Differential Analysis Research Articles

The Impact of Spliceosome Inhibition in SF3B1-Mutated Uveal Melanoma.

Unfortunately, treatment of patients with uveal melanoma (UM) with metastatic disease is limited. Twenty percent of patients with UM harbor a mutation in the splicing factor gene SF3B1, suggesting that aberrant spliceosome function plays a vital role in tumorigenesis. Splicing inhibitors exploit the preferential sensitivity of spliceosome-compromised leukemic cells to these compounds. We studied the effect of the splicing inhibitor E7107 using two UM cell lines and ex vivo cultured SF3B1- and BAP1-mutated primary UM tumor slices. These UM cell lines and ex vivo tumor slices were exposed for 24 hours to different concentrations of E7107. Tumor slices were stained with hematoxylin and eosin (H&E) and incubated with BAP1, MelanA, MIB-1, and caspase-3 antisera. The E7107-exposed UM cell lines exhibited decreased cell viability and increased apoptosis, with the greatest effect on SF3B1-mutated UM cells. A similar effect on UM tumor slices was observed upon exposure to E7107. Additionally, RNA was isolated for differential isoform expression analysis. No significant difference in isoform usage was found genome-wide. However, specific genes were differentially expressed after E7107 treatment in the SF3B1-mutated samples. Moreover, E7107 had the greatest effect on intron retention. This study indicates/suggests that mutated SF3B1 UM cells are more sensitive to the splicing inhibitor E7107 than wild-type SF3B1 UM cells.

Preparation and study of properties of sorbents based on the fibrous waste of “Bombyx mori” natural silk

The work presents information on obtaining hydrolyzed fibroin powder with high sorption properties under the influence of ultra-high frequency rays from the fibrous waste of the silk industry in an acidic environment, as well as information on its composition, structure, and sorption properties. During the research, it was found that the formation of hydrolyzed fibroin powder is caused by the hydrolysis of alpha- and random chains of fibroin. In differential scanning calorimetry analysis, it was shown that hydrolyzed fibroin is thermally structurally stable up to 210 °C and capable of sorption of gold and silver ions in large quantities. Using the samples obtained by treating the hydrolyzed fibroin powders in different medium solutions, cottonseed oil was whitened, and the peroxide content of the oil was reduced from 12 mmol/kg to 2.2 mmol/kg. By lowering it to this point, it is possible to increase the oil's shelf life.

Genomic and transcriptomic profiling of pre- and postneoadjuvant chemotherapy triple negative breast cancer tumors.

Our understanding of neoadjuvant treatment with microtubule inhibitors (MTIs) for triple negative breast cancer (TNBC) remains limited. To advance our understanding of the role of breast cancer driver genes' mutational status with pathological complete response (pCR; ypT0/isypN0) prediction and to identify distinct gene sets for MTIs like eribulin and paclitaxel, we carried out targeted genomic (n = 50) and whole transcriptomic profiling (n = 64) of TNBC tumor samples from the Japan Breast Cancer Research Group 22 (JBCRG-22) clinical trial. Lower PIK3CA, PTEN, and HRAS mutations were found in homologous recombination deficiency (HRD)-high (HRD score ≥ 42) tumors with higher pCR rates. When HRD-high tumors were stratified by tumor BRCA mutation status, the pCR rates in BRCA2-mutated tumors were higher (83% vs. 36%). Transcriptomic profiling of TP53-positive tumors identified downregulation of FGFR2 (false discovery rate p value = 2.07e-7), which was also the only common gene between HRD-high and -low tumors with pCR/quasi-pCR treated with paclitaxel and eribulin combined with carboplatin, respectively. Differential enrichment analysis of the HRD-high group posttreatment tumors revealed significant correlation (p = 0.006) of the glycan degradation pathway. FGFR2 expression and the differentially enriched pathways play a role in the response and resistance to MTIs containing carboplatin treatment in TNBC patients.

Exploring the hub Genes and Potential Mechanisms of Complement system-related Genes in Parkinson Disease: Based on Transcriptome Sequencing and Mendelian Randomization.

An accurate diagnosis of Parkinson's disease (PD) remains challenging and the exact cause of the disease is unclean. The aims are to identify hub genes associated with the complement system in PD and to explore their underlying molecular mechanisms. Initially, differentially expressed genes (DEGs) and key module genes related to PD were mined through differential expression analysis and WGCNA. Then, differentially expressed CSRGs (DE-CSRGs) were obtained by intersecting the DEGs, key module genes and CSRGs. Subsequently, MR analysis was executed to identify genes causally associated with PD. Based on genes with significant MR results, the expression level and diagnostic performance verification were achieved to yield hub genes. Functional enrichment and immune infiltration analyses were accomplished to insight into the pathogenesis of PD. qRT-PCR was employed to evaluate the expression levels of hub genes. After MR analysis and related verification, CD93, CTSS, PRKCD and TLR2 were finally identified as hub genes. Enrichment analysis indicated that the main enriched pathways for hub genes. Immune infiltration analysis found that the hub genes showed significant correlation with a variety of immune cells (such as myeloid-derived suppressor cell and macrophage). In the qRT-PCR results, the expression levels of CTSS, PRKCD and TLR2 were consistent with those we obtained from public databases. Hence, we mined four hub genes associated with complement system in PD which provided novel perspectives for the diagnosis and treatment of PD.

Weighted gene co-expression network analysis and identification of ginsenoside biosynthesis candidate genes for ginseng adventitious roots under MeJA treatment.

Ginseng (Panax ginseng) is an herb with a long history and a wide range of applications. Ginsenoside is one of the most representative and active ginseng compounds, with various pharmacological effects. Therefore, the development of bioreactors using methyl jasmonate (MeJA) as an inducer for targeted ginsenoside production is of great commercial value. Combined with transcriptomic research tools, screenings to obtain candidate genes involved in ginsenoside biosynthesis are crucial for future discoveries about the molecular mechanism of MeJA-regulated ginsenoside biosynthesis. In our study, the ginsenoside content of ginseng adventitious roots treated with MeJA at different times was analyzed. Transcriptome analysis was performed to investigate the effects of MeJA on changes in ginsenoside content in ginseng adventitious roots. The MeJA could significantly increase changes in the content of pro-ginsenodiol ginsenosides as well as pro-triol ginsenosides Rg3, Re, and Rf in ginseng adventitious roots. Differential gene expression analysis showed that a total of 14,009 differentially expressed genes were obtained from the screening of the present study. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that differentially expressed genes were mainly enriched under GO terms in response to stimuli, metabolic processes, and the regulation of biological processes, with significant annotation to the metabolic terms of terpenoids and polyketides. Two expression modules of genes highly related to ginsenoside biosynthesis were obtained via WGCNA. Our study provides a reference system for the targeted ginsenoside production using MeJA as an inducer, and also provides genetic and gene resources for subsequently validating genes related to the regulation of ginsenoside biosynthesis using weighted gene co-expression network analysis (WGCNA).

Uncovering the small proteome of Methanosarcina mazei using Ribo-seq and peptidomics under different nitrogen conditions

The mesophilic methanogenic archaeal model organism Methanosarcina mazei strain Gö1 is crucial for climate and environmental research due to its ability to produce methane. Here, we establish a Ribo-seq protocol for M. mazei strain Gö1 under two growth conditions (nitrogen sufficiency and limitation). The translation of 93 previously annotated and 314 unannotated small ORFs, coding for proteins ≤ 70 amino acids, is predicted with high confidence based on Ribo-seq data. LC-MS analysis validates the translation for 62 annotated small ORFs and 26 unannotated small ORFs. Epitope tagging followed by immunoblotting analysis confirms the translation of 13 out of 16 selected unannotated small ORFs. A comprehensive differential transcription and translation analysis reveals that 29 of 314 unannotated small ORFs are differentially regulated in response to nitrogen availability at the transcriptional and 49 at the translational level. A high number of reported small RNAs are emerging as dual-function RNAs, including sRNA154, the central regulatory small RNA of nitrogen metabolism. Several unannotated small ORFs are conserved in Methanosarcina species and overproducing several (small ORF encoded) small proteins suggests key physiological functions. Overall, the comprehensive analysis opens an avenue to elucidate the function(s) of multitudinous small proteins and dual-function RNAs in M. mazei.

RNA-seq and bulk RNA-seq data analysis of cancer-related fibroblasts (CAF) in LUAD to construct a CAF-based risk signature

Angiogenesis, metastasis, and resistance to therapy are all facilitated by cancer-associated fibroblasts (CAFs). A CAF-based risk signature can be used to predict patients’ prognoses for Lung adenocarcinoma (LUAD) based on CAF characteristics. The Gene Expression Omnibus (GEO) database was used to gather signal-cell RNA sequencing (scRNA-seq) data for this investigation. The GEO and TCGA databases were used to gather bulk RNA-seq and microarray data for LUAD. The scRNA-seq data were analyzed using the Seurat R program based on the CAF markers. Our goal was to use differential expression analysis to discover differentially expressed genes (DEGs) across normal and tumor samples in the TCGA dataset. Pearson correlation analysis was utilized to discover prognostic genes related with CAF, followed by univariate Cox regression analysis. Using Lasso regression, a risk signature based on CAF-related prognostic genes was created. A nomogram model was created based on the clinical and pathological aspects. 5 CAF clusters were identified in LUAD, 4 of which were associated with prognosis. From 2811 DEGs, 1002 genes were found to be significantly correlated with CAF clusters, which led to the creation of a risk signature with 8 genes. These 8 genes were primarily connected with 41 pathways, such as antigen paocessing and presentation, apoptosis, and cell cycle. Meanwhile, the risk signature was significantly associated with stromal and immune scores, as well as some immune cells. Multivariate analysis revealed that risk signature was an independent prognostic factor for LUAD, and its value in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the stage and CAF-based risk signature was constructed, which exhibited favorable predictability and reliability in the prognosis prediction of LUAD. CAF-based risk signatures can be effective in predicting the prognosis of LUAD, and they may provide new strategies for cancer treatments by interpreting the response of LUAD to immunotherapy.

Integrated approach of machine learning, Mendelian randomization and experimental validation for biomarker discovery in diabetic nephropathy.

To identify potential biomarkers and explore the mechanisms underlying diabetic nephropathy (DN) by integrating machine learning, Mendelian randomization (MR) and experimental validation. Microarray and RNA-sequencing datasets (GSE47184, GSE96804, GSE104948, GSE104954, GSE142025 and GSE175759) were obtained from the Gene Expression Omnibus database. Differential expression analysis identified the differentially expressed genes (DEGs) between patients with DN and controls. Diverse machine learning algorithms, including least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest, were used to enhance gene selection accuracy and predictive power. We integrated summary-level data from genome-wide association studies on DN with expression quantitative trait loci data to identify genes with potential causal relationships to DN. The predictive performance of the biomarker gene was validated using receiver operating characteristic (ROC) curves. Gene set enrichment and correlation analyses were conducted to investigate potential mechanisms. Finally, the biomarker gene was validated using quantitative real-time polymerase chain reaction in clinical samples from patients with DN and controls. Based on identified 314 DEGs, seven characteristic genes with high predictive performance were identified using three integrated machine learning algorithms. MR analysis revealed 219 genes with significant causal effects on DN, ultimately identifying one co-expressed gene, carbonic anhydrase II (CA2), as a key biomarker for DN. The ROC curves demonstrated the excellent predictive performance of CA2, with area under the curve values consistently above 0.878 across all datasets. Additionally, our analysis indicated a significant association between CA2 and infiltrating immune cells in DN, providing potential mechanistic insights. This biomarker was validated using clinical samples, confirming the reliability of our findings in clinical practice. By integrating machine learning, MR and experimental validation, we successfully identified and validated CA2 as a promising biomarker for DN with excellent predictive performance. The biomarker may play a role in the pathogenesis and progression of DN via immune-related pathways. These findings provide important insights into the molecular mechanisms underlying DN and may inform the development of personalized treatment strategies for this disease.

12353 Differential Gene Expression And Pathway Analysis In Growth Hormone Secreting Pituitary Tumors According To Granulation Pattern

Abstract Disclosure: H. Shin: None. Differential gene expression and pathway analysis in growth hormone-secreting pituitary tumors according to granulation pattern. Hye Ju Shin [1], Kyung Won Kim[2], Chan Woo Kang[2], Eun Jig Lee[2], Cheol Ryong Ku[2]. [1]Department of Clinical Drug Discovery & Development, Yonsei University College of Medicine, Seoul, Republic of Korea, [2]Endocrinology, Institute of Endocrine Research, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea Objective: The purpose of this research is to explain clinical variations in patients with acromegaly by exploring gene expression differences according to granulation patterns in growth hormone (GH)-secreting pituitary tumors. Materials & methods: Transcriptome analysis was conducted on 6 normal pituitary tissues and 15 GH-secreting pituitary tumors, including 9 densely granulated somatotroph tumors (DGSTs) and 6 sparsely granulated somatotroph tumors (SGSTs). Results: The median age at diagnosis was 50 years, with a predominance of female patients (60%). We identified 3111 differentially expressed genes (DEGs) in tumors compared to normal pituitaries, with 1117 DEGs unique to a specific granulation within tumors. SGST showed enriched the pathways involved in neuronal development (axon development, axonogenesis, axon guidance, synapse and presynapse organization, gliogenesis, glial cell differentiation, nerve development, synaptic membrane adhesion, semaphorin-plexin signaling pathway involved in neuron projection guidance) and acute inflammatory response. No pathways were significantly downregulated in SGST compared with those in DGST. Three signaling pathways (JAK-STAT, phosphatidylinositol 3-kinase, and MAP cascade) and three neuronal development processes (generation of neurons, nerve development, and neurogenesis) were significantly enriched in both GO and GSEA analysis. The PPI networks constructed with the up- and downregulated DEGs consisted of 128 and 132 PPI pairs, respectively. There were 10 hub proteins, top highly connected DEGs: ANLN, TLE3, TLE2, DMD, ADRA1A, RBFOX1, MMP2, LMO1, RUNX1T1, and NPPA. Conclusion: The results indicate that granulation-specific gene expression may underpin diverse clinical characteristics in acromegaly. Overall, this study emphasizes the potential for further investigation into these transcriptomic variations and their roles in disease pathology, particularly the involvement of genes linked to neuronal development, inflammatory response, and JAK-STAT signaling in SGST. Presentation: 6/3/2024

8574 Single cell multiomics suggests tumor cell energy metabolism heterogeneity in non-functioning gonadotroph pituitary adenomas

Abstract Disclosure: F.M. Ruf-Zamojski: None. Z. Zhang: None. W. Cheng: None. G.R. Smith: None. M. Zamojski: None. N. Mendelev: None. Y. Ge: None. D. Marrero-Rodríguez: None. K. Taniguchi-Ponciano: None. C.L. Andoniadou: None. E. Zaslavsky: None. X. Chen: None. O.G. Troyanskaya: None. M. Mercado: None. S.C. Sealfon: None. Pituitary adenomas cause hormonal dysregulation and severe morbidity. The absence of clear biomarkers for prognosis/treatment and the high risk of recurrence make management challenging. Non-functioning gonadotroph pituitary adenomas (NFPAs) represent proliferation of gonadotroph lineage cells without an increase in secretion of gonadotropins. Detection is often delayed until mass effects cause visual defects. Higher resolution molecular study may improve classification, diagnosis, treatment, and provide insight into adenoma biology. We analyzed four NFPAs using unbiased genome-wide same-cell single nucleus 10X Genomics multiome assay (transcriptome and chromatin accessibility) to define individual cell identity/states in comparison with normal gonadotrope cell references from twelve age/sex-matched human post-mortem pituitaries. In total, we generated high quality multiomics single-cell data for 33,832 adenoma cells and 5,451 normal gonadotropes. We identified tumor, immune, vascular, and proliferative cells confirming cellular heterogeneity. Multidimensional scaling analysis using Manhattan distances between cell types showed that NFPA gonadotropes were closer in gene expression to healthy gonadotropes among all pituitary cell types. In addition, we observed differences in the macrophage and endothelial cell populations between tumors and healthy pituitaries. Next, we studied gene regulatory circuitry (regulated gene, modulating transcription factor and its chromatin interaction site) using the new Control of Regulation Extracted from Multiomics Assays (CREMA, [1]) multiome analysis method which showed high variation between normal and tumor gonadotropes. Within each adenoma, the NFPA tumor cells encompassed two main subgroups of cells, one group (GT+ marker tumor cells) expressing established gonadotrope markers and another group not (GT- marker tumor cells). GT+ and GT- tumor cells formed a cluster distinct from healthy gonadotropes. GT+ and GT- tumor cells differed by their level of expression of mitochondrial genes, suggesting decreased aerobic capacity associated with the GT- tumor subgroup. Interestingly, differential analyses between the healthy and the NFPA gonadotropes from same-cell multiome data highlighted dissimilar gene expression and chromatin accessibility patterns.Our newly collected single cell data characterize the difference between NFPA tumor cells and normal gonadotrope cells. Our results suggest a Warburg-effect like difference in aerobic respiratory capacity among tumor cells within the same pituitary adenoma. Overall, this study brings new insights into the molecular characteristics of NFPAs, including tumor cell heterogeneity, and represents a new resource for the field. [1] PMID: 38084892. Presentation: 6/1/2024

Mutations in fibronectin dysregulate chondrogenesis in skeletal dysplasia.

Fibronectin (FN) is an extracellular matrix glycoprotein essential for the development and function of major vertebrate organ systems. Mutations in FN result in an autosomal dominant skeletal dysplasia termed corner fracture-type spondylometaphyseal dysplasia (SMDCF). The precise pathomechanisms through which mutant FN induces impaired skeletal development remain elusive. Here, we have generated patient-derived induced pluripotent stem cells as a cell culture model for SMDCF to investigate the consequences of FN mutations on mesenchymal stem cells (MSCs) and their differentiation into cartilage-producing chondrocytes. In line with our previous data, FN mutations disrupted protein secretion from MSCs, causing a notable increase in intracellular FN and a significant decrease in extracellular FN levels. Analyses of plasma samples from SMDCF patients also showed reduced FN in circulation. FN and endoplasmic reticulum (ER) protein folding chaperones (BIP, HSP47) accumulated in MSCs within ribosome-covered cytosolic vesicles that emerged from the ER. Massive amounts of these vesicles were not cleared from the cytosol, and a smaller subset showed the presence of lysosomal markers. The accumulation of intracellular FN and ER proteins elevated cellular stress markers and altered mitochondrial structure. Bulk RNA sequencing revealed a specific transcriptomic dysregulation of the patient-derived cells relative to controls. Analysis of MSC differentiation into chondrocytes showed impaired mesenchymal condensation, reduced chondrogenic markers, and compromised cell proliferation in mutant cells. Moreover, FN mutant cells exhibited significantly lower transforming growth factor beta-1 (TGFβ1) expression, crucial for mesenchymal condensation. Exogenous FN or TGFβ1 supplementation effectively improved the MSC condensation and promoted chondrogenesis in FN mutant cells. These findings demonstrate the cellular consequences of FN mutations in SMDCF and explain the molecular pathways involved in the associated altered chondrogenesis.

8786 Novel TGFbeta Ligand Regulated Genes in WT and FSTL3 KO Testis Identified by ChIP-Seq Analysis: Implications for Signalling Cross-talk

Abstract Disclosure: R. Ballesteros: None. A. Mukherjee: None. Folistatin Like 3 (FSTL3) is a known antagonist of activin and myostatin action that when deleted from the mouse genome displayed a set of phenotypic changes that are directly linked to glucose metabolism and reproductive function. Although our previous work showed that β-cell hyperplasia, increased pancreatic islet number and size and reduced visceral fat seen in FSTL3 knockout mice (FSTL3 KO) could be explained by enhanced activin and myostatin action, the molecular bases of the changes in the reproductive function seen in this mouse model remain elusive. In contrast to testicular degeneration produced by INHBA (activin A) transgenic overexpression in mice, deletion of FSTL3 results in increased testicular size, with increased Sertoli cell numbers and early meiotic entry of the first spermatogenic wave. This suggests a possibility that the phenotype in FSTL3 deleted mice might involve alteration of additional transcripts other than those induced by activin alone in the testis. To identify transcripts induced in FSTL3 deleted testis as a consequence of induced TGFβ ligand action we performed sequencing of Smad4 Chromatin immunoprecipitation (ChIP-Seq) from postnatal (3d) and post-pubertal (56d) whole testis. Our results show high activity of Smad4 signalling during postnatal stages compared to post-pubertal stages in both genotypes (Fstl3-KO vs wild-type). Interestingly, postnatal testis from FSTL3 KO contains significantly less activity from Smad4 signalling (69 peaks) compared to wild type (775 peaks). By contrast, on the whole, Smad4 signalling in post-pubertal stages is less active with 34 peaks in wild-type and 29 peaks in Fstl3-KO of which 8 genes are SMAD activated in both genotypes. To identify whether SMAD-dependent signalling produces significant differences in RNA expression, we then used the list of genes that generated peaks in the Smad4-ChIP-Seq experiment to filter our RNA-Seq data generated in a parallel experiment followed by differential gene expression analysis of GO terms by GSEA in postnatal testis from both genotypes. We found that Smad4-interacting genes in posnatal FSTL3 KO testis generate enrichment of 13 pathways including the androgen receptor signalling pathway. Taken together so far, our findings reveal a novel catalogue of SMAD-regulated genes in the testis, identifies a set of genes specifically upregulated in the testis in a SMAD-dependent manner upon FSTL3 deletion and also identify possible cross-talk between TGFβ and 13 other signalling pathways. Currently we are further analysing our data to identify whether there are SMAD regulated genes and pathways common in postnatal and postpubertal testes. We are also undertaking experiments to investigate expression pattern in FSTL3 KO testis to identify which pathways might specifically affect Sertoli cell proliferation and activity. Presentation: 6/2/2024

8786 Novel TGFbeta Ligand Regulated Genes in WT and FSTL3 KO Testis Identified by ChIP-Seq Analysis: Implications for Signalling Cross-talk

Abstract Disclosure: R. Ballesteros: None. A. Mukherjee: None. Folistatin Like 3 (FSTL3) is a known antagonist of activin and myostatin action that when deleted from the mouse genome displayed a set of phenotypic changes that are directly linked to glucose metabolism and reproductive function. Although our previous work showed that β-cell hyperplasia, increased pancreatic islet number and size and reduced visceral fat seen in FSTL3 knockout mice (FSTL3 KO) could be explained by enhanced activin and myostatin action, the molecular bases of the changes in the reproductive function seen in this mouse model remain elusive. In contrast to testicular degeneration produced by INHBA (activin A) transgenic overexpression in mice, deletion of FSTL3 results in increased testicular size, with increased Sertoli cell numbers and early meiotic entry of the first spermatogenic wave. This suggests a possibility that the phenotype in FSTL3 deleted mice might involve alteration of additional transcripts other than those induced by activin alone in the testis. To identify transcripts induced in FSTL3 deleted testis as a consequence of induced TGFβ ligand action we performed sequencing of Smad4 Chromatin immunoprecipitation (ChIP-Seq) from postnatal (3d) and post-pubertal (56d) whole testis. Our results show high activity of Smad4 signalling during postnatal stages compared to post-pubertal stages in both genotypes (Fstl3-KO vs wild-type). Interestingly, postnatal testis from FSTL3 KO contains significantly less activity from Smad4 signalling (69 peaks) compared to wild type (775 peaks). By contrast, on the whole, Smad4 signalling in post-pubertal stages is less active with 34 peaks in wild-type and 29 peaks in Fstl3-KO of which 8 genes are SMAD activated in both genotypes. To identify whether SMAD-dependent signalling produces significant differences in RNA expression, we then used the list of genes that generated peaks in the Smad4-ChIP-Seq experiment to filter our RNA-Seq data generated in a parallel experiment followed by differential gene expression analysis of GO terms by GSEA in postnatal testis from both genotypes. We found that Smad4-interacting genes in posnatal FSTL3 KO testis generate enrichment of 13 pathways including the androgen receptor signalling pathway. Taken together so far, our findings reveal a novel catalogue of SMAD-regulated genes in the testis, identifies a set of genes specifically upregulated in the testis in a SMAD-dependent manner upon FSTL3 deletion and also identify possible cross-talk between TGFβ and 13 other signalling pathways. Currently we are further analysing our data to identify whether there are SMAD regulated genes and pathways common in postnatal and postpubertal testes. We are also undertaking experiments to investigate expression pattern in FSTL3 KO testis to identify which pathways might specifically affect Sertoli cell proliferation and activity. Presentation: 6/2/2024

Metatranscriptomics provide insights into the role of the symbiont midichloria mitochondrii in Ixodes ticks.

Ticks are important vectors of bacterial, viral and protozoan pathogens of humans and animals worldwide. Candidatus Midichloria mitochondrii (hereafter M. mitochondrii) is a highly abundant bacterial endosymbiont found in many tick species, including two medically important ticks respectively found in Europe and Australia, Ixodes ricinus and Ixodes holocyclus. The present study aimed to determine the symbiont's biological role by identifying lateral gene transfer (LGT) events, characterising the transcriptome, and performing differential expression analyses. Metatranscriptomic data revealed that M. mitochondrii species in I. ricinus and I. holocyclus were equipped with the metabolic potential and were actively transcribing the genes for several important roles including heme, biotin and folate synthesis, oxidative stress response, osmotic regulation, and ATP production in microaerobic conditions. Differential expression analyses additionally showed an upregulation in stringent response and DNA repair genes in M. mitochondrii of I. holocyclus nymphs compared to adults. Low rates of differential expression suggest the symbiont may lack global gene regulation, as observed in other endosymbionts. Moreover, the identification of an LGT event and the proposed specialisation of the M. mitochondrii strains, mIxholo1 and mIxholo2, for different I. holocyclus life stages highlight the complex interactions between M. mitochondrii and their tick hosts.

Leveraging explainable deep learning methodologies to elucidate the biological underpinnings of Huntington’s disease using single-cell RNA sequencing data

BackgroundHuntington’s disease (HD) is a hereditary neurological disorder caused by mutations in HTT, leading to neuronal degeneration. Traditionally, HD is associated with the misfolding and aggregation of mutant huntingtin due to an extended polyglutamine domain encoded by an expanded CAG tract. However, recent research has also highlighted the role of global transcriptional dysregulation in HD pathology. However, understanding the intricate relationship between mRNA expression and HD at the cellular level remains challenging. Our study aimed to elucidate the underlying mechanisms of HD pathology using single-cell sequencing data.ResultsWe used single-cell RNA sequencing analysis to determine differential gene expression patterns between healthy and HD cells. HD cells were effectively modeled using a residual neural network (ResNet), which outperformed traditional and convolutional neural networks. Despite the efficacy of our approach, the F1 score for the test set was 96.53%. Using the SHapley Additive exPlanations (SHAP) algorithm, we identified genes influencing HD prediction and revealed their roles in HD pathobiology, such as in the regulation of cellular iron metabolism and mitochondrial function. SHAP analysis also revealed low-abundance genes that were overlooked by traditional differential expression analysis, emphasizing its effectiveness in identifying biologically relevant genes for distinguishing between healthy and HD cells. Overall, the integration of single-cell RNA sequencing data and deep learning models provides valuable insights into HD pathology.ConclusionWe developed the model capable of analyzing HD at single-cell transcriptomic level.

Characteristics of Myocardial Structure and Central Carbon Metabolism during the Early and Compensatory Stages of Cardiac Hypertrophy.

Cardiac hypertrophy is a classical forerunner of heart failure and myocardial structural and metabolic remodeling are closely associated with cardiac hypertrophy. We aim to investigate the characteristics of myocardial structure and central carbon metabolism of cardiac hypertrophy at different stages. Using echocardiography and pathological staining, early and compensatory cardiac hypertrophy were respectively defined as within 7 days and from 7 to 14 days after transverse aortic constriction (TAC) in mice. Among mass-spectrometry-based metabolomics, we identified 45 central carbon metabolites. Differential metabolite analysis showed that six metabolites, including citrate, cis-aconitate and so on, decreased significantly on day 1 after TAC. Ten metabolites, including l-lactate, (S)-2-hydroxyglutarate and so on, were obviously changed on days 10 and 14. Pathway analysis showed that these metabolites were involved in seven metabolic pathways, including carbohydrates, amino acids and so on. Western blot showed the expression of ATP-citrate lyase, malate dehydrogenase 1 and lactate dehydrogenase A in myocardium changed markedly on day 3, while the phosphorylation level of AMP-activated protein kinase did not show significantly difference. We hope our research will promote deeper understanding and early diagnosis of cardiac hypertrophy in clinical practice. All raw data were deposited in MetaboLights (MTBLS10555).

Characterization and Crystal Structural Analysis of Novel Carvedilol Adipate and Succinate Ethanol-Solvated Salts

Two ethanol-solvated adipate and succinate salts of carvedilol (CVD), a Biopharmaceutics Classification System class 2 drug, were synthesized by crystallizing ethanol with adipic acid (ADP) and succinic acid (SUA). Proton transfer from ADP and SUA to CVD and the presence of ethanol in the two novel compounds were confirmed using powder X-ray diffraction, Fourier transform infrared spectroscopy, differential scanning calorimetry, thermogravimetric analysis, and single-crystal X-ray diffraction measurements. The two novel ethanol-solvated salts exhibited enhanced solubility and dissolution rates compared with pure carvedilol in phosphate buffer (pH 6.8). Additionally, the morphologies and attachment energies of the two novel compounds and pure CVD were calculated based on their single-crystal structures, revealing a correlation between attachment energy and dissolution rate.

Quantum Insights into Partially Molecular Imprinted Microspheres for Anticancer Therapeutics: Experimental and Theoretical Studies.

Drug solubility is a determining factor for controlled release, and solubility-dependent release kinetics can be modified by changing the drug's state in the polymer matrix through partial molecular imprinting (PMI), although research in this area remains limited. This novel PMI approach creates nanocavities within the polymer by partially retaining the imprinting molecule and trapping the drug. Such a method holds promise for developing advanced biomaterial-based drug delivery systems for anticancer therapies. In this study, we developed microspheres designed for anticancer drug delivery utilizing PMI to enhance controlled release properties. Poly(vinyl alcohol) (PVA) microspheres were partially imprinted with aspirin (ASP) to create nanocavities for gemcitabine (GEM) molecules, inducing a polymorphic shift of GEM within the polymer matrix. This novel PMI approach enhanced drug release properties by enabling control over the drug crystallinity and release rate. The PVA-ASP-GEM complex showed zero-order release kinetics, releasing 21.6% of GEM over 48 h, maintaining steady state release profile. In contrast, nonimprinted PVA-GEM microspheres exhibited first-order kinetics with a faster release of 46.85% in the same period. Quantum insights from density functional theory (DFT) calculations revealed the superior stability of the PVA-ASP-GEM complex, with a binding free energy of -56.03 kcal/mol, compared to -29.07 kcal/mol for PVA-GEM. Molecular dynamics (MD) simulations demonstrated that ASP's presence created nanocavities that restricted GEM's movement, further contributing to the controlled release. Experimental validation through differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Raman spectroscopy confirmed the polymorphic transitions within the PVA-ASP-GEM complex. This PMI-based approach offers a promising method for modulating drug release kinetics and improving the stability of anticancer therapeutics, paving the way for innovative biomaterial-based drug delivery systems.

RNF144A as a potential risk gene for endometrial carcinoma: Insights from Mendelian randomization, bulk RNA sequencing, single-cell RNA, and experimental analysis.

Endometrial carcinoma (EC) is a prevalent gynecological malignancy that poses a significant threat to women's health worldwide. However, its pathogenesis and underlying mechanisms remains unclear. In this study, expression quantitative trait loci data, Mendelian randomization analysis, and differential expression analysis were performed to identify potential targets. A prognostic risk signature was subsequently constructed for EC patients based on the expression of these genes. Four bioinformatics algorithms, including generalized linear model, extreme gradient boosting, support vector machine, and random forest, were used to identify hub genes in EC. The expression of ring finger protein 144A (RNF144A) was validated using quantitative real-time polymerase chain reaction. Cellular proliferation and migration ability were evaluated using CCK-8 and Transwell assays, respectively. The genes RNF144A, ketohexokinase, and Rab interacting lysosomal protein like 2 were identified as potential targets for EC. Their differential expression was observed in EC patients, and Mendelian randomization analysis revealed a negative correlation between these genes and the development of EC. Mechanistic analyses suggested a strong association between these genes and the tumor immune microenvironment. The constructed risk signature was significantly associated with the prognosis, age, cancer stage, and grade of EC patients. Furthermore, based on interacted model algorithms, RNF144A was identified as a hub gene in EC. It was found to be significantly downregulated in EC samples, and its expression was positively correlated with the stage and grade of EC patients. In vitro experiments showed that overexpression of RNF144A significantly promoted cell growth and migration in EC cells. In conclusion, this study provides insights into the molecular mechanisms underlying EC progression and identifies preliminary candidate biomarkers for the development of EC treatment strategies.

Pancreatic cancer tumor organoids exhibit subtype-specific differences in metabolic profiles

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease characterized by complex metabolic rewiring that enables growth in changing nutrient availability and oxygen conditions. Transcriptome-based prognostic PDAC tumor subtypes, known as ‘basal-like’ and ‘classical’ subtypes are associated with differences in metabolic gene expression including genes involved in glycolysis. Tumor subtype-specific metabolism phenotypes may provide new targets for treatment development in PDAC, but their functional relevance has not been fully elucidated. We aimed to investigate differences in metabolic profiles and transcriptomes in tumor models derived from patients with basal-like and classical tumors.MethodsPatient-derived organoids (PDOs) were established from tumor biopsies collected from patients with metastatic PDAC, including three PDOs from basal-like and five PDOs from classical tumors. Metabolic analyses included assessment of differences in metabolic activity using Seahorse Glycolysis and Mito Stress tests and 13C-glucose metabolites tracing analysis. In order to investigate the influence of mitochondrial pyruvate transport on metabolic differences, PDOs were treated with the mitochondrial pyruvate carrier 1 (MPC1) inhibitor UK-5099. Prognostic relevance of MPC1 was determined using a tumor tissue microarray (TMA) in resectable, and proteomics profiling in metastatic PDAC datasets. Whole genome and transcriptome sequencing, differential gene expression and gene set enrichment analyses were performed in PDOs.ResultsMetastatic PDAC PDOs showed subtype-specific differences in glycolysis and oxidative phosphorylation (OXPHOS). Basal-like tumor-derived PDOs had a lower baseline extracellular acidification rate, but higher glycolytic reserves and oxygen consumption rate (OCR) than classical tumor-derived PDOs. OCR difference was eliminated following treatment with UK-5099. In the 13C-glucose metabolites tracing experiment, a basal-like tumor PDO showed lower fractions of some M + 2 metabolites but higher sensitivity to UK-5099 mediated reduction in M + 2 metabolites than a classical tumor PDO. Protein level analyses revealed lower MPC1 protein levels in basal-like PDAC cases and association of low MPC1 levels with clinicopathologic parameters of tumor aggressiveness in PDAC. PDO differential gene expression analyses identified additional subtype-specific cellular pathways and potential disease outcome biomarkers.ConclusionsOur findings point to distinct metabolic profiles in PDAC subtypes with basal-like tumor PDOs showing higher OXPHOS and sensitivity to MPC1 inhibition. Subtypes-specific metabolic vulnerabilities may be exploited for selective therapeutic targeting.