Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris

Krüppel-like factor 5 remodels lipid metabolism in exercised skeletal muscle

Regular physical activity induces a variety of health benefits, preventing and counteracting diseases caused by a sedentary lifestyle. However, the molecular underpinnings of skeletal muscle plasticity in exercise remain poorly understood. We identified a role of the Krüppel-Like Factor 5 (Klf5) in this process, in particular in the regulation of lipid homeostasis. Surprisingly, gain- and loss-of-function studies in muscle in vivo revealed seemingly opposite functions of Klf5 in the response to an acute exercise bout and chronic training, modulating lipid oxidation and synthesis, respectively. Thus, even though only transiently induced, the function of Klf5 is complex and fundamental for a normal long-term training response. These findings highlight the importance of this mediator of external stress response to adaptive remodeling of skeletal muscle tissue.

OSBP Participates in Neural Damage Repair by Regulating Lysosome Transport Under Oxidative Stress

Oxidative stress is a major pathological factor in acute brain injury, such as traumatic brain injury (TBI). As highly branched cells, the transport of lysosomes plays a crucial role in neuronal homeostasis. However, the effects and mechanisms of oxidative damage on axonal lysosome transport remain unknown. In this study, we demonstrated that the downregulation of the membrane lipid orchestrator oxysterol-binding protein (OSBP) induced by oxidative stress alters the subcellular distribution of lysosomes in neurons through regulating lysosomal phosphatidylinositol-4-monophosphate (PI(4)P)/phosphatidylinositol-3-monophosphate (PI(3)P) contents, thus disrupting lysosomal transport. The results of the cell experiments confirmed the occurrence of an autophagic pressure burst, disordered anterograde lysosome transport, and an imbalance in the PI(4)P/PI(3)P ratio in neurons after H2O2 treatment. Mechanistically, oxidative damage reduced neuronal OSBP protein levels, thus contributing to lysosomal PI(4)P storage. Furthermore, a protein‒liposome binding assay revealed that compared with liposomes containing PI(4)P, liposomes containing PI(3)P or cholesterol presented decreased coprecipitation of Arl8. The overexpression of OSBP restored the PI(4)P/PI(3)P content, improved the binding ability of Arl8 to bind to lysosomes, increased lysosome localization in neurites, and promoted axonal injury repair. Finally, overexpression of neuronal OSBP through adeno-associated virus intervention in vivo alleviated dendritic damage and improved the neurological function of mice with TBI. Taken together, these findings suggest that disturbance of OSBP induced by oxidative stress results in abnormal lysosomal distribution and contributes to neuronal malfunction in TBI, and OSBP could be a potential target to promote neuronal repair and regeneration by regulating lysosomal lipid composition and axonal localization.

SciGeneX: enhancing transcriptional analysis through gene module detection in single-cell and spatial transcriptomics data

The standard pipeline to analyze single-cell RNA-seq or spatial transcriptomics data focuses on a gene-centric approach that overlooks the collective behavior of genes. However, understanding cell populations necessitates recognizing intricate combinations of activated and repressed pathways. Therefore, a broader view of gene behavior offers more accurate insights into cellular heterogeneity in single-cell or spatial transcriptomics data. Here, we describe SciGeneX (Single-cell informative Gene eXplorer), a R package implementing a neighborhood analysis and a graph partitioning method to generate co-expression gene modules. These modules, whether shared or restricted to cell populations, collectively reflect cellular heterogeneity. Their combinations are able to highlight specific cell populations, even rare ones. SciGeneX uncovers rare and novel cell populations that were not observed before in human thymus spatial transcriptomics data. We show that SciGeneX outperforms existing methods on both artificial and experimental datasets. Overall, SciGeneX will aid in unravelling cellular and molecular diversity in single-cell and spatial transcriptomics studies.

Microenvironmental determinants of endothelial cell heterogeneity

During development, endothelial cells (ECs) undergo an extraordinary specialization by which generic capillary microcirculatory networks spanning from arteries to veins transform into patterned organotypic zonated blood vessels. These capillary ECs become specialized to support the cellular and metabolic demands of each specific organ, including supplying tissue-specific angiocrine factors that orchestrate organ development, maintenance of organ-specific functions and regeneration of injured adult organs. Here, we illustrate the mechanisms by which microenvironmental signals emanating from non-vascular niche cells induce generic ECs to acquire specific inter-organ and intra-organ functional attributes. We describe how perivascular, parenchymal and immune cells dictate vascular heterogeneity and capillary zonation, and how this system is maintained through tissue-specific signalling activated by vasculogenic and angiogenic factors and deposition of matrix components. We also discuss how perturbation of organotypic vascular niche cues lead to erasure of EC signatures, contributing to the pathogenesis of disease processes. We also describe approaches that use reconstitution of tissue-specific signatures of ECs to promote regeneration of damaged organs.

Antibody-Fab and -Fc features promote Mycobacterium tuberculosis restriction

Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), a leading cause of death by an infectious disease globally, has no efficacious vaccine. Antibodies are implicated in M. tuberculosis control, but the mechanisms of action remain poorly understood. We assembled a library of monoclonal antibodies (mAb) and screened for M. tuberculosis-restrictive activity in mice, identifying protective antibodies targeting diverse antigens. To dissect the mechanism of mAb-mediated M. tuberculosis restriction, we optimized a protective lipoarabinomannan-specific mAb, generating Fc variants. In vivo analysis of these Fc variants revealed a role for Fc-effector function in M. tuberculosis restriction. Restrictive Fc variants altered distribution of M. tuberculosis across innate immune cells. Single-cell transcriptomics highlighted distinctly activated pathways within innate immune cell subpopulations, identifying early activation of neutrophils as a key signature of mAb-mediated M. tuberculosis restriction. Therefore, antibody-mediated restriction of M. tuberculosis is associated with reorganization of the tissue-level immune response to infection and depends on the collaboration of antibody Fab and Fc.

Key Connectomes and Synaptic-Compartment-Specific Risk Genes Drive Pathological α-Synuclein Spreading

Previous studies have suggested that pathological α-synuclein (α-Syn) mainly transmits along the neuronal network, but several key questions remain unanswered: 1) How many and which connections in the connectome are necessary for predicting the progression of pathological α-Syn? 2) How to identify risk genes that affect pathology spreading functioning at presynaptic or postsynaptic regions, and are these genes enriched in different cell types? Here, these questions are addressed with novel mathematical models. Strikingly, the spreading of pathological α-Syn is predominantly determined by the key subnetworks composed of only 2% of the strongest connections in the connectome. Genes associated with the selective vulnerability of brain regions to pathological α-Syn transmission are further analyzed to distinguish those functioning at presynaptic versus postsynaptic regions. Those risk genes are significantly enriched in microglial cells of presynaptic regions and neurons of postsynaptic regions. Gene regulatory network analyses are then conducted to identify "key drivers" of genes responsible for selective vulnerability and overlapping with Parkinson's disease risk genes. By identifying and discriminating between key gene mediators of transmission operating at presynaptic and postsynaptic regions, this study has demonstrated for the first time that these are functionally distinct processes.

Fibroblast reprogramming in the dura mater of NTG-induced migraine-related chronic hypersensitivity model drives monocyte infiltration via Angptl1-dependent stromal signaling

BACKGROUND

Migraine, characterized by recurrent episodes of severe headache, remains mechanistically enigmatic. While traditional theories emphasize trigeminovascular activation, the role of meningeal stromal-immune crosstalk in disease chronicity is poorly understood.

METHODS

A migraine-related chronic hypersensitivity model was utilized via intermittent intraperitoneal nitroglycerin (NTG, 10 mg/kg, every other day for 9 days) and peripheral mechanical hypersensitivity was assessed using von Frey filaments. Single-cell RNA sequencing (scRNA-seq) was performed on dura tissues to construct a cellular atlas of NTG-induced remodeling. These data were then integrated with migraine genome-wide association study (GWAS) risk genes, cell-cell interaction networks, and transcriptional regulation analysis to dissect NTG-driven meningeal remodeling.

RESULTS

The NTG-induced migraine-related chronic hypersensitivity model demonstrated sustained mechanical allodynia, as evidenced by significantly decreased paw withdrawal thresholds (p < 0.0001). Single-cell profiling of the dura mater revealed a 2.4-fold expansion of a pro-inflammatory fibroblast subpopulation (Fibro_c5: 1.9% in Vehicle vs. 4.6% in NTG group), which exhibited marked activation of TNF-α/NF-κB signaling pathways (normalized enrichment score [NES] = 1.83). Concomitantly, we observed an 82% increase in meningeal monocytes (5.7-10.4%) that showed preferential interaction with Fibro_c5 fibroblasts through Angptl1-mediated stromal-immune crosstalk (log2 fold change = 1.41). Regulatory network analysis identified Mafk as the upstream transcriptional regulator orchestrating Angptl1 expression in this pathological communication axis.

CONCLUSION

Our study reveals that NTG reprograms meningeal fibroblasts to expand a pro-inflammatory fibroblast subtype, which drives migraine-related chronic hypersensitivity through TNF-α/NF-κB signaling and Angptl1-mediated monocyte crosstalk. The identified Mafk-Angptl1 axis presents a potential therapeutic target, though human validation remains essential.

TLR7 responses in glomerular macrophages accelerate the progression of glomerulonephritis in NZBWF1 mice

Systemic lupus erythematosus is a systemic autoimmune disease characterized by the production of autoantibodies and damage to multiple organs. Glomerulonephritis, a manifestation involving glomerular deposition of immune complexes and complement components, significantly contributes to disease morbidity. Although an endosomal single-stranded RNA sensor [Toll-like receptor 7 (TLR7)] is known to drive glomerulonephritis by promoting autoantibody production in B cells, the contribution of macrophage TLR7 responses to glomerulonephritis remains poorly understood. Here, we have examined Tlr7‒/‒ NZBWF1 (New Zealand Black/New Zealand White F1) mice and found that TLR7 deficiency ameliorates lupus nephritis by abolishing autoantibody production against RNA-associated antigens, C3 deposition, and macrophage accumulation in glomeruli. Furthermore, TLR7 signaling increased CD31 expression on glomerular endothelial cells and Ly6Clow macrophages but not on T and B cells, suggesting that CD31 mediates TLR7-dependent migration of monocytes into glomeruli. Compared to their splenic counterparts, glomerular macrophages produced IL-1β in a TLR7-dependent manner. In addition, single-cell RNA sequencing of glomerular macrophages revealed that TLR7 signaling induced expression of lupus-associated genes, including those encoding Chitinase 3 like 1, ferritin heavy chain 1, IKKε, and complement factor B (CfB). Although serum CfB did not increase in NZBWF1 mice, TLR7-dependent CfB protein expression was detected in glomerular macrophages. In addition, TLR7 signaling promoted C3 cleavage and deposition predominantly on mesangial cells. These findings suggest that TLR7 responses in glomerular macrophages accelerate the progression of glomerulonephritis in NZBWF1 mice.

Cholinergic regulation of thymocyte negative selection

The immune and nervous systems use a common chemical language for communication, namely, the cholinergic signaling involving acetylcholine (ACh) and its receptors (AChRs). Whether and how this language also regulates the development of the immune system is poorly understood. Here, we show that mouse CD4+CD8+ double-positive thymocytes express high levels of α9 nicotinic AChR (nAChR) and that this receptor controls thymic negative selection. α9 nAChR-deficient mice show an altered T cell receptor (TCR) repertoire and reduced CD4+ and CD8+ T cells in a mixed bone marrow chimera setting. α9 nAChR-mediated signaling regulates TCR strength and thymocyte survival. Thymic tuft cells, B cells and some T cells express choline acetyltransferase and are potential ACh sources, with ACh derived from T cells having the most important role. Furthermore, α9 nAChR deficiency during thymocyte development contributes to the altered development of autoimmune diseases in mice. Our results thus reveal a mechanism controlling immune cell development that involves cholinergic signaling.

A dynamic and multimodal framework to define microglial states

The widespread use of single-cell RNA sequencing has generated numerous purportedly distinct and novel subsets of microglia. Here, we challenge this fragmented paradigm by proposing that microglia exist along a continuum rather than as discrete entities. We identify a methodological over-reliance on computational clustering algorithms as the fundamental issue, with arbitrary cluster numbers being interpreted as biological reality. Evidence suggests that the observed transcriptional diversity stems from a combination of microglial plasticity and technical noise, resulting in terminology describing largely overlapping cellular states. We introduce a continuous model of microglial states, where cell positioning along the continuum is determined by biological aging and cell-specific molecular contexts. The model accommodates the dynamic nature of microglia. We advocate for a parsimonious approach toward classification and terminology that acknowledges the continuous spectrum of microglial states, toward a robust framework for understanding these essential immune cells of the CNS.

Navigating single-cell RNA-sequencing: protocols, tools, databases, and applications

Single-cell RNA-sequencing (scRNA-seq) technology brought about a revolutionary change in the transcriptomic world, paving the way for comprehensive analysis of cellular heterogeneity in complex biological systems. It enabled researchers to see how different cells behaved at single-cell levels, providing new insights into the process. However, despite all these advancements, scRNA-seq also experiences challenges related to the complexity of data analysis, interpretation, and multi-omics data integration. In this review, these complications were discussed in detail, directly pointing at the optimization of scRNA-seq approaches and understanding the world of single-cell and its dynamics. Different protocols and currently functional single-cell databases were also covered. This review highlights different tools for the analysis of scRNA-seq and their methodologies, emphasizing innovative techniques that enhance resolution and accuracy at a single-cell level. Various applications were explored across domains including drug discovery, tumor microenvironment (TME), biomarker discovery, and microbial profiling, and case studies were discussed to explain the importance of scRNA-seq by uncovering novel and rare cell types and their identification. This review underlines a crucial aspect of scRNA-seq in the advancement of personalized medicine and highlights its potential to understand the complexity of biological systems.

Amyloidogenic and non-amyloidogenic pathways of amyloid precursor protein processing in oligodendrocytes

Excessive accumulation of toxic amyloid-β (Aβ) species in the brain is a major pathological process triggering neurodegeneration in Alzheimer's disease (AD). Recent studies indicate that both neurons and glial cells, including oligodendrocyte lineages (OLs), contribute to brain homeostasis and affect AD pathology; however, the roles of oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLGs) in AD remain to be fully elucidated. This study examined Aβ production and related protein expression in primary cultured OLs. Primary cultured OLs produced Aβ40 and Aβ42 and expressed amyloid precursor protein (APP), β-secretase (BACE1) and γ-secretase (PS1) as well as α-secretase (ADAM10). OLGs express APP770 in addition to APP695. Treatment with a γ-secretase inhibitor reduced Aβ40 and Aβ42 production levels derived from OPCs/OLGs and suppressed OPC differentiation. Additionally, conditioned media from OLGs improved neuronal cell viability under oxidative stress and contained higher levels of sAPPα compared to OPCs. The neuroprotective effect of OLG was diminished by a sAPPα inhibitor, suggesting that OLG-derived sAPPα protects neurons under oxidative stress. These findings revealed that OLs produce pathogenic Aβ40/42 via the amyloidogenic pathway and secrete neuroprotective sAPPα via the non-amyloidogenic pathway. Elucidating the pathological shift from beneficial non-amyloidogenic to harmful amyloidogenic processes in OLs during AD onset and progression would provide crucial insights into novel therapeutic approaches.

IL-10 sensing by lung interstitial macrophages prevents bacterial dysbiosis-driven pulmonary inflammation and maintains immune homeostasis

Crosstalk between the immune system and the microbiome is critical for maintaining immune homeostasis. Here, we examined this communication and the impact of immune-suppressive IL-10 signaling on pulmonary homeostasis. We found that IL-10 sensing by interstitial macrophages (IMs) is required to prevent spontaneous lung inflammation. Loss of IL-10 signaling in IMs initiated an inflammatory cascade through the activation of classical monocytes and CD4+ T cell subsets, leading to chronic lung inflammation with age. Analyses of antibiotic-treated and germ-free mice established that lung inflammation in the animals lacking IL-10 signaling was triggered by commensal bacteria. 16S rRNA sequencing revealed Delftia acidovorans and Rhodococcus erythropolis as potential drivers of lung inflammation. Intranasal administration of these bacteria or transplantation of human fecal microbiota elicited lung inflammation in gnotobiotic Il10-deficient mice. These findings highlight that IL-10 sensing by IMs contributes to pulmonary homeostasis by preventing lung inflammation caused by commensal dysbiosis.

A single cell atlas of the mouse seminal vesicle

During mammalian reproduction, sperm are delivered to the female reproductive tract bathed in a complex medium known as seminal fluid, which plays key roles in signaling to the female reproductive tract and in nourishing sperm for their onwards journey. Along with minor contributions from the prostate and the epididymis, the majority of seminal fluid is produced by a somewhat understudied organ known as the seminal vesicle. Here, we report the first single-cell RNA-seq atlas of the mouse seminal vesicle, generated using tissues obtained from 23 mice of varying ages, exposed to a range of dietary challenges. We define the transcriptome of the secretory cells in this tissue, identifying a relatively homogeneous population of the epithelial cells which are responsible for producing the majority of seminal fluid. We also define the immune cell populations-including large populations of macrophages, dendritic cells, T cells, and NKT cells-which have the potential to play roles in producing the various immune mediators present in seminal plasma. Together, our data provide a resource for understanding the composition of an understudied reproductive tissue, with potential implications for paternal control of offspring development and metabolism.

Gene delivery of AGAT and GAMT boosts creatine levels in creatine transporter deficiency patient fibroblasts

Creatine is a critical metabolite used to buffer cellular energy demands in highly energetic tissues such as the brain and muscle. Genetic defects in endogenous creatine synthesis or transport across cellular membranes lead to a common set of phenotypes referred to as Cerebral Creatine Deficiency Syndrome (CCDS). The most common form of CCDS is Creatine Transporter 1 (CT1) Deficiency (CTD). It accounts for ~ 70% of cases and results from loss-of-function mutations in the X-linked gene SLC6A8. Affected individuals suffer from intellectual disability, autistic-like behaviors, and epilepsy. There are currently no effective therapies for this disorder, but gene therapy has emerged as a potential approach. The two enzymes which comprise the endogenous creatine synthetic pathway (AGAT and GAMT) are selectively expressed by specific cell types throughout the body. However, after synthesized, creatine uptake relies on the protein product of SLC6A8, CT1, to transport creatine into target cell types. We hypothesized that gene delivery of GATM (encoding AGAT) and GAMT into end-user cell types would bypass the need for CT1, allowing for intracellular synthesis of creatine. We tested this strategy in two human cell types: HEK293T cells and primary fibroblasts. Co-delivery of GATM and GAMT increased internal creatine concentrations by 7.6-fold in HEK293T cells and 12.3-fold in healthy control fibroblasts. We then employed this approach to primary fibroblasts from patients with CTD. This resulted in an up to 11.6-fold increase in intracellular creatine concentrations, far exceeding the intracellular concentration of creatine in healthy control fibroblasts. Importantly, overexpression of AGAT and GAMT resulted in proper targeting of these enzymes to their natural cellular compartment and did not impair the growth of patient fibroblasts. These findings establish gene therapy with GATM and GAMT as a potential strategy for patients with CTD.

Unveiling cell-type-specific mode of evolution in comparative single-cell expression data

While methodology for determining the mode of evolution in coding sequences has been well established, evaluation of adaptation events in emerging types of phenotype data needs further development. Here we propose an analysis framework (expression variance decomposition, EVaDe) for comparative single-cell expression data based on phenotypic evolution theory. After decomposing the gene expression variance into separate components, we use two strategies to identify genes exhibiting large between-taxon expression divergence and small within-cell-type expression noise in certain cell types, attributing this pattern to putative adaptive evolution. In a dataset of primate prefrontal cortex, we find that such human-specific key genes enrich with neurodevelopment-related functions, while most other genes exhibit neutral evolution patterns. Specific neuron types are found to harbor more of these key genes than other cell types, thus likely to have experienced more extensive adaptation. Reassuringly, at molecular sequence level, the key genes are significantly associated with the rapidly evolving conserved non-coding elements. An additional case analysis comparing the naked mole-rat (NMR) with the mouse suggests that innate-immunity-related genes and cell types have undergone putative expression adaptation in NMR. Overall, the EVaDe framework may effectively probe adaptive evolution mode in single-cell expression data.

Modulating the Protein Corona on Nanoparticles by Finely Tuning Cross-Linkers Improves Macrophage Targeting in Oral Small Interfering RNA Delivery

The protein corona (PC) plays an important role in regulating the in vivo fate of nanoparticles (NPs). Modulating the surface chemical properties of NPs to control PC formation provides an alternative impetus for the oral delivery of small interfering RNA (siRNA). Herein, using tripolyphosphate (TPP), hyaluronic acid, and poly-γ-glutamic acid as cross-linkers, three types of mannose-modified trimethyl chitosan-cysteine (MTC)-based NPs with distinct surface chemistries were prepared to encapsulate siRNA via ionic gelation. The MTC-based NPs that were cross-linked exclusively with TPP (MTC/TPP/siRNA NPs) exhibited greater thiol group accessibility on their surfaces, resulting in a stronger affinity for apolipoprotein (APO) B48 during translocation across intestinal epithelia. Moreover, intracellular transport of MTC/TPP/siRNA NPs via the endoplasmic reticulum and Golgi apparatus further increased adsorption of APOB48, a key component of chylomicrons, which follow a similar transport pathway. Benefiting from the elevated APOB48 levels within the PC, the orally delivered MTC/TPP/siRNA NPs showed higher uptake by hepatic macrophages and better therapeutic efficacy for acute liver injury. Our results elucidate the role of NP surface chemical characteristics and translocation mechanisms across intestinal epithelia in forming oral PC, providing valuable insights for designing NPs that achieve effective oral gene delivery by customizing PC formation in vivo.

RAPID LEAF FALLING 1 facilitates chemical defoliation and mechanical harvesting in cotton

Chemical defoliation stands as the ultimate tool in enabling the mechanical harvest of cotton, offering economic and environmental advantages. However, the underlying molecular mechanism that triggers leaf abscission through defoliant remains unsolved. In this study, we meticulously constructed a transcriptomic atlas through single-nucleus mRNA sequencing (snRNA-seq) of the abscission zone (AZ) from cotton petiole. We identified two newly-formed cell types, abscission cells and protection layer cells in cotton petiole AZ after defoliant treatment. GhRLF1 (RAPID LEAF FALLING 1), as one of the members of the cytokinin oxidase/dehydrogenase (CKX) gene family, was further characterized as a key marker gene unique to the abscission cells following defoliant treatment. Overexpression of GhRLF1 resulted in reduced cytokinin accumulation and accelerated leaf abscission. Conversely, CRISPR/Cas9-mediated loss of GhRLF1 function appeared to delay this process. Its interacting regulators, GhWRKY70, acting as "Pioneer" activator, and GhMYB108, acting as "Successor" activator, orchestrate a sequential modulation of GhWRKY70/GhMYB108-GhRLF1-CTK (cytokinin) within the AZ to regulate cotton leaf abscission. GhRLF1 not only regulates leaf abscission but also reduces cotton yield. Consequently, transgenic lines that exhibit rapid leaf falling and require less defoliant but show unaffected cotton yield were developed for mechanical harvesting. This was achieved using a defoliant-induced petiole-specific promoter, proPER21, to drive GhRLF1 (proPER21::RLF1). This pioneering biotechnology offers a new strategy for the chemical defoliation of machine-harvested cotton, ensuring stable production and reducing leaf debris in harvested cotton, thereby enhancing environmental sustainability.

Histone chaperones coupled to DNA replication and transcription control divergent chromatin elements to maintain cell fate

The manipulation of DNA replication and transcription can be harnessed to control cell fate. Central to the regulation of these DNA-templated processes are histone chaperones, which in turn are emerging as cell fate regulators. Histone chaperones are a group of proteins with diverse functions that are primarily involved in escorting histones to assemble nucleosomes and maintain the chromatin landscape. Whether distinct histone chaperone pathways control cell fate and whether they function using related mechanisms remain unclear. To address this, we performed a screen to assess the requirement of diverse histone chaperones in the self-renewal of hematopoietic stem and progenitor cells. Remarkably, all candidates were required to maintain cell fate to differing extents, with no clear correlation with their specific histone partners or DNA-templated process. Among all the histone chaperones, the loss of the transcription-coupled histone chaperone SPT6 most strongly promoted differentiation, even more than the major replication-coupled chromatin assembly factor complex CAF-1. To directly compare how DNA replication- and transcription-coupled histone chaperones maintain stem cell self-renewal, we generated an isogenic dual-inducible system to perturb each pathway individually. We found that SPT6 and CAF-1 perturbations required cell division to induce differentiation but had distinct effects on cell cycle progression, chromatin accessibility, and lineage choice. CAF-1 depletion led to S-phase accumulation, increased heterochromatic accessibility (particularly at H3K27me3 sites), and aberrant multilineage gene expression. In contrast, SPT6 loss triggered cell cycle arrest, altered accessibility at promoter elements, and drove lineage-specific differentiation, which is in part influenced by AP-1 transcription factors. Thus, CAF-1 and SPT6 histone chaperones maintain cell fate through distinct mechanisms, highlighting how different chromatin assembly pathways can be leveraged to alter cell fate.

scCompass: An Integrated Multi-Species scRNA-seq Database for AI-Ready

Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here scCompass is proposed, which provides a comprehensive resource designed to build large-scale, multi-species, and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from nearly 105 million single cells across 13 species. Using this extensive dataset, it is able to identify stable expression genes (SEGs) and organ-specific expression genes (OSGs) in humans and mice. Different scalable datasets are provided that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art single-cell foundation models. In summary, scCompass is highly efficient and scalable database for AI-ready, which combined with user-friendly data sharing, visualization, and online analysis, greatly simplifies data access and exploitation for researchers in single-cell biology (http://www.bdbe.cn/kun).

Resistance exercise and mechanical overload upregulate vimentin for skeletal muscle remodeling

We adopted a proteomic and follow-through approach to investigate how mechanical overload (MOV) potentially affects novel targets in skeletal muscle, and how a perturbation in this response could potentially affect the adaptive response. First, we determined that 10 wk of resistance training in 15 college-aged females increased sarcolemmal-associated protein content (+10.1%, P < 0.05). Sarcolemmal protein isolates were then queried using mass spectrometry-based proteomics, ∼10% (38/387) of proteins putatively associated with the sarcolemma or extracellular matrix (ECM) were upregulated (>1.5-fold, P < 0.05), and one target (intermediate filament vimentin; VIM) warranted further investigation due to its correlation to myofiber hypertrophy (r = 0.652, P = 0.009). VIM expression was then examined in 4-mo-old C57BL/6J mice following 10 and 20 days of plantaris MOV via synergist ablation. Relative to Sham (control) mice, VIM mRNA and protein content was significantly higher in MOV mice, and immunohistochemistry indicated that VIM predominantly resided in the ECM. MOV experiments were replicated in Pax7-DTA (satellite cell depleted) mice, which reduced VIM in the ECM by ∼74%. A third MOV experiment was performed in C57BL/6 mice intramuscularly injected with either AAV9-scrambled (control) or AAV9-VIM-shRNA. Although VIM-shRNA mice possessed lower VIM in the ECM (∼45%), plantaris masses in response to MOV were similar between groups. However, VIM-shRNA mice possessed smaller and more centrally nucleated MyHCemb-positive fibers in response to MOV. In summary, skeletal muscle VIM appears to be enriched in the ECM following MOV, satellite cells may regulate its expression, and a disruption in expression during MOV leads to an excessive regenerative phenotype.NEW & NOTEWORTHY Our highly integrative approach suggests that skeletal muscle vimentin seems to function as a mechanosensitive protein that becomes enriched in the extracellular matrix following MOV. Satellite cells may play a role in regulating their expression, and an exaggerated regenerative response occurs when vimentin expression becomes dysregulated during mechanical overload. Although these data implicate vimentin in aiding with tissue remodeling following MOV, more data are needed to determine the functional ramifications of VIM response deficiencies.

Multi-view clustering for single-cell RNA-seq data based on graph fusion

Single-cell RNA sequencing (scRNA-seq) provides transcriptome profiling of individual cells, allowing for in-depth studies of cell heterogeneity at cell resolution. While cell clustering lays the basic foundation of scRNA-seq data analysis, the high-dimensionality and frequent dropout events of the data raise great challenges. Although plenty of dedicated clustering methods have been proposed, they often fail to fully explore the underlying data structure. Here, we introduce scMCGF, a new multi-view clustering algorithm based on graph fusion. It utilizes multi-view data generated from transcriptomic data to learn the consistent and complementary information across different view, ultimately constructing a unified graph matrix for robust cell clustering. Specifically, scMCGF utilizes two-dimensional-reduction methods (principal component analysis and diffusion maps) to capture both linear and non-linear characteristics of the data. Additionally, it calculates a cell-pathway score matrix to incorporate pathway-level information. These three features, along with the pre-processed gene expression data, form the multi-view data. scMCGF iteratively refines the structure of similarity graphs of each view through adaptive learning and learns a unified graph matrix by weighting and fusing the individual similarity graph matrix. The final clustering results are obtained by applying the rank constraint on the Laplacian matrix of the unified graph matrix. Experiments results of 13 real data sets reveal that scMCGF outperforms eight state-of-the-art methods in clustering accuracy and robustness. Furthermore, biological analysis validates that the clustering results of scMCGF provide a reliable foundation for downstream investigations.

HRI protein kinase in cytoplasmic heme sensing and mitochondrial stress response: Relevance to hematological and mitochondrial diseases

Most iron in humans is bound in heme used as a prosthetic group for hemoglobin. Heme-regulated inhibitor (HRI) is responsible for coordinating heme availability and protein synthesis. Originally characterized in rabbit reticulocyte lysates, HRI was shown in 1976 to phosphorylate the α-subunit of eukaryotic initiation factor 2, revealing a new molecular mechanism for regulating protein synthesis. Since then, HRI research has mostly been focused on the biochemistry of heme inhibition through direct binding and heme sensing in balancing heme and globin synthesis to prevent proteotoxicity in erythroid cells. Beyond inhibiting translation of highly translated mRNAs, eukaryotic initiation factor 2α phosphorylation also selectively increases translation of certain poorly translated mRNAs, notably activating transcription factor 4 mRNA, for reprogramming of gene expression to mitigate stress, known as the integrated stress response (ISR). In recent years, there have been novel mechanistic insights of HRI-ISR in oxidative stress, mitochondrial function, and erythroid differentiation during heme deficiency. Furthermore, HRI-ISR is activated upon mitochondrial stress in several cell types, establishing the bifunctional nature of HRI protein. The role of HRI and ISR in cancer development and vulnerability is also emerging. Excitingly, the UBR4 ubiquitin ligase complex has been demonstrated to silence the HRI-ISR by degradation of activated HRI proteins, suggesting additional regulatory processes. Together, these recent advancements indicate that the HRI-ISR mechanistic axis is a target for new therapies for hematological and mitochondrial diseases as well as oncology. This review covers the historical overview of HRI biology, the biochemical mechanisms of regulating HRI, and the biological impacts of the HRI-ISR pathway in human diseases.

The molar dose of FAPI administered impacts on the FAP-targeted PET imaging and therapy in mouse syngeneic tumor models

PURPOSE

Since fibroblast activation protein (FAP), one predominant biomarker of cancer associated fibroblasts (CAFs), is highly expressed in the tumor stroma of various epidermal-derived cancers, targeting FAP for tumor diagnosis and treatment has shown substantial potentials in both preclinical and clinical studies. However, in preclinical settings, tumor-bearing mice exhibit relatively low absolute FAP expression levels, leading to challenges in acquiring high-quality PET images using radiolabeled FAP ligands (FAPIs) with low molar activity, because of which a saturation effect in imaging is prone to happen. Moreover, how exactly the molar dose of FAPI administered to a mouse influences the targeted PET imaging and radiotherapy remains unclear now. Therefore, this study aims to investigate the impacts of the molar dose of the administered FAPI on FAP-targeted PET imaging and radiotherapy in mouse syngeneic tumor models.

METHODS

[68Ga]Ga-FAPI-04 with various molar doses of FAPI-04 was administered to wild-type 4T1 tumor-bearing mice, followed by static PET imaging. Sigmoidal curves were generated to analyze the correlation between the standard uptake value (SUV) and the administered molar doses of FAPI-04. Similarly, [177Lu]Lu-DOTAGA.(SA.FAPi)2 with a consistent dose of radioactivity but containing different moles of DOTAGA.(SA.FAPi)2 were injected into 4T1 tumor-bearing mice to assess the therapeutic effect. [68Ga]Ga-FAPI-04 was also applied to different tumor models for PET/CT imaging.

RESULTS

A gradient blocking effect was observed with increasing FAPI molar dose in [68Ga]Ga-FAPI-04 PET imaging and [177Lu]Lu-DOTAGA.(SA.FAPi)2 treatment, with various imaging and therapeutic outcomes. [68Ga]Ga-FAPI-04 PET exhibit potentials to characterize murine derived FAP expression with low molar dose of administered FAPI-04 using various tumor models.

CONCLUSION

The molar dose of FAPI in [68Ga]Ga/[177Lu]Lu-FAPI had a substantial impact on FAP-targeted imaging and therapy in mouse syngeneic tumor models. To acquire enhanced reliability and reproducibility in preclinical situation, it is critical to carefully consider the molar dose of the radiotracer when applying radiolabeled FAP ligands to FAP-targeted imaging and radiotherapy.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

An overview of computational methods in single-cell transcriptomic cell type annotation

The rapid accumulation of single-cell RNA sequencing data has provided unprecedented computational resources for cell type annotation, significantly advancing our understanding of cellular heterogeneity. Leveraging gene expression profiles derived from transcriptomic data, researchers can accurately infer cell types, sparking the development of numerous innovative annotation methods. These methods utilize a range of strategies, including marker genes, correlation-based matching, and supervised learning, to classify cell types. In this review, we systematically examine these annotation approaches based on transcriptomics-specific gene expression profiles and provide a comprehensive comparison and categorization of these methods. Furthermore, we focus on the main challenges in the annotation process, especially the long-tail distribution problem arising from data imbalance in rare cell types. We discuss the potential of deep learning techniques to address these issues and enhance model capability in recognizing novel cell types within an open-world framework.

Decoupled GNNs based on multi-view contrastive learning for scRNA-seq data clustering

Clustering is pivotal in deciphering cellular heterogeneity in single-cell RNA sequencing (scRNA-seq) data. However, it suffers from several challenges in handling the high dimensionality and complexity of scRNA-seq data. Especially when employing graph neural networks (GNNs) for cell clustering, the dependencies between cells expand exponentially with the number of layers. This results in high computational complexity, negatively impacting the model's training efficiency. To address these challenges, we propose a novel approach, called decoupled GNNs, based on multi-view contrastive learning (scDeGNN), for scRNA-seq data clustering. Firstly, this method constructs two adjacency matrices to generate distinct views, and trains them using decoupled GNNs to derive the initial cell feature representations. These representations are then refined through a multilayer perceptron and a contrastive learning layer, ensuring the consistency and discriminability of the learned features. Finally, the learned representations are fused and applied to the cell clustering task. Extensive experimental results on nine real scRNA-seq datasets from various organisms and tissues show that the proposed scDeGNN method significantly outperforms other state-of-the-art scRNA-seq data clustering algorithms across multiple evaluation metrics.

Innate immune training in the neonatal response to sepsis

Neonates, especially those born prematurely, are highly vulnerable to infection-induced mortality. Numerous observational and immunological studies in newborns have shown that live attenuated vaccines have beneficial, non-specific effects (NSEs) against secondary infections to unrelated pathogens. These beneficial effects have been attributed to trained immunity, and emergency granulopoiesis plays an essential role. However, trained immunity has been shown to affect multiple myeloid subsets and how trained immunity influences the host protective response is still undefined. Here we show that Bacillus-Calmette-Guérin (BCG) vaccination improves survival to polymicrobial sepsis by simultaneously reprogramming broad aspects of myelopoiesis. Specifically, BCG vaccination expands multiple myeloid subsets, including the lineage (Lin)-Sca- 1+c-kit+ (LSK) and granulocytic-macrophage progenitors (GMPs), and increases CD11b+Gr1+ cell number, as well as their oxidative metabolism and capacity to stimulate T-cell proliferation in response to sepsis. Single-cell RNA sequencing of neonatal splenocytes suggests that BCG-vaccination changes the broad transcriptional landscape of multiple myeloid subsets. The result is the maturation of various neutrophil and monocyte subsets, stimulation of antimicrobial processes, and suppression of inflammatory pathways and myeloid-derived suppressor cell transcription. These findings reveal that BCG administration early after birth fundamentally reorganizes the myeloid landscape to benefit the subsequent response to polymicrobial infection.

Regional and aging-specific cellular architecture of non-human primate brains

BACKGROUND

Deciphering the functionality and dynamics of brain networks across different regions and age groups in non-human primates (NHPs) is crucial for understanding the evolution of human cognition as well as the processes underlying brain pathogenesis. However, systemic delineation of the cellular composition and molecular connections among multiple brain regions and their alterations induced by aging in NHPs remain largely unresolved.

METHODS

In this study, we performed single-nucleus RNA sequencing on 39 samples collected from 10 brain regions of two young and two aged rhesus macaques using the DNBelab C4 system. Validation of protein expression of signatures specific to particular cell types, brain regions, and aging was conducted through a series of immunofluorescence and immunohistochemistry staining experiments. Loss-of-function experiments mediated by short hairpin RNA (shRNA) targeting two age-related genes (i.e., VSNL1 and HPCAL4) were performed in U251 glioma cells to verify their aging effects. Senescence-associated beta-galactosidase (SA-β-gal) staining and quantitative PCR (qPCR) of senescence marker genes were employed to assess cellular senescence in U251 cells.

RESULTS

We have established a large-scale cell atlas encompassing over 330,000 cells for the rhesus macaque brain. Our analysis identified numerous gene expression signatures that were specific to particular cell types, subtypes, brain regions, and aging. These datasets greatly expand our knowledge of primate brain organization and highlight the potential involvement of specific molecular and cellular components in both the regionalization and functional integrity of the brain. Our analysis also disclosed extensive transcriptional alterations and cell-cell connections across brain regions in the aging macaques. Finally, by examining the heritability enrichment of human complex traits and diseases, we determined that neurological traits were significantly enriched in neuronal cells and multiple regions with aging-relevant gene expression signatures, while immune-related traits exhibited pronounced enrichment in microglia.

CONCLUSIONS

Taken together, our study presents a valuable resource for investigating the cellular and molecular architecture of the primate nervous system, thereby expanding our understanding of the mechanisms underlying brain function, aging, and disease.

ScAGCN: Graph Convolutional Network with Adaptive Aggregation Mechanism for scRNA-seq Data Dimensionality Reduction

With the development of single-cell RNA-sequencing (scRNA-seq) technology, scRNA-seq data analysis suffers huge challenges due to large scale, high dimensionality, high noise, and high sparsity. To achieve accurately embedded representation in the large-scale scRNA-seq data, we try to design a novel graph convolutional network with an adaptive aggregation mechanism. Based on the assumption that the aggregation order of different cells would be different, a graph convolutional network with an adaptive aggregation-based dimensionality reduction algorithm for scRNA-seq data is developed, named scAGCN. In scAGCN, a preprocessing consisting of quality control and feature selection is implemented. Then, an approximate nearest neighbor graph is rapidly constructed. Finally, a graph convolutional network with an adaptive aggregation mechanism is constructed, in which the neighborhood selection strategy based on node distribution and similarity boxplots is designed, and the aggregation function is optimized by defining a similarity measurement between neighborhood nodes and the central node. The results show that scAGCN outperforms existing dimensionality reduction methods on 15 real scRNA-seq datasets, especially in 10 large-scale scRNA-seq datasets.

Upregulating mTOR/S6 K Pathway by CASTOR1 Promotes Astrocyte Proliferation and Myelination in Gpam-/--induced mouse model of cerebral palsy

GPAM, a key enzyme for lipid synthesis, is predominantly expressed in astrocytes (ASTs), where it facilitates lipid supply for myelin formation. Our previous studies identified GPAM as a novel causative gene for cerebral palsy (CP) and led to the development of a CP mouse model with GPAM deficiency (Gpam-/-). The model closely recapitulated the clinical phenotype of children with CP, due to the restricted proliferation of ASTs in the brain, reduced the amount of lipid, thinner brain white matter, and myelin dysplasia. The mammalian target of rapamycin (mTOR) pathway plays an important role in cell proliferation and lipid synthesis. Cytosolic arginine sensor (CASTOR1) interacts with GATOR2 to regulate mTOR complex 1 (mTORC1). Targeted degradation of CASTOR1 can activate the mTOR pathway. However, it remains unclear the involvement of mTOR pathway in neurological diseases such as CP. In this study, we demonstrated that the mTOR pathway was inhibited in Gpam-/- mice. Notably, CASTOR1 could regulate the activity of mTOR/S6K pathway, functioning as a negative upstream regulator. Furthermore, inhibition of CASTOR1 upregulated mTOR/S6K signaling, promoting astrocyte proliferation and myelination, which in turn enhanced motor function in the Gpam-/--induced CP mouse model. Collectively, these findings reveal the role of astrocytic mTOR in the pathogenesis of CP mice, broaden the therapeutic strategies, and provide a promising candidate target for CP treatment.

Single-cell analysis of pig lung leukocytes and their response to influenza infection and oseltamivir therapy

Despite pigs being an important species in influenza A virus (IAV) epidemiology and a reliable preclinical model for human IAV infections, many aspects of the porcine pulmonary immune system remain poorly understood. Here, we characterized the single-cell landscape of lung leukocytes of healthy pigs and then compared them to pigs infected with 2009 pandemic H1N1 IAV with or without oseltamivir antiviral therapy. Our data show conserved features as well as species-specific differences in cell types and cell states compared with human and mouse lung lymphocytes. IAV infection induced a robust antiviral transcriptional response in multiple lymphoid and myeloid cell types, as well as distinct patterns of cell-cell crosstalk. Oseltamivir treatment substantially reduced these responses. Together, our findings describe key events in the pulmonary anti-IAV response of pigs that open new avenues to develop IAV vaccines and therapies. They should also enable the better use of pigs as a model for human IAV infection and immunity.

Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders

BACKGROUND

The intricate shared genetic architecture underlying allergic disorders-including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized.

METHODS

Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders.

RESULTS

A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p < 5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers.

CONCLUSION

Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions.

Correction of dysregulated lipid metabolism normalizes gene expression in oligodendrocytes and prolongs lifespan in female poly-GA C9orf72 mice

Clinical and genetic research links altered cholesterol metabolism with ALS development and progression, yet pinpointing specific pathomechanisms remain challenging. We investigated how cholesterol dysmetabolism interacts with protein aggregation, demyelination, and neuronal loss in ALS. Bulk RNAseq transcriptomics showed decreased cholesterol biosynthesis and increased cholesterol export in ALS mouse models (GA-Nes, GA-Camk2a GA-CFP, rNLS8) and patient samples (spinal cord), suggesting an adaptive response to cholesterol overload. Consequently, we assessed the efficacy of the cholesterol-binding drug 2-hydroxypropyl-β-cyclodextrin (CD) in a fast-progressing C9orf72 ALS mouse model with extensive poly-GA expression and myelination deficits. CD treatment normalized cholesteryl ester levels, lowered neurofilament light chain levels, and prolonged lifespan in female but not male GA-Nes mice, without impacting poly-GA aggregates. Single nucleus transcriptomics indicated that CD primarily affected oligodendrocytes, significantly restored myelin gene expression, increased density of myelinated axons, inhibited the disease-associated oligodendrocyte response, and downregulated the lipid-associated genes Plin4 and ApoD. These results suggest that reducing excess free cholesterol in the CNS could be a viable ALS treatment strategy.

Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning

Atherosclerosis is the major cause of cardiovascular diseases worldwide, and AIDS linked with chronic inflammation and immune activation, increases atherosclerosis risk. The application of bioinformatics and machine learning to identify hub genes for atherosclerosis and AIDS has yet to be reported. Thus, this study aims to identify the hub genes for atherosclerosis and AIDS. Gene expression profiles were downloaded from the Gene Expression Omnibus database. The Robust Multichip Average was performed for data preprocessing, and the limma package was used for screening differentially expressed genes. Enrichment analysis employed GO and KEGG, protein-protein interaction network was constructed. Hub genes were filtered using topological and machine learning algorithms and validated in external cohorts. Then immune infiltration and correlation analysis of hub genes were constructed. Nomogram, receiver operating curve, and single-sample gene set enrichment analysis were applied to evaluate hub genes. This study identified 48 intersecting genes. Enrichment analyses indicated that these genes are significantly enriched in viral response, inflammatory response, and cytokine signaling pathways. CCR5 and OAS1 were identified as common hub genes in atherosclerosis and AIDS for the first time, highlighting their roles in antiviral immunity, inflammation and immune infiltration. These findings contributed to understanding the shared pathogenesis of Atherosclerosis and AIDS and provided possible potential therapeutic targets for immunomodulatory therapy.

FFAR4-mediated IL-6 release from islet macrophages promotes insulin secretion and is compromised in type-2 diabetes

The function of islet macrophages is poorly understood. They promote glucose-stimulated insulin secretion (GSIS) in lean mice, however, the underlying mechanism has remained unclear. We show that activation of the free fatty acid receptor FFAR4 on islet macrophages leads to interleukin-6 (IL-6) release and that IL-6 promotes β-cell function. This mechanism is required for GSIS in lean male mice, but does not function anymore in islets from people with obesity and obese type 2 diabetic male mice. In islets from obese mice, FFAR4 downstream signaling in macrophages is strongly reduced, resulting in impaired FFAR4-mediated IL-6 release. However, IL-6 treatment can still improve GSIS in islets from people with obesity and obese type 2 diabetic mice. These data show that a defect in FFAR4-mediated macrophage activation contributes to reduced GSIS in type 2 diabetes and suggest that reactivating islet macrophage FFAR4 and promoting or mimicking IL-6 release from islet macrophages improves GSIS in type 2 diabetes.

The lung microvasculature promotes alveolar type 2 cell differentiation via secreted SPARCL1

Lung endothelial cells (ECs) and pericytes are closely juxtaposed with the respiratory epithelium before birth and thus may have instructive roles during development. To test this hypothesis, we screened EC-secreted proteins for their ability to alter cell differentiation in alveolar organoids. We identified secreted protein acidic and rich in cysteine-like protein 1 (SPARCL1) as an extracellular matrix molecule that can promote alveolar type 2 (AT2) cell differentiation in vitro. SPARCL1-treated organoids display lysozyme upregulation and a doubling in the number of AT2 cells at the expense of intermediate progenitors. SPARCL1 also induces the upregulation of nuclear factor κB (NF-κB) target genes, and suppression of NF-κB activation in lung organoids blocked SPARCL1 effects. NF-κB activation by lipopolysaccharide (LPS) was sufficient to induce AT2 cell differentiation; however, pharmacological inhibition of the pathway alone did not prevent it. These data support a role for SPARCL1 and NF-κB in alveolar cell differentiation and suggest a potential value in targeting this signaling axis to promote alveolar maturation and regeneration.

Intronic RNAscope probes enable precise identification of cardiomyocyte nuclei and cell cycle activity

Cardiac regeneration studies have been plagued by technical challenges in unequivocally identifying cardiomyocyte (CM) nuclei in cardiac sections, crucial for accurate identification of cycling CMs. The use of antibodies to sarcomeric proteins is error-prone, the CM specificity of common nuclear markers is controversial, and utilizing genetically modified mouse models poses risk of inducing unintended cardiac phenotypes. The application of RNAscope intronic probes overcomes the above shortcomings. Intronic probes label intronic RNAs within nuclei and can therefore be utilized as a method for nuclear localization. A Tnnt2 intronic RNAscope probe highly colocalized with Obscurin-H2B-GFP in adult mouse hearts, demonstrating CM specificity. Studies in embryos demonstrated that the Tnnt2 intronic RNAscope probe labeled CM nuclei that had undergone DNA replication, and remained closely associated with CM chromatin at all stages of mitosis, even with nuclear envelope breakdown. The efficiency, accuracy, and perdurance of the Tnnt2 intronic RNAscope probe even with nuclear envelope breakdown facilitated reliable investigation of dynamics of DNA synthesis and potential mitoses in CMs in both border and infarct zones after myocardial infarction (MI). Furthermore, we designed Myl2 and Myl4 intronic RNAscope probes, which labeled ventricular and atrial CM nuclei, respectively, and may help identify CM subtypes generated in vitro.

Genetic variation at 11q23.1 confers colorectal cancer risk by dysregulation of colonic tuft cell transcriptional activator POU2AF2

BACKGROUND

Common genetic variation at 11q23.1 is associated with colorectal cancer (CRC) risk, exerting local expression quantitative trait locus (cis-eQTL) effects on POU2AF2, COLCA1 and POU2AF3 genes. However, complex linkage disequilibrium and correlated expression has hindered elucidation of the mechanisms by which genetic variants impart underlying CRC risk.

OBJECTIVE

Undertake an interdisciplinary approach to understand how variation at 11q23.1 locus imparts CRC risk.

DESIGN

We employ analysis of RNA sequencing, single-cell RNA sequencing, chromatin immunoprecipitation sequencing and single-cell ATAC sequencing data to identify, prioritise and characterise the genes that contribute to CRC risk. We further validate these findings using mouse models and demonstrate parallel effects in human colonic mucosa.

RESULTS

We establish rs3087967 as a prime eQTL variant at 11q23.1, colocalising with CRC risk. Furthermore, rs3087967 influences expression of 21 distant genes, thereby acting as a trans-eQTL hub for a gene-set highly enriched for tuft cell markers. Epigenomic analysis implicates POU2AF2 as controlling the tuft cell-specific trans-genes, through POU2F3-correlated genomic regulation. Immunofluorescence confirms rs3087967 risk genotype (T) to be associated with a tuft cell deficit in the human colon. CRISPR-mediated deletion of the 11q23.1 risk locus genes in the mouse germline exacerbated the ApcMin/+ mouse phenotype on abrogation of Pou2af2 expression specifically.

CONCLUSION

We demonstrate that genotype at rs3087967 controls a portfolio of genes through misregulation of POU2AF2. POU2AF2 is the primary transcriptional activator of tuft cells with a tumour suppressive role in mouse models. We therefore implicate tuft cells as having a key tumour-protective role in the large bowel epithelium.

Eosinophil innate immune memory after bacterial skin infection promotes allergic lung inflammation

Microbial exposure at barrier interfaces drives development and balance of the immune system, but the consequences of local infections for systemic immunity and secondary inflammation are unclear. Here, we show that skin exposure to the bacterium Staphylococcus aureus persistently shapes the immune system of mice with specific impact on progenitor and mature bone marrow neutrophil and eosinophil populations. The infection-imposed changes in eosinophils were long-lasting and associated with functional as well as imprinted epigenetic and metabolic changes. Bacterial exposure enhanced cutaneous allergic sensitization and resulted in exacerbated allergen-induced lung inflammation. Functional bone marrow eosinophil reprogramming and pulmonary allergen responses were driven by the alarmin interleukin-33 and the complement cleavage fragment C5a. Our study highlights the systemic impact of skin inflammation and reveals mechanisms of eosinophil innate immune memory and organ cross-talk that modulate systemic responses to allergens.

Cell Storage Conditions Impact Single-Cell Proteomic Landscapes

Single cell transcriptomics (SCT) has revolutionized our understanding of cellular heterogeneity, yet the emergence of single cell proteomics (SCP) promises a more functional view of cellular dynamics. A challenge is that not all mass spectrometry facilities can perform SCP, and not all laboratories have access to cell sorting equipment required for SCP, which together motivate an interest in sending bulk cell samples through the mail for sorting and SCP analysis. Shipping requires cell storage, which has an unknown effect on SCP results. This study investigates the impact of cell storage conditions on the proteomic landscape at the single cell level, utilizing Data-Independent Acquisition (DIA) coupled with Parallel Accumulation Serial Fragmentation (diaPASEF). Three storage conditions were compared in 293T cells: (1) 37 °C (control), (2) 4 °C overnight, and (3) -196 °C storage followed by liquid nitrogen preservation. Both cold and frozen storage induced significant alterations in the cell diameter, elongation, and proteome composition. By elucidating how cell storage conditions alter cellular morphology and proteome profiles, this study contributes foundational technical information about SCP sample preparation and data quality.

Transmembrane Serine Protease TMPRSS11B promotes an acidified tumor microenvironment and immune suppression in lung squamous cell carcinoma

Lung cancer is the leading cause of cancer-related deaths worldwide. Existing therapeutic options have limited efficacy, particularly for lung squamous cell carcinoma (LUSC), underscoring the critical need for the identification of new therapeutic targets. We previously demonstrated that the Transmembrane Serine Protease TMPRSS11B promotes transformation of human bronchial epithelial cells and enhances lactate export from LUSC cells. To determine the impact of TMPRSS11B activity on the host immune system and the tumor microenvironment (TME), we evaluated the effect of Tmprss11b depletion in a syngeneic mouse model. Tmprss11b depletion significantly reduced tumor burden in immunocompetent mice and triggered an infiltration of immune cells. RNA FISH analysis and spatial transcriptomics in the autochthonous Rosa26-Sox2-Ires-Gfp LSL/LSL ; Nkx2-1 fl/fl ; Lkb 1 fl/fl (SNL) model revealed an enrichment of Tmprss11b expression in LUSC tumors, specifically in Krt13 + hillock-like cells. Ultra-pH sensitive nanoparticle imaging and metabolite analysis identified regions of acidification, elevated lactate, and enrichment of M2-like macrophages in LUSC tumors. These results demonstrate that TMPRSS11B promotes an acidified and immunosuppressive TME and nominate this enzyme as a therapeutic target in LUSC.

Artificial variables help to avoid over-clustering in single-cell RNA sequencing

Standard single-cell RNA sequencing (scRNA-seq) pipelines nearly always include unsupervised clustering as a key step in identifying biologically distinct cell types. A follow-up step in these pipelines is to test for differential expression between the identified clusters. When algorithms over-cluster, downstream analyses can produce misleading results. In this work, we present "recall" (calibrated clustering with artificial variables), a method for protecting against over-clustering by controlling for the impact of reusing the same data twice when performing differential expression analysis, commonly known as "double dipping." Importantly, our approach can be applied to a wide range of clustering algorithms. Using real and simulated data, we show that recall provides state-of-the-art clustering performance and can rapidly analyze large-scale scRNA-seq studies, even on a personal laptop.

Bcl7b and Bcl7c subunits of BAF chromatin remodeling complexes are largely dispensable for hematopoiesis

Chromatin remodelers have emerged as prominent regulators of hematopoietic cell development and potential drivers of various human hematological malignancies. ATP-dependent BAF chromatin remodeling complexes, related to yeast SWI/SNF, determine gene expression programs and consequently contribute to the self-renewal, commitment, and lineage-specific differentiation of hematopoietic stem cells (HSCs) and progenitors. Here, we investigated the elusive biological function of the core Bcl7b and Bcl7c subunits of BAF complexes in hematopoietic tissue. Our analysis of mouse constitutive knockout alleles revealed that both Bcl7b and Bcl7c are dispensable for animal survival and steady-state adult hematopoiesis. Bcl7b and Bcl7c double knockout (dKO) mice can maintain long-term hematopoiesis with no observable effect on the HSC compartment. Moreover, we show that Bcl7b/Bcl7c dKO HSCs are capable of normal multilineage hematopoietic reconstitution after competitive serial transplantation. Collectively, these studies suggest that the Bcl7b and Bcl7c subunits of BAF complexes are dispensable for normal hematopoiesis.

CORN 2.0 - Condition Orientated Regulatory Networks 2.0

Gene regulation is a fundamental process that allows organisms to adapt to their environment and increase complexity through the action of nucleic acid-binding proteins (NBPs), such as transcription factors (TFs), which regulate specific sets of genes under distinct conditions. These regulatory interactions form transcriptional regulatory networks (TRNs), which can be further broken down into transcriptional regulatory sub-networks (TRSNs) centered around individual TFs. TRSNs are more stable and practical for analysis, making them ideal for studying gene regulation under specific conditions. Condition-Oriented Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/corn/home) is a comprehensive library of condition-based TRSNs, including those induced by natural compounds, small molecules, drug treatments, and gene perturbations. CORN 2.0 represents a significant update, associating 7540 specific conditions with 71934 TRSNs across 52 human cell lines, involving 542 transcription factors (TFs). Notably, CORN 2.0 includes 1550 natural compound-triggered TRSNs, providing a valuable resource for studying the pharmacological effects of natural products. This study demonstrates the utility of CORN in three key areas: personalized medicine, induced pluripotency transitions, and natural compound-associated pharmacology. By linking specific conditions to their corresponding TRSNs, CORN enables researchers to explore how gene regulatory networks are altered under various conditions, offering insights into disease mechanisms and potential therapeutic interventions.

Life-long microbiome rejuvenation improves intestinal barrier function and inflammaging in mice

BACKGROUND

Alterations in the composition and function of the intestinal microbiota have been observed in organismal aging across a broad spectrum of animal phyla. Recent findings, which have been derived mostly in simple animal models, have even established a causal relationship between age-related microbial shifts and lifespan, suggesting microbiota-directed interventions as a potential tool to decelerate aging processes. To test whether a life-long microbiome rejuvenation strategy could delay or even prevent aging in non-ruminant mammals, we performed recurrent fecal microbial transfer (FMT) in mice throughout life. Transfer material was either derived from 8-week-old mice (young microbiome, yMB) or from animals of the same age as the recipients (isochronic microbiome, iMB) as control. Motor coordination and strength were analyzed by rotarod and grip strength tests, intestinal barrier function by serum LAL assay, transcriptional responses by single-cell RNA sequencing, and fecal microbial community properties by 16S rRNA gene profiling and metagenomics.

RESULTS

Colonization with yMB improved coordination and intestinal permeability compared to iMB. yMB encoded fewer pro-inflammatory factors and altered metabolic pathways favoring oxidative phosphorylation. Ecological interactions among bacteria in yMB were more antagonistic than in iMB implying more stable microbiome communities. Single-cell RNA sequencing analysis of intestinal mucosa revealed a salient shift of cellular phenotypes in the yMB group with markedly increased ATP synthesis and mitochondrial pathways as well as a decrease of age-dependent mesenchymal hallmark transcripts in enterocytes and TA cells, but reduced inflammatory signaling in macrophages.

CONCLUSIONS

Taken together, we demonstrate that life-long and repeated transfer of microbiota material from young mice improved age-related processes including coordinative ability (rotarod), intestinal permeability, and both metabolic and inflammatory profiles mainly of macrophages but also of other immune cells. Video Abstract.

Application of bioinformatic tools in cell type classification for single-cell RNA-seq data

The advancements in single-cell RNA sequencing (scRNAseq) technology have significantly transformed genomics research, enabling the handling of thousands of cells in each experiment. As of now, 32,068 research studies have been cataloged in the Pubmed database. The primary aim of scRNAseq investigations is to identify cell types, understand the antitumor immune response, and identify new and uncommon cell types. Traditional techniques for identifying cell types include microscopy, histology, and pathological characteristics. However, the complexity of instruments and the need for precise experimental design make it difficult to fully capture the overall heterogeneity. Unsupervised clustering and supervised classification methods have been used to solve this task. Supervised cell type classification methods have gained popularity as large-scale, high-quality, well-annotated and more robust results compared to clustering methods. A recent study showed that support vector machine (SVM) gives a high-quality classification performance in different scenarios. In this article, we compare and evaluate the performance of four different kernels (sigmoid, linear, radial, polynomial) of SVM. The results of the experiments on three standard scRNA-seq datasets indicate that SVM with linear and SVM with sigmoid kernel classify the cells more accurately (approx. 99 %) where SVM linear kernel method has remarkably fast computation time and we also evaluate the results using some single cell specific evaluation matrices F-1 score, MCC, AUC value. Additionally, it sheds light on the potential use of kernels of SVM to give underlying information of single-cell RNA-Seq data more effectively.

Computer-assisted interpretation, in-depth exploration and single cell type annotation of RNA sequence data using k-means clustering algorithm

At now, the majority of approaches rely on manual techniques for annotating cell types subsequent to clustering the data obtained from single-cell RNA sequencing (scRNA-seq). These approaches require a significant amount of physical exertion and depend substantially on the user's skill, perhaps resulting in uneven outcomes and inconsistency in treatment. In this paper, we provide a computer-assisted interpretation of every single cell of a tissue sample, along with an in-depth exploration of an individual cell's molecular, phenotypic and functional attributes. The paper will also perform k-means clustering followed by silhouette validation based on similar phenotype and functional attributes, and also, cell type annotation is performed, where we match a cell's gene profile against some known database by applying certain statistical conditions. Finally, all the genes are mapped spatially on the tissue sample. This paper is an aid to medicine to know which cells are expressed/not expressed in a tissue sample and their spatial location on the tissue sample.

Towards multimodal foundation models in molecular cell biology

The rapid advent of high-throughput omics technologies has created an exponential growth in biological data, often outpacing our ability to derive molecular insights. Large-language models have shown a way out of this data deluge in natural language processing by integrating massive datasets into a joint model with manifold downstream use cases. Here we envision developing multimodal foundation models, pretrained on diverse omics datasets, including genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial profiling. These models are expected to exhibit unprecedented potential for characterizing the molecular states of cells across a broad continuum, thereby facilitating the creation of holistic maps of cells, genes and tissues. Context-specific transfer learning of the foundation models can empower diverse applications from novel cell-type recognition, biomarker discovery and gene regulation inference, to in silico perturbations. This new paradigm could launch an era of artificial intelligence-empowered analyses, one that promises to unravel the intricate complexities of molecular cell biology, to support experimental design and, more broadly, to profoundly extend our understanding of life sciences.