The testis is a complex organ that undergoes extensive developmental changes from the embryonic stage to adulthood. The development of germ cells, which give rise to spermatozoa, is tightly regulated ...by the surrounding somatic cells.
To better understand the dynamics of these changes, we constructed a transcriptional cell atlas of the testis, integrating single-cell RNA sequencing data from over 26,000 cells across five developmental stages: fetal germ cells, infants, childhood, peri-puberty, and adults. We employed various analytical techniques, including clustering, cell type assignments, identification of differentially expressed genes, pseudotime analysis, weighted gene co-expression network analysis, and evaluation of paracrine cell-cell communication, to comprehensively analyze this transcriptional cell atlas of the testis.
Our analysis revealed remarkable heterogeneity in both somatic and germ cell populations, with the highest diversity observed in Sertoli and Myoid somatic cells, as well as in spermatogonia, spermatocyte, and spermatid germ cells. We also identified key somatic cell genes, including RPL39, RPL10, RPL13A, FTH1, RPS2, and RPL18A, which were highly influential in the weighted gene co-expression network of the testis transcriptional cell atlas and have been previously implicated in male infertility. Additionally, our analysis of paracrine cell-cell communication supported specific ligand-receptor interactions involved in neuroactive, cAMP, and estrogen signaling pathways, which support the crucial role of somatic cells in regulating germ cell development.
Overall, our transcriptional atlas provides a comprehensive view of the cell-to-cell heterogeneity in the testis and identifies key somatic cell genes and pathways that play a central role in male fertility across developmental stages.
Understanding the specific type of brain malignancy, source of brain metastasis, and underlying transformation mechanisms can help provide better treatment and less harm to patients. The tumor ...microenvironment plays a fundamental role in cancer progression and affects both primary and metastatic cancers. The use of single-cell RNA sequencing to gain insights into the heterogeneity profiles in the microenvironment of brain malignancies is useful for guiding treatment decisions. To comprehensively investigate the heterogeneity in gliomas and brain metastasis originating from different sources (lung and breast), we integrated data from three groups of single-cell RNA-sequencing datasets obtained from GEO. We gathered and processed single-cell RNA sequencing data from 90,168 cells obtained from 17 patients. We then employed the R package Seurat for dataset integration. Next, we clustered the data within the UMAP space and acquired differentially expressed genes for cell categorization. Our results underscore the significance of macrophages as abundant and pivotal constituents of gliomas. In contrast, lung-to-brain metastases exhibit elevated numbers of AT2, cytotoxic CD4+ T, and exhausted CD8+ T cells. Conversely, breast-to-brain metastases are characterized by an abundance of epithelial and myCAF cells. Our study not only illuminates the variation in the TME between brain metastasis with different origins but also opens the door to utilizing established markers for these cell types to differentiate primary brain metastatic cancers.
Spermatogenesis is a complex process of cellular division and differentiation that begins with spermatogonia stem cells and leads to functional spermatozoa production. However, many of the molecular ...mechanisms underlying this process remain unclear. Single-cell RNA sequencing (scRNA-seq) is used to sequence the entire transcriptome at the single-cell level to assess cell-to-cell variability. In this study, more than 33,000 testicular cells from different scRNA-seq datasets with normal spermatogenesis were integrated to identify single-cell heterogeneity on a more comprehensive scale. Clustering, cell type assignments, differential expressed genes and pseudotime analysis characterized 5 spermatogonia, 4 spermatocyte, and 4 spermatid cell types during the spermatogenesis process. The UTF1 and ID4 genes were introduced as the most specific markers that can differentiate two undifferentiated spermatogonia stem cell sub-cellules. The C7orf61 and TNP can differentiate two round spermatid sub-cellules. The topological analysis of the weighted gene co-expression network along with the integrated scRNA-seq data revealed some bridge genes between spermatogenesis's main stages such as DNAJC5B, C1orf194, HSP90AB1, BST2, EEF1A1, CRISP2, PTMS, NFKBIA, CDKN3, and HLA-DRA. The importance of these key genes is confirmed by their role in male infertility in previous studies. It can be stated that, this integrated scRNA-seq of spermatogenic cells offers novel insights into cell-to-cell heterogeneity and suggests a list of key players with a pivotal role in male infertility from the fertile spermatogenesis datasets. These key functional genes can be introduced as candidates for filtering and prioritizing genotype-to-phenotype association in male infertility.
Drug repurposing is an approach that holds promise for identifying new therapeutic uses for existing drugs. Recently, knowledge graphs have emerged as significant tools for addressing the challenges ...of drug repurposing. However, there are still major issues with constructing and embedding knowledge graphs. This study proposes a two-step method called DrugRep-HeSiaGraph to address these challenges. The method integrates the drug-disease knowledge graph with the application of a heterogeneous siamese neural network. In the first step, a drug-disease knowledge graph named DDKG-V1 is constructed by defining new relationship types, and then numerical vector representations for the nodes are created using the distributional learning method. In the second step, a heterogeneous siamese neural network called HeSiaNet is applied to enrich the embedding of drugs and diseases by bringing them closer in a new unified latent space. Then, it predicts potential drug candidates for diseases. DrugRep-HeSiaGraph achieves impressive performance metrics, including an AUC-ROC of 91.16%, an AUC-PR of 90.32%, an accuracy of 84.63%, a BS of 0.119, and an MCC of 69.31%. We demonstrate the effectiveness of the proposed method in identifying potential drugs for COVID-19 as a case study. In addition, this study shows the role of dipeptidyl peptidase 4 (DPP-4) as a potential receptor for SARS-CoV-2 and the effectiveness of DPP-4 inhibitors in facing COVID-19. This highlights the practical application of the model in addressing real-world challenges in the field of drug repurposing. The code and data for DrugRep-HeSiaGraph are publicly available at https://github.com/CBRC-lab/DrugRep-HeSiaGraph.
Autism is a neurodevelopmental disorder that is usually diagnosed in early childhood. Timely diagnosis and early initiation of treatments such as behavioral therapy are important in autistic people. ...Discovering critical genes and regulators in this disorder can lead to early diagnosis. Since the contribution of miRNAs along their targets can lead us to a better understanding of autism, we propose a framework containing two steps for gene and miRNA discovery.
The first step, called the FA_gene algorithm, finds a small set of genes involved in autism. This algorithm uses the WGCNA package to construct a co-expression network for control samples and seek modules of genes that are not reproducible in the corresponding co-expression network for autistic samples. Then, the protein-protein interaction network is constructed for genes in the non-reproducible modules and a small set of genes that may have potential roles in autism is selected based on this network. The second step, named the DMN_miRNA algorithm, detects the minimum number of miRNAs related to autism. To do this, DMN_miRNA defines an extended Set Cover algorithm over the mRNA-miRNA network, consisting of the selected genes and corresponding miRNA regulators.
In the first step of the framework, the FA_gene algorithm finds a set of important genes; TP53, TNF, MAPK3, ACTB, TLR7, LCK, RAC2, EEF2, CAT, ZAP70, CD19, RPLP0, CDKN1A, CCL2, CDK4, CCL5, CTSD, CD4, RACK1, CD74; using co-expression and protein-protein interaction networks. In the second step, the DMN_miRNA algorithm extracts critical miRNAs, hsa-mir-155-5p, hsa-mir-17-5p, hsa-mir-181a-5p, hsa-mir-18a-5p, and hsa-mir-92a-1-5p, as signature regulators for autism using important genes and mRNA-miRNA network. The importance of these key genes and miRNAs is confirmed by previous studies and enrichment analysis.
This study suggests FA_gene and DMN_miRNA algorithms for biomarker discovery, which lead us to a list of important players in ASD with potential roles in the nervous system or neurological disorders that can be experimentally investigated as candidates for ASD diagnostic tests.
Wound healing is a complex process involving the coordinated interaction of various genes and molecular
pathways. The study aimed to uncover novel therapeutic targets, biomarkers and candidate genes ...for drug development
to improve successful wound repair interventions.
Materials and Methods: This study is a network-meta analysis study. Nine wound healing microarray datasets obtained
from the Gene Expression Omnibus (GEO) database were used for this study. Differentially expressed genes (DEGs)
were described using the Limma package and shared genes were used as input for weighted gene co-expression
network analysis. The Gene Ontology analysis was performed using the EnrichR web server, and construction of a
protein-protein interaction (PPI) network was achieved by the STRING and Cytoscape.
Results: A total of 424 DEGs were determined. A co-expression network was constructed using 7692 shared genes
between nine data sets, resulting in the identification of seven modules. Among these modules, those with the top 20
genes of up and down-regulation were selected. The top down-regulated genes, including TJP1, SEC61A1, PLEK,
ATP5B, PDIA6, PIK3R1, SRGN, SDC2, and RBBP7, and the top up-regulated genes including RPS27A, EEF1A1,
HNRNPA1, CTNNB1, POLR2A, CFL1, CSNk1E, HSPD1, FN1, and AURKB, which can potentially serve as therapeutic
targets were identified. The KEGG pathway analysis found that the majority of the genes are enriched in the "Wnt
signaling pathway".
Conclusion: In our study of nine wound healing microarray datasets, we identified DEGs and co-expressed modules
using WGCNA. These genes are involved in important cellular processes such as transcription, translation, and posttranslational
modifications. We found nine down-regulated genes and ten up-regulated genes, which could serve as
potential therapeutic targets for further experimental validation. Targeting pathways related to protein synthesis and cell
adhesion and migration may enhance wound healing, but additional experimental validation is needed to confirm the
effectiveness and safety of targeted interventions.
The etiologic agent SARS-CoV-2 has caused the outbreak of COVID-19 which is spread widely around the world. It is vital to uncover and investigate the full genome sequence of SARS-CoV-2 throughout ...the world to track changes in this virus. To this purpose, SARS-CoV-2 full genome sequence profiling of 20 patients in Iran and different countries that already had a travel history to Iran or contacts with Iranian cases were provided from the GISAID database. The bioinformatics analysis showed 44 different nucleotide mutations that caused 26 nonsynonymous mutations in protein sequences with regard to the reference full genome of the SARS-CoV-2 sequence (NC_045512.2). R207C, V378I, M2796I, L3606F, and A6407V in ORF1ab were common mutations in these sequences. Also, some of the detected mutations only were found in Iranian data in comparison with all the available sequences of SARS-CoV-2. The position of S protein mutations showed they were far from the binding site of this protein with angiotensin-converting enzyme-2 (ACE2) as the host cell receptor. These results can be helpful to design specific diagnostic tests, trace the SARS-CoV-2 sequence changes in Iran, and explore therapeutic drugs and vaccines.
The most severe type of male infertility is non-obstructive azoospermia (NOA), where there is no sperm in the ejaculate due to failure of spermatogenesis, affecting 10%–20% of infertile men with ...azoospermia. Genetic studies have identified dozens of NOA genes. The main aim of the present study is to identify a novel monogenic mutation that may cause NOA.
We studied the pedigree of a consanguineous family with three NOA and one fertile brother by a family-based exome-sequencing, segregation analysis, insilico protein modeling and single-cell RNA sequencing data analysis.
Bioinformatics analysis followed by sanger sequencing revealed that three NOA brothers were homozygous for a rare missense variant in Cyclin Dependent Kinase Regulatory Subunit Associated Protein 2 (Centrosomin) CDK5RAP2 (NM_018249:exon26:c.A4003T:p.R1335W, rs761196443). Protein modeling demonstrated that CDK5RAP2, Arg1335Trp resided nearby the Microtubule Associated Protein RP/EB Family Member 1 (EB1/MAPRE1) interaction site. As a consequence of the R1335W mutation, the positively charged Arginine was replaced by to the hydrophobic tryptophan residue, possibly leading to local instability in the structure and perturbation in the CDK5RAP2-MAPRE1 interaction.
Our study reports a novel missense variant of CDK5RAP2 that segregates in homozygosity with male infertility and NOA in a consanguineous family. In silico structural predictions and gene expression data indicate a potential role of the CDK5RAP2 variant in causing defective centrosomic maturation during spermatogenesis.
Key Clinical Message
Fazio‐Londe disease and Brown‐Vialetto‐Van Laere syndrome are rare related neurological disorders. Although SLC52A3 and SLC52A2 that encode riboflavin transporters are their only ...known causative genes, many patients without mutations in these genes have been reported. Clinical and genetic data of a patient with features suggestive of Fazio‐Londe disease are presented. Neurological examination revealed significant involvement of cranial nerves and weakness in the lower extremities. Pontobulbar presentations were prominent. EDX study suggested motor neuronopathy. Hearing was normal. She was diagnosed with FL disease. Response to riboflavin supplementation was not favorable. The patient's pedigree suggested recessive inheritance. SLC52A3 and SLC52A2 were screened and mutations were not observed. Results of exome sequencing and segregation analysis suggested that a mutation in TNRC18 is a candidate cause of disease in the patient. The three dimensional structure of the TNRC18 protein was predicted and it was noted that its two conserved domains (BAH and Tudor) interact and that the valine residue affected by the mutation is positioned close to both domains. A mutation in TNRC18 is cautiously reported as the possible cause of FL disease in the patient. The finding warrants further inquiries on TNRC18 about which little is presently known.
The function of the immune system in prostate cancer (PC) might promote carcinogenesis. PC is a common cancer in men. Regulatory B cells (Bregs) are a new subtype of B cells that have suppressive ...roles in the immune system. Interleukin-10 (IL-10) is a dominant mediator of immune suppression released by Bregs.
The purpose of this research was to examine the frequency of CD19+IL10+ B cells and IL-10 mRNA expression in patients with PC compared to patients with benign prostatic hyperplasia (BPH).
Forty paraffin tissue samples from patients with PC and 32 paraffin tissue samples from patients with BPH were entered in this study. The immunohistochemistry staining was used to evaluate the pattern expression of CD19 and IL-10 markers. IL-10 mRNA expression in fresh tissue was determined by real time-polymerase chain reaction (RT-PCR).
The frequency of CD19+IL-10+ B cells and IL-10 mRNA expression in PC patients were significantly higher than patients with BPH. Also, there was no meaningful relationship between the frequency of IL-10+CD19+ B cells and gleason scores in patients with PC.
Our findings suggested that frequency of IL-10+CD19+ B cells correlates with progressive stage of PC.
PDF
