Sequence Data Research Articles

Bone marrow adipogenic lineage precursors are the major regulator of bone resorption in adult mice

Bone resorption by osteoclasts is a critical step in bone remodeling, a process important for maintaining bone homeostasis and repairing injured bone. We previously identified a bone marrow mesenchymal subpopulation, marrow adipogenic lineage precursors (MALPs), and showed that its production of RANKL stimulates bone resorption in young mice using Adipoq-Cre. To exclude developmental defects and to investigate the role of MALPs-derived RANKL in adult bone, we generated inducible reporter mice (Adipoq-CreER Tomato) and RANKL deficient mice (Adipoq-CreER RANKLflox/flox, iCKO). Single cell-RNA sequencing data analysis and lineage tracing revealed that Adipoq+ cells contain not only MALPs but also some mesenchymal progenitors capable of osteogenic differentiation. In situ hybridization showed that RANKL mRNA is only detected in MALPs, but not in osteogenic cells. RANKL deficiency in MALPs induced at 3 months of age rapidly increased trabecular bone mass in long bones as well as vertebrae due to diminished bone resorption but had no effect on the cortical bone. Ovariectomy (OVX) induced trabecular bone loss at both sites. RANKL depletion either before OVX or at 6 weeks post OVX protected and restored trabecular bone mass. Furthermore, bone healing after drill-hole injury was delayed in iCKO mice. Together, our findings demonstrate that MALPs play a dominant role in controlling trabecular bone resorption and that RANKL from MALPs is essential for trabecular bone turnover in adult bone homeostasis, postmenopausal bone loss, and injury repair.

Jennwenomyces guizhouensis sp. nov. from a freshwater habitat in Guizhou, China

During a study on hyphomycetous fungi, two isolates were obtained from submerged decaying wood in Guizhou Province, China. Based on phylogenetic analysis of combined LSU and ITS sequence data and detailed morphological comparisons with other asexual species within Junewangiaceae, a new species, Jennwenomyces guizhouensis, is introduced. This species is characterized by its navicular or obclavate to cylindro-clavate conidia and unique phylogenetic position. Both morphological data and molecular analyses support its taxonomic placement. A description, illustrations, and phylogenetic analysis results of the new species are provided. Notably, J. guizhouensis represents the second reported lignicolous asexual species from a freshwater habitat in China, expanding our understanding of fungal diversity in aquatic ecosystems.

An epidemiological framework for improving the accuracy of whole-genome sequence-based antimicrobial resistance surveillance in Salmonella.

Whole-genome sequence-based surveillance of bacteria for determinants of antimicrobial resistance promises many advantages over traditional, wet-lab approaches. However, adjustments to parameters used to identify genetic determinants from sequencing data can affect results and interpretation of the important determinants in circulation. Using a dataset of whole-genome sequences from 1633 isolates of Salmonella Heidelberg and S. Kentucky collected from surveillance of Canadian poultry production, we queried the genomic data using an in-silico AMR detection tool, StarAMR, applying a range of parameter values required for the detection pipeline to test for differences in detection accuracy. We compared the results from each iteration to phenotypic antimicrobial susceptibility results, and generated estimates of sensitivity and specificity using regression models that controlled for the effects of multiple sampling events and variables, and interactions between covariates. Results from our analyses revealed small, yet significant effects of the input parameters on the sensitivity and specificity of the AMR detection tool, and these effects differed based on the serovar and drug class in question. Findings from this study may have implications for the incorporation of whole-genome sequence-based approaches to the surveillance of antimicrobial resistance determinants in bacteria sampled from food products and animals related to food production.

Study on DNA damage gene in spermatogonial stem cells from idiopathic non-obstructive azoospermia（NOA） : an bioinformatics investigation based on scRNA-seq data.

DNA damage may affect homeostasis on spermatogonial stem cells(SSCs), while the details relationship with male infertility still remains unclear. Therefore, it is important that further research into the mechanisms related to DNA damage and genomic stability on spermatogonial stem cells. scRNA-seq datasets from Idiopathic non-obstructive azoospermia (NOA) and normal testes were collected and testicular cells were further annotated via UMAP. Based annotation on the sequencing data, WGCNA analysis on the deferentially expressed genes was conducted , LASSO regression and the MNC calculation algorithm in Cytoscape were carried out to find genes associated with DNA damage repair. It was found that SSCs were mainly concentrated in normal samples, and the differences in subcluster pathways reflected the heterogeneity of NOA. While the characteristics of the interaction between Leydig cells and other cells were clarified, and the importance of the PTN signaling pathway in SSCs development was discovered, which participates in SSCs development through SDC2. Combining the marker genes of SSCs and DNA damage-related genes in single-cell analysis, a PPI network was constructed. Through LASSO regression and the MNC calculation algorithm in Cytoscape, ATRX, DOT1L, and RUVBL2 were finally identified as key diagnostic genes. Our results revealed predictable mechanisms of testicular micro-environment and DNA damage in the regulation of human SSCs and propose potential therapeutic targets for male infertility. Subsequently, further research to confirm the predicted potential mechanisms, pathways, and therapeutic targets should be conducted.

Mediation of macrophage M1 polarization dynamics change by ubiquitin-autophagy-pathway regulated NLRP3 inflammasomes in PD-1 inhibitor-related myocardial inflammatory injury.

Immune checkpoint inhibitors (ICIs)-induced cardiac injury is a life-threatening immune-related adverse events (irAEs). However, the current understanding of its pathogenesis and therapeutic options is relatively limited. We aimed to provide a comprehensive overview of the myocardial inflammatory injury process and underlying mechanisms associated with ICIs. We conducted a descriptive analysis of lung cancer patients with ICIs-induced myocarditis at our institution and validated our clinical findings using single-cell sequencing (scRNA-seq) data. Furthermore, we established animal and cellular models to investigate the underlying mechanisms. Our findings revealed that lung cancer patients with ICIs-induced myocarditis exhibit an early increase in peripheral blood monocytes, which migrate to the heart and differentiate into macrophages, ultimately leading to myocardial inflammation. Mechanistically, programmed death-1 (PD-1) inhibition triggers myocardial inflammation through the activation of the signal transducer and activator of transcription 1 (STAT1)/nuclear factor kappa-B (NF-κB)/oligomerization domain (NOD)-like receptor thermal protein domain-associated protein 3 (NLRP3) signaling pathway and drives the polarization of macrophages towards the M1 phenotype. However, the ubiquitin (Ub)-autophagy pathway degrades NLRP3 inflammasomes, resulting in the gradual resolution of inflammation and the transition of M1 macrophages to the M2 phenotype. Finally, mouse experiments confirmed that NLRP3 inhibition using MCC950 effectively alleviates myocardial inflammatory injury. We recommend monitoring fluctuations in peripheral blood monocyte counts in lung cancer patients undergoing ICIs treatment. Additionally, MCC950 holds potential as a therapeutic agent for ICIs-induced cardiac inflammation injury.

ScDrugLink: Single-Cell Drug Repurposing for CNS Diseases via Computationally Linking Drug Targets and Perturbation Signatures.

Central nervous system (CNS) diseases such as glioblastoma (GBM), multiple sclerosis (MS), and Alzheimer's disease (AD) remain challenging due to their complexity and limited treatments. Conventional drug repurposing strategies often rely on bulk RNA sequencing data, which can overlook cellular heterogeneity and mask rare but critical cell populations. Here, we introduce scDrugLink, a computational method that integrates single-cell transcriptomic data with drug targets and perturbation signatures to improve repurposing. For each cell type, scDrugLink constructs a Drug2Cell matrix based on drug targets to estimate promotion/inhibition scores and derives sensitivity/resistance scores by reverse matching signatures and disease-associated genes. These scores are then "linked," yielding robust therapeutic rankings. In our study, we present a systematic evaluation of single-cell drug repurposing methods for CNS diseases. Applied to atlas data for GBM, MS, and AD, scDrugLink surpassed three state-of-the-art methods (ASGARD, DrugReSC, and scDrugPrio), achieving area under the receiver operating characteristic curve (AUC) ranges of 0.6286-0.7242 and area under the precision-recall curve (AUPRC) ranges of 0.3412-0.5484. It also ranked top when comparing AUC and AUPRC at the level of individual cell types. Moreover, applying the "linking" principle to baseline methods boosted their performance, on average improving AUC and AUPRC by 0.0160 and 0.0244, respectively. Despite the advancements, the complexity and heterogeneity of CNS diseases, along with incomplete drug data, indicate that further improvement is necessary. We discuss these challenges and suggest directions for enhancing single-cell drug repurposing in the future.

Direct profiling of non-adenosines in poly(A) tails of endogenous and therapeutic mRNAs with Ninetails

Stability and translation of mRNAs, both endogenous and therapeutic, is determined by poly(A) tail. Direct RNA sequencing enables single-molecule measurements of poly(A) lengths, avoiding amplification bias. It also holds potential for observation of non-adenosines within poly(A), known to influence mRNA fate. However, there is no computational method to detect composite tails in Direct Sequencing data. To address this gap, we introduce the Ninetails, a neural network-based tool that accurately identifies and quantifies non-adenosines in poly(A) tails. Examination of different biological contexts revealed widespread non-adenosine decorations, with frequencies influenced by the origin of poly(A) tails differing by mRNA class, cell type, and species. Notably, substrates of cytoplasmic TENT5-polymerases and mitochondrially encoded mRNAs are enriched in composite tails. For mRNA therapeutics, we show that the composition of poly(A) tails in mRNA vaccines is dynamic during its cellular lifetime and that the manufacturing protocol of synthetic mRNAs affects the purity of poly(A) tails.

Development and validation of a novel cell type estimation method for targeted bisulfite sequencing data.

Epidemiological studies of DNA methylation often use buccal swabs, which contain mixtures of cell types, but no low-cost methods exist for statistical correction in candidate gene studies using targeted bisulfite sequencing. This study aims to address this gap by estimating the proportion of buccal epithelial cells in swab and mouthwash samples. We applied a recently described and smoothly to implement method for estimating the proportion of buccal epithelial cells in buccal swab and mouthwash samples using targeted bisulfite sequencing. Additionally, we investigated the methylation of actinin alpha 3 (ACTN3), a marker for cell type-specific methylation, following psychosocial and physical stress. The proposed estimation method showed strong correlation with the EpiDISH algorithm and effectively controlled for cellular heterogeneity. Over 90% of the variance in ACTN3 methylation was explained by including the epithelial cell proportion in the model. Our findings provide a solution for controlling cellular heterogeneity in buccal swab and mouthwash DNA methylation studies. This method is particularly relevant for candidate gene studies in clinical settings, but future work should refine it for more detailed analyses of cell type proportions to improve precision.

FOXL2 drives the differentiation of supporting gonadal cells in early ovarian development

BackgroundForkhead box L2 (FOXL2) is a transcription factor from the forkhead box family primarily expressed in the pituitary, ovaries, and eyelids. Human mutations in FOXL2 cause blepharophimosis, ptosis, epicanthus and inversus syndrome (BPES), which can be associated with primary ovarian insufficiency, and is indirectly linked with differences of sex development (DSD). Animal studies have shown the crucial role that FOXL2 plays in the development, function, and maintenance of the ovary as well as in sex determination. However, the specific role of FOXL2 in early human somatic cell ovarian development is largely unknown.MethodsIn this study, we utilised CRISPR/Cas9 genome activation and a previously published in-house 14-day gonadal differentiation protocol to study the role of FOXL2.ResultsOur results demonstrate that FOXL2 downregulates coelomic epithelial markers GATA4 and LHX9, female gonadal markers RSPO1 and WNT4, and male gonadal markers SOX9, NR0B1 and DHH. The differentially expressed genes were mostly associated with Kyoto encyclopaedia of genes and genomes (KEGG) pathways relating to cell adhesion molecules and gene ontology (GO) pathways relating to extracellular matrix and junction formation. Furthermore, a comparative analysis with existing single cell RNA sequencing data from human in vivo-derived samples elucidated that FOXL2 initiates the downregulation of coelomic epithelial genes GATA4, LHX9 and UPK3B at day 6. By day 8, the genes ARX and GATA2 are transiently upregulated by FOXL2 induction and then downregulated as the genes LGR5, TSPAN8, OSR1 and TAC1 become upregulated.ConclusionsThese findings suggest that FOXL2 facilitates the exit of differentiating cells from the coelomic epithelium and initially drives them towards a transitional identity before progressing into early supporting gonadal-like cells. The findings of this study significantly advance our understanding of normal gonadal development which can be used as a basis to elucidate pathological gonadal development underlying BPES.

Global distribution and predictive modeling of Vibrio vulnificus abundance

The proliferation of the potentially pathogenic bacterium Vibrio vulnificus due to climate change poses a growing public health threat worldwide. Here we present a global reanalysis of archived 16S ribosomal RNA gene sequencing data, suitable for the identification of bacteria and archaea, to evaluate its current distribution and determine predictors of relative abundance. Two random forest models were trained to predict relative abundance using either satellite data or the prokaryotic community. The models indicated that, besides temperature and salinity, both chlorophyll-a and surface currents likely played a role in relative V. vulnificus abundance and that non-vulnificus Vibrio spp. and Pseudoaltermonas spp. were bacterial predictors of V. vulnificus. Collectively, this indicates decaying phytoplankton blooms stimulate V. vulnificus relative abundance. A poleward trend could accelerate due to climate change-induced modifications of phytoplankton dynamics and currents; factors that should be integrated into predictive modelling to estimate future risks.

Single-cell transcriptomic analysis reveals CD8 + T cell heterogeneity and identifies a prognostic signature in cervical cancer

BackgroundIn recent years, immunotherapy has made significant progress. However, the understanding of the heterogeneity and function of T cells, particularly CD8 + T cells, in cervical cancer (CESC) microenvironment remains insufficient. We aim to characterize the heterogeneity, developmental trajectory, regulatory network, and intercellular communication of CD8 + T cells in cervical squamous cell carcinoma and to construct a prognostic risk model based on the transcriptomic characteristics of CD8 + T cells.MethodsWe integrated single-cell RNA sequencing data from CESC tumor samples with bulk transcriptome data from TCGA and GEO databases. We identified CD8 + T cell subsets in the CESC microenvironment, revealing significant interactions between CD8 + T cells and other cell types through intercellular communication analysis. Pseudotime trajectory analysis revealed dynamic transcriptional regulation during CD8 + T cell differentiation and functional acquisition processes. We constructed a transcriptional regulatory network for CESC CD8 + T cells, identifying key transcription factors. Based on CD8 + T cell-related genes, a prognostic risk model comprising eight core genes was developed and validated using machine learning.ResultsWe identified four distinct CD8 + T cell subsets, namely progenitor, intermediate, proliferative, and terminally differentiated, each exhibiting unique transcriptomic characteristics and functional properties. CD8 + T cell subsets interact with macrophages through different ligand-receptor networks, including the CCL-CCR signaling pathway and costimulatory molecules. Sorafenib was identified as a potential immunotherapeutic drug through drug screening. Experimental validation demonstrated that sorafenib enhances the cytotoxicity of CD8 + T cells by increasing the secretion of IFN-γ and TNF-α, thereby significantly inhibiting the invasiveness and survival of CESC cells.ConclusionsOur study provides valuable insights into the heterogeneity and functional diversity of CD8 + T cells in CESC. We demonstrate that a CD8 + T cell-related prognostic signature may serve as a potential tool for risk stratification in patients with CESC. Additionally, our finding suggests that sorafenib could be a promising therapeutic candidate for improving antitumor immunity in this patient population.

Single-cell RNA sequencing and spatial transcriptomics reveal the heterogeneity and intercellular communication of cancer-associated fibroblasts in gastric cancer

BackgroundGastric cancer is a highly aggressive malignancy characterized by a complex tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are a key component of the TME, exhibit significant heterogeneity and play crucial roles in tumor progression. Therefore, a comprehensive understanding of CAFs is essential for developing novel therapeutic strategies for gastric cancer.MethodsThis study investigates the characteristics and functional information of CAF subtypes and explores the intercellular communication between CAFs and malignant epithelial cells (ECs) in gastric cancer by analyzing single-cell sequencing data from 24 gastric cancer samples. CellChat was employed to map intercellular communication, and Seurat was used to integrate single-cell sequencing data with spatial transcriptome data to reconstruct a comprehensive single-cell spatial map. The spatial relationship between apCAFs and cancer cells was analyzed using multicolor immunohistochemistry.ResultsCells were categorized into nine distinct categories, revealing a positive correlation between the proportions of epithelial cells (ECs) and fibroblasts. Furthermore, six fibroblast subpopulations were identified: inflammatory (iCAFs), pericytes, matrix (mCAFs), antigen-presenting (apCAFs), smooth muscle cells (SMCs), and proliferative CAFs (pCAFs). Each of these subpopulations was linked to various biological processes and immune responses. Malignant ECs exhibited heightened intercellular communication, particularly with CAF subpopulations, through specific ligand-receptor interactions. High-density regions of CAF subpopulations displayed spatial exclusivity, with pericytes serving as a source for iCAFs, mCAFs, and apCAFs. Notably, malignant ECs and apCAFs showed increased interactions, with certain ligand-receptor pairs potentially impacting the prognosis of gastric cancer. Multiplex immunohistochemistry (mIHC) confirmed the close spatial proximity of apCAFs to cancer cells in gastric cancer.ConclusionOur study provided a comprehensive characterization of CAF heterogeneity in gastric cancer and revealed the intricate intercellular networks within the TME. The identified CAF subpopulations and their interactions with malignant cells could serve as potential therapeutic targets.

Exploration of Conserved Human Adipose Subpopulations Using Targeted Single-Nuclei RNA Sequencing Data Sets.

Smooth-muscle cells and pericytes are mural cells. Pericytes can differentiate into myofibroblasts, chondrocytes, vascular smooth-muscle cells, and adipocytes, marking them as a distinct progenitor population. Our goal was to molecularly define the progenitor cell populations in human adipose tissues and test the adipogenic potential of human mural cells. We used informatic analysis of single-cell RNA sequencing data from human tissues to identify and define pericytes and adipose progenitor cells found in human adipose tissues, including perivascular, brown, and white adipose tissues. We established tissue-specific patterns of gene expression in pericytes and other putative human adipocyte progenitor cells. PPARG-expressing pericytes were present in multiple human adipose depots with consistent expression of COL25A1, MYO1B, and POSTN. We also found evidence of tissue-specific pericyte markers. Although there is some conservation between human and mouse adipose tissues, human pericyte populations have unique, depot-specific gene expression signatures. Immunofluorescence staining of human adipose tissue revealed the presence of pericytes both distant from and adjacent to vasculature in human adipose tissue. Additionally, we demonstrated the potential of human brain pericytes and aortic vascular smooth-muscle cells to differentiate into adipocytes invitro on the basis of intracellular lipid accumulation and expression of adipocyte markers. Human adipose cell populations are distinct from mice, and the pericyte subpopulation in human adipose tissues are present across adipose depots. Given that vascular mural cells, including pericytes and smooth-muscle cells, can undergo adipogenesis, we postulate that they are a novel source of adipocytes in the vascular microenvironment.

Chromosome-scale assembly of the Xenocypris davidi using PacBio HiFi reads and Hi-C technologies

Xenocypris davidi is a benthic fish species widely distributed in the water systems south of the Yellow River in China, playing a significant role in aquatic ecosystems. Despite its ecological and economic importance, genomic resources for X. davidi are limited, hindering a comprehensive understanding of its evolutionary adaptations and genetic improvements. This study presents the first chromosome-level genome assembly of X. davidi, utilizing PacBio long-reads, Illumina short reads, and Hi-C sequencing data. The genome assembly spans 1.05 Gb with a scaffold N50 length of 33.99 Mb, and 95.12% of the genome sequence was successfully anchored onto 24 pseudochromosomes. We identified 27,360 protein-coding genes, of which 26,672 were functionally annotated. This genome sequence provides a valuable resource for exploring the molecular basis of agronomic traits in X. davidi and will facilitate its genetic enhancement.

KMT2D Regulates Tooth Enamel Development.

Amelogenesis, the process of enamel formation, is tightly regulated and essential for producing the tooth enamel that protects teeth from decay and wear. Disruptions in amelogenesis can result in amelogenesis imperfecta, a group of genetic conditions characterized by defective enamel, including enamel hypoplasia, marked by thin or underdeveloped enamel. Mutations in the KMT2D (MLL4) gene, which encodes histone H3 lysine 4 methyltransferase, are associated with Kabuki syndrome, a developmental disorder that can involve dental anomalies such as enamel hypoplasia. However, the specific role of KMT2D in amelogenesis remains poorly understood. To address this gap, we generated a conditional knockout (cKO) mouse model with ectoderm-specific deletion of Kmt2d (Krt14-Cre;Kmt2dfl/fl, or Kmt2d-cKO) and characterized the resulting enamel defects using gross, radiographic, histologic, cellular, and molecular analyses. Micro-computed tomography and scanning electron microscopy revealed that adult Kmt2d-cKO mice exhibited 100% penetrant amelogenesis imperfecta, characterized by hypoplastic and hypomineralized enamel, partially phenocopying human Kabuki syndrome. Additionally, Kmt2d-cKO neonates developed molar tooth germs with subtle cusp shape alterations and mild delays in ameloblast differentiation at birth. RNA sequencing analysis of the first molar tooth germ at birth revealed that 33.7% of known amelogenesis-related genes were significantly downregulated in the Kmt2d-cKO teeth. Integration with KMT2D CUT&RUN sequencing results identified 8 overlapping genes directly targeted by KMT2D. Reanalysis of a single-cell RNA sequencing data set in the developing mouse incisors revealed distinct roles for these genes in KMT2D-regulated differentiation across various cell subtypes within the dental epithelium. Among these genes, Satb1 and Sp6 are likely direct targets involved in the differentiation of preameloblasts into ameloblasts. Taken together, we propose that KMT2D plays a crucial role in amelogenesis by directly activating key genes involved in ameloblast differentiation, offering insights into the molecular basis of enamel development and related dental pathologies.

Diverse ancestral representation improves genetic intolerance metrics

The unprecedented scale of genomic databases has revolutionized our ability to identify regions in the human genome intolerant to variation—regions often implicated in disease. However, these datasets remain constrained by limited ancestral diversity. Here, we analyze whole-exome sequencing data from 460,551 UK Biobank and 125,748 Genome Aggregation Database (gnomAD) participants across multiple ancestries to test several key intolerance metrics, including the Residual Variance Intolerance Score (RVIS), Missense Tolerance Ratio (MTR), and Loss-of-Function Observed/Expected ratio (LOF O/E). We demonstrate that increasing ancestral representation, rather than sample size alone, critically drives their performance. Scores trained on variation observed in African and Admixed American ancestral groups show higher resolution in detecting haploinsufficient and neurodevelopmental disease risk genes compared to scores trained on European ancestry groups. Most strikingly, MTR trained on 43,000 multi-ancestry exomes demonstrates greater predictive power than when trained on a nearly 10-fold larger dataset of 440,000 non-Finnish European exomes. We further find that European ancestry group-based scores are likely approaching saturation. These findings highlight the need for enhanced population representation in genomic resources to fully realize the potential of precision medicine and drug discovery. Ancestry group-specific scores are publicly available through an interactive portal: http://intolerance.public.cgr.astrazeneca.com/.

Simvastatin modulates osteogenic differentiation in Stem Cells isolated from Apical Papilla

BackgroundSimvastatin modulates numerous stem cell functions, including stemness maintenance and differentiation. The present study aimed to explore the effect of simvastatin on the osteogenic differentiation of Stem Cells isolated from Apical Papilla (SCAPs) in vitro.MethodsCells were isolated from apical papilla, and mesenchymal stem cell features were characterised. Cells were treated with various concentrations of simvastatin (100-1,000 nM). The mRNA expression profile of simvastatin-treated SCAPs was examined using RNA sequencing technique. The osteogenic differentiation abilities were assessed. Alkaline phosphatase activity was determined. The mineralisation was visualised using Alizarin Red S and Von Kossa staining. The osteogenic marker gene expression was determined using a quantitative polymerase chain reaction.ResultsRNA sequencing data demonstrated that simvastatin upregulated genes enriched in those pathways involving osteogenic differentiation, including the TGF-β signalling pathway, FoxO signalling pathway, and MAPK signalling pathway, while the downregulated genes were involved in pathways related to cell proliferation and apoptosis, for example, DNA replication, cell cycle, and p53 signalling pathway. Simvastatin promoted mineral deposition in a dose-dependent manner, corresponding with the upregulation of osteogenic marker genes namely OSX, DMP1, DSPP, and OCN. Pretreatment with TGF-β receptor inhibitor, SB431542, resulted in a moderately attenuated effect on simvastatin-induced mineralisation and osteogenic marker gene expression.ConclusionsSimvastatin enhances osteogenic differentiation in SCAPs, potentially via TGF-β signalling, implicating its potential role as an adjunctive molecule in dental pulp healing and regeneration in vital pulp treatment approaches.Graphical

Full-length 16S rRNA Sequencing Reveals Gut Microbiome Signatures Predictive of MASLD in children with obesity

BackgroundThe gut microbiota plays a crucial role in metabolic dysfunction-associated steatotic liver disease (MASLD). Next-generation sequencing technologies are essential for exploring the gut microbiome. While recent advancements in full-length 16S (FL16S) rRNA sequencing offer better taxonomic resolution, whether they establish stronger associations with the risk of MASLD remains to be determined.MethodThis study utilized long-read FL16S and short-read V3-V4 16S rRNA sequencing to profile gut microbiome compositions in age-, sex-, and BMI-matched case–control pairs of obese children with and without MASLD. A random forest predictive model was employed, using gut-microbiota features selected based on the top 35 most abundant taxa or a linear discriminant analysis score greater than 3. The model's performance was evaluated by comparing the area under the receiver operating characteristic curve (AUC) through a tenfold cross-validation method.ResultsSubjects with MASLD exhibited significantly elevated serum alanine aminotransferase, triglycerides, and homeostasis model assessment of insulin resistance levels compared to controls. At the genus level, the gut microbiome compositions detected by both FL16S and V3-V4 sequencing were similar, predominantly comprising Phocaeicola and Bacteroides, followed by Prevotella, Bifidobacterium, Parabacteroides, and Blautia. The AUC for the model based on FL16S sequencing data (86.98%) was significantly higher than that based on V3-V4 sequencing data (70.27%), as determined by DeLong's test (p = 0.008).ConclusionFL16S rRNA sequencing data demonstrates stronger associations with the risk of MASLD in obese children, highlighting its potential for real-world clinical applications.

The dynamically evolving cell states and ecosystem from benign nevi to melanoma.

Approximately 30% of non-chronically sun-damaged melanomas originate from nevi, yet the dynamic changes and crucial mechanisms driving the transition from benign nevi to melanoma remain elusive. Here, we performed single-cell transcriptome sequencing on multiple paired tissue sites from 5 patients diagnosed with melanoma arising in congenital melanocytic nevi (CMN), identifying four distinct states of melanocyte subpopulations during the progression from nevi to melanoma, characterized by dynamic changes in their functions and regulatory pathways. In the nevi state, interferon regulatory factor 1 (IRF1) was specifically upregulated in melanocytes, fibroblasts, and endothelial cells (ECs), potentially activating immune surveillance in the microenvironment. Conversely, the critical inhibitory checkpoint HLA-E for NK cells exhibited high expression in a cluster of malignant melanocytes and fibroblasts enriched in melanoma. This interaction with ligands expressed in NK cells could potentially serve as a key factor leading to immune evasion. In malignant melanoma samples, we detected high expression of Midkine (MDK) in melanocytes. It is a pivotal factor that facilitates melanoma invasion and malignant transformation, potentially through interaction with ECs to stimulate angiogenesis. The targets identified in our study are crucial factors in detecting the malignant transformation of nevi. Ultimately, we developed a malignant progression model capable of predicting patient prognosis and malignant progression status using bulk RNA sequencing (RNA-seq) data. Our study provides a high-resolution atlas of the malignant transformation of melanoma from nevi and highlights potential targets for further investigation.

MastR: An R Ppackage for Automated Identification of Tissue-Specific Gene Signatures in Multi-Group Differential Expression Analysis.

Biomarker discovery is important and offers insight into potential underlying mechanisms of disease. While existing biomarker identification methods primarily focus on single cell RNA sequencing (scRNA-seq) data, there remains a need for automated methods designed for labeled bulk RNA-seq data from sorted cell populations or experiments. Current methods require curation of results or statistical thresholds and may not account for tissue background expression. Here we bridge these limitations with an automated marker identification method for labeled bulk RNA-seq data that explicitly considers background expressions. We developed mastR, a novel tool for accurate marker identification using transcriptomic data. It leverages robust statistical pipelines like edgeR and limma to perform pairwise comparisons between groups, and aggregates results using rank-product-based permutation test. A signal-to-noise ratio approach is implemented to minimize background signals. We assessed the performance of mastR-derived NK cell signatures against published curated signatures and found that the mastR-derived signature performs as well, if not better than the published signatures. We further demonstrated the utility of mastR on simulated scRNA-seq data and in comparison with Seurat in terms of marker selection performance. mastR is freely available from https://bioconductor.org/packages/release/bioc/html/mastR.html. A vignette and guide are available at https://davislaboratory.github.io/mastR. All statistical analyses were carried out using R (version ≥ 4.3.0) and Bioconductor (version ≥3.17). Supplementary data are available at Bioinformatics online.