Small Molecule Metabolism Research Articles

Transcriptome analysis of liver and ileum reveals potential regulation of long non-coding RNA in pigs with divergent feed efficiency.

LncRNA plays a significant role in regulating feed efficiency. This study aims to explore the key long non-coding RNAs, associated genes, and pathways in pigs with extreme feed efficiencies. We screened pigs with extremely high and low RFI through a 12-week animal growth trial and then conducted transcriptome analysis on their liver and ileum tissues. We analyzed the differential expressed lncRNAs, miRNAs, and mRNAs through target gene prediction and functional analysis. And we identified key lncRNAs and their potential regulatory genes associated with feed efficiency through the construction of competitive endogenous RNA network. Differentially expressed lncRNAs were pinpointed in the liver, revealing 23 crucial target genes primarily associated with GTP metabolism and glycolipid biosynthesis. In the ileum, a screening identified 92 pivotal target genes, mainly linked to lipid and small molecule metabolism. Moreover, LOC106504303 and LOC102160805 emerged as potentially significant lncRNAs respectively, playing roles in mitochondrial oxidative phosphorylation in the liver, and lipid and cholesterol metabolism in the ileum. The lncRNAs regulate energy metabolism and biosynthesis in the liver, and the digestive absorption capacity in the small intestine, affecting the feed efficiency of pigs.

Denoising Drug Discovery Data for Improved Absorption, Distribution, Metabolism, Excretion, and Toxicity Property Prediction.

Predicting absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of small molecules is a key task in drug discovery. A major challenge in building better ADMET models is the experimental error inherent in the data. Furthermore, ADMET predictors are typically regression tasks due to the continuous nature of the data, which makes it difficult to apply existing denoising methods from other domains as they largely focus on classification tasks. Here, we develop denoising schemes based on deep learning to address this. We find that the training error (TE) can be used to identify the noise in regression tasks while ensemble-based and forgotten event-based metrics fail to detect the noise. The most significant performance increase occurs when the original model is finetuned with the denoised data using TE as the noise detection metric. Our method has the ability to improve models with medium noise and does not degrade the performance of models with noise outside this range (low noise and high noise regimes). To our knowledge, our denoising scheme is the first to improve model performance for ADMET data and has implications for improving models for experimental assay data in general.

Genomic and transcriptomic analyses of chemical hepatocarcinogenesis aggravated by oncoprotein loss

Background and Aims: The chemical carcinogen diethylnitrosamine (DEN) is often used to induce hepatocellular carcinoma (HCC) in mice. Curiously, several labs have reported that removal of oncoproteins from hepatocytes exacerbated DEN-induced HCC, with mechanisms unknown. This study aimed at deciphering molecular mechanisms underlying the tumor suppressive effect of oncoproteins. Methods and Results: We generated mutant mouse lines with hepatocyte-specific deletions of Met, Ptpn11/Shp2, Ikk, or ctnnb1/-catenin, and assessed DEN-induced tumorigenesis in the wild type (WT) and mutant mice. To systematically examine genetic and molecular signaling alternations, we performed whole exome and RNA sequencing on liver samples collected at the pre-cancer and established cancer stages. Although the mutational profiles of DEN-induced tumors were barely different in WT and mutant mice, oncoprotein ablation increased DEN-induced mutational burdens, especially in Shp2-deficient tumors. RNA-sequencing revealed multiple changes in signaling pathways, in particular upregulated epithelial-mesenchymal transition (EMT), cell migration and tumor metastasis as well as downregulated small molecule metabolism that were affected by oncoprotein ablation. We identified key molecules and pathways that are associated with hepatic innate immunity and implicated in liver tumorigenesis. In addition, we unveiled markedly changed expression of a few miRNAs in human HCC database. Conclusion: The aggravation of DEN-induced HCC progression seen on oncoprotein ablation could be caused by common and distinct genomic and signaling alterations. This study reveals a new level of complexity in hepato-carcinogenesis and elucidates molecular mechanisms underlying tumor evolution and recurrence.

Human brain proteome-wide association study provides insights into the genetic components of protein abundance in obesity.

Genome-wide association studies have identified multiple genetic variants associated with obesity. However, most obesity-associated loci were waiting to be translated into new biological insights. Given the critical role of brain in obesity development, we sought to explore whether obesity-associated genetic variants could be mapped to brain protein abundances. We performed proteome-wide association studies (PWAS) and colocalization analyses to identify genes whose cis-regulated brain protein abundances were associated with obesity-related traits, including body fat percentage, trunk fat percentage, body mass index, visceral adipose tissue, waist circumference, and waist-to-hip ratio. We then assessed the druggability of the identified genes and conducted pathway enrichment analysis to explore their functional relevance. Finally, we evaluated the effects of the significant PWAS genes at the brain transcriptional level. By integrating human brain proteomes from discovery (ROSMAP, N = 376) and validation datasets (BANNER, N = 198) with genome-wide summary statistics of obesity-related phenotypes (N ranged from 325,153 to 806,834), we identified 51 genes whose cis-regulated brain protein abundance was associated with obesity. These 51 genes were enriched in 11 metabolic processes, e.g., small molecule metabolic process and metabolic pathways. Fourteen of the 51 genes had high drug repurposing value. Ten of the 51 genes were also associated with obesity at the transcriptome level, suggesting that genetic variants likely confer risk of obesity by regulating mRNA expression and protein abundance of these genes. Our study provides new insights into the genetic component of human brain protein abundance in obesity. The identified proteins represent promising therapeutic targets for future drug development.

Network Pharmacological Study of the Active Ingredient of Panax Notoginseng Saponins for the Treatment of Lung Cancer by Inhibiting AKR1C3

Background: Lung cancer is the malignancy with the second highest diagnostic rate and the leading cause of cancer-related death. Objective: This study aims to investigate the potential mechanism and molecular targets of Panax notoginseng saponins (PNS) in inhibiting lung cancer through network pharmacology. Methods: Pharmacodynamic targets of each compound of PNS were searched from TargetNet, SwissTargetPrediction, and BatMan-TCM databases. Next, the differential expression genes (DEGs) in lung cancer were obtained from the Gene Expression Omnibus (GEO) database and screened by R package. Later, the STRING 11.0 database was utilized to analyze the protein-protein interaction (PPI) network of common targets of PNS-lung cancer, clusterProfiler to perform gene ontology (GO) annotation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the common targets, and Cytoscape 3.8.0 to construct and analyze the "ingredient-target" network for the common targets of PNS-lung cancer. Results: A total of 154 potential pharmacodynamic targets of PNS, 2399 DEGs of lung cancer-related diseases, and 21 common targets of PNS-lung cancer were obtained by database search and screening. The 21 common targets were mainly involved in biological processes (such as small molecule metabolism and cytokine production) and were major components of cellular structures (such as neuronal cell bodies and membrane rafts). Besides, these targets could function as carboxylic ester hydrolases, G protein-coupled amine receptors, and oxidoreductase. They were mainly enriched in 14 signaling pathways, like neuroactive ligand-receptor interaction, regulation of lipolysis in adipocytes, and calcium signaling pathway. Furthermore, the molecular docking results revealed that aldo-keto reductase family 1 member C3 (AKR1C3) and melanin metabolic enzyme (MME) may be direct targets of ginsenoside Rg1 and notoginsenoside R2. Conclusion: Our study showed that ginsenosides inhibit the progression of lung cancer through multiple targets and pathways. More importantly, PNS may treat lung cancer by directly inhibiting AKR1C3.

Targeted metabolomics analysis approach to unravel the biofilm formation pathways of Enterococcus faecalis clinical isolates.

(i) To characterize Enterococcus faecalis biofilm formation pathways by semi-targeted metabolomics and targeted nitrogen panel analysis of strong (Ef63) and weak (Ef 64) biofilm forming E. faecalis clinical isolates and (ii) to validate the identified metabolic markers using targeted inhibitors. Previous proteomics profiling of E. faecalis clinical isolates with strong and weak biofilm formation revealed that differences in metabolic activity levels of small molecule, nucleotide and nitrogen compound metabolic processes and biosynthetic pathways, cofactor metabolic process, cellular amino acid and derivative metabolic process and lyase activity were associated with differences in biofilm formation. Hence, semi-targeted analysis of Ef 63, Ef 64 and ATC control strain Ef 29212 was performed by selecting metabolites that were part of both the previously identified pathways and a curated library with confirmed physical and chemical identity, followed by confirmatory targeted nitrogen panel analysis. Significantly regulated metabolites (p < .05) were selected based on fold change cut-offs of 1.2 and 0.8 for upregulation and downregulation, respectively, and subjected to pathway enrichment analysis. The identified metabolites and pathways were validated by minimum biofilm inhibitory concentration (MBIC) and colony forming unit (CFU) assays with targeted inhibitors. Metabolomics analysis showed upregulation of betaine, hypoxanthine, glycerophosphorylcholine, tyrosine, inosine, allantoin and citrulline in Ef 63 w.r.t Ef 64 and Ef 29212, and thesemetabolites mapped to purinemetabolism, urea cycle and aspartate metabolism pathways. MBIC and CFU assays using compounds against selected metabolites and metabolic pathways, namely glutathione against hypoxanthine and hydroxylamine against aspartate metabolism showed inhibitory effects against E. faecalis biofilm formation. The study demonstrated the importance of oxidative stress inducers such as hypoxanthine and aspartate metabolism pathway in E. faecalis biofilm formation. Targeted therapeutics against these metabolic markers can reduce the healthcare burden associated with E. faecalis infections.

Integrative multiomics analysis identifies molecular subtypes and potential targets of hepatocellular carcinoma.

The liver is anatomically divided into eight segments based on the distribution of Glisson's triad. However, the molecular mechanisms underlying each segment and its association with hepatocellular carcinoma (HCC) heterogeneity are not well understood. In this study, our objective is to conduct a comprehensive multiomics profiling of the segmentation atlas in order to investigate potential subtypes and therapeutic approaches for HCC. A high throughput liquid chromatography-tandem mass spectrometer strategy was employed to comprehensively analyse proteome, lipidome and metabolome data, with a focus on segment-resolved multiomics profiling. To classify HCC subtypes, the obtained data with normal reference profiling were integrated. Additionally, potential therapeutic targets for HCC were identified using immunohistochemistry assays. The effectiveness of these targets were further validated through patient-derived organoid (PDO) assays. A multiomics profiling of 8536 high-confidence proteins, 1029 polar metabolites and 3381 nonredundant lipids was performed to analyse the segmentation atlas of HCC. The analysis of the data revealed that in normal adjacent tissues, the left lobe was primarily involved in energy metabolism, while the right lobe was associated with small molecule metabolism. Based on the normal reference atlas, HCC patients with segment-resolved classification were divided into three subtypes. The C1 subtype showed enrichment in ribosome biogenesis, the C2 subtype exhibited an intermediate phenotype, while the C3 subtype was closely associated with neutrophil degranulation. Furthermore, using the PDO assay, exportin 1 (XPO1) and 5-lipoxygenase (ALOX5) were identified as potential targets for the C1 and C3 subtypes, respectively. Our extensive analysis of the segmentation atlas in multiomics profiling defines molecular subtypes of HCC and uncovers potential therapeutic strategies that have the potential to enhance the prognosis of HCC.

Auxiliary diagnosis and prognosis evaluation of KIF4A, RAD51AP1 and CDKN3 in esophageal cancer

To investigate the expression of mRNA in esophageal cancer (ESCA) tissues and its potential and diagnostic and prognostic value by high-throughput sequencing data. Using the Cancer Genome Atlas Program (TCGA) database in USA by integrative bioinformatics analysis methods, the gene expression profiles and clinical data of 173 patients with ECSA were collected. The mRNA expression levels in ESCA tissue and para-cancerous tissue samples were analyzed using DESeq2, edgeR and limma to screen the differentially expressed genes (DEGs). DEGs-related protein network diagrams were drawn. GO and KEGG function enrichment analysis were performed and the hub genes were screened and the survival analysis of hub genes was analyzed. Genes related to the prognosis of ESCA were selected and their prognostic value in ESCA was analyzed. Finally, the receiver operating characteristic curve was drawn to evaluate its diagnostic value. The results showed that using TCGA cancer data, a total of 620 up-regulated DEGs and 668 down-regulated DEGs with significant differential expression between ESCA and para-cancerous tissues were screened. DEGs were mainly involved in receptor complexes, ubiquitin ligase complexes, etc., playing GTPase activity, phospholipid binding, and other molecular functions, and participating in the regulation of intracellular substance transport, small molecule metabolism, and other biological processes. Protein functional enrichment analysis showed that these proteins were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, Epstein-Barr virus infection, neutrophil extracellular trap formation, and other pathways involved in the formation and development process of ESCA. Survival analysis showed that the overall survival rate of ESCA patients with high expression of KIF4A, RAD51AP1, and CDKN3 was significantly shortened, and the difference was statistically significant (P<0.05). Furthermore, the areas under the curve (AUC) of KIF4A, RAD51AP1, and CDKN3 for diagnosing esophageal cancer were 0.956, 0.951 and 0.979, respectively, with sensitivities and specificities both exceeding 80%. Additionally, ROC results of the combined diagnostic model of these three genes showed an AUC of 0.979, with sensitivities and specificities of 0.914 and 1, respectively. This indicates that KIF4A, RAD51AP1 and CDKN3 have individual or combined auxiliary diagnostic value for ESCA. In conclusion, KIF4A, RAD51AP1 and CDKN3 have high diagnostic efficiency for ESCA, and their increased expression is closely related to the prognosis, suggesting that these three genes could be used as auxiliary diagnostic and prognostic factors for ESCA.

Role of CENPF and NDC80 in the rehabilitation nursing of hepatocellular carcinoma and cirrhosis: An observational study.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally and often develops on the foundation of chronic liver disease or cirrhosis. Cirrhosis is a clinically prevalent chronic progressive liver disease characterized by diffuse liver damage resulting from long-term or repeated actions of 1 or more etiological factors. However, the impact of CENPF and nuclear division cycle 80 (NDC80) genes on rehabilitation nursing of HCC and cirrhosis remains unclear. HCC and cirrhosis datasets GSE63898 and GSE89377 profile files were downloaded from the gene expression omnibus database generated on platforms GPL13667 and GPL6947, respectively. Differentially expressed genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), construction and analysis of protein-protein interaction (PPI) networks, functional enrichment analysis, gene set enrichment analysis (GSEA), survival analysis, immune infiltration analysis, and comparative toxicogenomics database (CTD) analysis were conducted. Gene expression heatmaps were plotted. miRNAs regulating central DEGs were selected through TargetScan. A total of 626 DEGs were identified. According to gene ontology (GO) analysis, they were primarily enriched in small molecule metabolic processes, drug metabolic processes, binding of identical proteins, and lipid metabolic processes. Kyoto Encyclopedia of Gene and Genome (KEGG) analysis results indicated that the target genes were mainly enriched in metabolic pathways, phagosomes, glycine, serine, and threonine metabolism. The construction and analysis of the PPI network revealed 3 core genes (NDC80, CENPF, RRM2). Gene expression heatmaps showed that core genes (CENPF, NDC80) were highly expressed in HCC and cirrhosis samples. CTD analysis found that 2 genes (CENPF and NDC80) were associated with liver, jaundice, ascites, fever, dyspepsia, and hepatic encephalopathy. CENPF and NDC80 are highly expressed in HCC and cirrhosis, and CENPF and NDC80 might be the biomarkers of rehabilitation nursing of HCC and cirrhosis.

Comprehensive analysis of differentially expressed mRNA profiles in chicken jejunum and cecum following Eimeria maxima infection

Coccidiosis, a protozoan disease that substantially impacts poultry production, is characterized by an intracellular parasite. The study utilized 48 one-day-old Horro chickens, randomly divided into the infected (I) and control (C) groups. The challenge group of chickens were administered Eimeria maxima oocysts via oral gavage at 21 days old, and each chicken received 2ml containing 7×104 sporulated oocysts. The total RNAs of chicken jejunum and cecum tissues were isolated from three samples, each from I and C groups. Our study aimed to understand the host immune-parasite interactions and compare immune response mRNA profiles in chicken jejunum and cecum tissues at 4 and 7 days post-infection with Eimeria maxima. The results showed that 823 up- and 737 down-regulated differentially expressed mRNA (DEmRNA) in jejunum at 4 days infection and control (J4I verses J4C), and 710 up- and 368 down-regulated DEGs in jejunum at 7 days infection and control (J7I verses J7C) were identified. In addition, DEmRNA in cecum tissue, 1424 up- and 1930 down-regulated genes in cecum at 4 days infection and control (C4I verses C4C), and 77 up- and 191 down-regulated genes in cecum at 7 days infection and control (C7I verses C7C) were detected. The crucial DEmRNAs, including SLC7A5, IL1R2, GLDC, ITGB6, ADAMTS4, IL1RAP, TNFRSF11B, IMPG2, WNT9A, and FOXF1, played pivotal roles in the immune response during Eimeria maxima infection of chicken jejunum. In addition, the potential detection of FSTL3, RBP7, CCL20, DPP4, PRKG2, TFPI2, and CDKN1A in the cecum during the host immune response against Eimeria maxima infection is particularly noteworthy. Furthermore, our functional enrichment analysis revealed the primary involvement of DEmRNAs in small molecule metabolic process, immune response function, inflammatory response, and toll-like receptor 10 signaling pathway in the jejunum at 4 and 7 days post-infection. Similarly, in the cecum, DEmRNAs at 4 and 7 days post-infection were enriched in processes related to oxidative stress response and immune responses. Our findings provide new insights and contribute significantly to the field of poultry production and parasitology.

Construction and validation of somatic mutation-derived long non-coding RNAs signatures of genomic instability to predict prognosis of hepatocellular carcinoma.

Long non-coding RNAs (LncRNAs) have been found to be a potential prognostic factor for cancers, including hepatocellular carcinoma (HCC). Some LncRNAs have been confirmed as potential indicators to quantify genomic instability (GI). Nevertheless, GI-LncRNAs remain largely unexplored. This study established a GI-derived LncRNA signature (GILncSig) that can predict the prognosis of HCC patients. To establish a GILncSig that can predict the prognosis of HCC patients. Identification of GI-LncRNAs was conducted by combining LncRNA expression and somatic mutation profiles. The GI-LncRNAs were then analyzed for functional enrichment. The GILncSig was established in the training set by Cox regression analysis, and its predictive ability was verified in the testing set and TCGA set. In addition, we explored the effects of the GILncSig and TP53 on prognosis. A total of 88 GI-LncRNAs were found, and functional enrichment analysis showed that their functions were mainly involved in small molecule metabolism and GI. The GILncSig was constructed by 5 LncRNAs (miR210HG, AC016735.1, AC116351.1, AC010643.1, LUCAT1). In the training set, the prognosis of high-risk patients was significantly worse than that of low-risk patients, and similar results were verified in the testing set and TCGA set. Multivariate Cox regression analysis and stratified analysis confirmed that the GILncSig could be used as an independent prognostic factor. Receiver operating characteristic curve analysis of the GILncSig showed that the area under the curve (0.773) was higher than the two LncRNA signatures published recently. Furthermore, the GILncSig may have a better predictive performance than TP53 mutation status alone. We established a GILncSig that can predict the prognosis of HCC patients, which will help to guide prognostic evaluation and treatment decisions.

Isolation, identification and transcriptome analysis of triadimefon-degrading strain Enterobacter hormaechei TY18.

Triadimefon, a type of triazole systemic fungicide, has been extensively used to control various fungal diseases. However, triadimefon could lead to severe environmental pollution, and even threatens human health. To eliminate triadimefon residues, a triadimefon-degrading bacterial strain TY18 was isolated from a long-term polluted site and was identified as Enterobacter hormaechei. Strain TY18 could grow well in a carbon salt medium with triadimefon as the sole nitrogen source, and could efficiently degrade triadimefon. Under triadimefon stress, a total of 430 differentially expressed genes (DEGs), including 197 up-regulated and 233 down-regulated DEGs, were identified in strain TY18 using transcriptome sequencing (RNA-Seq). Functional classification and enrichment analysis revealed that these DEGs were mainly related to amino acid transport and metabolism, carbohydrate transport and metabolism, small molecule and pyrimidine metabolism. Interestingly, the DEGs encoding monooxygenase and hydrolase activity acting on carbon-nitrogen were highly up-regulated, might be mainly responsible for the metabolism in triadimefon. Our findings in this work suggest that strain E. hormaechei TY18 could efficiently degrade triadimefon for the first time. They provide a great potential to manage triadimefon biodegradation in the environment successfully.

Association of Altered Plasma Lipidome with Disease Severity in COVID-19 Patients.

The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

Comparative transcriptomic analysis of the different developmental stages of ovary in the cuttlefish Sepia pharaonis

The cuttlefish, Sepia pharaonis, is characterized by rapid growth and strong disease resistance, making it an important commercially farmed cephalopod species in the southeastern coastal regions of China. However, in the reproductive process of S. pharaonis, there are challenges such as a low output of eggs, poor quality, and low survival rates of newly hatched juveniles. Therefore, there is an urgent need to study the molecular mechanisms underlying ovarian development in this species. In this study, we conducted the first transcriptomic analysis of the ovary at four developmental stages: the undeveloped stage, developing stage, nearly-ripe stage, and ripe stage, and compared the transcriptomics among these four stages using Illumina sequencing technology. The total numbers of clean reads of the four stages ranged from 40,890,772 to 52,055,714 reads. A total of 136,829 DEGs were obtained, GC base ratios of raw data were between 38.44 and 44.59%, and the number of uniquely mapped reads spanned from 88.08 to 95.90%. The Pearson correlation coefficient demonstrated a strong correlation among different samples within the same group, PCA and Anosim analysis also revealed that the grouping of these four stages was feasible, and each stage could be distinguished from the others. GO enrichment analysis demonstrated that ovarian follicle growth, sex differentiation, and transforming growth factor beta receptor, played a foreshadowing role at the early ovarian development stage, and the terms of small molecule metabolic process, peptide metabolic process, and catalytic activity were prominent at the mature stage. Meanwhile, KEGG analysis showed that the early ovarian development of S. pharaonis was mainly associated with the cell cycle, DNA replication, and carbon metabolism, while the mid-late ovarian development was involved with the signal transduction, endocrine system, and reproduction pathway. RT-qPCR further confirmed the consistent expression patterns of genes such as 17β-HSD, GH, VGS, NFR, and NYR in the ovaries of S. pharaonis, exhibiting elevated levels of expression during the maturation stage. Conversely, ER and OM exhibited high expression levels during the early stages of ovarian development. These transcriptomic data provide insights into the molecular mechanisms of S. pharaonis ovarian development. The findings of this study will contribute to improving the reproduction and development of cuttlefish and enriching the bioinformatics knowledge of cephalopods.

Molecular mechanism of acid stress response of Alicyclobacillus acidoterrestris DSM 3922T under sublethal pH

Alicyclobacillus acidoterrestris (A. acidoterrestris) causes the spoilage of pasteurized acidic fruit juice due to its unique thermoacidophilic properties, which caused economic losses to fruit juice industry. To reveal the molecular regulatory mechanism of how A. acidoterrestris responded to acid stress is the key to hazard control of this microbe. Herein, acid-responsive proteome expression profiles of A. acidoterrestris were analyzed using label-free quantitative mass spectrometry to investigate its acid resistance mechanism at sublethal pH. Totally, 325 differential expression proteins were identified during acid stress (pH 2.5, 15 min duration), of which the expressions of 83 proteins were up-regulated and the other 242 protein expressions were down-regulated. The identified differentially expressed proteins were mainly involved in small molecule metabolism, organic nitrogen compounds metabolism, organic acid metabolism, and signal transduction. Overall, they were mapped into 97 metabolic pathways. Combination of KEGG pathway analysis and protein functional analysis suggested that the pH homeostasis system variation and relevant changes in metabolic pathways, cell membrane permeability and DNA repair are the main acid resistance mechanisms of A. acidoterrestris. Our finding implied that A. acidoterrestris might sense and transmit pH signals from the external environment through NhaB protein which holds histidine-dependent acid resistance system, initiating a series of acid tolerance reactions. Taken together, our study demonstrated global physiological response of A. acidoterrestris to sublethal pH, which provided a better understanding of acid adaption mechanism of A. acidoterrestris.

The maize ATP-binding cassette (ABC) transporter ZmMRPA6 confers cold and salt stress tolerance in plants.

ZmMRPA6 was cloned and characterized as the first ATP-binding cassette (ABC) transporter in maize to be proven to participate in cold and salt tolerance. Homologous genes AtABCC4 and AtABCC14 of ZmMRPA6 also responded to salt stress. ATP-binding cassette (ABC) proteins are major transmembrane transporters that play significant roles in plant development against various abiotic stresses. However, available information regarding stress-related ABC genes in maize is minimal. In this study, a maize ABC transporter gene, ZmMRPA6, was identified through genome-wide association analysis (GWAS) for cold tolerance in maize seeds germination and functionally characterized. During germination and seedling stages, the zmmrpa6 mutant exhibited enhanced resistance to cold or salt stress. Mutated of ZmMRPA6 did not affect the expression of downstream response genes related cold or salt response at the transcriptional level. Mass spectrometry analysis revealed that most of the differential proteins between zmmrpa6 and wild-type plants were involved in response to stress process including oxidative reduction, hydrolase activity, small molecule metabolism, and photosynthesis process. Meanwhile, the plants which lack the ZmMRPA6 homologous genes AtABCC4 or AtABCC14 were sensitive to salt stress in Arabidopsis. These results indicated that ZmMRPA6 and its homologous genes play a conserved role in cold and salt stress, and functional differentiation occurs in monocotyledonous and dicotyledonous plants. In summary, these findings dramatically improved our understanding of the function of ABC transporters resistance to abiotic stresses in plants.

Comparative proteomics reveals the mechanism of cyclosporine production and mycelial growth in Tolypocladium inflatum affected by different carbon sources.

Cyclosporine A (CsA) is a secondary cyclopeptide metabolite produced by Tolypocladium inflatum that is widely used clinically as an immunosuppressant. CsA production and mycelial growth differed when T. inflatum was cultured in different carbon source media. During early fermentation, CsA was preferred to be produced in fructose medium, while the mycelium preferred to accumulate in sucrose medium. On the sixth day, the difference was most pronounced. In this study, high-throughput comparative proteomics methods were applied to analyze differences in protein expression of mycelial samples on day 6, revealing the proteins and mechanisms that positively regulate CsA production related to carbon metabolism. The differences included small molecule acid metabolism, lipid metabolism, organic catabolism, exocrine secretion, CsA substrate Bmt synthesis, and transcriptional regulation processes. The proteins involved in the regulation of mycelial growth related to carbon metabolism were also revealed and were associated with waste reoxidation processes or coenzyme metabolism, small molecule synthesis or metabolism, the stress response, genetic information or epigenetic changes, cell component assembly, cell wall integrity, membrane metabolism, vesicle transport, intramembrane localization, and the regulation of filamentous growth. This study provides a reliable reference for CsA production from high-efficiency fermentation. This study provides key information for obtaining more CsA high-yielding strains through metabolic engineering strategies.

Network pharmacology and molecular docking-based study on exploring the potential mechanism of Lycium barbarum L: In the treatment of atherosclerosis.

Goji berries (Lycium barbarum L) are herbal medicine that have a long history of use and multiple pharmacological activities. In this study, we investigated the potential therapeutic effects of Goji berries on atherosclerosis (AS) using network pharmacology and molecular docking. The active compounds of Goji berries were identified using the Traditional Chinese Medicine Systems Pharmacology platform, as well as the literature and the targets of each active compound were obtained using the Swiss Target Prediction database. The AS-related targets were collected from the GeneCards and OMIM databases to obtain the common targets of Goji berries and AS. The drug-compound-target-disease network and protein-protein interaction network were constructed using the Cytoscape software to obtain the core target proteins of Goji berries related to AS. Gene ontology analysis of the core targets and Kyoto encyclopedia of genes and genomes pathway enrichment analysis were performed by Metascape. The target-chemical correlations were verified using AutoDock molecular docking. After analysis, 44 active compounds within Goji berries were obtained that exhibit associations with AS. Among these, the proteins exhibiting the highest degrees of interaction within the compound-targeted protein protein-protein interaction network were AKT1, SRC, MAPK3, MAPK1, RELA, and STAT3. The gene ontology-biology process analysis showed that compound-targeted proteins were mainly involved in regulating small molecule metabolic process, cellular response to chemical stress, reactive oxygen species metabolic process, and regulation of inflammatory response. Kyoto encyclopedia of genes and genomes pathway mainly included lipid and AS in which AKT1, SRC, MAPK3, and MAPK1 were involved. Advanced glycation end-product-receptor for advanced glycation end-product signaling pathway in diabetic complications, Chagas disease, and pancreatic disease. Molecular docking assessment showed that fucosterol is bound to AKT1, MAPK3, and SRC. This study demonstrates that network pharmacology and molecular docking analyses contribute to a better understanding of Goji berries active compounds and targets as potential therapeutic drugs for treating AS.

Genetic background influences the 5XFAD Alzheimer's disease mouse model brain proteome.

There is an urgent need to improve the translational validity of Alzheimer's disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable the discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. In this study, we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in the hippocampus and cortex (n = 3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across the hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress responses and neuronal synapse/signaling. The modules with the strongest relationship to human disease-neuronal synapse/signaling and lysosome/stress response-were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated with AD genotype in the hippocampus compared with the cortex. Our findings suggest that the genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.

In fission yeast, 65 non-essential mitochondrial proteins related to respiration and stress become essential in low-glucose conditions.

Mitochondria perform critical functions, including respiration, ATP production, small molecule metabolism, and anti-oxidation, and they are involved in a number of human diseases. While the mitochondrial genome contains a small number of protein-coding genes, the vast majority of mitochondrial proteins are encoded by nuclear genes. In fission yeast Schizosaccharomyces pombe, we screened 457 deletion (del) mutants deficient in nuclear-encoded mitochondrial proteins, searching for those that fail to form colonies in culture medium containing low glucose (0.03-0.1%; low-glucose sensitive, lgs), but that proliferate in regular 2-3% glucose medium. Sixty-five (14%) of the 457 deletion mutants displayed the lgs phenotype. Thirty-three of them are defective either in dehydrogenases, subunits of respiratory complexes, the citric acid cycle, or in one of the nine steps of the CoQ10 biosynthetic pathway. The remaining 32 lgs mutants do not seem to be directly related to respiration. Fifteen are implicated in translation, and six encode transporters. The remaining 11 function in anti-oxidation, amino acid synthesis, repair of DNA damage, microtubule cytoskeleton, intracellular mitochondrial distribution or unknown functions. These 32 diverse lgs genes collectively maintain mitochondrial functions under low (1/20-1/60× normal) glucose concentrations. Interestingly, 30 of them have homologues associated with human diseases.