Single-cell Analysis Research Articles

Viscoelastic Fluid Focusing Chip-ICP-MS Single-Cell Analysis Enables Elucidating the Effect of Extracellular Polymeric Substances on Bioaccumulation of Hg2+/HgS in Microcystis aeruginosa Cell.

Understanding the interactions between mercury and microalgae, especially the interactions between inorganic mercury (IHg) and extracellular polymeric substances (EPS, a protective barrier between cells and their external environment), is essential for elucidating mercury's toxicological mechanisms. Given the inherent cell heterogeneity, a novel analysis system of an online viscoelastic fluid focusing chip-time-resolved analysis inductively coupled plasma mass spectrometry has been developed to investigate the bioaccumulation of HgS nanoparticles and Hg2+ in single Microcystis aeruginosa (M. aeruginosa) cells, exploring the interaction mechanisms between HgS/Hg2+ accumulation in algal cells and EPS. The single-cell analysis results reveal minimal bioavailability of HgS within algal cells, with mercury's toxicity to M. aeruginosa being species-dependent. Notably, algal cells exhibited more heterogeneity in HgS uptake than in Hg2+ uptake. Under Hg2+/HgS stress, M. aeruginosa cells with EPS removed (EPS-R algal cells) showed an increased level of bioaccumulation of mercury compared to those with EPS (EPS-C algal cells), highlighting the critical role of EPS in mercury bioaccumulation. Overall, the designed viscoelastic fluid microfluidic focusing chip integrates focusing and cleaning functions, featuring easy fabrication, simple operation, low sample loss, and relatively high throughput. Under the optimal conditions, the sample throughput is 1195 min-1 and the cell recovery is 90%. Besides, this research offers novel insights into the interaction mechanisms between Hg2+/HgS and EPS in microalgal cells and unveils the specific toxic effects of Hg2+/HgS on M. aeruginosa at the single-cell level, contributing to a deeper understanding of mercury's ecological and toxicological impact in aquatic environments.

SCUBA implements a storage format-agnostic API for single-cell data access in R

While robust tools exist for the analysis of single-cell datasets in both Python and R, interoperability is limited, and analysis tools generally only accept one object class. Considerable programming expertise is required to integrate tools across package ecosystems into a comprehensive analysis, due to their differing languages and internal data structures. This complicates validation of results and leads to inconsistent visualizations between analysis suites. Conversion between object formats is the most common solution, but this is difficult and error-prone due to the rapid pace of development of the analysis suites and their underlying data structures. To address this, we created SCUBA (Single-Cell Unified Backend API), an R package that implements a unified data access API for all common R and Python single-cell object formats. SCUBA extends the data access approach from the widely used Seurat package to SingleCellExperiment and anndata objects. SCUBA also implements new data-specific access functions for all supported object types. Performance scales well across all SCUBA-supported formats. In addition to performance, SCUBA offers several advantages over object conversion for the visualization and further analysis of pre-processed single-cell data. First, SCUBA extracts only data required for the operation at hand, leaving the original object unmodified. This process is simpler, less error prone, and less memory intensive than object conversion, which operates on the entire dataset. Second, code written with SCUBA can use any supported object class as input, with simple and consistent syntax across object formats. This allows a single analysis script or package (like our interactive single-cell browser, scExploreR) to work seamlessly with multiple object types, reducing the complexity of the code and improving both readability and reproducibility. Adoption of SCUBA will ultimately improve collaboration and reproducible research in single-cell analysis by lowering the barriers between package ecosystems.

Protein catabolites as blood-based biomarkers of aging physiology: Findings from the Dog Aging Project.

Our understanding of age-related physiology and metabolism has grown through the study of systems biology, including transcriptomics, single-cell analysis, proteomics and metabolomics. Studies in lab organisms in controlled environments, while powerful and complex, fall short of capturing the breadth of genetic and environmental variation in nature. Thus, there is now a major effort in geroscience to identify aging biomarkers and to develop aging interventions that might be applied across the diversity of humans and other free-living species. To meet this challenge, the Dog Aging Project (DAP) is designed to identify cross-sectional and longitudinal patterns of aging in complex systems, and how these are shaped by the diversity of genetic and environmental variation among companion dogs. Here we surveyed the plasma metabolome from the first year of sampling of the Precision Cohort of the DAP. By incorporating extensive metadata and whole genome sequencing information, we were able to overcome the limitations inherent in breed-based estimates of genetic and physiological effects, and to probe the physiological and dietary basis of the age-related metabolome. We identified a significant effect of age on approximately 40% of measured metabolites. Among other insights, we discovered a potentially novel biomarker of age in the post-translationally modified amino acids (ptmAAs). The ptmAAs, which can only be generated by protein hydrolysis, covaried both with age and with other biomarkers of amino acid metabolism, and in a way that was robust to diet. Clinical measures of kidney function mediated about half of the higher ptmAA levels in older dogs. This work identifies ptmAAs as robust indicators of age in dogs, and points to kidney function as a physiological mediator of age-associated variation in the plasma metabolome.

Hippo signaling cooperates with p53 to regulate lung airway mucous cell metaplasia.

Airway mucous cell metaplasia is a significant feature of many chronic airway diseases, such as chronic obstructive pulmonary disease (COPD), cystic fibrosis, and asthma. However, the mechanisms underlying this process remain poorly understood. Here, we employ in vivo mouse genetic models to demonstrate that Hippo and p53 cooperate to modulate the differentiation of club cells into goblet cells. We reveal that ablation of Mst1 and Mst1 (Mst1/2), the core components of Hippo signaling, significantly reduces mucous metaplasia in the lung airways in a lipopolysaccharide (LPS)-induced lung inflammation murine model while promoting club cell proliferation in a Yap-dependent manner. Additionally, we show that deleting Mst1/2 is sufficient to suppress p53 deficiency-mediated goblet cell metaplasia. Finally, single-cell RNA analysis reveals a downregulation of Yap and p53 signaling in goblet cells in the human airways. These findings underscore the important role of Hippo and p53 signaling in regulating airway mucous metaplasia.

Single-cell transcriptome analysis reveals atypical monocytes circulating ahead of acute graft-versus-host disease clinical onset.

Acute graft-versus-host disease (aGVHD) represents the rejection of the recipient's skin, gut, and liver tissues of an allogeneic hematopoietic stem cell transplantation (HSCT) by the donor T-cells. The onset of aGVHD is often rapid and its evolution is unpredictable. We undertook the single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) collected before aGVHD clinical onset in three patients and from one patient afterward. We used four HSCT recipients who remained free of aGVHD as controls. This analysis unveiled the presence of particular subpopulations of circulating monocytes and cytotoxic T cells (CTLs) in pre-aGVHD samples up to 18 days before clinical disease. These pre-aGVHD monocytes were characterized by an upregulation of the M2 polarity marker CD163 and the transmembrane protein SIGLEC1/CD169. At the same time, their CTL counterparts stood out for the upregulation of the CXCL10 receptor CXCR3 and the antigenic stimulation marker CD70. The occurrence of CD163/SIGLEC1 co-expressing monocytes upstream of aGVHD onset was validated using transcriptomic data from an independent cohort and by flow cytometry in additional blood samples. These findings point to potential early diagnostic tools and preventive therapeutic strategies for aGVHD.

Single-cell multi-modal integrative analyses highlight functional dynamic gene regulatory networks directing human cardiac development

Illuminating the precise stepwise genetic programs directing cardiac development provides insights into the mechanisms of congenital heart disease and strategies for cardiac regenerative therapies. Here, we integrate invitro and invivo human single-cell multi-omic studies with high-throughput functional genomic screening to reveal dynamic, cardiac-specific gene regulatory networks (GRNs) and transcriptional regulators during human cardiomyocyte development. Interrogating developmental trajectories reconstructed from single-cell data unexpectedly reveal divergent cardiomyocyte lineages with distinct gene programs based on developmental signaling pathways. High-throughput functional genomic screens identify key transcription factors from inferred GRNs that are functionally relevant for cardiomyocyte lineages derived from each pathway. Notably, we discover a critical heat shock transcription factor 1 (HSF1)-mediated cardiometabolic GRN controlling cardiac mitochondrial/metabolic function and cell survival, also observed in fetal human cardiomyocytes. Overall, these multi-modal genomic studies enable the systematic discovery and validation of coordinated GRNs and transcriptional regulators controlling the development of distinct human cardiomyocyte populations.

Mouse Corneal Immune Cell Heterogeneity Revealed by Single-Cell RNA Sequencing.

This study aimed to define the heterogeneity, spatial localization, and functional roles of immune cells in the mouse cornea using single-cell RNA sequencing (scRNA-seq) and immunofluorescent staining. Enriched mouse corneal immune cells (C57BL/6 strain, age 16-20 weeks) underwent single-cell RNA sequencing library preparation, sequencing, and analysis with Seurat, Monocle 3, and CellChat packages in R. Pathway analysis used Qiagen Ingenuity Pathway Analysis software. Immunostaining confirmed cell distribution. We identified 14 distinct immune cell clusters (56% myeloid and 44% lymphoid). Myeloid populations included resident macrophages, conventional dendritic cells (cDC2s), Langerhans cells, neutrophils, monocytes, and mast cells. Additionally, lymphocyte subsets (B, CD8, CD4, γδT, natural killer, natural killer T, and group 2 innate lymphoid cells) were found. We also found three new subtypes of resident macrophages in the cornea. Trajectory analysis suggested a differentiation pathway from monocytes to conventional dendritic cells, resident macrophages, and LCs. Intercellular communication network analysis using cord diagram identified amyloid precursor protein, chemokine (C-C motif) ligands (2, 3, 4, 6, 7, 9, and 12), Cxcl2, Mif, Tnf, Tgfb1, Igf1, and Il10 as prominent ligands involved in these interactions. Sexually dimorphic gene expression patterns were observed, with male myeloid cells expressing genes linked to immune regulation (Egr1, Foxp1, Mrc1, and Il1rn) and females showing higher expression of antigen presentation genes (Clic1, Psmb8, and Psmb9). Finally, immunostaining confirmed the spatial distribution of these cell populations within the cornea. This study unveils a diverse immune landscape in the mouse cornea, with evidence for cell differentiation and sex-based differences. Immunostaining validates the spatial distribution of these populations, furthering our knowledge of corneal immune function.

Single-cell RNA-seq analysis revealed the stemness of a specific cluster of B cells in acute lymphoblastic leukemia progression.

Childhood acute lymphoblastic leukemia (ALL) is a common pediatric cancer. The heterogeneous characterization of B cells in ALL progression poses new challenges to researchers. We used single-cell sequencing to explore the critical role of B cells in regulating the ALL immune microenvironment. We collected the single cell (sc) RNA-seq data of ALL and health sample from the gene expression omnibus (GEO) database, the "Seurat" and "harmony" R package was used for quality control and scRNA-seq analysis, in which the CellMarker2.0 database was used for cell type annotation. Subsequently, the FindAllMarkers function was used to identify the differentially expressed genes (DEGs) among various cell types and the DAVID database was applied for the biological process of DEGs. Then, the "inferCNV" package was used for copy number variation, regulons and cell communication were performed by SCENIC tool and CellChat package. The role of the target gene in regulating ALL progression was assessed using RT-qPCR, Transwell and scratch healing assays. We identified nine mainly cell clusters after scRNA-seq analysis, in which the B cells had higher infiltration proportion in the ALL samples and were sub-clustered into five cell sub-groups. The B cells 1 is closely associated with cell proliferation and stemness (TNFAIP3 and KDM5B), and the significant CNV of amplification occurred on chr6 and chr21 that supported stemness of B cells1. RXRB is a key transcription factor mediated the proliferation of B cells 1, which in turn suppressed hematopoietic stem cells (HSCs) proliferation and promoted cytotoxic NK/T cells activation through diverse cell communication ways. One of the key regulators of B cells is MYC, which promotes the migration and invasive ability of cell line leukemia cell lines. This study reveals the stemness characteristics of B cells and their critical role in ALL progression, a finding that provides new potential directions for the development of targeted therapies against ALL.

Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis and machine learning.

Metabolic dysfunction-associated steatohepatitis (MASH) is a highly prevalent liver disease globally, with a significant risk of progressing to cirrhosis and even liver cancer. Efferocytosis, a process implicated in a broad spectrum of chronic inflammatory disorders, has been reported to be associated with the pathogenesis of MASH; however, its precise role remains obscure. Thus, we aimed to identify and validate efferocytosis linked signatures for detection of MASH. We retrieved gene expression patterns of MASH from the GEO database and then focused on assessing the differential expression of efferocytosis-related genes (EFRGs) between MASH and control groups. This analysis was followed by a series of in-depth investigations, including protein-protein interaction (PPI), correlation analysis, and functional enrichment analysis, to uncover the molecular interactions and pathways at play. To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. Additionally, we conducted immune infiltration and single-cell transcriptome analyses in both MASH and control samples, providing insights into the immune cell landscape and cellular heterogeneity in these conditions. This research pinpointed 39 genes exhibiting a robust correlation with efferocytosis in MASH. Among these, five potential diagnostic biomarkers-TREM2, TIMD4, STAB1, C1QC, and DYNLT1-were screened using two distinct machine learning models. Subsequent external validation and animal experimentation validated the upregulation of TREM2 and downregulation of TIMD4 in MASH samples. Notably, both TREM2 and TIMD4 demonstrated area under the curve (AUC) values exceeding 0.9, underscoring their significant potential in facilitating the diagnosis of MASH. Our study comprehensively elucidated the relationship between MASH and efferocytosis, constructing a favorable diagnostic model. Furthermore, we identified potential therapeutic targets for MASH treatment and offered novel insights into unraveling the underlying mechanisms of this disease.

Long-Term Stable and Multifeature Microfluidic Impedance Flow Cytometry Based on a Constricted Channel for Single-Cell Mechanical Phenotyping.

The microfluidic impedance flow cytometer (m-IFC) using constricted microchannels is an appealing choice for the high-throughput measurement of single-cell mechanical properties. However, channels smaller than the cells are susceptible to irreversible blockage, extremely affecting the stability of the system and the throughput. Meanwhile, the common practice of extracting a single quantitative index, i.e., total cell passage time, through the constricted part is inadequate to decipher the complex mechanical properties of individual cells. Herein, this study presents a long-term stable and multifeature m-IFC based on a constricted channel for single-cell mechanical phenotyping. The blockage problem is effectively overcome by adding tiny xanthan gum (XG) polymers. The cells can pass through the constricted channel at a flow rate of 500 μL/h without clogging, exhibiting high throughput (∼240 samples per second) and long-term stability (∼2 h). Moreover, six detection regions were implemented to capture the multiple features related to the whole process of a single cell passing through the long-constricted channel, e.g., creep, friction, and relaxation stages. To verify the performance of the multifeature m-IFC, cells treated with perturbations of microtubules and microfilaments within the cytoskeleton were detected, respectively. It suggests that the extracted features provide more comprehensive clues for single-cell analysis in structural and mechanical transformation. Overall, our proposed multifeature m-IFC exhibits the advantages of nonclogging and high throughput, which can be extended to other cell types for nondestructive and real-time mechanical phenotyping in cost-effective applications.

Multiple Machine Learning Models, Molecular Subtyping and Singlecell Analysis Identify PANoptosis-related Core Genes and their Association with Subtypes in Crohn's Disease.

PANoptosis plays an important role in many inflammatory diseases. However, there are no reports on the association between PANoptosis and CD. This study used five machine learning algorithms - least absolute shrinkage and selection operator, support vector machine, random forest, decision tree and Gaussian mixture models - to construct CD's PANoptosis signature. Unsupervised hierarchical clustering analysis was used to identify PANoptosis-associated subgroups of CD. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were conducted to compare the PANoptosis-associated subgroups of CD among the potential biological mechanisms. Single sample GSEA was used to assess immune microenvironmental differences among the subgroups. The potential role of PANoptosis in CD was further explored using single-cell RNA-Seq (scRNA-Seq) for PANoptosis scoring, differential analysis, pseudotime analysis, cellular communication analysis and weighted gene co-expression network analysis (WGCNA) analysis. CD's PANoptosis signature consisted of seven genes: CEACAM6, CHP2, PIK3R1, CASP10, PSMB1, PSMB8 and UBC. The PANoptosis signature in multiple cohorts had a strong ability to recognise CD. The levels of immune cell infiltration and the vigour of the immune responses significantly varied between the two subpopulations of CD associated with PANoptosis. Multiple lines of evidence from the GO, KEGG, GSEA, GSVA, scRNA-Seq and WGCNA analyses suggested that I-kappaB kinase/NF- kappaB signalling, mitogen-activated protein kinase (MAPK), leukocyte activation and leukocyte migration were mechanisms closely associated with PANoptosis in CD. This study is the first to construct a PANoptosis signature with excellent efficacy in recognising CD. PANoptosis may mediate the process of CD through inflammatory and immune mechanisms, such as NF- kappaB, MAPK and leukocyte migration.

Arterial-Lymphatic-Like Endothelial Cells Appear in Hereditary Hemorrhagic Telangiectasia 2 and Contribute to Vascular Leakage and Arteriovenous Malformations.

Arteriovenous malformations (AVMs) are characteristic of hereditary hemorrhagic telangiectasia. Loss-of-function mutations in the activin receptor-like kinase 1 (Alk1) are linked to hemorrhagic telangiectasia type 2. Endothelial-specific deletion of Alk1, endothelial lineage tracing, transcriptomics of single-cell analysis, and electron microscopy were performed to examine the vascular phenotype and characteristics of ALK1-deficient endothelial cells (ECs) after EC-specific Alk1 deletion. Ischemia assays were used to examine the cell capacity for vascular malformation. Connectivity Map with transcriptomic analysis was applied to identify chemical compounds. Specific methods for arteriovenous malformations, such as micro-computed tomography, with other molecular and cell biological tools were also performed. We performed endothelial-specific deletion of Alk1 in mice and found severe arteriovenous malformations and vascular leakage. The transcriptomics of single-cell analysis revealed a new distinctive cell cluster formed after Alk1 deletion where the cells coexpressed arterial and lymphatic endothelial markers. The analysis projected that these cells potentially originated from arterial ECs after Alk1 deletion. This new population was referred to as arterial-lymphatic-like ECs according to its cellular markers, and its appearance was validated in the pulmonary small arteries after Alk1 deletion. Transplantation of these cells caused vascular malformations. Endothelial lineage tracing confirmed that these new arterial-lymphatic-like ECs were derived from ALK1 depleted ECs, potentially arterial ECs. We discovered that SOX17 (SRY-box transcription factor 17) induction was responsible for the derivation of these arterial-lymphatic-like ECs. We showed that direct binding of MDM2 (mouse double minute 2) was required for Sox17 to execute this activity. Inhibition of MDM2 reduced the arteriovenous malformations in the mouse model. Together, our studies revealed the mechanistic underpinnings of ALK1 signaling in regulating the endothelial phenotype and provided possibilities for new therapeutic strategies in hemorrhagic telangiectasia type 2.

Deletions Rate-Limit Breast and Ovarian Cancer Initiation.

Optimizing prevention and early detection of cancer requires understanding the number, types and timing of driver mutations. To quantify this, we exploited the elevated cancer incidence and mutation rates in germline BRCA1 and BRCA2 (gBRCA1/2) carriers. Using novel statistical models, we identify genomic deletions as the likely rate-limiting mutational processes, with 1-3 deletions required to initiate breast and ovarian tumors. gBRCA1/2 -driven hereditary and sporadic tumors undergo convergent evolution to develop a similar set of driver deletions, and deletions explain the elevated cancer risk of gBRCA1/2 -carriers. Orthogonal mutation timing analysis identifies deletions of chromosome 17 and 13q as early, recurrent events. Single-cell analyses confirmed deletion rate differences in gBRCA1/2 vs. non-carrier tumors as well as cells engineered to harbor gBRCA1/2 . The centrality of deletion-associated chromosomal instability to tumorigenesis shapes interpretation of the somatic evolution of non-malignant tissue and guides strategies for precision prevention and early detection.

Single Cell VDJ Sequencing of Normal and Malignant B and T Cells.

Recent developments in single cell sequencing technologies enable researchers to examine heterogeneity of cell types and subclusters even deeper. First assays were only available for transcriptome analysis of up to 10,000 cells, but nowadays up to 60,000 cells or even more can be analyzed. Whereas initially only analysis of mRNA expression was possible, currently single cell methods multiplied, with extension of assays for examination of surface molecule expression, DNA accessibility (ATAC-seq), antigen specificity, and B or T cell receptor repertoires. Also, spatial transcriptomics or CRISPR screenings, augmenting classical CRISPR/Cas9 screens by combining them with transcriptomic data at single cell level, can be evaluated. The composition of B and T cell clones-of malignant cells in lymphomas and leukemia, as well as of infiltrating B or T cell clones in other types of cancer-is especially important in tumor research, as these clones may give valuable hints for tumor development and control. This chapter presents detailed methods for implementation and analysis of single cell B and/or T cell receptor repertoire sequencing on the Chromium system from 10× Genomics and the Rhapsody™ system from BD Bioscience.

Soybean isoflavones protect dopaminergic neurons from atrazine damage by inhibiting VPS13A to increase autophagy

Atrazine (ATR) is a broad-spectrum herbicide with dopaminergic (DAergic) neurotoxicity that can cause Parkinson’s disease (PD)-like syndrome. However, research on preventing ATR neurotoxicity is unclear. Soybean isoflavones (SI) are natural plant compounds with neuroprotective effects. In this study, we found that pre-administration of SI prevented ATR-induced motor dysfunction and substantia nigra pathological damage. RNA-seq datasets revealed that the neuroprotective effect of SI was related to autophagy. Further experiments showed that ATR inhibited autophagy, and SI pre-administration before ATR exposure increased autophagy. In addition, single-cell data analysis combined with experimental verification showed that the gene VPS13A was a key target by which SI protected DAergic neurons from ATR damage, and inhibiting VPS13A-induced autophagy was a key mechanism enabling SI prevention of neuron damage. Together, these findings provide new insights for the development of preventive measures and intervention targets protecting against functional neuronal damage caused by ATR and other herbicides.

Circulating RAC1 contributed to steroid-sensitive nephrotic syndrome: Mendelian randomization, single-cell RNA-sequencing, proteomic, and experimental evidence

Objectives The small GTPase Rac1 (RAC1) has been linked to podocyte disorders and steroid-sensitive nephrotic syndrome (SSNS). The aim of this study was to explore and validate the potential causal association between circulating RAC1 and SSNS. Methods The association between circulating RAC1 and SSNS at both gene expression and proteomic levels was investigated using Mendelian randomization analysis, and further validated by single-cell RNA-sequencing, proteomic analysis, and experimental studies. The genetic instruments comprised cis-expression quantitative trait loci (cis-eQTLs) associated with RAC1 gene expression and protein QTLs correlated with plasma RAC1 protein levels. Causal associations were estimated utilizing the inverse variance weighted and MR-PRESSO methods. Validation of RAC1 expression was conducted through single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with SSNS and healthy controls. Proteomic analysis was performed among patients with minimal change nephrotic syndrome. Experimental validation was conducted using a puromycin aminonucleoside (PAN)-induced nephrosis model. Results Increased expression of RAC1 was associated with a higher risk of SSNS (gene expression level: odds ratio [OR], 1.53; 95% confidence interval [CI], 1.02–2.28; protein level: OR, 1.82; 95% CI, 1.05–3.17). The results of MR-PRESSO were consistent (gene expression level: OR, 1.49; 95% CI, 1.17–1.92; protein level: OR, 1.81; 95% CI, 1.16–2.85). Single-cell RNA sequencing and proteomic analysis confirmed elevated RAC1 expression in patients with SSNS compared to healthy controls. Experimental data further supported increased RAC1 expression in PAN-induced nephropathy. Conclusions Increased expression of RAC1 might be causally associated with SSNS, suggesting that targeting RAC1 might represent a potential therapeutic strategy for SSNS.

Integrative analysis of single-cell and bulk multi-omics data to reveal subtype-specific characteristics and therapeutic strategies in clear cell renal cell carcinoma patients.

Background: Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of malignant renal cell carcinoma and is well known as a common genitourinary cancer. Stratifying tumors based on heterogeneity is essential for better treatment options. Methods: In this study, consensus clusters were constructed based on gene expression, DNA methylation, and gene mutation data, which were combined with multiple clustering algorithms. After identifying two heterogeneous subtypes, we analyzed the molecular characteristics, immunotherapy response, and drug sensitivity differences of each subtype. And we further integrated bulk data and single-cell RNA sequencing (scRNA-Seq) data to infer the immune cell composition and malignant tumor cell proportion of subtype-related cell subpopulations. Results: Among the two identified consensus subtypes (CS1 and CS2), CS1 was enriched in more inflammation-related and oncogenic pathways than CS2. Simultaneously, CS1 showed a worse prognosis and we found more copy number variations and BAP1 mutations in CS1. Although CS1 had a high immune infiltration score, it exhibited high expression of suppressive immune features. Based on the prediction of immunotherapy and drug sensitivity, we inferred that CS1 may respond poorly to immunotherapy and be less sensitive to targeted drugs. The analysis of bulk data integrated with single-cell data further reflected the high expression of inhibitory immune features in CS1 and the high proportion of malignant tumor cells. And CS2 contained a large number of plasmacytoid B cells, presenting an activated immune microenvironment. Finally, the robustness of our subtypes was successfully validated in four external datasets. Conclusion: In summary, we conducted a comprehensive analysis of multi-omics data with 10 clustering algorithms to reveal the molecular characteristics of KIRC patients and validated the relevant conclusions by single-cell analysis and external data. Our findings discovered new KIRC subtypes and may further guide personalized and precision treatments.

Mechanism of bacterial predation via ixotrophy.

Ixotrophy is a contact-dependent predatory strategy of filamentous bacteria in aquatic environments for which the molecular mechanism remains unknown. We show that predator-prey contact can be established by gliding motility or extracellular assemblages we call "grappling hooks." Cryo-electron microscopy identified the grappling hooks as heptamers of a type IX secretion system substrate. After close predator-prey contact is established, cryo-electron tomography and functional assays showed that puncturing by a type VI secretion system mediated killing. Single-cell analyses with stable isotope-labeled prey revealed that prey components are taken up by the attacker. Depending on nutrient availability, insertion sequence elements toggle the activity of ixotrophy. A marine metagenomic time series shows coupled dynamics of ixotrophic bacteria and prey. We found that the mechanism of ixotrophy involves multiple cellular machineries, is conserved, and may shape microbial populations in the environment.

Exploiting β-Lactams-Induced Lysis and DNA Fragmentation for Rapid Molecular Antimicrobial Susceptibility Testing of Neisseria Gonorrhoeae via Dual-Digital PCR.

The evolution of antimicrobial resistance (AMR) presents substantial challenges to global medical health systems. Neisseria gonorrhoeae (N. gonorrhoeae), in particular, has developed resistance to all currently available antimicrobials. Addressing this issue necessitates not only discovering new antimicrobials but also deepening the understanding of bacterial responses to these agents, which can lead to new markers for rapid antimicrobial susceptibility testing (AST). Such advancements can enhance treatment outcomes and promote antimicrobial stewardship. In this study, single-cell techniques, including live-cell imaging, flow cytometry, and digital polymerase chain reaction (PCR) are utilized, to investigate the lysis dynamics and molecular features of N. gonorrhoeae upon exposure to β-lactam antimicrobials. Distinct patterns of bacterial lysis and DNA fragmentation are uncovered in susceptible strains. Leveraging these discoveries, A microfluidic dual-digital PCR approach that combines single-cell and single-molecule analyses, facilitating rapid and efficient phenotypic molecular AST for N. gonorrhoeae against β-lactams is developed. This proof-of-concept validation demonstrates the effectiveness of the method in accessing antimicrobial susceptibility across a range of bacterial strains, contributing valuable insights for advancing the battle against AMR.

Abstract A052: RNF43 p.G659fs mutation in MSI-high colorectal cancer leads to natural killer cell dysfunction

Abstract RNF43_p.G659fsV*41 mutation (RNF43659mut) is found in approximately 8% of colorectal cancers (CRCs) and is enriched in microsatellite-instability high (MSI-high) tumors. Previously, we reported that RNF43659mut promotes tumor growth independent of WNT signaling and activates PI3K/AKT signaling in CRC, conferring vulnerability to PI3K/MTOR inhibition. In addition, RNF43659mut was associated with decreased interferon signaling suggesting a link with anti-tumor immunity. Thus, in the current work we investigated the role of RNF43659mut in CRC immunomodulation. The immune-cell landscape was evaluated in RNF43659mut compared with RNF43-wild type (wt) MSI-high CRCs in two cohorts; single-cell (sc)-RNA-sequencing data from treatment-naïve primary tumors from 34 patients (cohort-1) and multiplex immunofluorescence / whole exome sequencing data from an independent cohort of 91 patients (cohort-2). Healthy donor blood-derived natural killer (NK) cell responses and cytotoxicity were investigated in co-cultures with RNF43659mut isogenic tumor lines and with patient-derived organoids harboring RNF43659mut or overexpressing RNF43wt. A third patient cohort with MSI-high CRCs treated with immune checkpoint blockade was analyzed to understand the impact of RNF43659mut on immunotherapy efficacy. Interrogation of sc-RNASeq data in cohort-1 revealed a significant enrichment of NK cells in the RNF43659mut patient samples compared to the RNF43wt ones. This finding was also confirmed by multiplex immunofluorescence in cohort-2. Single-cell transcriptomic analyses in cohort-1 showed increased inhibitory markers on NK cells despite their enrichment in RNF43659mut tumors. RNAseq analysis of sorted NK cells co-cultured with RNF43659mut isogenic tumor lines further supported their dysfunctional state. Flow cytometric analyses of NK cell maturation, activation, and inhibitory markers in NK cells co-cultured with RNF43659mut isogenic tumor lines and organoids highlighted decreased levels of NCAM1 (CD56)dim and NCAM1 (CD56)bright subsets, FCGR3A (CD16), and KLRK1 (NKG2D), along with increased levels of KLRC1 (NKG2A), KIR3DL1 (NKB1) and TIGIT inhibitory markers. There was reduced NK cell mediated tumor cell killing in RNF43659mut isogenic tumor lines and organoids. We postulated that aberrant signaling of the PI3K/AKT pathway with RNF43659mut could lead to NK cell dysfunction. Indeed, siRNA-mediated blocking of PI3K/AKT pathway restored the NK-cell dysfunctional phenotype and tumor cell killing in co-cultures with RNF43659mut isogenic tumor lines and organoids. Conversely, overexpression of WT RNF43 in RNF43659mut organoids downregulated PI3K/AKT signaling and increased NK cell cytotoxicity. Lastly, MSI-high CRC tumors harboring RNF43659mut in patients treated with immunotherapy showed less benefit from immune checkpoint blockade. PI3K/AKT activation due to RNF43659mut in MSI-high CRC leads to NK cell dysfunction and reduced NK cell cytotoxicity. This could be responsible for immunotherapy failure, warranting further investigation. Citation Format: Pushpamali De Silva, Samantha Fitzgerald, Jules Cazaubiel, Matan Hofree, Tomotaka Ugai, Juha P Väyrynen, Dane Ford-Roshon, Lishan Fang, Ana Garrido-Castro, Nir Hacohen, Kimmie Ng, Shuji Ogino, Jonathan A Nowak, Marios Giannakis. RNF43 p.G659fs mutation in MSI-high colorectal cancer leads to natural killer cell dysfunction [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr A052.