High-throughput Single-cell Sequencing Research Articles

Single-Cell Antigen Receptor Sequencing in Pigs with Influenza.

Understanding the pulmonary adaptive immune system of pigs is important as respiratory pathogens present a major challenge for swine producers and pigs are increasingly used to model human pulmonary diseases. Single-cell RNA sequencing (scRNAseq) has accelerated the characterization of cellular phenotypes in the pig respiratory tract under both healthy and diseased conditions. However, combining scRNAseq with recovery of paired T cell receptor (TCR) α and β chains as well as B cell receptor (BCR) heavy and light chains to interrogate their repertoires has not to our knowledge been demonstrated for pigs. Here, we developed primers to enrich porcine TCR α and β chains along with BCR κ and λ light chains and IgM, IgA, and IgG heavy chains that are compatible with the 10x Genomics VDJ sequencing protocol. Using these pig-specific assays, we sequenced the T and B cell receptors of cryopreserved lung cells from CD1D -expressing and -deficient pigs after one or two infections with influenza A virus (IAV) to examine whether natural killer T (NKT) cells alter pulmonary TCR and BCR repertoire selection. We also performed paired single-cell RNA and receptor sequencing of FACS-sorted T cells longitudinally sampled from the lungs of IAV-vaccinated and -infected pigs to track clonal expansion in response to IAV exposure. All pigs presented highly diverse repertoires. Pigs re-exposed to influenza antigens from either vaccination or infection exhibited higher numbers of expanded CD4 and CD8 T cell clonotypes with activated phenotypes, suggesting potential IAV reactive T cell populations. Our results demonstrate the utility of high throughput single-cell TCR and BCR sequencing in pigs.

High-Throughput Single-Cell Metabolic Labeling, Sorting, and Sequencing of Active Antibiotic-Resistant Bacteria in the Environment.

Active antibiotic-resistant bacteria (ARB) play a major role in spreading antimicrobial resistance (AMR) in the environment; however, they have remained largely unexplored. Herein, we coupled bio-orthogonal noncanonical amino acid tagging with high-throughput fluorescence-activated single-cell sorting (FACS) and sequencing to characterize the phenome and genome of active ARB in complex environmental matrices. Active ARB, conferring resistance to six antibiotics throughout wastewater treatment, were distinguished and quantified. The percentage and concentration of active ARB ranged from 0.28% to 45.3% and from 1.1 × 104 to 2.09 × 107 cells/mL, respectively. Notably, the final effluents retained up to 4.79 × 104 cells/mL of active ARB. Targeted FACS and genomic sequencing revealed a distinct taxonomic composition of active ARB compared with that of the overall population. The coexistence of antibiotic resistome and mobilome in active ARB was also identified, including three high-quality metagenomic assembly genomes assigned to pathogenic bacteria, highlighting the substantial health risks due to their activity, phenotypic resistance, mobility, and pathogenicity. This study advances our understanding of previously overlooked active ARB in the environment by linking their resistance phenotype to their genotype. This high-throughput method will enable efficient quantitative surveillance of active AMR, providing valuable insights into risk control and management.

High-throughput single-cell sequencing of activated sludge microbiome

Wastewater treatment plants (WWTPs) represent one of biotechnology's largest and most critical applications, playing a pivotal role in environmental protection and public health. In WWTPs, activated sludge (AS) plays a major role in removing contaminants and pathogens from wastewater. While metagenomics has advanced our understanding of microbial communities, it still faces challenges in revealing the genomic heterogeneity of cells, uncovering the microbial dark matter, and establishing precise links between genetic elements and their host cells as a bulk method. These issues could be largely resolved by single-cell sequencing, which can offer unprecedented resolution to show the unique genetic information. Here we show the high-throughput single-cell sequencing to the AS microbiome. The single-amplified genomes (SAGs) of 15,110 individual cells were clustered into 2,454 SAG bins. We find that 27.5% of the genomes in the AS microbial community represent potential novel species, highlighting the presence of microbial dark matter. Furthermore, we identified 1,137 antibiotic resistance genes (ARGs), 10,450 plasmid fragments, and 1,343 phage contigs, with shared plasmid and phage groups broadly distributed among hosts, indicating a high frequency of horizontal gene transfer (HGT) within the AS microbiome. Complementary analysis using 1,529 metagenome-assembled genomes from the AS samples allowed for the taxonomic classification of 98 SAG bins, which were previously unclassified. Our study establishes the feasibility of single-cell sequencing in characterizing the AS microbiome, providing novel insights into its ecological dynamics, and deepening our understanding of HGT processes, particularly those involving ARGs. Additionally, this valuable tool could monitor the distribution, spread, and pathogenic hosts of ARGs both within AS environments and between AS and other environments, which will ultimately contribute to developing a health risk evaluation system for diverse environments within a One Health framework.

Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics

Recent advances in single-cell sequencing technology have revolutionized our ability to acquire whole transcriptome data. However, uncovering the underlying transcriptional drivers and nonequilibrium driving forces of cell function directly from these data remains challenging. We address this by learning cell state vector fields from discrete single-cell RNA velocity to quantify the single-cell global nonequilibrium driving forces as landscape and flux. From single-cell data, we quantified the Waddington landscape, showing that optimal paths for differentiation and reprogramming deviate from the naively expected landscape gradient paths and may not pass through landscape saddles at finite fluctuations, challenging conventional transition state estimation of kinetic rate for cell fate decisions due to the presence of the flux. A key insight from our study is that stem/progenitor cells necessitate greater energy dissipation for rapid cell cycles and self-renewal, maintaining pluripotency. We predict optimal developmental pathways and elucidate the nucleation mechanism of cell fate decisions, with transition states as nucleation sites and pioneer genes as nucleation seeds. The concept of loop flux quantifies the contributions of each cycle flux to cell state transitions, facilitating the understanding of cell dynamics and thermodynamic cost, and providing insights into optimizing biological functions. We also infer cell-cell interactions and cell-type-specific gene regulatory networks, encompassing feedback mechanisms and interaction intensities, predicting genetic perturbation effects on cell fate decisions from single-cell omics data. Essentially, our methodology validates the landscape and flux theory, along with its associated quantifications, offering a framework for exploring the physical principles underlying cellular differentiation and reprogramming and broader biological processes through high-throughput single-cell sequencing experiments.

ScMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data

The recent advances in high-throughput single-cell sequencing have created an urgent demand for computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are required to avoid biases towards a specific modality and overcome sparsity. Batch effects obfuscating biological signals must also be taken into account. Here, we introduce a new single-cell multiomics integration model, Single-cell Multiomics Autoencoder Integration (scMaui) based on variational product-of-experts autoencoders and adversarial learning. scMaui calculates a joint representation of multiple marginal distributions based on a product-of-experts approach which is especially effective for missing values in the modalities. Furthermore, it overcomes limitations seen in previous VAE-based integration methods with regard to batch effect correction and restricted applicable assays. It handles multiple batch effects independently accepting both discrete and continuous values, as well as provides varied reconstruction loss functions to cover all possible assays and preprocessing pipelines. We demonstrate that scMaui achieves superior performance in many tasks compared to other methods. Further downstream analyses also demonstrate its potential in identifying relations between assays and discovering hidden subpopulations.

Recent Innovations and Technical Advances in High-Throughput Parallel Single-Cell Whole-Genome Sequencing Methods.

Single-cell whole-genome sequencing (scWGS) detects cell heterogeneity at the aspect of genomic variations, which are inheritable and play an important role in life processes such as aging and cancer progression. The recent explosive development of high-throughput single-cell sequencing methods has enabled high-performance heterogeneity detection through a vast number of novel strategies. Despite the limitation on total cost, technical advances in high-throughput single-cell whole-genome sequencing methods are made for higher genome coverage, parallel throughput, and level of integration. This review highlights the technical advancements in high-throughput scWGS in the aspects of strategies design, data efficiency, parallel handling platforms, and their applications on human genome. The experimental innovations, remaining challenges, and perspectives are summarized and discussed.

The correlation between TRIM28 expression and immune checkpoints in CRPC.

This study delves into the unexplored realm of castration-resistant prostate cancer (CRPC) by investigating the role of TRIM28 and its intricate molecular mechanisms using high-throughput single-cell transcriptome sequencing and advanced bioinformatics analysis. Our comprehensive examination unveiled dynamic TRIM28 expression changes, particularly in immune cells such as macrophages and CD8+ T cells within CRPC. Correlation analyses with TCGA data highlighted the connection between TRIM28 and immune checkpoint expression and emphasized its pivotal influence on the quantity and functionality of immune cells. Using TRIM28 knockout mouse models, we identified differentially expressed genes and enriched pathways, unraveling the potential regulatory involvement of TRIM28 in the cGAS-STING pathway. Invitro, experiments further illuminated that TRIM28 knockout in prostate cancer cells induced a notable anti-tumor immune effect by inhibiting M2 macrophage polarization and enhancing CD8+ T cell activity. This impactful discovery was validated in an insitu transplant tumor model, where TRIM28 knockout exhibited a deceleration in tumor growth, reduced proportions of M2 macrophages, and enhanced infiltration of CD8+ T cells. In summary, this study elucidates the hitherto unknown anti-tumor immune role of TRIM28 in CRPC and unravels its potential regulatory mechanism via the cGAS-STING signaling pathway. These findings provide novel insights into the immune landscape of CRPC, offering promising directions for developing innovative therapeutic strategies.

Research progress in isolation and identification of rumen probiotics.

With the increasing research on the exploitation of rumen microbial resources, rumen probiotics have attracted much attention for their positive contributions in promoting nutrient digestion, inhibiting pathogenic bacteria, and improving production performance. In the past two decades, macrogenomics has provided a rich source of new-generation probiotic candidates, but most of these "dark substances" have not been successfully cultured due to the restrictive growth conditions. However, fueled by high-throughput culture and sorting technologies, it is expected that the potential probiotics in the rumen can be exploited on a large scale, and their potential applications in medicine and agriculture can be explored. In this paper, we review and summarize the classical techniques for isolation and identification of rumen probiotics, introduce the development of droplet-based high-throughput cell culture and single-cell sequencing for microbial culture and identification, and finally introduce promising cultureomics techniques. The aim is to provide technical references for the development of related technologies and microbiological research to promote the further development of the field of rumen microbiology research.

The Identification of RPL4 as a Hub Gene Associated with Goat Litter Size via Weighted Gene Co-Expression Network Analysis.

Reproduction in goats is a highly complex and dynamic process of life regulation, involving coordinated regulation from various aspects such as central nervous system regulation, reproductive system development, oocyte maturation, and fertilized egg development. In recent years, researchers have identified numerous genes associated with goat reproductive performance through high-throughput sequencing, single-cell sequencing, gene knockout, and other techniques. However, there is still an urgent need to explore marker genes related to goat reproductive performance. In this study, a single-cell RNA sequencing dataset of oocytes (GSE136005) was obtained from the Gene Expression Omnibus (GEO) database. Weighted Gene Co-expression Network Analysis (WGCNA) was utilized to identify modules highly correlated with goat litter size. Through gene function enrichment analysis, it was found that genes within the modules were mainly enriched in adhesive junctions, cell cycle, and other signaling pathways. Additionally, the top 30 hub genes with the highest connectivity in WGCNA were identified. Subsequently, using Protein-Protein Interaction (PPI) network analysis, the top 30 genes with the highest connectivity within the modules were identified. The intersection of hub genes, key genes in the PPI network, and differentially expressed genes (DEGs) led to the identification of the RPL4 gene as a key marker gene associated with reproductive capacity in goat oocytes. Overall, our study reveals that the RPL4 gene in oocytes holds promise as a biological marker for assessing goat litter size, deepening our understanding of the regulatory mechanisms underlying goat reproductive performance.

Abstract 6433: Anti-CD36 monoclonal antibody can sensitize the neoadjuvant chemotherapy response in PDAC by eliminating the senescent tertiary lymphatic structure

Abstract Objective: Pancreatic ductal adenocarcinoma (PDAC) is deadly and aggressive. Neoadjuvant chemotherapy (NAC) may reduce tumor volume and alter the resectability of the tumor. The efficacy of neoadjuvant chemotherapy in patients is still limited. Tertiary lymphoid structures (TLSs) develop in peripheral non-lymphoid tissues and are essential for the immune response and correlate with chemotherapy in various tumor types. However, more research is needed to determine how TLSs affect neoadjuvant chemotherapy in PDAC. We aim to determine how neoadjuvant chemotherapy affects tumor-infiltrating lymphocytes (TLSs) in PDAC patients. We also want to find a biomarker to boost PDAC neoadjuvant chemotherapy response. Methods: We retrospectively collected formalin-fixed paraffin embedded (FFPE) tissues from 115 PDAC patients without preoperative treatment and 72 patients pretreated with neoadjuvant chemotherapy. Multispectral images were processed using AI-powered image analysis software (Tissue Gnostics; Zeiss, Germany). The 10X Genomics platform was used to sequence single cells in tissue samples from five patients who received neoadjuvant chemotherapy (NAC) and five patients who had not received any treatment before analysis (pretreatment naïve, PN). TLS was separated using Laser Microdissection. The mouse model was created by orthotopically injecting tumor cells into the pancreas. Results: Patients who received NAC have a senescent microenvironment. High-throughput single-cell sequencing showed that the senescent gene signature score was enriched in the NAC group, especially in immune cells. The percentage of p16+ CD20+ B cells and P16+ CD3+ T cells in TLSs also increased in the NAC group. Spatial transcriptomics analysis exhibited that CD36 is highly expressed in senescent TLSs, which suggested that CD36 may be a marker for senescent TLSs. Moreover, CD36+ TLSs induced the infiltration of MDSCs and regulatory T cells. CD36+ TLSs were an independent prognostic factor for poor overall survival (OS) (HR=0.67, p=0.002) and progression-free survival (PFS) (HR=0.71, p=0.003). A mice orthotopic xenograft model showed that an anti-CD36 monoclonal antibody eliminated senescent TLSs in pancreatic tissue. MDSCs and Tregs in the surrounding tissue also decreased. Additionally, in vivo KPC mice model showed that the combination of an anti-CD36 and chemotherapy reduced tumor volume and increased survival compared to chemotherapy alone. Conclusion: NAC has the potential to induce the senescence of tumor-associated TLSs, a phenomenon that has been linked to unfavorable prognosis in PDAC. CD36 serves as a viable marker for senescent TLSs that can be targeted. The administration of an anti-CD36 monoclonal antibody can potentially enhance the efficacy of chemotherapy in PDAC by selectively eliminating CD36+ senescent TLSs in mouse models. Citation Format: Jingrui Yan, Tianxing Zhou, Chao Yang, Yongjie Xie, Jun Yu, Jihui Hao. Anti-CD36 monoclonal antibody can sensitize the neoadjuvant chemotherapy response in PDAC by eliminating the senescent tertiary lymphatic structure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6433.

Single-cell transcriptome atlas reveals somatic cell embryogenic differentiation features during regeneration.

Understanding somatic cell totipotency remains a challenge facing scientific inquiry today. Plants display remarkable cell totipotency expression, illustrated by single-cell differentiation during somatic embryogenesis (SE) for plant regeneration. Determining cell identity and exploring gene regulation in such complex heterogeneous somatic cell differentiation have been major challenges. Here, we performed high-throughput single-cell sequencing assays to define the precise cellular landscape and revealed the modulation mode of marker genes during embryogenic differentiation in cotton (Gossypium hirsutum L.) as the crop for biotechnology application. We demonstrated that nonembryogenic calli (NEC) and primary embryogenic calli (PEC) tissues were composed of heterogeneous cells that could be partitioned into four broad populations with six distinct cell clusters. Enriched cell clusters and cell states were identified in NEC and PEC samples, respectively. Moreover, a broad repertoire of new cluster-specific genes and associated expression modules were identified. The energy metabolism, signal transduction, environmental adaptation, membrane transport pathways, and a series of transcription factors were preferentially enriched in cell embryogenic totipotency expression. Notably, the SE-ASSOCIATED LIPID TRANSFER PROTEIN (SELTP) gene dose-dependently marked cell types with distinct embryogenic states and exhibited a parabolic curve pattern along the somatic cell embryogenic differentiation trajectory, suggesting that SELTP could serve as a favorable quantitative cellular marker for detecting embryogenic expression at the single-cell level. In addition, RNA velocity and Scissor analysis confirmed the pseudo-temporal model and validated the accuracy of the scRNA-seq data, respectively. This work provides valuable marker-genes resources and defines precise cellular taxonomy and trajectory atlases for somatic cell embryogenic differentiation in plant regeneration.

Smith-specific regulatory T cells halt the progression of lupus nephritis

Antigen-specific regulatory T cells (Tregs) suppress pathogenic autoreactivity and are potential therapeutic candidates for autoimmune diseases such as systemic lupus erythematosus (SLE). Lupus nephritis is associated with autoreactivity to the Smith (Sm) autoantigen and the human leucocyte antigen (HLA)-DR15 haplotype; hence, we investigated the potential of Sm-specific Tregs (Sm-Tregs) to suppress disease. Here we identify a HLA-DR15 restricted immunodominant Sm T cell epitope using biophysical affinity binding assays, then identify high-affinity Sm-specific T cell receptors (TCRs) using high-throughput single-cell sequencing. Using lentiviral vectors, we transduce our lead Sm-specific TCR into Tregs derived from patients with SLE who are anti-Sm and HLA-DR15 positive. Compared with polyclonal mock-transduced Tregs, Sm-Tregs potently suppress Sm-specific pro-inflammatory responses in vitro and suppress disease progression in a humanized mouse model of lupus nephritis. These results show that Sm-Tregs are a promising therapy for SLE.

Massively parallel single-cell sequencing of diverse microbial populations.

Single-cell genetic heterogeneity is ubiquitous in microbial populations and an important aspect of microbial biology; however, we lack a broadly applicable and accessible method to study this heterogeneity in microbial populations. Here, we show a simple, robust and generalizable method for high-throughput single-cell sequencing of target genetic loci in diverse microbes using simple droplet microfluidics devices (droplet targeted amplicon sequencing; DoTA-seq). DoTA-seq serves as a platform to perform diverse assays for single-cell genetic analysis of microbial populations. Using DoTA-seq, we demonstrate the ability to simultaneously track the prevalence and taxonomic associations of >10 antibiotic-resistance genes and plasmids within human and mouse gut microbial communities. This workflow is a powerful and accessible platform for high-throughput single-cell sequencing of diverse microbial populations.

Microfluidic-assisted single-cell RNA sequencing facilitates the development of neutralizing monoclonal antibodies against SARS-CoV-2.

As a class of antibodies that specifically bind to a virus and block its entry, neutralizing monoclonal antibodies (neutralizing mAbs) have been recognized as a top choice for combating COVID-19 due to their high specificity and efficacy in treating serious infections. Although conventional approaches for neutralizing mAb development have been optimized for decades, there is an urgent need for workflows with higher efficiency due to time-sensitive concerns, including the high mutation rate of SARS-CoV-2. One promising approach is the identification of neutralizing mAb candidates via single-cell RNA sequencing (RNA-seq), as each B cell has a unique transcript sequence corresponding to its secreted antibody. The state-of-the-art high-throughput single-cell sequencing technologies, which have been greatly facilitated by advances in microfluidics, have greatly accelerated the process of neutralizing mAb development. Here, we provide an overview of the general procedures for high-throughput single-cell RNA-seq enabled by breakthroughs in droplet microfluidics, introduce revolutionary approaches that combine single-cell RNA-seq to facilitate the development of neutralizing mAbs against SARS-CoV-2, and outline future steps that need to be taken to further improve development strategies for effective treatments against infectious diseases.

2189. Colistin Heteroresistance in Enterobacter due to Base Heterozygosity at Certain phoPQ Locations

Abstract Background Enterobacter species are major nosocomial pathogens, and the clinical implications and mechanisms of colistin heteroresistance (CHR) in Enterobacter remain unclear. Methods We used the population analysis profile (PAP) assay to determine the presence of CHR in Enterobacter. To examine whether CHR leads to treatment failure, we conducted in vitro time-killing assays and in vivo assays using murine intra-abdominal infection models. To determine the genetic mechanism for the CHR phenotype, we conducted whole-genome sequencing and ultra-deep second-generation sequencing. A schematic outline of methods and main results Results In this study, we found that 30% of Enterobacter clinical strains causing bloodstream infections at West China Hospital exhibited CHR, which was associated with treatment failure and fatal infections, as demonstrated by in vitro time-kill tests and in vivo mouse infection modeling. We identified base alterations in the phoP-phoQ gene as the main resistance mechanism in Enterobacter CHR and that this heterogeneity originated from colistin selection and base heterozygosity, as detected by ultra-deep second-generation sequencing. We also found that several different resistance subpopulations existed simultaneously in the same strain with different resistance mechanisms. Time-kill experiments in Enterobacter isolates with CHR or susceptible to colistin CHR strains lead to in vivo colistin treatment failure Phenotypic and genomic study of a CHR strain Conclusion We presented evidence for "genetic heterogeneity" in Enterobacter CHR strains, which is consistent with "phenotypic heterogeneity" and genetically explains the unstable and transient HR. This provides important insights and a fresh perspective into the mechanisms and clinical implications of Enterobacter CHR and underscores the importance of deep sequencing, prompting the research of high-throughput microbial single-cell sequencing as a method for detecting "genetic heterogeneity." Frequency of bases that mediate colistin resistance at the same locus of phoP-Q in the parental and resistant strains Disclosures All Authors: No reported disclosures

Human monoclonal antibodies against Staphylococcus aureus A protein identified by high-throughput single-cell sequencing of phase I clinical volunteers' B cells

Methicillin-resistant Staphylococcus aureus, poses a significant threat through infections in both community and hospital settings. To address this challenge, we conducted a phase I clinical trial study involving a recombinant Staphylococcus aureus vaccine. Utilizing peripheral blood lymphocytes from 64 subjects, we isolated antigen-specific memory B cells for subsequent single-cell sequencing. Among the 676 identified antigen-binding IgG1+ clones, we selected the top 10 antibody strains for construction within expression vectors. Successful expression and purification of these monoclonal antibodies led to the discovery of a highly expressed human antibody, designated as IgG-6. This antibody specifically targets the pentameric form of the Staphylococcus aureus protein A (SpA5). In vivo assessments revealed that IgG-6 provided prophylactic protection against MRSA252 infection. This study underscores the potential of human antibodies as an innovative strategy against Staphylococcus aureus infections, offering a promising avenue for further research and clinical development.

A high-throughput single-cell RNA expression profiling method identifies human pericyte markers.

We sought to identify and optimise a universally available histological marker for pericytes in the human brain. Such a marker could be a useful tool for researchers. Further, identifying a gene expressed relatively specifically in human pericytes could provide new insights into the biological functions of this fascinating cell type. We analysed single-cell RNA expression profiles derived from different human and mouse brain regions using a high-throughput and low-cost single-cell transcriptome sequencing method called EasySci. Through this analysis, we were able to identify specific gene markers for pericytes, some of which had not been previously characterised. We then used commercially (and therefore universally) available antibodies to immunolabel the pericyte-specific gene products in formalin-fixed paraffin-embedded (FFPE) human brains and also performed immunoblots to determine whether appropriately sized proteins were recognised. In the EasySci data sets, highly pericyte-enriched expression was notable for SLC6A12 and SLC19A1. Antibodies against these proteins recognised bands of approximately the correct size in immunoblots of human brain extracts. Following optimisation of the immunohistochemical technique, staining for both antibodies was strongly positive in small blood vessels and was far more effective than a PDGFRB antibody at staining pericyte-like cells in FFPE human brain sections. In an exploratory sample of other human organs (kidney, lung, liver, muscle), immunohistochemistry did not show the same pericyte-like pattern of staining. The SLC6A12 antibody was well suited for labelling pericytes in human FFPE brain sections, based on the combined results of single-cell RNA-seq analyses, immunoblots and immunohistochemical studies.

Accessible high-throughput single-cell whole-genome sequencing with paired chromatin accessibility

Single-cell whole-genome sequencing (scWGS) enables the assessment of genome-level molecular differences between individual cells with particular relevance to genetically diverse systems like solid tumors. The application of scWGS was limited due to a dearth of accessible platforms capable of producing high-throughput profiles. We present a technique that leverages nucleosome disruption methodologies with thewidely adopted 10× Genomics ATAC-seq workflow to produce scWGS profiles for high-throughput copy-number analysis without new equipment or custom reagents. We further demonstrate the use of commercially available indexed transposase complexes from ScaleBio for sample multiplexing, reducing the per-sample preparation costs. Finally, we demonstrate that sequential indexed tagmentation with an intervening nucleosome disruption step allows for the generation of both ATAC and WGS data from the same cell, producing comparable data to the unimodal assays. By exclusively utilizing accessible commercial reagents, we anticipate that these scWGS and scWGS+ATAC methods can be broadly adopted by the research community.

Prognostic Markers within the Tumour Microenvironment in Classical Hodgkin Lymphoma.

Classical Hodgkin lymphoma (cHL) accounts for 0.4% of all new cancer cases globally. Despite high cure rates with standard treatment, approximately 15% of patients still experience relapsed or refractory (RR) disease, and many of these eventually die from lymphoma-related causes. Exciting new targeted agents such as anti-PD-1 agents and brentuximab vedotin have changed the therapeutic paradigm beyond chemotherapy and radiotherapy alone. Advances in understanding of the molecular biology are providing insights in the context of novel therapies. The signature histology of cHL requires the presence of scant malignant Hodgkin Reed-Sternberg cells (HRSCs) surrounded by a complex immune-rich tumour microenvironment (TME). The TME cellular composition strongly influences outcomes, yet knowledge of the precise characteristics of TME cells and their interactions with HRSCs is evolving. Novel high-throughput technologies and single-cell sequencing allow deeper analyses of the TME and mechanisms elicited by HRSCs to propagate growth and avoid immune response. In this review, we explore the evolution of knowledge on the prognostic role of immune cells within the TME and provide an up-to-date overview of emerging prognostic data on cHL from new technologies that are starting to unwind the complexity of the cHL TME and provide translational insights into how to improve therapy in the clinic.

Hypoxia-induced AFAP1L1 regulates pathological neovascularization via the YAP-DLL4-NOTCH axis

BackgroundPathological neovascularization plays a pivotal role in the onset and progression of tumors and neovascular eye diseases. Despite notable advancements in the development of anti-angiogenic medications that target vascular endothelial growth factor (VEGF) and its receptors (VEGFRs), the occurrence of adverse reactions and drug resistance has somewhat impeded the widespread application of these drugs. Therefore, additional investigations are warranted to explore alternative therapeutic targets. In recent years, owing to the swift advancement of high-throughput sequencing technology, pan-cancer analysis and single-cell sequencing analysis have emerged as pivotal methodologies and focal areas within the domain of omics research, which is of great significance for us to find potential targets related to the regulation of pathological neovascularization.MethodsPan-cancer analysis and scRNA-seq data analysis were employed to forecast the association between Actin filament-associated protein 1 like 1 (AFAP1L1) and the development of tumors and endothelial cells. Tumor xenograft model and ocular pathological neovascularization model were constructed as well as Isolectin B4 (IsoB4) staining and immunofluorescence staining were used to assess the effects of AFAP1L1 on the progression of neoplasms and neovascular eye diseases in vivo. Transwell assay, wound scratch assay, tube forming assay, three-dimensional germination assay, and rhodamine-phalloidin staining were used to evaluate the impact of AFAP1L1 on human umbilical vein endothelial cells (HUVECs) function in vitro; Dual luciferase reporting, qRT-PCR and western blot were used to investigate the upstream and downstream mechanisms of pathological neovascularization mediated by AFAP1L1.ResultsOur investigation revealed that AFAP1L1 plays a crucial role in promoting the development of various tumors and demonstrates a strong correlation with endothelial cells. Targeted suppression of AFAP1L1 specifically in endothelial cells in vivo proves effective in inhibiting tumor formation and ocular pathological neovascularization. Mechanistically, AFAP1L1 functions as a hypoxia-related regulatory protein that can be activated by HIF-1α. In vitro experiments demonstrated that reducing AFAP1L1 levels can reverse hypoxia-induced excessive angiogenic capacity in HUVECs. The principal mechanism of angiogenesis inhibition entails the regulation of tip cell behavior through the YAP-DLL4-NOTCH axis.ConclusionIn conclusion, AFAP1L1, a newly identified hypoxia-related regulatory protein, can be activated by HIF-1α. Inhibiting AFAP1L1 results in the inhibition of angiogenesis by suppressing the germination of endothelial tip cells through the YAP-DLL4-NOTCH axis. This presents a promising therapeutic target to halt the progression of tumors and neovascular eye disease.