Single-cell Gene Expression Analysis Research Articles

Low-intensity ultrasound ameliorates brain organoid integration and rescues microcephaly deficits.

Human brain organoids represent a remarkable platform for modeling neurological disorders and a promising brain repair approach. However, the effects of physical stimulation on their development and integration remain unclear. Here, we report that low-intensity ultrasound significantly increases neural progenitor cell proliferation and neuronal maturation in cortical organoids. Histological assays and single-cell gene expression analyses reveal that low-intensity ultrasound improves the neural development in cortical organoids. Following organoid grafts transplantation into the injured somatosensory cortices of adult mice, longitudinal electrophysiological recordings and histological assays reveal that ultrasound-treated organoid grafts undergo advanced maturation. They also exhibit enhanced pain-related gamma-band activity and more disseminated projections into the host brain than the untreated groups. Finally, low-intensity ultrasound ameliorates neuropathological deficits in a microcephaly brain organoid model. Hence, low-intensity ultrasound stimulation advances the development and integration of brain organoids, providing a strategy for treating neurodevelopmental disorders and repairing cortical damage.

Clinical and CSF single-cell profiling of post-COVID-19 cognitive impairment.

Natural history and mechanisms for persistent cognitive symptoms ("brain fog") following acute and often mild COVID-19 are unknown. In a large prospective cohort of people who underwent testing a median of 9months after acute COVID-19 in the New York City/New Jersey area, we found that cognitive dysfunction is common; is not influenced by mood, fatigue, or sleepiness; and is correlated with MRI changes in very few people. In a subgroup that underwent cerebrospinal fluid analysis, there are no changes related to Alzheimer's disease or neurodegeneration. Single-cell gene expression analysis in the cerebrospinal fluid shows findings consistent with monocyte recruitment, chemokine signaling, cellular stress, and suppressed interferon response-especially in myeloid cells. Longitudinal analysis shows slow recovery accompanied by key alterations in inflammatory genes and increased protein levels of CXCL8, CCL3L1, and sTREM2. These findings suggest that the prognosis for brain fog following COVID-19 correlates with myeloid-related chemokine and interferon-responsive genes.

SingmiR: a single-cell miRNA alignment and analysis tool.

Single-cell RNA sequencing(RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login athttps://www.ccb.uni-saarland.de/singmir.

Abstract 7041: Tumor-immune interactions and cisplatin resistance in localized muscle-invasive bladder cancer

Abstract Background: Cisplatin-based chemotherapy followed by radical cystectomy remains the standard-of-care treatment for patient with localized muscle-invasive bladder cancer (MIBC). Neoadjuvant clinical trials studying the combination of cisplatin-based chemotherapy and immune checkpoint blockade (ICB) in MIBC reported encouraging pathologic complete response rates. However, the molecular mechanisms and cellular programs involved in response and resistance to cisplatin and ICB in MIBC remain incompletely characterized. Our goal is to define cellular transcriptional programs and chromatin accessible regions in cancer cells and infiltrating immune cells associated with response and resistance to neoadjuvant systemic therapy. Methods: We performed single-cell Multiome ATAC and Gene expression sequencing (simultaneous identification of gene expression and open chromatin regions within the same cell) of tumors that had a complete response – “responders” – and tumors that had no response or progressed – “non-responders” – through neoadjuvant cisplatin-based chemotherapy (n=15). Single cell suspensions were prepared following the 10x Genomics protocol. Cell Ranger ARC was used for sequence alignment, peak calling, and generation of count matrices. Downstream single-cell gene expression analysis was performed with Scanpy and ATAC-seq with Seurat. Results: We identified two distinct urothelial cell populations in "responders" vs "non-responders" based on single cell gene expression and genome wide chromatin accessibility regions. Cancer cells in “non-responders” preferentially express basal cell gene expression signatures. “Non-responders” were significantly enriched in suppressive tumor-associated macrophages (TAMs). Interestingly, SPP1+ TAMs known to have a pro-tumoral role and promote resistance to ICB were exclusively identified in “non-responders”. Conclusion: Single cell and genome wide chromatin accessibility regions identify heterogenous urothelial cell populations expressing basal cell markers in tumors resistant to neoadjuvant cisplatin-based chemotherapy. “Non-responders” are significantly enriched with TAMs implicated in resistance to ICB. Future studies will better define the implications of these findings in cancer therapeutics for patients with MIBC. Citation Format: Filipe La Fuente De Carvalho, Jihyun Lee, Kevin Bi, Breanna Titchen, Konrad Stawiski, Jihye Park, Amanda Garza, Daniel Michaud, Jennifer Guerriero, Elizabeth Mittendorf, Kent Mouw, Eliezer Van Allen. Tumor-immune interactions and cisplatin resistance in localized muscle-invasive bladder cancer [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 7041.

The effector program of human CD8 T cells supports tissue remodeling.

CD8 T lymphocytes are classically viewed as cytotoxic T cells. Whether human CD8 T cells can, in parallel, induce a tissue regeneration program is poorly understood. Here, antigen-specific assay systems revealed that human CD8 T cells not only mediated cytotoxicity but also promoted tissue remodeling. Activated CD8 T cells could produce the epidermal growth factor receptor (EGFR)-ligand amphiregulin (AREG) and sensitize epithelial cells for enhanced regeneration potential. Blocking the EGFR or the effector cytokines IFN-γ and TNF could inhibit tissue remodeling. This regenerative program enhanced tumor spheroid and stem cell-mediated organoid growth. Using single-cell gene expression analysis, we identified an AREG+, tissue-resident CD8 T cell population in skin and adipose tissue from patients undergoing abdominal wall or abdominoplasty surgery. These tissue-resident CD8 T cells showed a strong TCR clonal relation to blood PD1+TIGIT+ CD8 T cells with tissue remodeling abilities. These findings may help to understand the complex CD8 biology in tumors and could become relevant for the design of therapeutic T cell products.

Nasopharyngeal lymphatic plexus is a hub for cerebrospinal fluid drainage.

Cerebrospinal fluid (CSF) in the subarachnoid space around the brain has long been known to drain through the lymphatics to cervical lymph nodes1-17, but the connections and regulation have been challenging to identify. Here, using fluorescent CSF tracers in Prox1-GFP lymphatic reporter mice18, we found that the nasopharyngeal lymphatic plexus is a major hub for CSF outflow to deep cervical lymph nodes. This plexus had unusual valves and short lymphangions but no smooth-muscle coverage, whereas downstream deep cervical lymphatics had typical semilunar valves, long lymphangions and smooth muscle coverage that transported CSF to the deep cervical lymph nodes. α-Adrenergic and nitric oxide signalling in the smooth muscle cells regulated CSF drainage through the transport properties of deep cervical lymphatics. During ageing, the nasopharyngeal lymphatic plexus atrophied, but deep cervical lymphatics were not similarly altered, and CSF outflow could still be increased by adrenergic or nitric oxide signalling. Single-cell analysis of gene expression in lymphatic endothelial cells of the nasopharyngeal plexus of aged mice revealed increased type I interferon signalling and other inflammatory cytokines. The importance of evidence for the nasopharyngeal lymphatic plexus functioning as a CSF outflow hub is highlighted by its regression during ageing. Yet, the ageing-resistant pharmacological activation of deep cervical lymphatic transport towards lymph nodes can still increase CSF outflow, offering an approach for augmenting CSF clearance in age-related neurological conditions in which greater efflux would be beneficial.

Transcriptional profiling of human cartilage endplate cells identifies novel genes and cell clusters underlying degenerated and non-degenerated phenotypes

BackgroundLow back pain is a leading cause of disability worldwide and is frequently attributed to intervertebral disc (IVD) degeneration. Though the contributions of the adjacent cartilage endplates (CEP) to IVD degeneration are well documented, the phenotype and functions of the resident CEP cells are critically understudied. To better characterize CEP cell phenotype and possible mechanisms of CEP degeneration, bulk and single-cell RNA sequencing of non-degenerated and degenerated CEP cells were performed.MethodsHuman lumbar CEP cells from degenerated (Thompson grade ≥ 4) and non-degenerated (Thompson grade ≤ 2) discs were expanded for bulk (N=4 non-degenerated, N=4 degenerated) and single-cell (N=1 non-degenerated, N=1 degenerated) RNA sequencing. Genes identified from bulk RNA sequencing were categorized by function and their expression in non-degenerated and degenerated CEP cells were compared. A PubMed literature review was also performed to determine which genes were previously identified and studied in the CEP, IVD, and other cartilaginous tissues. For single-cell RNA sequencing, different cell clusters were resolved using unsupervised clustering and functional annotation. Differential gene expression analysis and Gene Ontology, respectively, were used to compare gene expression and functional enrichment between cell clusters, as well as between non-degenerated and degenerated CEP samples.ResultsBulk RNA sequencing revealed 38 genes were significantly upregulated and 15 genes were significantly downregulated in degenerated CEP cells relative to non-degenerated cells (|fold change| ≥ 1.5). Of these, only 2 genes were previously studied in CEP cells, and 31 were previously studied in the IVD and other cartilaginous tissues. Single-cell RNA sequencing revealed 11 unique cell clusters, including multiple chondrocyte and progenitor subpopulations with distinct gene expression and functional profiles. Analysis of genes in the bulk RNA sequencing dataset showed that progenitor cell clusters from both samples were enriched in “non-degenerated” genes but not “degenerated” genes. For both bulk- and single-cell analyses, gene expression and pathway enrichment analyses highlighted several pathways that may regulate CEP degeneration, including transcriptional regulation, translational regulation, intracellular transport, and mitochondrial dysfunction.ConclusionsThis thorough analysis using RNA sequencing methods highlighted numerous differences between non-degenerated and degenerated CEP cells, the phenotypic heterogeneity of CEP cells, and several pathways of interest that may be relevant in CEP degeneration.

Dual-Fluorescence Chromosome-Located Labeling System for Accurate In Vivo Single-Cell Gene Expression Analysis in Pseudomonas syringae.

Epigenetic regulation as a means for bacterial adaptation is receiving increasing interest in the last decade. Significant efforts have been directed towards understanding the mechanisms giving raise to phenotypic heterogeneity within bacterial populations and its adaptive relevance. Phenotypic heterogeneity mostly refers to phenotypic variation not linked to genetic differences nor to environmental stimuli. Recent findings on the relevance of phenotypic heterogeneity on some bacterial complex traits are causing a shift from traditional assays where bacterial phenotypes are defined by averaging population-level data, to single-cell analysis that focus on bacterial individual behavior within the population. Fluorescent labeling is a key asset for single-cell gene expression analysis using flow cytometry, fluorescence microscopy, and/or microfluidics.We previously described the generation of chromosome-located transcriptional gene fusions to fluorescent reporter genes using the model bacterial plant pathogen Pseudomonas syringae. These fusions allow researchers to follow variation in expression of the gene(s) of interest, without affecting gene function. In this report, we improve the analytic power of the method by combining such transcriptional fusions with constitutively expressed compatible fluorescent reporter genes integrated in a second, neutral locus of the bacterial chromosome. Constitutively expressed fluorescent reporters allow for the detection of all bacteria comprising a heterogeneous population, regardless of the level of expression of the concurrently monitored gene of interest, thus avoiding the traditional use of stains often incompatible with samples from complex contexts such as the leaf.

FastCAR: fast correction for ambient RNA to facilitate differential gene expression analysis in single-cell RNA-sequencing datasets

Cell type-specific differential gene expression analyses based on single-cell transcriptome datasets are sensitive to the presence of cell-free mRNA in the droplets containing single cells. This so-called ambient RNA contamination may differ between samples obtained from patients and healthy controls. Current ambient RNA correction methods were not developed specifically for single-cell differential gene expression (sc-DGE) analyses and might therefore not sufficiently correct for ambient RNA-derived signals. Here, we show that ambient RNA levels are highly sample-specific. We found that without ambient RNA correction, sc-DGE analyses erroneously identify transcripts originating from ambient RNA as cell type-specific disease-associated genes. We therefore developed a computationally lean and intuitive correction method, Fast Correction for Ambient RNA (FastCAR), optimized for sc-DGE analysis of scRNA-Seq datasets generated by droplet-based methods including the 10XGenomics Chromium platform. FastCAR uses the profile of transcripts observed in libraries that likely represent empty droplets to determine the level of ambient RNA in each individual sample, and then corrects for these ambient RNA gene expression values. FastCAR can be applied as part of the data pre-processing and QC in sc-DGE workflows comparing scRNA-Seq data in a health versus disease experimental design. We compared FastCAR with two methods previously developed to remove ambient RNA, SoupX and CellBender. All three methods identified additional genes in sc-DGE analyses that were not identified in the absence of ambient RNA correction. However, we show that FastCAR performs better at correcting gene expression values attributed to ambient RNA, resulting in a lower frequency of false-positive observations. Moreover, the use of FastCAR in a sc-DGE workflow increases the cell-type specificity of sc-DGE analyses across disease conditions.

Post-Transplant T Cell Clonotype Diversity Is Associated with Survival in Patients with TP53-Mutated Acute Myeloid Leukemia

Background TP53 mutations are associated with unfavorable outcomes in various cancer types and present an obstacle to achieving sustained remission in acute myeloid leukemia (AML). Even with allogeneic hematopoietic stem cell transplantation (HSCT), the risk of relapse approximates 80%, with dismal long-term survival. This could imply methods of immune escape in TP53 mutated leukemias that allow them to evade the graft-versus-leukemia (GVL) effect, which is a critical mechanism of disease control with HSCT. This study investigates the dynamics of immune reconstitution at single-cell resolution in TP53-mutated AML at pre- and multiple post-HSCT timepoints in patients who either remain in long-term remission or relapse following HSCT. Methods We collected 26 longitudinal bone marrow aspirates and 1 peripheral blood sample from 12 patients with TP53-mutated AML who underwent HSCT at the Dana-Farber Cancer Institute between 2015-21. All patients received HLA-matched T-cell replete HSCT in morphologic remission, with standard tacrolimus/methotrexate-based prophylaxis and peripheral blood stem cells. We categorized the patients into two cohorts based on their treatment response: long-term remission (>3.5 years, cohort 1, n=4) or relapse (cohort 2, n=8). We performed paired 5' single-cell RNA and T cell receptor (TCR) sequencing on sorted viable mononuclear from each sample and CD3+ T cells from selected samples using 10x Genomics procedures. In total, we analyzed 44 samples (27 mononuclear, 17 CD3+), resulting in 250,640 high-quality single-cell transcriptomes, including 137,649 T cells and NK cells. Data analysis was performed using Cell Ranger Multi (10x Genomics) and R 4.3 with the tidyverse 2.0, Seurat 5.1, and scRepertoire 1.1 packages. Results We focused our initial analysis on the 2-6-month post-HSCT period that is critical for immune reconstitution. This included eight samples from seven patients in the two cohorts (1: remission, 2: relapse, pink box in Figure 1). Of these 7 patients, 4 were in the relapse cohort, with these relapses occurring >4 months post-HSCT. No significant difference in T-cell chimerism was seen between these 7 patients in this 2-6 month period. Based on canonical gene expression signatures, we annotated cell types and selected T cells for further evaluation (Figure 2). First, we found that the CD4/CD8 ratio differed between the cohorts, indicating a relative CD8+ T cell expansion in the relapse cohort (cohort 1: 1.69, cohort 2: 0.55, P<0.0001). Second, we found lower TCR diversity in the relapse cohort (inverse Simpson index, cohort 1: 234.6, cohort 2: 83.0, P<0.0001). This difference remained significant when subsampling the same number of T cells per patient and when restricting all samples to the 3 to 4-month timepoint. Considering the disparity in CD8 T cell numbers between the cohorts, we also analyzed repertoire diversity, specifically in CD8+ T cells, and found that the observed significance persisted. To further investigate TCR diversity, we overlaid T cell clonotypes (cells that share the same TCR sequence) in a UMAP visualization, which highlighted increased hyperexpanded CD8+ T cells in the relapse cohort (Figure 2). Finally, we found that greater clonotype expansion was correlated with the expression of key T cell genes, including CD8A, CD8B, PRF1, NKG7, and GZMA. These results suggest that cytotoxic CD8+ T cells link lower TCR diversity to the likelihood of disease relapse. Conclusions By performing deep analysis of single-cell gene expression linked to TCR clonotypes, we discover new insights into the biology of hematopoietic reconstitution after HSCT of patients with TP53-mutated AML. Despite having analyzed a limited number of samples, we find that patients who remain in long-term remission have significantly higher CD8+ TCR diversity between 2-6 months post-HSCT, while those who relapsed between 5-18 months post-HSCT showed lower TCR diversity and hyperexpanded CD8+ clones at the same timepoints. This work suggests that early post-HSCT TCR diversity could be a biomarker associated with GVL and warrants further study. In ongoing and future analyses, we will mine the current dataset for further insights into the factors influencing survival in TP53-mutated AML patients. We also plan to extend the measurement of TCR diversity as a predictor of survival for validation in a larger cohort.

A Novel, Probe-Based and Instrument-Free Method for Improved Ultrahigh-Throughput Single-Cell Gene Expression Analysis of Peripheral Blood Mononuclear Cells

Single-cell gene expression assays are critical tools for identifying functional subtypes of immune cells, as well as changes within cells resulting from pathology or treatment. However, most current methods are expensive, low in sample throughput, rely on reverse transcription and lack the sensitivity to consistently measure low expressed genes from single cells - preventing measurements of many key immune biomarkers and molecular pathways. Another problem with existing single-cell sequencing methods is that many of the cell-associated reads either fail to map to transcripts or map to uninformative ribosomal and mitochondrial genes. Some methods also require the use of live cells, which means the single-cell assay has to be carried out at the specific time of treatment or when culture is terminated. The aforementioned limitations have contributed to most single-cell sequencing studies being restricted to small numbers of samples and have prevented their wider scale adoption in biopharma, clinical, translational and applied applications. Here we report on the development and performance of a novel combinatorial split-pool-based workflow, TempO-LINC™, that adds cell-identifying molecular barcodes onto high-sensitivity gene expression probes within fixed cells. Cells can be fixed at the end of a treatment, or when obtained from a patient and stably stored for months until they are ready to be processed with other samples through the TempO-LINC assay. All probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000 cells per run. TempO-LINC simultaneously processes up to 96 fixed cell samples per run, has a simple workflow that is amenable to automation and as we will show, has a higher gene detection rate than existing single-cell platforms. We will also show that TempO-LINC has an observed doublet rate of less than 0.5% for 12,500 cells analyzed. Critically, TempO-LINC reduces sample sequencing costs and although we show the assay accurately profiles the whole transcriptome (23,000 transcripts), it can also be targeted to measure only genes/pathways of interest - dramatically reducing sequencing costs yet further. We applied TempO-LINC to assay PBMCs and a human hepatocyte model for toxicology and demonstrated the ability to correctly identify unique cell states and molecular pathways from these populations. We will also present time course and dose response data from compound treatment of cells. All of these features position TempO-LINC as a potential disruptive technology that hematology researchers, clinicians and drug developers can use for new large-scale applications/studies using single-cell sequencing across thousands of samples while obtaining improved data quality.

ScMuffin: an R package to disentangle solid tumor heterogeneity by single-cell gene expression analysis

IntroductionSingle-cell (SC) gene expression analysis is crucial to dissect the complex cellular heterogeneity of solid tumors, which is one of the main obstacles for the development of effective cancer treatments. Such tumors typically contain a mixture of cells with aberrant genomic and transcriptomic profiles affecting specific sub-populations that might have a pivotal role in cancer progression, whose identification eludes bulk RNA-sequencing approaches. We present scMuffin, an R package that enables the characterization of cell identity in solid tumors on the basis of a various and complementary analyses on SC gene expression data.ResultsscMuffin provides a series of functions to calculate qualitative and quantitative scores, such as: expression of marker sets for normal and tumor conditions, pathway activity, cell state trajectories, Copy Number Variations, transcriptional complexity and proliferation state. Thus, scMuffin facilitates the combination of various evidences that can be used to distinguish normal and tumoral cells, define cell identities, cluster cells in different ways, link genomic aberrations to phenotypes and identify subtle differences between cell subtypes or cell states. We analysed public SC expression datasets of human high-grade gliomas as a proof-of-concept to show the value of scMuffin and illustrate its user interface. Nevertheless, these analyses lead to interesting findings, which suggest that some chromosomal amplifications might underlie the invasive tumor phenotype and the presence of cells that possess tumor initiating cells characteristics.ConclusionsThe analyses offered by scMuffin and the results achieved in the case study show that our tool helps addressing the main challenges in the bioinformatics analysis of SC expression data from solid tumors.

Control of murine brown adipocyte development by GATA6.

Brown adipose tissue (BAT) is a thermogenic organ that protects animals against hypothermia and obesity. BAT derives from the multipotent paraxial mesoderm; however, the identity of embryonic brown fat progenitor cells and regulators of adipogenic commitment are unclear. Here, we performed single-cell gene expression analyses of mesenchymal cells during mouse embryogenesis with a focus on BAT development. We identified cell populations associated with the development of BAT, including Dpp4+ cells that emerge at the onset of adipogenic commitment. Immunostaining and lineage-tracing studies show that Dpp4+ cells constitute the BAT fascia and contribute minorly as adipocyte progenitors. Additionally, we identified the transcription factor GATA6 as a marker of brown adipogenic progenitor cells. Deletion of Gata6 in the brown fat lineage resulted in a striking loss of BAT. Together, these results identify progenitor and transitional cells in the brown adipose lineage and define a crucial role for GATA6 in BAT development.

Using combined single-cell gene expression, TCR sequencing and cell surface protein barcoding to characterize and track CD4+ T cell clones from murine tissues.

Single-cell gene expression analysis using sequencing (scRNA-seq) has gained increased attention in the past decades for studying cellular transcriptional programs and their heterogeneity in an unbiased manner, and novel protocols allow the simultaneous measurement of gene expression, T-cell receptor clonality and cell surface protein expression. In this article, we describe the methods to isolate scRNA/TCR-seq-compatible CD4+ T cells from murine tissues, such as skin, spleen, and lymph nodes. We describe the processing of cells and quality control parameters during library preparation, protocols for multiplexing of samples, and strategies for sequencing. Moreover, we describe a step-by-step bioinformatic analysis pipeline from sequencing data generated using these protocols. This includes quality control, preprocessing of sequencing data and demultiplexing of individual samples. We perform quantification of gene expression and extraction of T-cell receptor alpha and beta chain sequences, followed by quality control and doublet detection, and methods for harmonization and integration of datasets. Next, we describe the identification of highly variable genes and dimensionality reduction, clustering and pseudotemporal ordering of data, and we demonstrate how to visualize the results with interactive and reproducible dashboards. We will combine different analytic R-based frameworks such as Bioconductor and Seurat, illustrating how these can be interoperable to optimally analyze scRNA/TCR-seq data of CD4+ T cells from murine tissues.

Quantum annealing-based clustering of single cell RNA-seq data.

Cluster analysis is a crucial stage in the analysis and interpretation of single-cell gene expression (scRNA-seq) data. It is an inherently ill-posed problem whose solutions depend heavily on hyper-parameter and algorithmic choice. The popular approach of K-means clustering, for example, depends heavily on the choice of K and the convergence of the expectation-maximization algorithm to local minima of the objective. Exhaustive search of the space for multiple good quality solutions is known to be a complex problem. Here, we show that quantum computing offers a solution to exploring the cost function of clustering by quantum annealing, implemented on a quantum computing facility offered by D-Wave [1]. Out formulation extracts minimum vertex cover of an affinity graph to sub-sample the cell population and quantum annealing to optimise the cost function. A distribution of low-energy solutions can thus be extracted, offering alternate hypotheses about how genes group together in their space of expressions.

Transcriptional changes of the aging lung.

Aging is a natural process associated with declined organ function and higher susceptibility to developing chronic diseases. A systemic single-cell type-based study provides a unique opportunity to understand the mechanisms behind age-related pathologies. Here, we use single-cell gene expression analysis comparing healthy young and aged human lungs from nonsmoker donors to investigate age-related transcriptional changes. Our data suggest that aging has a heterogenous effect on lung cells, as some populations are more transcriptionally dynamic while others remain stable in aged individuals. We found that monocytes and alveolar macrophages were the most transcriptionally affected populations. These changes were related to inflammation and regulation of the immune response. Additionally, we calculated the LungAge score, which reveals the diversity of lung cell types during aging. Changes in DNA damage repair, fatty acid metabolism, and inflammation are essential for age prediction. Finally, we quantified the senescence score in aged lungs and found that the more biased cells toward senescence are immune and progenitor cells. Our study provides a comprehensive and systemic analysis of the molecular signatures of lung aging. Our LungAge signature can be used to predict molecular signatures of physiological aging and to detect common signatures of age-related lung diseases.

Divergent Population-Specific Effects of Chronic Ethanol Exposure on Excitability and Inhibitory Transmission in Male and Female Rat Central Amygdala.

The central nucleus of the amygdala (CeA) is implicated in alcohol use disorder (AUD) and AUD-associated plasticity. The CeA is a primarily GABAergic nucleus that is subdivided into lateral and medial compartments with genetically diverse subpopulations. GABAA receptors are heteromeric pentamers with subunits conferring distinct physiological characteristics. GABAA receptor signaling in the CeA has been implicated in ethanol-associated plasticity; however, population-specific changes in inhibitory signaling and subunit expression remain unclear. Here, we combined electrophysiology with single-cell gene expression analysis of population markers and GABAA receptor subunits to examine population-specific changes in inhibitory control in male and female rats following chronic ethanol exposure. We found that chronic ethanol exposure and withdrawal produced global changes in GABAA receptor subunit expression at the transcript and protein levels, increased excitability in female CeA neurons, and increased inhibitory synaptic transmission in male CeA neurons. When we examined CeA neurons at the single-cell level we found heterogenous populations, as previously reported. We observed ethanol-induced increases in excitability only in somatostatin neurons in the CeA of females, decreases in excitability only in the protein kinase C delta (PKCd) population in males, and ethanol-induced increases in inhibitory transmission in male PKCd and calbindin 2-expressing CeA neurons. There were no population-specific differences in GABAA receptor (Gabr) subunits in males but reduced GabrA5 expression in female somatostatin neurons. Collectively, these findings suggest that defined CeA populations display differential ethanol sensitivity in males and females, which may play a role in sex differences in vulnerability to AUD or expression of AUD pathology.SIGNIFICANCE STATEMENT The CeA is involved in the effects of ethanol in the brain; however, the population-specific changes in CeA activity remain unclear. We used recordings of CeA neuronal activity and single-cell gene expression to examine population-specific changes in inhibitory control in male and female rats following chronic ethanol exposure and found sex- and population-specific effects of chronic ethanol exposure and withdrawal. Specifically, female CeA neurons displayed increased excitability in the somatostatin CeA population, whereas male CeA neurons displayed increased inhibitory control in both PKCd and calbindin populations and decreased excitability in the PKCd population. These findings identify CeA populations that display differential sensitivity to ethanol exposure, which may contribute to sex differences in vulnerability to alcohol use disorder.

Single-cell joint analysis of gene expression and histone modifications in droplets.

Single-cell joint analysis of gene expression and histone modifications in droplets.

Abstract PR016: Systemic T cell metabolic and effector function changes following treatment with PD1 and CTLA4 in patients with kidney cancer

Abstract Background: We have previously shown that dysfunctional renal cell carcinoma (RCC) tumor infiltrating lymphocytes (TIL) have glycolytic insufficiencies, and effector function can be rescued by bypassing glycolysis and modulating mitochondrial fitness (Beckermann et al., 2020). We have also shown that RCC TIL biology may be captured in a subset of the peripheral blood T cells, providing an opportunity to assess the tumor immune landscape in noninvasive liquid biopsy from peripheral blood samples (Siska et al., 2018). Methods: We evaluated the peripheral blood of twenty patients with RCC undergoing systemic therapy with PD1 and CTLA4, ten of whom had primary progressive disease and ten who had clinical benefit (SD, PR, CR for 6 months or greater), studying samples before and after three weeks on treatment. Single Cell mRNA gene expression and TCR clonal analysis was assessed in a subset of patients as well as ArcherDx V(D)J sequencing on matched tumor tissue. To assess the impact of mitochondrial membrane potential on T cell responses in patients with ccRCC we flow sorted viable, CD3+ PBMCs with high or low mitochondrial potential. The peripheral blood was analyzed for protein changes using a 44-plex labeled CyTOF antibody panel focused on T cells surface markers, as well as effector and metabolic function. Results: From peripheral blood of patients with ccRCC we find that CD3+ T cells are predominantly composed of subgroups with mitochondrial high membrane potential and expand in number after αPD1+αCTLA4 therapy. Peripheral T cells with low mitochondrial membrane potential are enriched for gene expression pathways associated with cytotoxicity. T cells with mitochondrial low potential also tended to have oligoclonal TCR expansion that were frequently shared between tumor and blood compared to that of mitochondrial high potential T cells. Mitochondrial low T cells were enriched for genes associated with cytotoxicity including CTSW, CD8, KLRK1, and KLRD. The tumor T cell repertoire demonstrated the greatest similarity with peripheral T cells that had low mitochondrial membrane potential. Shared T cells between the tumor and periphery are enriched for chemotaxis, antigen binding, and cytotoxicity signaling pathways. At the protein level, patients with response have lower metabolic activity and greater CD4+ effector T cells, consistent with the scRNA-seq data, while patients with progressive disease have more metabolically active profiles. Conclusions: Single cell gene expression and mass cytometry analysis shows that systemic changes occur in patients with kidney cancer undergoing αPD1 and αCTLA4 treatment. Shared TCR from TIL exist in oligoclonally expanded T cells in the peripheral blood. These shared T cells are enriched in subsets with low mitochondrial membrane potential and express markers of effector function and upregulate cytotoxic T cell pathways. Citation Format: Dalton Greenwood, Paul Lindau, Caroline Roe, Madelyn Landis, Rachel Hongo, Brian Rini, Jonathan Irish, W. Kimryn Rathmell, Jeffrey Rathmell, Kathryn Beckermann. Systemic T cell metabolic and effector function changes following treatment with PD1 and CTLA4 in patients with kidney cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Kidney Cancer Research; 2023 Jun 24-27; Austin, Texas. Philadelphia (PA): AACR; Cancer Res 2023;83(16 Suppl):Abstract nr PR016.

Trps1 acts as a regulator of Sf-1 transcription and testosterone synthesis in mouse Leydig cells.

Infertility has attracted global concern, and disruption of testosterone is a common cause of male infertility. Exploring the critical factors in testosterone biosynthesis may provide new insights for disease research and clinical therapy. Research on trichorhinophalangeal syndrome-1 (Trps1) gene has recently been focus on cancers; it is yet unknown whether Trps1 produces a marked effect in the male reproductive system. In the current study, single-cell RNA sequencing analysis of trichorhinophalangeal syndrome-1 gene (Trps1) expression in mouse testes and cleavage under targets and tagmentation and RNA sequencing were utilized to investigate the functionality of Trps1 in mouse Leydig cells. Knockdown of Trps1 increased testosterone synthesis in vitro and vivo using adeno-associated viral delivery and conditional knockout models. The results showed that Trps1 was abundantly expressed in Leydig cells. The expression levels of both steroidogenic factor-1 (Sf-1) and steroidogenic enzymes (Cyp11a1, Hsd3b, Cyp17a1, and Hsd17b3) as well as testosterone secretion were increased after Trps1 deficiency in vivo and vitro. Furthermore, disruption of Trps1 reduced histone deacetylase 1/2 activity and increased histone H3 acetylation in the Sf-1 promoter, thereby promoting testosterone secretion. Interestingly, Sf-1 also regulated the transcription of Trps1 through activating transcription factor 2. These results indicate that Trps1 targets Sf-1 to affect steroidogenesis through histone acetylation and shed light on the critical role of Trps1 functioning in the mouse Leydig cells.