3.89-5.65) and 3.89 (95% CI: 6.05-8.11) respectively. Additionally, moderate and high groups significantly reduced the risk of high cardiovascular health risk, defined as an LE8 score below 50, with odds ratios (OR) of 0.73 and 0.65 respectively. Subgroup analysis and sensitivity analysis proved the stability of the results. In the low intake group, food intake shows a linear negative correlation with LE8, whereas in the high intake group, it exhibits a linear positive correlation. In contrast, in the moderate live microbe intake group, the relationship between food intake and LE8 presents a distinct inverted "U" shape. Conclusion: This study highlights the potential benefits of medium to high dietary intake of live microbe in improving LE8 scores and CVH in adults. These findings advocate for the inclusion of live microbes in dietary recommendations, suggesting their key role in CVH enhancement.

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nuclei using Microwell-seq3.

Single cell chromatin accessibility profiling and transcriptome sequencing are the most widely used technologies for single-cell genomics. Here, we present Microwell-seq3, a high-throughput and facile platform for high-sensitivity single-nucleus chromatin accessibility or full-length transcriptome profiling. The method combines a preindexing strategy and a penetrable chip-in-a-tube for single nucleus loading and DNA amplification and therefore does not require specialized equipment. We used Microwell-seq3 to profile chromatin accessibility in more than 200,000 single nuclei and the full-length transcriptome in ~50,000 nuclei from multiple adult mouse tissues. Compared with the existing polyadenylated transcript capture methods, integrative analysis of cell type-specific regulatory elements and total RNA expression uncovered comprehensive cell type heterogeneity in the brain. Gene regulatory networks based on chromatin accessibility profiling provided an improved cell type communication model. Finally, we demonstrated that Microwell-seq3 can identify malignant cells and their specific regulons in spontaneous lung tumors of aged mice. We envision a broad application of Microwell-seq3 in many areas of research.

High-Throughput Host-Microbe Single-Cell RNA Sequencing Reveals Ferroptosis-Associated Heterogeneity during Acinetobacter baumannii Infection.

Interactions between host and bacterial cells are integral to human physiology. The complexity of host-microbe interactions extends to different cell types, spatial aspects, and phenotypic heterogeneity, requiring high-resolution approaches to capture their full complexity. The latest breakthroughs in single-cell RNA sequencing (scRNA-seq) have opened up a new era of studies in host-pathogen interactions. Here, we first report a high-throughput cross-species dual scRNA-seq technology by using random primers to simultaneously capture both eukaryotic and bacterial RNAs (scRandom-seq). Using reference cells, scRandom-seq can detect individual eukaryotic and bacterial cells with high throughput and high specificity. Acinetobacter baumannii (A.b) is a highly opportunistic and nosocomial pathogen that displays resistance to many antibiotics, posing a significant threat to human health, calling for discoveries and treatment. In the A.b infection model, scRandom-seq witnessed polarization of THP-1 derived-macrophages and the intracellular A.b-induced ferroptosis-stress in host cells. The inhibition of ferroptosis by Ferrostatin-1 (Fer-1) resulted in the improvement of cell vitality and resistance to A.b infection, indicating the potential to resist related infections. scRandom-seq provides a high-throughput cross-species dual single-cell RNA profiling tool that will facilitate future discoveries in unraveling the complex interactions of host-microbe interactions in infection systems and tumor micro-environments.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq.

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Effects of Banxia Baizhu Tianma Decoction in alleviating atherosclerosis based on the regulation of perivascular adipose.

ETHNOPHARMACOLOGICAL RELEVANCE: The occurrence and development of atherosclerosis, a common chronic inflammatory vascular disease, are closely related to cardiovascular and cerebrovascular diseases. Banxia Baizhu Tianma Decoction (BBTD) is a representative traditional Chinese medicine formula that resolves phlegm, disperses wind, invigorates the spleen and eliminates dampness and is also a commonly used clinical medication for treating vascular diseases. AIM OF THE STUDY: To explore the pharmacological mechanisms of BBTD in alleviating atherosclerosis, the present study was carried out by conducting an integrative analysis of aortic and perivascular adipose tissue (PVAT) proteomics and metabolomics. MATERIALS AND METHODS: Eight-week-old ApoE-/- mice were randomly divided into the BBTD group and the model group, and nine age-matched C57BL/6J (C57) mice were used as the control group (n = 9). The C57 mice were fed a standard diet, while the ApoE-/- mice were fed a high-fat, high-cholesterol diet for 12 weeks. Mice in the BBTD group were transgastrically administered BBTD at a dose of 17.8 g/kg/day for 8 weeks, while the model group and control group mice received an equivalent volume of saline by gavage. Histomorphology of the aortas and PVAT was assessed by HE staining, oil red O staining, Masson staining, and α-SMA and CD68 immunohistochemical methods. An integrative analysis of aortic proteomics, PVAT proteomics and PVAT metabolomics was conducted to study the pharmacological mechanisms of BBTD. RESULTS: Compared to the model group, mice treated with BBTD had thicker fibrous caps, increased collagen content, less erosion of smooth muscle cells and infiltration of macrophages, as well as a relatively low inflammatory response level, suggesting that BBTD treatment reduced plaque vulnerability. Omics analysis suggested that BBTD treatment demonstrated anti-atherosclerotic effects and increased plaque stability in the aorta by activating the TGF-beta pathway. Simultaneously, BBTD inhibited PVAT inflammation levels (decreased the levels of MCP and IL-6). Proteomics and metabolomics of PVAT suggested that the targets of BBTD included upregulation of the α-linolenic acid metabolic pathway and downregulation of multiple inflammatory pathways, such as the NF-kappa B signalling pathway, primary immunodeficiency and Th17 cell differentiation in PVAT. CONCLUSIONS: BBTD reduces the vulnerability of atherosclerotic plaques and inhibits the inflammatory phenotype of perivascular adipose tissue.

Bibliometric analysis of residual cardiovascular risk: trends and frontiers.

BACKGROUND: The presence of residual cardiovascular risk is an important cause of cardiovascular events. Despite the significant advances in our understanding of residual cardiovascular risk, a comprehensive analysis through bibliometrics has not been performed to date. Our objective is to conduct bibliometric studies to analyze and visualize the current research hotspots and trends related to residual cardiovascular risk. This will aid in understanding the future directions of both basic and clinical research in this area. METHODS: The literature was obtained from the Web of Science Core Collection database. The literature search date was September 28, 2022. Bibliometric indicators were analyzed using CiteSpace, VOSviewer, Bibliometrix (an R package), and Microsoft Excel. RESULT: A total of 1167 papers were included, and the number of publications is increasing rapidly in recent years. The United States and Harvard Medical School are the leading country and institution, respectively, in the study of residual cardiovascular risk. Ridker PM and Boden WE are outstanding investigators in this field. According to our research results, the New England Journal of Medicine is the most influential journal in the field of residual cardiovascular risk, whereas Atherosclerosis boasts the highest number of publications on this topic. Analysis of keywords and landmark literature identified current research hotspots including complications of residual cardiovascular risk, risk factors, and pharmacological prevention strategies. CONCLUSION: In recent times, global attention toward residual cardiovascular risk has significantly increased. Current research is focused on comprehensive lipid-lowering, residual inflammation risk, and dual-pathway inhibition strategies. Future efforts should emphasize strengthening international communication and cooperation to promote the comprehensive evaluation and management of residual cardiovascular risk.

OpenNAU: An open-source platform for normalizing, analyzing, and visualizing cancer untargeted metabolomics data.

Objective: As an important part of metabolomics analysis, untargeted metabolomics has become a powerful tool in the study of tumor mechanisms and the discovery of metabolic markers with high-throughput spectrometric data which also poses great challenges to data analysis, from the extraction of raw data to the identification of differential metabolites. To date, a large number of analytical tools and processes have been developed and constructed to serve untargeted metabolomics research. The different selection of analytical tools and parameter settings lead to varied results of untargeted metabolomics data. Our goal is to establish an easily operated platform and obtain a repeatable analysis result. Methods: We used the R language basic environment to construct the preprocessing system of the original data and the LAMP (Linux+Apache+MySQL+PHP) architecture to build a cloud mass spectrum data analysis system. Results: An open-source analysis software for untargeted metabolomics data (openNAU) was constructed. It includes the extraction of raw mass data and quality control for the identification of differential metabolic ion peaks. A reference metabolomics database based on public databases was also constructed. Conclusions: A complete analysis system platform for untargeted metabolomics was established. This platform provides a complete template interface for the addition and updating of the analysis process, so we can finish complex analyses of untargeted metabolomics with simple human-computer interactions. The source code can be downloaded from https://github.com/zjuRong/openNAU.

Discovery of Novel Biphenyl Carboxylic Acid Derivatives as Potent URAT1 Inhibitors.

Urate transporter 1 (URAT1) is a clinically validated target for the treatment of hyperuricemia and gout. Due to the absence of protein structures, the molecular design of new URAT1 inhibitors generally resorts to ligand-based approaches. Two series of biphenyl carboxylic acids were designed based on the structures of URAT1 inhibitors Epaminurad and Telmisartan via a strategy of pharmacophore fusion. Fifty-one novel compounds were synthesized and most of them showed obvious inhibition against human URAT1. A1 and B21 were identified as the most potent URAT1 inhibitors in series A and B, respectively. They exhibited IC50 values of 0.93 µM and 0.17 µM, which were comparable or superior to the clinical uricosuric drug benzbromarone. The results confirmed the effectiveness of ligand-based approaches in identifying novel and potent URAT1 inhibitors.

Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte.

Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.

An intelligent data analysis-based medical management method for lower limb health of football athletes.

With increasingly mature commercial operations, football has become the most popular sport in the world. As the main body of football, athletes are prone to injury due to an increasing degree of competition intensity. Their health determines the length of these athletes careers, especially regarding the lower limbs that are mainly used. Therefore, the smart visualization approaches that can realize such function are in urgent demand in the area of sports healthcare. Benefitted by the strong ability of perception and analysis, a convolutional neural network (CNN) is utilized to construct an intelligent data analysis-based medical management method for the lower limb health of football athletes. First, the CNN is formulated as the main backbone, and its parameters are optimized for multiple rounds during the training stage. Then, a statistical analysis software named SPSS is introduced to assess the effect mechanism of different postures on lower limbs. Some experiments are carried out on simulative data to evaluate the proposed method, and results show a good performance of the proposed method.

Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq.

Bacteria colonize almost all parts of the human body and can differ significantly. However, the population level transcriptomics measurements can only describe the average bacteria population behaviors, ignoring the heterogeneity among bacteria. Here, we report a droplet-based high-throughput single-microbe RNA-seq assay (smRandom-seq), using random primers for in situ cDNA generation, droplets for single-microbe barcoding, and CRISPR-based rRNA depletion for mRNA enrichment. smRandom-seq showed a high species specificity (99%), a minor doublet rate (1.6%), a reduced rRNA percentage (32%), and a sensitive gene detection (a median of ~1000 genes per single E. coli). Furthermore, smRandom-seq successfully captured transcriptome changes of thousands of individual E. coli and discovered a few antibiotic resistant subpopulations displaying distinct gene expression patterns of SOS response and metabolic pathways in E. coli population upon antibiotic stress. smRandom-seq provides a high-throughput single-microbe transcriptome profiling tool that will facilitate future discoveries in microbial resistance, persistence, microbe-host interaction, and microbiome research.

Single Extracellular Vesicle Analysis Using Droplet Microfluidics.

Extracellular vesicles (EVs) are lipid-bound nanometer-sized vesicles released by all cell types that contain molecular payload such as proteins and/or nucleic acids. EVs are a key facet of cell-to-cell communication and have the potential to be used in the diagnosis of numerous diseases, chief among them being cancer. However, most methods of EV analysis struggle to identify the rare, malformed proteins indicative of tumor cells as tumor EVs represent only a tiny fraction of the bulk EVs present in the bloodstream. Here, we present a method of single EV analysis, utilizing droplet microfluidics to encapsulate EVs, which are labeled with DNA barcodes linked to antibodies, in droplets with the DNA extension used to amplify the signals associated with each EV. The amplified DNA can then be sequenced to assess the protein content of individual EVs, enabling the detection of rare proteins and EV subpopulations within a bulk EV sample.

Highly parallel, wash-free, and ultrasensitive centrifugal droplet digital protein detection in sub-microliter blood.

The ability to efficiently detect low-abundance protein biomarkers in tiny blood samples is a significant challenge in clinical and laboratory settings. Currently, high-sensitivity approaches require specialized instrumentation, involve multiple washing steps, and lack the ability to parallelize, preventing their widespread implementation. Herein, we developed a parallelized, wash-free, and ultrasensitive centrifugal droplet digital protein detection (CDPro) technology that achieves a femtomolar limit of detection (LoD) of target proteins with sub-microliters of plasma. The CDPro combines two techniques, namely a centrifugal microdroplet generation device and a digital immuno-PCR assay. Miniaturized centrifugal devices enable emulsification of hundreds of samples within 3 minutes using a common centrifuge. The bead-free digital immuno-PCR assay not only eliminates the need for multistep washing, but also possesses ultra-high detection sensitivity and accuracy. We characterized the performance of CDPro using recombinant interleukins (IL-3 and IL-6) as example targets and reported a LoD of 0.0128 pg mL-1. We also quantified IL-6 from 7 human clinical blood samples using the CDPro with only 0.5 µL plasma, which showed excellent agreement with an existing clinical protein diagnostic system with 25 µL plasma from those samples (R2 = 0.98).