Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R

Benchmarking spatial transcriptomics technologies with the multi-sample SpatialBenchVisium dataset

BACKGROUND

Spatial transcriptomics allows gene expression to be measured within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics' Visium platform, a popular method which enables transcriptome-wide profiling of tissue sections. Visium offers a range of sample handling and library construction methods which introduces a need for benchmarking to compare data quality and assess how well the technology can recover expected tissue features and biological signatures.

RESULTS

Here we present SpatialBenchVisium, a unique reference dataset generated from spleen tissue of mice responding to malaria infection spanning several tissue preparation protocols (both fresh frozen and FFPE, with either manual or CytAssist tissue placement). We note better quality control metrics in reference samples prepared using probe-based capture methods, particularly those processed with CytAssist, validating the improvement in data quality produced with the platform. Our analysis of replicate samples extends to explore spatially variable gene detection, the outcomes of clustering and cell deconvolution using matched single-cell RNA-sequencing data and publicly available reference data to identify cell types and tissue regions expected in the spleen. Multi-sample differential expression analysis recovered known gene signatures related to biological sex or gene knockout.

Developmental molecular signatures define de novo cortico-brainstem circuit for skilled forelimb movement

Skilled movement relies on descending cortical projections to the brainstem and spinal cord. While corticospinal neurons (CSN) have long been recognized for their role in fine motor control, the contribution of cortical projections to the brainstem remains poorly understood. Here, we identify a previously unrecognized direct cortico-brainstem circuit that emerges early in development and persists into adulthood. A subset of subcerebral projection neurons (SCPN) limit their projections to the brainstem from the earliest stages of axon extension without ever extending to the spinal cord. Using FACS purification and single-cell RNA sequencing, we show that these cortico-brainstem neurons (CBN) can be prospectively identified by the expression of Neuropeptide Y (Npy) in development. Functional silencing of Npy+ CBN in adulthood leads to impaired skilled forelimb reaching, demonstrating their essential role in adult motor control. Npy+ CBN project preferentially to rostral brainstem regions, including the midbrain reticular formation. These findings reveal developmental molecular signatures that define cortico-brainstem pathways for adult skilled movement. Our work provides new insights into the developmental logic that establishes descending cortical circuits and opens avenues for targeted investigation of their roles in motor function and recovery after injury.

Secreted neurofilament light chain after neuronal damage induces myeloid cell activation and neuroinflammation

Neurofilament light chain (NfL) is a neuron-specific cytoskeletal protein that provides structural support for axons and is released into the extracellular space following neuronal injury. While NfL has been extensively studied as a disease biomarker, the underlying release mechanisms and role in neurodegeneration remain poorly understood. Here, we find that neurons secrete low baseline levels of NfL, while neuronal damage triggers calpain-driven proteolysis and release of fragmented NfL. Secreted NfL activates microglial cells, which can be blocked with anti-NfL antibodies. We utilize in vivo single-cell RNA sequencing to profile brain cells after injection of recombinant NfL into the mouse hippocampus and find robust macrophage and microglial responses. Consistently, NfL knockout mice ameliorate microgliosis and delay symptom onset in the SOD1 mouse model of amyotrophic lateral sclerosis (ALS). Our results show that released NfL can activate myeloid cells in the brain and is, thus, a potential therapeutic target for neurodegenerative diseases.

Single-cell genome and transcriptome sequencing without upfront whole-genome amplification reveals cell state plasticity of melanoma subclones

Single-cell multi-omics methods enable the study of cell state diversity, which is largely determined by the interplay of the genome, epigenome, and transcriptome. Here, we describe Gtag&T-seq, a genome-and-transcriptome sequencing (G&T-seq) protocol of the same single cells that omits whole-genome amplification (WGA) by using direct genomic tagmentation (Gtag). Gtag drastically decreases the cost and improves coverage uniformity at single-cell and pseudo-bulk levels compared to WGA-based G&T-seq. We also show that transcriptome-based DNA copy number inference has limited resolution and accuracy, underlining the importance of affordable multi-omic approaches. Applying Gtag&T-seq to a melanoma xenograft model before treatment and at minimal residual disease revealed differential cell state plasticity and treatment response between cancer subclones. In summary, Gtag&T-seq is a low-cost and accurate single-cell multi-omics method that explores genetic alterations and their functional consequences in single cells at scale.

T-bet+ CXCR3+ B cells drive hyperreactive B-T cell interactions in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS). Self-peptide-dependent autoproliferation (AP) of B and T cells is a key mechanism in MS. Here, we show that pro-inflammatory B-T cell-enriched cell clusters (BTECs) form during AP and mirror features of a germinal center reaction. T-bet+CXCR3+ B cells are the main cell subset amplifying and sustaining their counterpart Th1 cells via interferon (IFN)-γ and are present in highly inflamed meningeal tissue. The underlying B cell activation signature is reflected by epigenetic modifications and receptor-ligand interactions with self-reactive T cells. AP+ CXCR3+ B cells show marked clonal evolution from memory to somatically hypermutated plasmablasts and upregulation of IFN-γ-related genes. Our data underscore a key role of T-bet+CXCR3+ B cells in the pathogenesis of MS in both the peripheral immune system and the CNS compartment, and thus they appear to be involved in both early relapsing-remitting disease and the chronic stage.

Multi-task benchmarking of spatially resolved gene expression simulation models

BACKGROUND

Computational methods for spatially resolved transcriptomics (SRT) are often developed and assessed using simulated data. The effectiveness of these evaluations relies on the ability of simulation methods to accurately reflect experimental data. However, a systematic evaluation framework for spatial simulators is currently lacking.

RESULTS

Here, we present SpatialSimBench, a comprehensive evaluation framework that assesses 13 simulation methods using ten distinct STR datasets. We introduce simAdaptor, a tool that extends single-cell simulators by incorporating spatial variables, enabling them to simulate spatial data. SimAdaptor ensures SpatialSimBench is backwards compatible, facilitating direct comparisons between spatially aware simulators and existing non-spatial single-cell simulators through the adaption. Using SpatialSimBench, we demonstrate the feasibility of leveraging existing single-cell simulators for SRT data and highlight performance differences among methods. Additionally, we evaluate the simulation methods based on a total of 35 metrics across data property estimation, various downstream analyses, and scalability. In total, we generated 4550 results from 13 simulation methods, ten spatial datasets, and 35 metrics.

CONCLUSIONS

Our findings reveal that model estimation can be influenced by distribution assumptions and dataset characteristics. In summary, our evaluation framework provides guidelines for selecting appropriate methods for specific scenarios and informs future method development.

Sox9 and nuclear factor I transcription factors regulate the timing of neurogenesis and ependymal maturation in dopamine progenitors

Correct timing of neurogenesis is crucial for generating the correct number and subtypes of glia and neurons in the embryo, and for preventing tumours and stem cell depletion in the adults. Here, we analyse how the midbrain dopamine (mDA) neuron progenitors transition into cell cycle arrest (G0) and begin to mature into ependymal cells. Comparison of mDA progenitors from different embryonic stages revealed upregulation of the genes encoding Sox9 and nuclear factor I transcription factors during development. Their conditional inactivation in the early embryonic midbrain led to delayed G0 entry and ependymal maturation in the entire midbrain ventricular zone, reduced gliogenesis and increased generation of neurons, including mDA neurons. In contrast, their inactivation in late embryogenesis did not result in mitotic re-entry, suggesting that these factors are necessary for G0 induction, but not for its maintenance. Our characterisation of adult ependymal cells by single-cell RNA sequencing and histology show that mDA-progenitor-derived cells retain several progenitor features but also secrete neuropeptides and contact neighbouring cells and blood vessels, indicating that these cells may form part of the circumventricular organ system.

Targeting Piezo1 channel to alleviate intervertebral disc degeneration

Background

Low back pain impacts over 600 million people worldwide, predominantly due to intervertebral disc degeneration. This study focuses on the role of Piezo1, a crucial mechanosensitive ion channel protein, in the pathology and potential treatment of disc degeneration.

Materials and methods

To investigate the effects of disc-specific Piezo1 deletion, we generated Aggrecan CreERT2 ; Piezo1 fl/fl mice and examined both lumbar spine instability (LSI)- and aging-induced disc degeneration. Additionally, the effect of pharmacological inhibition of Piezo1 was evaluated using GsMTx4, a potent Piezo1 antagonist, in an ex vivo model stimulated with IL-1β to induce disc degeneration. Assessments included histological examinations, immunofluorescence, and western blot analyses to thoroughly characterize the alterations in the intervertebral discs.

Results

Elevated expression of Piezo1 was detected in the nucleus pulposus (NP) of intervertebral discs with advanced disc degeneration in both aged mice and human patients. Inducible deletion of Piezo1 expression in aggrecan-expressing disc cells significantly reduced lumbar disc degeneration, decreased extracellular matrix (ECM) degradation, and lowered apoptosis in NP cells, observed in both aged mice and those undergoing LSI surgery. Excessive compression loading (CL) upregulated Piezo1 expression, induced ECM disruption, and increased apoptosis in NP cells, whereas inhibition of Piezo1 with GsMTx4 effectively mitigated these pathological changes. Furthermore, in ex vivo cultured mouse discs, GsMTx4 treatment significantly alleviated IL-1β-induced degenerative damages, restored ECM anabolism, and reduced apoptosis.

Conclusions

The findings suggest that Piezo1 plays a critical role in the development of disc degeneration and highlight its potential as a therapeutic target. Inhibiting Piezo1 could offer a novel strategy for treating or preventing this critical disease.

Translational potential of this article

This research highlights the involvement of Piezo1 in the development of intervertebral disc degeneration and emphasizes the potential for targeting Piezo1 as a therapeutic strategy to delay or reverse this condition.

kallisto, bustools and kb-python for quantifying bulk, single-cell and single-nucleus RNA-seq

The term 'RNA-seq' refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, single cells or single nuclei. The kallisto, bustools and kb-python programs are free, open-source software tools for performing this analysis that together can produce gene expression quantification from raw sequencing reads. The quantifications can be individualized for multiple cells, multiple samples or both. Additionally, these tools allow gene expression values to be classified as originating from nascent RNA species or mature RNA species, making this workflow amenable to both cell-based and nucleus-based assays. This protocol describes in detail how to use kallisto and bustools in conjunction with a wrapper, kb-python, to preprocess RNA-seq data. Execution of this protocol requires basic familiarity with a command line environment. With this protocol, quantification of a moderately sized RNA-seq dataset can be completed within minutes.

Genome-wide transcriptional silencing and mRNA stabilization allow the coordinated expression of the meiotic program in mice

The transcriptional dynamic of mammalian cells when these transit from the ubiquitous mitotic to a meiotic-specific program is key to understand this switch central to sexual reproduction. By quantifying active RNA polymerase II and nascent transcripts using single cell dataset and ethynyl-uridine pool-down with sorted cells from synchronized testes, we detailed the transcriptional activity of murine male germ cells. When spermatogonia differentiate, transcription slows down, reaching minimal activity at meiotic entry and resumes during pachytene stage. This event, we termed EMLT (for early meiotic low transcription), is distinct from the silencing of sex chromosomes as it is independent of Setdb1, though it is accompanied by the same chromatin mark, H3K9me3. EMLT is delayed in Stra8KO but occurs in mutants altering meiotic chromosome structure or double-strand break formation or repair. By comparing transcript abundance and nascent transcription we unveil a massive event of messenger RNA stabilization that parallels EMLT. Altogether our data indicate that meiosis is initiated with a nearly silent genome, and we propose that the stabilization of transcripts at that time facilitates the meiotic entry by synchronizing the expression of several meiotic subprograms.

Chronic intermittent fasting impairs β cell maturation and function in adolescent mice

Intermittent fasting (IF) is a nutritional lifestyle intervention with broad metabolic benefits, but whether the impact of IF depends on the individual's age is unclear. Here, we investigated the effects of IF on systemic metabolism and β cell function in old, middle-aged, and young mice. Short-term IF improves glucose homeostasis across all age groups without altering islet function and morphology. In contrast, while chronic IF is beneficial for adult mice, it results in impaired β cell function in the young. Using single-cell RNA sequencing (scRNA-seq), we delineate that the β cell maturation and function scores are reduced in young mice. In human islets, a similar pattern is observed in type 1 (T1D), but not type 2 (T2D), diabetes, suggesting that the impact of chronic IF in adolescence is linked to the development of β cell dysfunction. Our study suggests considering the duration of IF in younger persons, as it may worsen rather than reduce diabetes outcomes.

Transcriptomic characterization of human lateral septum neurons reveals conserved and divergent marker genes across species

The lateral septum (LS) is a midline, subcortical structure that is a critical regulator of social behaviors. Mouse studies have identified molecularly distinct neuronal populations within the LS, which control specific facets of social behavior. Despite its known molecular heterogeneity in the mouse and critical role in regulating social behavior, comprehensive molecular profiling of the human LS has not been performed. Here, we conducted single-nucleus RNA sequencing (snRNA-seq) to generate transcriptomic profiles of the human LS and compared human LS profiles to recently collected mouse LS snRNA-seq datasets. Our analyses identified TRPC4 as a conserved molecular marker of the mouse and human LS, while FREM2 is enriched only in the human LS. We also identify a distinct neuronal cell type marked by OPRM1, the gene encoding the μ-opioid receptor. Together, these results highlight transcriptional heterogeneity of the human LS and identify robust marker genes for the human LS.

CHOIR improves significance-based detection of cell types and states from single-cell data

Clustering is a critical step in the analysis of single-cell data, as it enables the discovery and characterization of putative cell types and states. However, most popular clustering tools do not subject clustering results to statistical inference testing, leading to risks of overclustering or underclustering data and often resulting in ineffective identification of cell types with widely differing prevalence. To address these challenges, we present CHOIR (clustering hierarchy optimization by iterative random forests), which applies a framework of random forest classifiers and permutation tests across a hierarchical clustering tree to statistically determine which clusters represent distinct populations. We demonstrate the enhanced performance of CHOIR through extensive benchmarking against 14 existing clustering methods across 100 simulated and 4 real single-cell RNA-seq, ATAC-seq, spatial transcriptomic, and multi-omic datasets. CHOIR can be applied to any single-cell data type and provides a flexible, scalable, and robust solution to the important challenge of identifying biologically relevant cell groupings within heterogeneous single-cell data.

Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation

The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we present transcriptome-wide spatial gene expression maps of the human dentate gyrus and investigate age-associated changes across the lifespan. Genes associated with neurogenesis and the extracellular matrix are enriched in infants and decline throughout development and maturation. Following infancy, inhibitory neuron markers increase, and cellular proliferation markers decrease. We also identify spatio-molecular signatures that support existing evidence for protracted maturation of granule cells during adulthood and age-associated increases in neuroinflammation-related gene expression. Our findings support the notion that the hippocampal neurogenic niche undergoes major changes following infancy and identify molecular regulators of brain aging in glial- and neuropil-enriched tissue.

T-cells specific for KSHV and HIV migrate to Kaposi sarcoma tumors and persist over time

Kaposi sarcoma-associated herpesvirus (KSHV) is the etiologic agent of Kaposi sarcoma (KS), which causes significant morbidity and mortality worldwide, particularly in people living with HIV (PLWH) and in sub-Saharan Africa where KSHV seroprevalence is high. Postulating that T-cells specific for KSHV and HIV would be attracted to KS tumors, we performed transcriptional profiling and T-cell receptor (TCR) repertoire analysis of tumor biopsies from 144 Ugandan adults with KS, 106 of whom were also living with HIV. We show that CD8+ T-cells and M2-polarized macrophages are the most common immune cells in KS tumors. The TCR repertoire of T-cells associated with KS tumors is shared across spatially and temporally distinct tumors from the same individual. Clusters of T-cells with predicted shared specificity for uncharacterized antigens, potentially encoded by KSHV or HIV, comprise ~25% of the T-cells in KS tumors. Single-cell RNA-sequencing of blood from a subset of 9 adults captured 4,283 unique αβ TCRs carried in 14,698 putative KSHV- or HIV-specific T-cells, which carried an antigen-experienced effector phenotype. T-cells engineered to express a representative sample of these TCRs showed high-avidity recognition of KSHV- or HIV-encoded antigens. These results suggest that a poly-specific, high-avidity KSHV- and HIV-specific T-cell response, potentially inhibited by M2 macrophages, migrates to and localizes with KS tumors. Further analysis of KSHV- and HIV-specific T-cells in KS tumors will provide insight into the pathogenesis of KS and could guide the development of specific immune therapy based on adoptive transfer or vaccination.

Bacterial profiles of the oral, vaginal, and rectal mucosa and colostrum of periparturient sows

The commensal microbiota influences the health, feeding efficiency, and reproductive performance of sows. The microbiota composition in the alimentary and genitourinary tracts and in colostrum/milk during pregnancy and lactation also impacts the microbiota and immune system, growth, and health of the piglets. Knowledge of the microbial compositions is important for evaluation of these effects and for discovering ways to improve the health and productivity of the sows. Oral, vaginal, and rectal mucosa and colostrum were sampled from 32 sows of variable parity in late pregnancy, and colostrum within 6 hours of delivery of the first piglet, on four commercial piglet-producing farms in Finland. Microbial compositions were analyzed by 16S rRNA gene amplicon sequencing. The most abundant genera of the oral microbiota were Rothia, Moraxella, and Streptococcus. The rectal microbiota was dominated by Clostridium sensu stricto 1. Streptococcus was the most abundant genus in the vagina and colostrum. Moderate differences in diversity and composition were observed between farms. The relative abundances of the genera Neisseria (MaAsLin 2 q = 0.002, ANCOMBC q = 0.005), Fusobacterium (MaAsLin 2 q = 0.008, ANCOMBC q = 0.04) and Bacteroides (MaAsLin 2 q < 0.005, ANCOMBC q = 0.06) were lower in oral samples and Romboutsia (MaAsLin 2 q = 0.07, ANCOMBC q = 0.05), Turicibacter (MaAsLin 2 q = 0.08, ANCOMBC q = 0.02) and Lachnospiraceae_UCG_007 (MaAsLin 2 q = 0.1, ANCOMBC q = 0.05) were higher in rectal samples of multiparous compared to primiparous sows. In vaginal samples there was a tendency of higher relative abundances of the genera Fusobacterium and Streptococcus in multiparous than primiparous sows. Among the differentially abundant taxa, F. necrophorum and F. nucleatum were identified in oral samples, F. gastrosuis and F. necrophorum in vaginal samples, and S. dysgalactiae in colostrum samples. This study provides a comprehensive overview of the mucosal and colostrum microbiota of periparturient sows during normal production conditions on Finnish commercial farms.

The impact of regular sauerkraut consumption on the human gut microbiota: a crossover intervention trial

BACKGROUND

Sauerkraut is a fermented food that has been suspected to have a beneficial impact on the gut microbiome, but scientific evidence is sparse. In this crossover intervention trial with 87 participants (DRKS00027007), we investigated the impact of daily consumption of fresh or pasteurized sauerkraut for 4 weeks on gut microbial composition and the metabolome in a healthy study population.

RESULTS

Using shotgun metagenomic sequencing, we observed changes in single bacterial species following fresh and pasteurized sauerkraut consumption. More pronounced changes were observed in the pasteurized sauerkraut intervention arm. Only pasteurized sauerkraut consumption increased serum short-chain fatty acids (SCFAs).

CONCLUSIONS

The gut microbiome of healthy individuals is rather resilient to short-term dietary interventions even though single species might be affected by sauerkraut consumption. Video Abstract.

Intercellular bridges are essential for transposon repression and meiosis in the male germline

Germ cell connectivity via intercellular bridges is a widely conserved feature across metazoans. However, its functional significance is poorly understood. Intercellular bridges are essential for fertility in male mice as genetic ablation of a critical bridge component, TEX14, causes spermatogenic failure, but the underlying reasons are unknown. Here we utilized a Tex14 hypomorph with reduced intercellular bridges along with Tex14-null mice that completely lack bridges to examine the roles of germ cell connectivity during spermatogenesis. We report that in males deficient for TEX14 and intercellular bridges, germ cells fail to complete meiotic DNA replication, synapsis and meiotic double-strand break repair. They also derepress retrotransposons and accumulate retrotransposon-encoded proteins during meiosis. Single-cell RNA-sequencing confirms sharing of transcripts between wild-type spermatids and demonstrates its partial attenuation in Tex14 hypomorphs, indicating that intercellular bridges enable cytoplasmic exchange between connected germ cells in testes. Our findings suggest that regulation of meiosis is non-cell-intrinsic and inform a model in which intercellular bridges influence critical meiotic events and protect germline genome integrity during spermatogenesis.

tagtango: an application to compare single-cell annotations

SUMMARY

In this article, we present tagtango, an innovative R package and web application designed for robust and intuitive comparison of single-cell clusters and annotations. It offers an interactive platform that simplifies the exploration of differences and similarities among different clustering and annotation methods. Leveraging single-cell data analysis and different visualizations, it allows researchers to dissect the underlying biological differences across groups. tagtango is a user-friendly application that is portable and works seamlessly across multiple operating systems.

AVAILABILITY AND IMPLEMENTATION

tagtango is freely available at https://github.com/bernibra/tagtango as an R package as well as an online web service at https://tagtango.unil.ch.

Characteristics of a CCL21 Gene-Modified Dendritic Cell Vaccine Utilized for a Clinical Trial in Non-Small Cell Lung Cancer

The treatment of non-small cell lung cancer has made major strides with the use of immune checkpoint inhibitors; however, there remains a significant need for therapies that can overcome immunotherapy resistance. Dendritic cell (DC) vaccines have been proposed as a therapy that can potentially enhance the antitumor immune response. We have embarked on a phase I clinical trial of a vaccine consisting of monocyte-derived DCs (moDC) modified to express the chemokine C-C motif chemokine ligand 21 (CCL21-DC) given in combination with pembrolizumab. In this study, we report a comprehensive characterization of this CCL21-DC vaccine and interrogate the effects of multiple factors in the manufacturing process. We show that the cellular makeup of the CCL21-DC vaccine is heterogeneous because of the presence of passenger lymphocytes at a proportion that is highly variable among patients. Single-cell RNA sequencing of vaccines revealed further heterogeneity within the moDC compartment, with cells spanning a spectrum of DC phenotypes. Transduction with a CCL21-containing adenoviral vector augmented CCL21 secretion by moDCs, but otherwise had a minimal effect on vaccine characteristics. A single freeze-thaw cycle for stored vaccines was associated with minor alterations to the DC phenotype, as was the use of healthy donors rather than patient autologous blood. Our results highlight important considerations for the production of DC vaccines and identify underexplored factors that may affect their efficacy and immunologic impact.

IL-33-activated ILC2s induce tertiary lymphoid structures in pancreatic cancer

Tertiary lymphoid structures (TLSs) are de novo ectopic lymphoid aggregates that regulate immunity in chronically inflamed tissues, including tumours. Although TLSs form due to inflammation-triggered activation of the lymphotoxin (LT)-LTβ receptor (LTβR) pathway1, the inflammatory signals and cells that induce TLSs remain incompletely identified. Here we show that interleukin-33 (IL-33), the alarmin released by inflamed tissues2, induces TLSs. In mice, Il33 deficiency severely attenuates inflammation- and LTβR-activation-induced TLSs in models of colitis and pancreatic ductal adenocarcinoma (PDAC). In PDAC, the alarmin domain of IL-33 activates group 2 innate lymphoid cells (ILC2s) expressing LT that engage putative LTβR+ myeloid organizer cells to initiate tertiary lymphoneogenesis. Notably, lymphoneogenic ILC2s migrate to PDACs from the gut, can be mobilized to PDACs in different tissues and are modulated by gut microbiota. Furthermore, we detect putative lymphoneogenic ILC2s and IL-33-expressing cells within TLSs in human PDAC that correlate with improved prognosis. To harness this lymphoneogenic pathway for immunotherapy, we engineer a recombinant human IL-33 protein that expands intratumoural lymphoneogenic ILC2s and TLSs and demonstrates enhanced anti-tumour activity in PDAC mice. In summary, we identify the molecules and cells of a druggable pathway that induces inflammation-triggered TLSs. More broadly, we reveal a lymphoneogenic function for alarmins and ILC2s.

scRNA seq of an F1 cross of Marek's disease resistant and susceptible chickens identifies allele specific expression signatures enriched in transcription modulators

Marek's disease (MD), a T cell lymphoma disease in chickens, is caused by the Marek's disease virus (MDV) found ubiquitously in the poultry industry. Genetically resistant Line 63 (L6) and susceptible Line 72 (L7) chickens have been instrumental to research on avian immune system response to MDV infection. In this study we characterized molecular signatures unique to splenic immune cell types across different genetic backgrounds 6 days after infection. Using three populations, L6, L7, and an F1 cross between L6xL7, we evaluated the immune cell transcriptome of responding cell types using single cell RNA sequencing. Several MDV genes were found expressed mainly in cytotoxic T cells while ICP4 and MEQ MDV genes were expressed across infected cell types. Using the F1 we quantified allele specific expression (ASE) of biallelic SNPs and found biased expression of parental alleles specific to immune cell subtypes. We identified 22 SNPs with ASE in response to MDV infection mapped to gene rich regions surrounding 59 genes of critical importance for chromatin remodeling and transcriptional regulation. Histone deacetylase genes (HDAC1 and HDAC8) had increased expression of L6 alleles, while small nuclear RNA genes (SNORA68 and SNORA72) expressed higher levels of L7 alleles with infection in T cell subsets. SNPs with ASE also mapped genes important for an adequate immune response including GNLY (cytotoxic activity) and PDIA3 (component of MHC class I peptide loading complex), and genes known to promote viral replication (MCM5 and EIF3M). These results show that functional variants associated with susceptibility to MD may have a bigger impact in subsets of immune cell types, and by characterizing the transcriptomes of these subtypes we can unravel molecular signatures specific to MD genomic resistance.

Cyclin O controls entry into the cell-cycle variant required for multiciliated cell differentiation

Multiciliated cells (MCCs) ensure fluid circulation in various organs. Their differentiation is marked by the amplification of cilia-nucleating centrioles, driven by a genuine cell-cycle variant, which is characterized by wave-like expression of canonical and non-canonical cyclins such as Cyclin O (CCNO). Patients with CCNO mutations exhibit a subtype of primary ciliary dyskinesia called reduced generation of motile cilia (RGMC). Here, we show that Ccno is activated at the crossroads of the onset of MCC differentiation, the entry into the MCC cell-cycle variant, and the activation of the centriole biogenesis program. Its absence blocks the G1/S-like transition of the cell-cycle variant, interrupts the centriologenesis transcription program, and compromises the production of centrioles and cilia in mouse brain and human respiratory MCCs. Altogether, our study identifies CCNO as a core regulator of entry into the MCC cell-cycle variant and the interruption of this variant as one etiology of RGMC.

Cyclin switch tailors a cell cycle variant to orchestrate multiciliogenesis

Meiosis, endoreplication, and asynthetic fissions are variations of the canonical cell cycle where either replication or mitotic divisions are muted. Here, we identify a cell cycle variantconserved across organs and mammals, where both replication and mitosis are muted, and that orchestrates the differentiation of post-mitotic progenitors into multiciliated cells (MCCs). MCC progenitors reactivate most of the cell cycle transcriptional program but replace the temporal expression of cyclins E2 and A2 with non-canonical cyclins O and A1. In addition, the primary APC/C inhibitor Emi1 is silenced. Re-expressing cyclins E2 and A2 and/or Emi1 can induce partial replication or mitosis. This shows that a cell can co-opt the cell cycle genetic program and regulate only certain elements to qualitatively and quantitatively divert CDK activity toward differentiation rather than division. We propose this cell cycle variant to exploit the existence of a cytoplasmic-or centriolar-CDK threshold lower than the S-phase threshold.

Correcting scale distortion in RNA sequencing data

RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used for population-based studies designed to identify genetic determinants of various diseases. Naturally, the accuracy of these tests should be verified and improved if possible. In this study, we aimed to detect and correct for expression level-dependent errors which are not corrected by conventional normalization techniques. We examined several RNA-seq datasets from the Cancer Genome Atlas (TCGA), Stand Up 2 Cancer (SU2C), and GTEx databases with various types of preprocessing. By applying local averaging, we found expression-level dependent biases that differ from sample to sample in all datasets studied. Using simulations, we show that these biases corrupt gene-gene correlation estimations and t tests between subpopulations. To mitigate these biases, we introduce two different nonlinear transforms based on statistical considerations that correct these observed biases. We demonstrate that these transforms effectively remove the observed per-sample biases, reduce sample-to-sample variance, and improve the characteristics of gene-gene correlation distributions. Using a novel simulation methodology that creates controlled differences between subpopulations, we show that these transforms reduce variability and increase sensitivity of two population tests. The improvements in sensitivity and specificity were of the order of 3-5% in most instances after the data was corrected for bias. Altogether, these results improve our capacity to understand gene-gene relationships, and may lead to novel ways to utilize the information derived from clinical tests.

Single-cell transcriptomics of bronchoalveolar lavage during PRRSV infection with different virulence

Porcine reproductive and respiratory syndrome virus (PRRSV) causes significant economic losses in the global swine industry due to its high genetic diversity and different virulence levels, which complicate disease management and vaccine development. This study evaluated longitudinal changes in the immune cell composition of bronchoalveolar lavage fluid and the clinical outcomes across PRRSV strains with varying virulence, using techniques including single-cell transcriptomics. In highly virulent infection, faster viral replication results in an earlier peak lung-damage time point, marked by significant interstitial pneumonia, a significant decrease in macrophages, and an influx of lymphocytes. Viral tracking reveals less than 5% of macrophages are directly infected, and further analysis indicates bystander cell death, likely regulated by exosomal microRNAs as a significant factor. In contrast, the peak intermediate infection shows a delayed lung-damage time point with fewer cell population modifications. Furthermore, anti-inflammatory M2-like macrophages (SPP1-CXCL14high) are identified and their counts increase during the peak lung-damage time point, likely contributing to local defense and lung recovery, which is not observed in high virulent infection. These findings provide a comprehensive description of the immune cellular landscape and differential PRRSV virulence mechanisms, which will help build new hypotheses to understand PRRSV pathogenesis and other respiratory infections.

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

An essential task in spatial transcriptomics is identifying spatially variable genes (SVGs). Here, we present Celina, a statistical method for systematically detecting cell type-specific SVGs (ct-SVGs)-a subset of SVGs exhibiting distinct spatial expression patterns within specific cell types. Celina utilizes a spatially varying coefficient model to accurately capture each gene's spatial expression pattern in relation to the distribution of cell types across tissue locations, ensuring effective type I error control and high power. Celina proves powerful compared to existing methods in single-cell resolution spatial transcriptomics and stands as the only effective solution for spot-resolution spatial transcriptomics. Applied to five real datasets, Celina uncovers ct-SVGs associated with tumor progression and patient survival in lung cancer, identifies metagenes with unique spatial patterns linked to cell proliferation and immune response in kidney cancer, and detects genes preferentially expressed near amyloid-β plaques in an Alzheimer's model.

Fibroblastic reticular cells generate protective intratumoral T cell environments in lung cancer

Stringent control of T cell activity in the tumor microenvironment is essential for the generation of protective antitumor immunity. However, the identity, differentiation, and functions of the cells that create critical fibroblastic niches promoting tumor-infiltrating T cells remain elusive. Here, we show that CCL19-expressing fibroblastic reticular cells (FRCs) generate interconnected T cell environments (TEs) in human non-small cell lung cancer, including tertiary lymphoid structures and T cell tracks. Analysis of the FRC-T cell interactome in TEs indicated molecular networks regulating niche-specific differentiation of CCL19-expressing fibroblasts and T cell activation pathways. Single-cell transcriptomics and cell fate-mapping analyses in mice confirmed that FRCs in TEs originate from mural and adventitial progenitors. Ablation of intratumoral FRC precursors decreased antitumor T cell activity, resulting in reduced tumor control during coronavirus vector-based immunotherapy. In summary, specialized FRC niches in the tumor microenvironment govern the quality and extent of antitumor T cell immunity.

Fabrication and modulation of flexible electromagnetic metamaterials

Flexible electromagnetic metamaterials are a potential candidate for the ideal material for electromagnetic control due to their unique physical properties and structure. Flexible electromagnetic metamaterials can be designed to exhibit specific responses to electromagnetic waves within a particular frequency range. Research shows that flexible electromagnetic metamaterials exhibit significant electromagnetic control characteristics in microwave, terahertz, infrared and other frequency bands. It has a wide range of applications in the fields of electromagnetic wave absorption and stealth, antennas and microwave devices, communication information and other fields. In this review, the currently popular fabrication methods of flexible electromagnetic metamaterials are first summarized, highlighting the electromagnetic modulation capability in different frequency bands. Then, the applications of flexible electromagnetic metamaterials in four aspects, namely electromagnetic stealth, temperature modulation, electromagnetic shielding, and wearable sensors, are elaborated and summarized in detail. In addition, this review also discusses the shortcomings and limitations of flexible electromagnetic metamaterials for electromagnetic control. Finally, the conclusion and perspective of the electromagnetic properties of flexible electromagnetic metamaterials are presented.

Novel Assignment of Gene Markers to Hematological and Immune Cells Based on Single-Cell Transcriptomics

There are many different cells that perform highly specialized functions in the human hematological and immune systems. Due to the relevance of their activity, in this work we investigated the cell types and subtypes that form this complex system, using single-cell RNA sequencing (scRNA-seq) to dissect and assess the markers that best define each cell population. We first developed an optimized computational workflow for analyzing large scRNA-seq datasets. We then used it to find gene markers of the different cell types present in bone marrow (BM) and peripheral blood (PB). We analyzed three different single-cell datasets to find specific cell markers using this strategy: first, we searched in the CD marker genes and then in the genes encoding membrane proteins and finally in all detected protein-coding genes. This allowed us not only to confirm known CDs that best mark some cell types (e.g., monocytes, B cells, NK cells, etc.) but also to test the ability of new genes to distinguish specific cell types. Finally, we applied a machine learning method (Random Forest) to test the accuracy of the different markers we found. As a result of all this work, we have found and propose specific and robust gene signatures to identify different types and subtypes of hematological and immune cells.

Evaluating the transcriptional regulators of arterial gene expression via a catalogue of characterized arterial enhancers

The establishment and growth of the arterial endothelium require the coordinated expression of numerous genes. However, regulation of this process is not yet fully understood. Here, we combined in silico analysis with transgenic mice and zebrafish models to characterize arterial-specific enhancers associated with eight key arterial identity genes (Acvrl1/Alk1, Cxcr4, Cxcl12, Efnb2, Gja4/Cx37, Gja5/Cx40, Nrp1, and Unc5b). Next, to elucidate the regulatory pathways upstream of arterial gene transcription, we investigated the transcription factors binding each arterial enhancer compared to a similar assessment of non-arterial endothelial enhancers. These results found that binding of SOXF and ETS factors was a common occurrence at both arterial and pan-endothelial enhancers, suggesting neither are sufficient to direct arterial specificity. Conversely, FOX motifs independent of ETS motifs were over-represented at arterial enhancers. Further, MEF2 and RBPJ binding was enriched but not ubiquitous at arterial enhancers, potentially linked to specific patterns of behaviour within the arterial endothelium. Lastly, there was no shared or arterial-specific signature for WNT-associated TCF/LEF, TGFβ/BMP-associated SMAD1/5 and SMAD2/3, shear stress-associated KLF4, or venous-enriched NR2F2. This cohort of well-characterized and in vivo-verified enhancers can now provide a platform for future studies into the interaction of different transcriptional and signaling pathways with arterial gene expression.

The Human Microglia Atlas (HuMicA) unravels changes in disease-associated microglia subsets across neurodegenerative conditions

Dysregulated microglia activation, leading to neuroinflammation, is crucial in neurodegenerative disease development and progression. We constructed an atlas of human brain immune cells by integrating nineteen single-nucleus RNA-seq and single-cell RNA-seq datasets from multiple neurodegenerative conditions, comprising 241 samples from patients with Alzheimer's disease, autism spectrum disorder, epilepsy, multiple sclerosis, Lewy body diseases, COVID-19, and healthy controls. The integrated Human Microglia Atlas (HuMicA) included 90,716 nuclei/cells and revealed nine populations distributed across all conditions. We identified four subtypes of disease-associated microglia and disease-inflammatory macrophages, recently described in mice, and shown here to be prevalent in human tissue. The high versatility of microglia is evident through changes in subset distribution across various pathologies, suggesting their contribution in shaping pathological phenotypes. A GPNMB-high subpopulation was expanded in AD and MS. In situ hybridization corroborated this increase in AD, opening the question on the relevance of this population in other pathologies.

edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets

edgeR is an R/Bioconductor software package for differential analyses of sequencing data in the form of read counts for genes or genomic features. Over the past 15 years, edgeR has been a popular choice for statistical analysis of data from sequencing technologies such as RNA-seq or ChIP-seq. edgeR pioneered the use of the negative binomial distribution to model read count data with replicates and the use of generalized linear models to analyze complex experimental designs. edgeR implements empirical Bayes moderation methods to allow reliable inference when the number of replicates is small. This article announces edgeR version 4, which includes new developments across a range of application areas. Infrastructure improvements include support for fractional counts, implementation of model fitting in C and a new statistical treatment of the quasi-likelihood pipeline that improves accuracy for small counts. The revised package has new functionality for differential methylation analysis, differential transcript expression, differential transcript and exon usage, testing relative to a fold-change threshold and pathway analysis. This article reviews the statistical framework and computational implementation of edgeR, briefly summarizing all the existing features and functionalities but with special attention to new features and those that have not been described previously.

Transformer-based modeling of Clonal Selection and Expression Dynamics reveals resistance mechanisms in breast cancer

Understanding transcriptional heterogeneity in cancer cells and its implication for treatment response is critical to identify how resistance occurs and may be targeted. Such heterogeneity can be captured by in vitro studies through clonal barcoding methods. We present TraCSED (Transformer-based modeling of Clonal Selection and Expression Dynamics), a dynamic deep learning approach for modeling clonal selection. Using single-cell gene expression and the fitness of barcoded clones, TraCSED identifies interpretable gene programs and the time points at which they are associated with clonal selection. When applied to cells treated with either giredestrant, a selective estrogen receptor (ER) antagonist and degrader, or palbociclib, a CDK4/6 inhibitor, pathways dynamically associated with resistance are revealed. For example, ER activity is associated with positive selection around day four under palbociclib treatment and this adaptive response can be suppressed by combining the drugs. Yet, in the combination treatment, one clone still emerged. Clustering based on partial least squares regression found that high baseline expression of both SNHG25 and SNCG genes was the primary marker of positive selection to co-treatment and thus potentially associated with innate resistance - an aspect that traditional differential analysis methods missed. In conclusion, TraCSED enables associating features with phenotypes in a time-dependent manner from scRNA-seq data.

Decreased lipidated ApoE-receptor interactions confer protection against pathogenicity of ApoE and its lipid cargoes in lysosomes

While apolipoprotein E (APOE) is the strongest genetic modifier for late-onset Alzheimer's disease (LOAD), the molecular mechanisms underlying isoform-dependent risk and the relevance of ApoE-associated lipids remain elusive. Here, we report that impaired low-density lipoprotein (LDL) receptor (LDLR) binding of lipidated ApoE2 (lipApoE2) avoids LDLR recycling defects observed with lipApoE3/E4 and decreases the uptake of cholesteryl esters (CEs), which are lipids linked to neurodegeneration. In human neurons, the addition of ApoE carrying polyunsaturated fatty acids (PUFAs)-CE revealed an allelic series (ApoE4 > ApoE3 > ApoE2) associated with lipofuscinosis, an age-related lysosomal pathology resulting from lipid peroxidation. Lipofuscin increased lysosomal accumulation of tau fibrils and was elevated in the APOE4 mouse brain with exacerbation by tau pathology. Intrahippocampal injection of PUFA-CE-lipApoE4 was sufficient to induce lipofuscinosis in wild-type mice. Finally, the protective Christchurch mutation also reduced LDLR binding and phenocopied ApoE2. Collectively, our data strongly suggest decreased lipApoE-LDLR interactions minimize LOAD risk by reducing the deleterious effects of endolysosomal targeting of ApoE and associated pathogenic lipids.

Clec12a controls colitis by tempering inflammation and restricting expansion of specific commensals

Microbiota composition regulates colitis severity, yet the innate immune mechanisms that control commensal communities and prevent disease remain unclear. We show that the innate immune receptor, Clec12a, impacts colitis severity by regulating microbiota composition. Transplantation of microbiota from a Clec12a-/- animal is sufficient to worsen colitis in wild-type mice. Clec12a-/- mice have expanded Faecalibaculum rodentium, and treatment with F. rodentium similarly exacerbates disease. However, Clec12a-/- animals are resistant to colitis development when rederived into an 11-member community, underscoring the role of specific species. Colitis in Clec12a-/- mice is dependent on monocytes, and cytokine and sequencing analysis in Clec12a-/- macrophages and serum shows enhanced inflammation with a reduction in phagocytic genes. F. rodentium specifically binds to Clec12a, and Clec12a-/--deficient macrophages are impaired in their ability to phagocytose F. rodentium. Thus, Clec12a contributes to an innate-immune-surveillance mechanism that controls the expansion of potentially harmful commensals while limiting inflammation.

Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.

Distant Metastases of Breast Cancer Resemble Primary Tumors in Cancer Cell Composition but Differ in Immune Cell Phenotypes

Breast cancer is the most commonly diagnosed cancer in women, with distant metastasis being the main cause of breast cancer-related deaths. Elucidating the changes in the tumor and immune ecosystems that are associated with metastatic disease is essential to improve understanding and ultimately treatment of metastasis. Here, we developed an in-depth, spatially resolved single-cell atlas of the phenotypic diversity of tumor and immune cells in primary human breast tumors and matched distant metastases, using imaging mass cytometry to analyze a total of 75 unique antibody targets. Although the same tumor cell phenotypes were typically present in primary tumors and metastatic sites, suggesting a strong founder effect of the primary tumor, their proportions varied between matched samples. Notably, the metastatic site did not influence tumor phenotype composition, except for the brain. Metastatic sites exhibited a lower number of immune cells overall but had a higher proportion of myeloid cells as well as exhausted and cytotoxic T cells. Myeloid cells showed distinct tissue-specific compositional signatures and increased presence of potentially matrix remodeling phenotypes in metastatic sites. This analysis of tumor and immune cell phenotypic composition of metastatic breast cancer highlights the heterogeneity of the disease within patients and across distant metastatic sites, indicating myeloid cells as the predominant immune modulators that could potentially be targeted at these sites. Significance: Multiplex imaging analysis of matched primary and metastatic breast tumors provides a phenotypic and spatial map of tumor microenvironments, revealing similar compositions of cancer cells and divergent immunologic features between matched samples.

Circulating tumor cell plasticity determines breast cancer therapy resistance via neuregulin 1-HER3 signaling

Circulating tumor cells (CTCs) drive metastasis, the leading cause of death in individuals with breast cancer. Due to their low abundance in the circulation, robust CTC expansion protocols are urgently needed to effectively study disease progression and therapy responses. Here we present the establishment of long-term CTC-derived organoids from female individuals with metastatic breast cancer. Multiomics analysis of CTC-derived organoids along with preclinical modeling with xenografts identified neuregulin 1 (NRG1)-ERBB2 receptor tyrosine kinase 3 (ERBB3/HER3) signaling as a key pathway required for CTC survival, growth and dissemination. Genome-wide CRISPR activation screens revealed that fibroblast growth factor receptor 1 (FGFR1) signaling serves a compensatory function to the NRG1-HER3 axis and rescues NRG1 deficiency in CTCs. Conversely, NRG1-HER3 activation induced resistance to FGFR1 inhibition, whereas combinatorial blockade impaired CTC growth. The dynamic interplay between NRG1-HER3 and FGFR1 signaling reveals the molecular basis of cancer cell plasticity and clinically relevant strategies to target it. Our CTC organoid platform enables the identification and validation of patient-specific vulnerabilities and represents an innovative tool for precision medicine.

Dissection of Gene Expression at the Single-Cell Level: scRNA-seq

Sequencing approaches that allowed for a better resolution of the transcriptome have been a major goal in the transcriptomics field since the development of RNA-seq techniques. While RNA-seq provides gene expression data from one entire sample in bulk, single-cell analysis allows for a better characterization of gene expression associated to specific cell types. Single-cell RNA-seq (scRNA-seq) is a reliable technique to unravel transcriptomic features of the tissues of interest dissociated at a single-cell level. The main feature of the single-cell technique is its ability to generate barcoded individual cells that allow for tracking the origin of thousands to millions of transcripts and reveal new cell types associated to diseases and different cell types and states. In this chapter, we discuss how scRNA-seq has become the gold standard to deepen the understanding of the gene expression with single-cell resolution.

Acquired resistance to PD-L1 inhibition enhances a type I IFN-regulated secretory program in tumors

Therapeutic inhibition of programmed cell death ligand (PD-L1) is linked to alterations in interferon (IFN) signaling. Since IFN-regulated intracellular signaling can control extracellular secretory programs in tumors to modulate immunity, we examined IFN-related secretory changes in tumor cells following resistance to PD-L1 inhibition. Here we report an anti-PD-L1 treatment-induced secretome (PTIS) in tumor models of acquired resistance that is regulated by type I IFNs. These secretory changes can suppress activation of T cells ex vivo while diminishing tumor cell cytotoxicity, revealing that tumor-intrinsic treatment adaptations can exert broad tumor-extrinsic effects. When reimplanted in vivo, resistant tumor growth can slow or stop when PTIS components are disrupted individually, or when type I IFN signaling machinery is blocked. Interestingly, genetic and therapeutic disruption of PD-L1 in vitro can only partially recapitulate the PTIS phenotype highlighting the importance of developing in vivo-based resistance models to more faithfully mimic clinically-relevant treatment failure. Together, this study shows acquired resistance to immune-checkpoint inhibitors 'rewires' tumor secretory programs controlled by type I IFNs that, in turn, can protect from immune cell attack.

Endogenous self-peptides guard immune privilege of the central nervous system

Despite the presence of strategically positioned anatomical barriers designed to protect the central nervous system (CNS), it is not entirely isolated from the immune system1,2. In fact, it remains physically connected to, and can be influenced by, the peripheral immune system1. How the CNS retains such responsiveness while maintaining an immunologically unique status remains an outstanding question. Here, in searching for molecular cues that derive from the CNS and enable its direct communication with the immune system, we identified an endogenous repertoire of CNS-derived regulatory self-peptides presented on major histocompatibility complex class II (MHC-II) molecules in the CNS and at its borders. During homeostasis, these regulatory self-peptides were found to be bound to MHC-II molecules throughout the path of lymphatic drainage from the brain to its surrounding meninges and its draining cervical lymph nodes. However, in neuroinflammatory disease, the presentation of regulatory self-peptides diminished. After boosting the presentation of these regulatory self-peptides, a population of suppressor CD4+ T cells was expanded, controlling CNS autoimmunity in a CTLA-4- and TGFβ-dependent manner. CNS-derived regulatory self-peptides may be the molecular key to ensuring a continuous dialogue between the CNS and the immune system while balancing overt autoreactivity. This sheds light on how we conceptually think about and therapeutically target neuroinflammatory and neurodegenerative diseases.

Deciphering the senescence-based tumoral heterogeneity and characteristics in pancreatic cancer: Results from parallel bulk and single-cell transcriptome data

The prevalent intra- and intertumoral heterogeneity results in undesirable prognosis and therapy failure of pancreatic cancer, potentially resulting from cellular senescence. Herein, integrated analysis of bulk and single-cell RNA-seq profiling was conducted to characterize senescence-based heterogeneity in pancreatic cancer. Publicly available bulk and single-cell RNA sequencing from pancreatic cancer patients were gathered from TCGA-PAAD, PACA-AU, PACA-CA, and GSE154778 datasets. The activity of three senescence-related pathways (cell cycle, DNA repair, and inflammation) was scored utilizing ssGSEA algorithm. A series of functional verifications of crucial genes were accomplished in patient tissue and pancreatic cancer cells. Based upon them, unsupervised clustering analysis was executed to classify pancreatic cancer samples into distinct senescence-based clusters at the bulk and single-cell levels. For single-cell transcriptome profiling, cell clustering and annotation were implemented, and malignant cells were recognized utilizing infercnv algorithm. Two senescence-based clusters were established and highly reproducible at the bulk level, with the heterogeneity in prognosis, clinicopathological features, genomic CNVs, oncogenic pathway activity, immune microenvironment and immune checkpoints. Senescence-relevant gene CHGA, UBE2C and MCM10 were proved to correlate with the migration and prognosis of pancreatic cancer. At the single-cell level, seven cell types were annotated, comprising ductal cells 1, ductal cells 2, fibroblasts, macrophages, T cells, stellate cells, and endothelial cells. The senescence-based classification was also proven at the single-cell level. Ductal cells were classified as malignant cells and non-malignant cells. In the tumor microenvironment of malignant cells, hypoxia and angiogenesis affected senescent phenotype. The heterogeneity in senescence was also observed between and within cell types. Altogether, our findings unveil that cellular senescence contributes to intra- and intertumoral heterogeneity in pancreatic cancer, which might facilitate the development of therapeutics and precision therapy in pancreatic cancer.

Dendritic cells type 1 control the formation, maintenance, and function of tertiary lymphoid structures in cancer

Tertiary lymphoid structures (TLS) are organized immune cell aggregates that arise in chronic inflammatory conditions. In cancer, TLS are associated with better prognosis and enhanced response to immunotherapy, making these structures attractive therapeutic targets. However, the mechanisms regulating TLS formation and maintenance in cancer are incompletely understood. Using spatial transcriptomics and multiplex imaging across various human tumors, we found an enrichment of mature dendritic cells (DC) expressing high levels of CCR7 in TLS, prompting us to investigate the role of DC in the formation and maintenance of TLS in solid tumors. To address this, we developed a novel murine model of non-small cell lung cancer (NSCLC) that forms mature TLS, containing B cell follicles with germinal centers and T cell zones with T follicular helper cells (TFH) and TCF1+PD-1+ progenitor exhausted CD8+ T cells (Tpex). Here we show that, during the early stages of tumor development, TLS formation relies on IFNγ-driven maturation of the conventional DC type 1 (cDC1) subset, their migration to tumor-draining lymph nodes (tdLN), and recruitment of activated T cells to the tumor site. As tumors progress, TLS maintenance becomes independent of T cell egress from tdLN, coinciding with a significant reduction of cDC1 migration to tdLN. Instead, mature cDC1 accumulate within intratumoral CCR7 ligand-enriched stromal hubs. Notably, timed depletion of cDC1 or disruption of their migration to these stromal hubs after TLS are formed alters TLS maintenance. Importantly, we found that cDC1-mediated antigen presentation to both CD4+ and CD8+ T cells and intact CD40 signaling, is critical for the maintenance of TLS, the preservation of the TFH cell pool, the formation of germinal center and the production of tumor-specific IgG antibodies. These findings underscore the key role of mature cDC1 in establishing and maintaining functional TLS within tumor lesions and highlight the potential for cDC1-targeting therapies as a promising strategy to enhance TLS function and improve anti-tumor immunity in patients with cancer.

Unsupervised multi-scale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypes

Cell clustering is an essential step in uncovering cellular architectures in single cell RNA-sequencing (scRNA-seq) data. However, the existing cell clustering approaches are not well designed to dissect complex structures of cellular landscapes at a finer resolution. Here, we develop a multi-scale clustering (MSC) approach to construct sparse cell-cell correlation network for identifying de novo cell types and subtypes at multiscale resolution in an unsupervised manner. Based upon simulated, silver and gold standard data as well as real scRNA-seq data in diseases, MSC showed much improved performance in comparison to established benchmark methods, and identified biologically meaningful cell hierarchy to facilitate the discovery of novel disease associated cell subtypes and mechanisms.

Acute Myeloid Leukemia Skews Therapeutic WT1-specific CD8 TCR-T Cells Towards an NK-like Phenotype that Compromises Function and Persistence

Acute myeloid leukemia (AML) that is relapsed and/or refractory post-allogeneic hematopoietic cell transplantation (HCT) is usually fatal. In a prior study, we demonstrated that AML relapse in high-risk patients was prevented by post-HCT immunotherapy with Epstein-Barr virus (EBV)-specific donor CD8+ T cells engineered to express a high-affinity Wilms Tumor Antigen 1 (WT1)-specific T-cell receptor (TTCR-C4). However, in the present study, infusion of EBV- or Cytomegalovirus (CMV)-specific TTCR-C4 did not clearly improve outcomes in fifteen patients with active disease post-HCT. TCRC4-transduced EBV-specific T cells persisted longer post-transfer than CMV-specific T cells. Persisting TTCR-C4 skewed towards dysfunctional natural killer-like terminal differentiation, distinct from the dominant exhaustion programs reported for T-cell therapies targeting solid tumors. In one patient with active AML post-HCT, a sustained TTCR-C4 effector-memory profile correlated with long-term TTCR-C4 persistence and disease control. These findings reveal complex mechanisms underlying AML-induced T-cell dysfunction, informing future therapeutic strategies for addressing post-HCT relapse.

Integrative analysis of single-Cell RNA sequencing and experimental validation in the study of abdominal aortic aneurysm progression

BACKGROUND

Abdominal aortic aneurysm (AAA) is a complex vascular disorder characterized by the progressive dilation of the abdominal aorta, with a high risk of rupture and mortality. Understanding the cellular interactions and molecular mechanisms underlying AAA development is critical for identifying potential therapeutic targets.

METHODS

This study utilized datasets GSE197748, GSE164678 and GSE183464 from the GEO database, encompassing bulk and single-cell RNA sequencing data from AAA and control samples. We performed principal component analysis, differential expression analysis, and functional enrichment analysis to identify key pathways involved in AAA. Cell-cell interactions were investigated using CellPhoneDB, focusing on fibroblasts, vascular smooth muscle cells (VSMCs), and macrophages. We further validated our findings using a mouse model of AAA induced by porcine pancreatic enzyme infusion, followed by gene expression analysis and co-immunoprecipitation experiments.

RESULTS

Our analysis revealed significant alterations in gene expression profiles between AAA and control samples, with a pronounced immune response and cell adhesion pathways being implicated. Single-cell RNA sequencing data highlighted an increased proportion of pro-inflammatory macrophages, along with changes in the composition of fibroblasts and VSMCs in AAA. CellPhoneDB analysis identified critical ligand-receptor interactions, notably collagen type I alpha 1 chain (COL1A1)/COL1A2-CD18 and thrombospondin 1 (THBS1)-CD3, suggesting complex communication networks between fibroblasts and VSMCs. In vivo experiments confirmed the upregulation of these genes in AAA mice and demonstrated the functional interaction between COL1A1/COL1A2 and CD18.

CONCLUSION

The interaction between fibroblasts and VSMCs, mediated by specific ligand-receptor pairs such as COL1A1/COL1A2-CD18 and THBS1-CD3, plays a pivotal role in AAA pathogenesis.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

Cell type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures

Identifying the molecular effects of human genetic variation across cellular contexts is crucial for understanding the mechanisms underlying disease-associated loci, yet many cell types and developmental stages remain underexplored. Here, we harnessed the potential of heterogeneous differentiating cultures (HDCs), an in vitro system in which pluripotent cells asynchronously differentiate into a broad spectrum of cell types. We generated HDCs for 53 human donors and collected single-cell RNA sequencing data from over 900,000 cells. We identified expression quantitative trait loci in 29 cell types and characterized regulatory dynamics across diverse differentiation trajectories. This revealed novel regulatory variants for genes involved in key developmental and disease-related processes while replicating known effects from primary tissues and dynamic regulatory effects associated with a range of complex traits.

Single-Cell RNA Sequencing of PBMCs Identified Junction Plakoglobin (JUP) as Stratification Biomarker for Endometriosis

This study aimed to identify unique characteristics in the peripheral blood mononuclear cells (PBMCs) of endometriosis patients and develop a non-invasive early diagnostic tool. Using single-cell RNA sequencing (scRNA-seq), we constructed the first single-cell atlas of PBMCs from endometriosis patients based on 107,964 cells and 25,847 genes. Within CD16+ monocytes, we discovered JUP as a dysregulated gene. To assess its diagnostic potential, we measured peritoneal fluid (PF) and serum JUP levels in a large cohort of 199 patients including 20 women with ovarian cancer (OC). JUP was barely detectable in PF but was significantly elevated in the serum of patients with endometriosis and OC, with levels 1.33 and 2.34 times higher than controls, respectively. Additionally, JUP was found in conditioned culture media of CD14+/CD16+ monocytes aligning with our scRNA-seq data. Serum JUP levels correlated with endometriosis severity and endometrioma presence but were unaffected by dysmenorrhea, menstrual cycle, or adenomyosis. When combined with CA125 (cancer antigen 125) JUP enhanced the specificity of endometriosis diagnosis from 89.13% (CA125 measured alone) to 100%. While sensitivity remains a challenge at 19%, our results suggest that JUP's potential to enhance diagnostic accuracy warrants additional investigation. Furthermore, employing serum JUP as a stratification marker unlocked the potential to identify additional endometriosis-related genes, offering novel insights into disease pathogenesis.