Integrative single-cell analysis of longitudinal t(8;21) AML reveals heterogeneous immune cell infiltration and prognostic signatures.

Introduction: Immunotherapies targeting T cells in solid cancers are revolutionizing clinical treatment. Novel immunotherapies have had extremely limited benefit for acute myeloid leukemia (AML). Here, we characterized the immune microenvironment of t(8;21) AML patients to determine how immune cell infiltration status influenced prognosis. Methods: Through multi-omics studies of primary and longitudinal t(8;21) AML samples, we characterized the heterogeneous immune cell infiltration in the tumor microenvironment and their immune checkpoint gene expression. Further external cohorts were also included in this research. Results: CD8+ T cells were enriched and HAVCR2 and TIGIT were upregulated in the CD34+CD117dim%-High group; these features are known to be associated with immune exhaustion. Data integration analysis of single-cell dynamics revealed that a subset of T cells (cluster_2) (highly expressing GZMB, NKG7, PRF1 and GNLY) evolved and expanded markedly in the drug-resistant stage after relapse. External cohort analysis confirmed that the cluster_2 T-cell signature could be utilized to stratify patients by overall survival outcome. Discussion: In conclusion, we discovered a distinct T-cell signature by scRNA-seq that was correlated with disease progression and drug resistance. Our research provides a novel system for classifying patients based on their immune microenvironment.

Protocol for the application of single-cell damage in murine intestinal organoid models.

Spatially defined organoid damage enables the study of cellular repair processes. However, capturing dynamic events in living tissues is technically challenging. Here, we present a protocol for the application of single-cell damage in intestinal organoid models. We describe steps for isolating and cultivating murine colon organoids, lentivirus generation and transduction of organoids, single-cell ablation by a femtosecond laser, and follow-up imaging analysis. We provide examples for the image acquisition pipeline of dynamic processes in organoids using a confocal microscope. For complete details on the use and execution of this protocol, please refer to Donath et al.1,2.

Protocol for machine-learning-based 3D image analysis of nuclear envelope tubules in cultured cells.

The nuclear envelope can form complex structures in physiological and pathological contexts. Current approaches to quantify nuclear envelope structures can be time-consuming or inaccurate. Here, we present a protocol to measure nuclear envelope tubules induced by DNA double-strand breaks using a mid-throughput approach. We describe steps for the induction of these nuclear envelope structures and 3D image analysis using machine-learning-based image segmentation. This protocol can be applied to analyze various nuclear envelope structures in contexts beyond DNA repair. For complete details on the use and execution of this protocol, please refer to Shokrollahi et al.1.

Isolation, expansion, and adoptive transfer of human ILC2s for the treatment of mice bearing liquid and solid tumors.

Type 2 innate lymphoid cells (ILC2s) are crucial in regulating immune responses and various physiological processes, including tissue repair, metabolic homeostasis, inflammation, and cancer surveillance. Here, we present a protocol that outlines the isolation, expansion, and adoptive transfer of human ILC2s from peripheral blood mononuclear cells for an in vivo lineage tracking experiment in a mouse model. Additionally, we detail the steps involved in the adoptive transfer of human ILC2s to recipient mice bearing human liquid or solid tumors. For complete details on the use and execution of this protocol, please refer to Li et al.1.

Data acquisition approaches for single cell proteomics.

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.

The octapeptide-repeat surface protein of Entamoeba nuttalli is a novel virulence factor that promotes adherence to host cells.

Entamoeba nuttalli is genetically the closest to Entamoeba histolytica, the causative agent of human amebiasis, and its natural host is Macaca species. A unique E. nuttalli specific surface protein (PTORS) containing 42 repeats of octapeptide was identified by comparative genomic analysis of Entamoeba species. We aimed to elucidate the function of this protein. When trophozoites from various E. nuttalli strains were examined by immunofluorescence microscopy and flow cytometry using a PTORS-specific monoclonal antibody, only a limited proportion of trophozoites were stained, indicating that the protein was not commonly expressed in all E. nuttalli trophozoite. The proportion of trophozoites expressing PTORS increased after passage in hamster livers, suggesting that the protein functions in the virulence of trophozoites in the liver tissue. Single-cell analysis revealed that in the cluster including trophozoites with PTORS gene expression, genes of virulence-related proteins were also upregulated. Trophozoites of E. histolytica transfected with PTORS showed enhanced adherence and subsequent phagocytic activity towards human Jurkat cells, independent of the lectin. E. histolytica trophozoites expressing PTORS formed larger liver abscesses in hamsters. These results demonstrate that PTORS is a novel virulence factor in Entamoeba species.

Identifying potential therapeutic targets in lung adenocarcinoma: a multi-omics approach integrating bulk and single-cell RNA sequencing with Mendelian randomization.

Our research aimed to identify new therapeutic targets for Lung adenocarcinoma (LUAD), a major subtype of non-small cell lung cancer known for its low 5-year survival rate of 22%. By employing a comprehensive methodological approach, we analyzed bulk RNA sequencing data from 513 LUAD and 59 non-tumorous tissues, identifying 2,688 differentially expressed genes. Using Mendelian randomization (MR), we identified 74 genes with strong evidence for a causal effect on risk of LUAD. Survival analysis on these genes revealed significant differences in survival rates for 13 of them. Our pathway enrichment analysis highlighted their roles in immune response and cell communication, deepening our understanding. We also utilized single-cell RNA sequencing (scRNA-seq) to uncover cell type-specific gene expression patterns within LUAD, emphasizing the tumor microenvironment's heterogeneity. Pseudotime analysis further assisted in assessing the heterogeneity of tumor cell populations. Additionally, protein-protein interaction (PPI) network analysis was conducted to evaluate the potential druggability of these identified genes. The culmination of our efforts led to the identification of five genes (tier 1) with the most compelling evidence, including SECISBP2L, PRCD, SMAD9, C2orf91, and HSD17B13, and eight genes (tier 2) with convincing evidence for their potential as therapeutic targets.

The role of metabolic memory in diabetic kidney disease: identification of key genes and therapeutic targets.

Diabetic kidney disease (DKD) is characterized by complex pathogenesis and poor prognosis; therefore, an exploration of novel etiological factors may be beneficial. Despite glycemic control, the persistence of transient hyperglycemia still induces vascular complications due to metabolic memory. However, its contribution to DKD remains unclear. Using single-cell RNA sequencing data from the Gene Expression Omnibus (GEO) database, we clustered 12 cell types and employed enrichment analysis and a cell‒cell communication network. Fibrosis, a characteristic of DKD, was found to be associated with metabolic memory. To further identify genes related to metabolic memory and fibrosis in DKD, we combined the above datasets from humans with a rat renal fibrosis model and mouse models of metabolic memory. After overlapping, NDRG1, NR4A1, KCNC4 and ZFP36 were selected. Pharmacology analysis and molecular docking revealed that pioglitazone and resveratrol were possible agents affecting these hub genes. Based on the ex vivo results, NDRG1 was selected for further study. Knockdown of NDRG1 reduced TGF-ß expression in human kidney-2 cells (HK-2 cells). Compared to that in patients who had diabetes for more than 10 years but not DKD, NDRG1 expression in blood samples was upregulated in DKD patients. In summary, NDRG1 is a key gene involved in regulating fibrosis in DKD from a metabolic memory perspective. Bioinformatics analysis combined with experimental validation provided reliable evidence for identifying metabolic memory in DKD patients.

Nitrate recovery from groundwater and simultaneous upcycling into single-cell protein using a novel hybrid biological-inorganic system.

Nitrate pollution in groundwater is a serious problem worldwide, as its concentration in many areas exceeds the WHO-defined drinking water standard (50 mg/L). Hydrogen-oxidizing bacteria (HOB) are a group of microorganisms capable of producing single-cell protein (SCP) using hydrogen and oxygen. Furthermore, HOB can utilize various nitrogen sources, including nitrate. This study developed a novel hybrid biological-inorganic (HBI) system that coupled a new submersible water electrolysis system driven by renewable electricity with HOB fermentation for in-situ nitrate recovery from polluted groundwater and simultaneously upcycling it together with CO2 into single-cell protein. The performance of the novel HBI system was first evaluated in terms of bacterial growth and nitrate removal efficiency. With 5 V voltage applied and the initial nitrate concentration of 100 mg/L, the nitrate removal efficiency of 85.52 % and raw of 47.71 % (with a broad amino acid spectrum) were obtained. Besides, the HBI system was affected by the applied voltages and initial nitrogen concentrations. The water electrolysis with 3 and 4 V cannot provide sufficient H2 for HOB and the removal of nitrate was 57.12 % and 59.22 % at 180 h, while it reached 65.14 % and 65.42 % at 5 and 6 V, respectively. The nitrate removal efficiency reached 58.40 % and 50.72 % within 180 h with 200 and 300 mg/L initial nitrate concentrations, respectively. Moreover, a larger anion exchange membrane area promoted nitrate removal. The monitored of the determination of different forms of nitrogen indicated that around 60 % of the recovered nitrate was assimilated into cells, and 40 % was bio-converted to N2. The results demonstrate a potentially sustainable method for remediating nitrate contaminant in groundwater, upcycling waste nitrogen, CO2 sequestration and valorization of renewable electricity into food or feed.

Concepts and new developments in droplet-based single cell multi-omics.

Single cell sequencing technologies have become a fixture in the molecular profiling of cells due to their ease, flexibility, and commercial availability. In particular, partitioning individual cells inside oil droplets via microfluidic reactions enables transcriptomic or multi-omic measurements for thousands of cells in parallel. Complementing the multitude of biological discoveries from genomics analyses, the past decade has brought new capabilities from assay baselines to enable a deeper understanding of the complex data from single cell multi-omics. Here, we highlight four innovations that have improved the reliability and understanding of droplet microfluidic assays. We emphasize new developments that further orient principles of technology development and guidelines for the design, benchmarking, and implementation of new droplet-based methodologies.

Advances in single-cell transcriptomics in animal research.

Understanding biological mechanisms is fundamental for improving animal production and health to meet the growing demand for high-quality protein. As an emerging biotechnology, single-cell transcriptomics has been gradually applied in diverse aspects of animal research, offering an effective method to study the gene expression of high-throughput single cells of different tissues/organs in animals. In an unprecedented manner, researchers have identified cell types/subtypes and their marker genes, inferred cellular fate trajectories, and revealed cell‒cell interactions in animals using single-cell transcriptomics. In this paper, we introduce the development of single-cell technology and review the processes, advancements, and applications of single-cell transcriptomics in animal research. We summarize recent efforts using single-cell transcriptomics to obtain a more profound understanding of animal nutrition and health, reproductive performance, genetics, and disease models in different livestock species. Moreover, the practical experience accumulated based on a large number of cases is highlighted to provide a reference for determining key factors (e.g., sample size, cell clustering, and cell type annotation) in single-cell transcriptomics analysis. We also discuss the limitations and outlook of single-cell transcriptomics in the current stage. This paper describes the comprehensive progress of single-cell transcriptomics in animal research, offering novel insights and sustainable advancements in agricultural productivity and animal health.

Establishment of a CD8+ T cells-related prognostic risk model for acral melanoma based on single-cell and bulk RNA sequencing.

BACKGROUND: CD8+ T cells have been recognized as crucial factors in the prognosis of melanoma. However, there is currently a lack of gene markers that accurately describe their characteristics and functions in acral melanoma (AM), which hinders the development of personalized medicine. METHODS: Firstly, we explored the composition differences of immune cells in AM using single-cell RNA sequencing (scRNA-seq) data and comprehensively characterized the immune microenvironment of AM in terms of composition, developmental differentiation, function, and cell communication. Subsequently, we constructed and validated a prognostic risk scoring model based on differentially expressed genes (DEGs) of CD8+ T cells using the TCGA-SKCM cohort through Lasso-Cox method. Lastly, immunofluorescence staining was performed to validate the expression of four genes (ISG20, CCL4, LPAR6, DDIT3) in AM and healthy skin tissues as included in the prognostic model. RESULTS: The scRNA-seq data revealed that memory CD8+ T cells accounted for the highest proportion in the immune microenvironment of AM, reaching 70.5%. Cell-cell communication analysis showed extensive communication relationships among effector CD8+ T cells. Subsequently, we constructed a prognostic scoring model based on DEGs derived from CD8+ T cell sources. Four CD8+ T cell-related genes were included in the construction and validation of the prognostic model. Additionally, immunofluorescence results demonstrated that ISG20 and CCL4 were downregulated, while LPAR6 and DDIT3 were upregulated in AM tissues compared to normal skin tissues. CONCLUSION: Identifying biomarkers based on the expression levels of CD8+ T cell-related genes may be an effective approach for establishing prognostic models in AM patients. The independently prognostic risk evaluation model we constructed provides new insights and theoretical support for immunotherapy in AM.

Protocol to achieve high-resolution single-cell transcriptomics of cardiomyocytes in multiple species.

Single-cell RNA sequencing (scRNA-seq) remains state-of-the-art for transcriptomic cell-mapping. Here, we provide a protocol to generate high-resolution scRNA-seq of rare cardiomyocyte populations (e.g., regenerating/dividing, etc.) from mouse and zebrafish hearts as well as induced pluripotent stem cells, collected in time to achieve detailed transcriptomic insight. We describe the serial steps of viability staining, methanol fixation, storage, and cell sorting to preserve RNA integrity suited for scRNA-seq as well as the quality assessment of the data as shown by examples. For complete details on the use and execution of this protocol, please refer to Bak et al.1.

Aberrant migration features in primary skin fibroblasts of Huntington's disease patients hold potential for unraveling disease progression using an image based machine learning tool.

Huntington's disease (HD) is a complex neurodegenerative disorder with considerable heterogeneity in clinical manifestations. While CAG repeat length is a known predictor of disease severity, this heterogeneity suggests the involvement of additional genetic and environmental factors. Previously we revealed that HD primary fibroblasts exhibit unique features, including distinct nuclear morphology and perturbed actin cap, resembling characteristics seen in Hutchinson-Gilford Progeria Syndrome (HGPS). This study establishes a link between actin cap deficiency and cell motility in HD, which correlates with the HD patient disease severity. Here, we examined single-cell motility imaging features in HD primary fibroblasts to explore in depth the relationship between cell migration patterns and their respective HD patients' clinical severity status (premanifest, mild and severe). The single-cell analysis revealed a decline in overall cell motility in correlation with HD severity, being most prominent in severe HD subgroup and HGPS. Moreover, we identified seven distinct spatial clusters of cell migration in all groups, which their proportion varies within each group becoming a significant HD severity classifier between HD subgroups. Next, we investigated the relationship between Lamin B1 expression, serving as nuclear envelope morphology marker, and cell motility finding that changes in Lamin B1 levels are associated with specific motility patterns within HD subgroups. Based on these data we present an accurate machine learning classifier offering comprehensive exploration of cellular migration patterns and disease severity markers for future accurate drug evaluation opening new opportunities for personalized treatment approaches in this challenging disorder.

Atlas of metastatic gastric cancer links ferroptosis to disease progression and immunotherapy response.

BACKGROUND & AIMS: Metastases from gastric adenocarcinoma (GAC) lead to high morbidity and mortality. Developing innovative and effective therapies requires a comprehensive understanding of the tumor and immune biology of advanced GAC. Yet, collecting matched specimens from advanced, treatment-naïve GAC patients poses a significant challenge, limiting the scope of current research, which has predominantly focused on localized tumors. This gap hinders a deeper insight into the metastatic dynamics of GAC. METHODS: We performed in-depth single-cell transcriptome and immune profiling on 68 paired, treatment-naïve, primary-metastatic tumors to delineate alterations in cancer cells and their tumor microenvironment (TME) during metastatic progression. To validate our observations, we conducted comprehensive functional studies both in vitro and in vivo, employing cell lines, multiple PDX and novel mouse models of GAC. RESULTS: Liver and peritoneal metastases exhibited distinct properties in cancer cells and dynamics of TME phenotypes, supporting the notion that cancer cells and their local TMEs co-evolve at metastatic sites. Our study also revealed differential activation of cancer meta-programs across metastases. We observed evasion of cancer cell ferroptosis via GPX4 upregulation during GAC progression. Conditional depletion of Gpx4 or pharmacological inhibition of ferroptosis resistance significantly attenuated tumor growth and metastatic progression. Additionally, ferroptosis-resensitizing treatments augmented the efficacy of CAR T-cell therapy. CONCLUSIONS: This study represents the largest single-cell dataset of metastatic GACs to date. High-resolution mapping of the molecular and cellular dynamics of GAC metastasis has revealed a rationale for targeting ferroptosis defense in combination with CAR T-cell therapy as a novel therapeutic strategy with potential immense clinical implications.

Highlighting immune features of the tumor ecosystem and prognostic value of Tfh and Th17 cell infiltration in head and neck squamous cell carcinoma by single-cell RNA-seq.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) typically present with a complex anatomical distribution, often accompanied by insidious symptoms. This combination contributes to its high incidence and poor prognosis. It is now understood that the immune features of cellular components within the tumor ecosystem and their complex interactions are critical factors influencing both tumor progression and the effective immune response. METHODS: We obtained single-cell RNA sequencing data of 26,496 cells from three tumor tissues and five normal tissues and performed subsequent analyses. Immunohistochemical staining on tumor sections was used to validate the presence of malignant cells. Additionally, we included bulk RNA sequencing data from 502 HNSCC patients. Kaplan-Meier analysis and the log-rank test were employed to assess predictors of patient outcomes. RESULTS: We identified three epithelial subclusters exhibiting immune-related features. These subclusters promoted the infiltration of T cells, dendritic cells, and monocytes into the tumor microenvironment. Additionally, cancer-associated fibroblasts displayed tumor-promoting and angiogenesis characteristics, contrasting with the predominant antigen-presenting and inflammatory roles observed in fibroblasts from normal tissues. Furthermore, tumor endothelial subsets exhibited a double-sided effect, promoting tumor progression and enhancing the effectiveness of immune response. Finally, follicular helper T cells and T helper 17 cells were found to be significantly correlated with improved outcomes in HNSCC patients. These CD4+ T cell subpopulations could promote the anti-tumor immune response by recruiting and activating B and T cells. CONCLUSION: Our findings provide deeper insights into the immune features of the tumor ecosystem and reveal the prognostic significance of follicular helper T cells and T helper 17 cells. These findings may pave the way for the development of therapeutic approaches.

Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts.

BACKGROUND: Tumor heterogeneity presents a formidable challenge in understanding the mechanisms driving tumor progression and metastasis. The heterogeneity of hepatocellular carcinoma (HCC) in cellular level is not clear. METHODS: Integration analysis of single-cell RNA sequencing data and spatial transcriptomics data was performed. Multiple methods were applied to investigate the subtype of HCC tumor cells. The functional characteristics, translation factors, clinical implications and microenvironment associations of different subtypes of tumor cells were analyzed. The interaction of subtype and fibroblasts were analyzed. RESULTS: We established a heterogeneity landscape of HCC malignant cells by integrated 52 single-cell RNA sequencing data and 5 spatial transcriptomics data. We identified three subtypes in tumor cells, including ARG1+ metabolism subtype (Metab-subtype), TOP2A+ proliferation phenotype (Prol-phenotype), and S100A6+ pro-metastatic subtype (EMT-subtype). Enrichment analysis found that the three subtypes harbored different features, that is metabolism, proliferating, and epithelial-mesenchymal transition. Trajectory analysis revealed that both Metab-subtype and EMT-subtype originated from the Prol-phenotype. Translation factor analysis found that EMT-subtype showed exclusive activation of SMAD3 and TGF-ß signaling pathway. HCC dominated by EMT-subtype cells harbored an unfavorable prognosis and a deserted microenvironment. We uncovered a positive loop between tumor cells and fibroblasts mediated by SPP1-CD44 and CCN2/TGF-ß-TGFBR1 interaction pairs. Inhibiting CCN2 disrupted the loop, mitigated the transformation to EMT-subtype, and suppressed metastasis. CONCLUSION: By establishing a heterogeneity landscape of malignant cells, we identified a three-subtype classification in HCC. Among them, S100A6+ tumor cells play a crucial role in metastasis. Targeting the feedback loop between tumor cells and fibroblasts is a promising anti-metastatic strategy.

90-day oral toxicity study in rats of a protein-rich powder derived from Xanthobacter sp. SoF1.

Xanthobacter sp. SoF1 (SoF1) is an autotrophic hydrogen-oxidizing bacteria that produces protein-rich biomass and has potential to be an alternative protein source that is more environmentally sustainable than animal and plant derived proteins. A protein-rich powder derived from SoF1 was the test material in a 90-day repeated-dose oral toxicity study to explore major toxic effects, demonstrate target organs, and provide an estimate of a no-observed-adverse-effect level (NOAEL). Daily doses of 0 (vehicle only), 375, 750, and 1500 mg/kg bw/day of the test material were administered by gavage to 10 Han:WIST rats/sex/group. An additional group was administered 1290 mg/kg bw/day whey protein concentrate as positive control. No treatment-related adverse effects were observed, and no target organs were determined after 90/91 days of consecutive administration of the test item. A NOAEL of 1500 mg/kg bw/day was determined.

Single-cell investigation of lead toxicity from neurodevelopment to neurodegeneration: Current review and future opportunities.

Human exposure to the metal lead (Pb) is prevalent and associated with adverse neurodevelopmental and neurodegenerative outcomes. Pb disrupts normal brain function by inducing oxidative stress and neuroinflammation, altering cellular metabolism, and displacing essential metals. Prior studies on the molecular impacts of Pb have examined bulk tissues, which collapse information across all cell types, or in targeted cells, which are limited to cell autonomous effects. These approaches are unable to represent the complete biological implications of Pb exposure because the brain is a cooperative network of highly heterogeneous cells, with cellular diversity and proportions shifting throughout development, by brain region, and with disease. New technologies are necessary to investigate whether Pb and other environmental exposures alter cell composition in the brain and whether they cause molecular changes in a cell-type-specific manner. Cutting-edge, single-cell approaches now enable research resolving cell-type-specific effects from bulk tissues. This article reviews existing Pb neurotoxicology studies with genome-wide molecular signatures and provides a path forward for the field to implement single-cell approaches with practical recommendations.

Exploring new frontiers in type 1 diabetes through advanced mass-spectrometry-based molecular measurements.

Type 1 diabetes (T1D) is a devastating autoimmune disease for which advanced mass spectrometry (MS) methods are increasingly used to identify new biomarkers and better understand underlying mechanisms. For example, integration of MS analysis and machine learning has identified multimolecular biomarker panels. In mechanistic studies, MS has contributed to the discovery of neoepitopes, and pathways involved in disease development and identifying therapeutic targets. However, challenges remain in understanding the role of tissue microenvironments, spatial heterogeneity, and environmental factors in disease pathogenesis. Recent advancements in MS, such as ultra-fast ion-mobility separations, and single-cell and spatial omics, can play a central role in addressing these challenges. Here, we review recent advancements in MS-based molecular measurements and their role in understanding T1D.