A travel guide to Cytoscape plugins

Metabolomics and proteomics reveal the inhibitory effect of Lactobacillus crispatus on cervical cancer

Cervical cancer remains a significant global health issue due to its high morbidity and mortality rates. Recently, Lactobacillus crispatus has been recognized for its crucial role in maintaining cervical health. While some studies have explored the use of L. crispatus to mitigate cervical cancer, the underlying mechanisms remain largely unknown. In this study, we employed non-targeted proteomics and metabolomics to investigate how L. crispatus affects the growth of cervical cancer cells (SiHa) and normal cervical cells (Ect1/E6E7). Our findings indicated that the inhibitory effect of L. crispatus on SiHa cells was associated with various biological processes, notably the ferroptosis pathway. Specifically, L. crispatus was found to regulate the expression of proteins such as HMOX1, SLC39A14, VDAC2, ACSL4, and LPCAT3 by SiHa cells, which are closely related to ferroptosis. Additionally, it activated the tricarboxylic acid (TCA) cycle in SiHa cells, leading to increased levels of reactive oxygen species (ROS) and lipid peroxides (LPO). These results revealed the therapeutic potential of L. crispatus in targeting the ferroptosis pathway for cervical cancer treatment, opening new avenues for research and therapy in cervical cancer.

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Chlorogenic acid attenuates idiopathic pulmonary fibrosis: An integrated analysis of network pharmacology, molecular docking, and experimental validation

AIMS

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung condition, the cause of which remains unknown and for which no effective therapeutic treatment is currently available. Chlorogenic acid (CGA), a natural polyphenolic compound found in different plants and foods, has emerged as a promising agent due to its anti-inflammatory, antioxidant, and antifibrotic properties. However, the molecular mechanisms underlying the therapeutic effect of CGA in IPF remain unclear. The purpose of this study was to analyze the pharmacological impact and underlying mechanisms of CGA in IPF.

MAIN METHODS

Using network pharmacology analysis, genes associated with IPF and potential molecular targets of CGA were identified through specialized databases, and a protein-protein interaction (PPI) network was constructed. Molecular docking was performed to accurately select potential therapeutic targets. To investigate the effects of CGA on lung histology and key gene expression, a murine model of bleomycin-induced lung fibrosis was used.

KEY FINDINGS

Network pharmacology analysis identified 384 were overlapped between CGA and IPF. Key targets including AKT1, TP53, JUN, CASP3, BCL2, MMP9, NFKB1, EGFR, HIF1A, and IL1B were identified. Pathway analysis suggested the involvement of cancer, atherosclerosis, and inflammatory processes. Molecular docking confirmed the stable binding between CGA and targets. CGA regulated the expression mRNA of EGFR, MMP9, AKT1, BCL2 and IL1B and attenuated pulmonary fibrosis in the mouse model.

SIGNIFICANCE

CGA is a promising multi-target therapeutic agent for IPF, which is supported by its efficacy in reducing fibrosis through the modulation of key pathways. This evidence provides a basis to further investigate CGA as an IPF potential treatment.

Transcription factor AtNAC002 positively regulates Cu toxicity tolerance in Arabidopsis thaliana

Copper (Cu) is an essential micronutrient for plant growth and development, but environmental Cu pollution has become increasingly severe, adversely affecting both ecosystems and crop productivity. In this study, we identified the AtNAC002 gene as a positive regulator of Cu toxicity in Arabidopsis thaliana. We found that AtNAC002 expression was induced by Cu excess, and the atnac002 mutant was Cu-sensitive, accumulating more Cu than the wild-type. Additionally, atnac002 mutants exhibit reduced activities of antioxidant enzymes (SOD, POD, and CAT), leading to increased levels of reactive oxygen species and malondialdehyde, which decrease Cu resistance. AtNAC002 might play a role in vacuolar and mitochondrial Cu compartmentalization by regulating genes involved in Cu detoxification, specifically COX11 and HCC1. Furthermore, AtNAC002 was implicated in flavone and flavanol biosynthesis, with the atnac002 mutant showing reduced flavonoid content. Our findings suggest that AtNAC002 is integral to the regulation of Cu toxicity tolerance in A. thaliana. This knowledge is critical for advancing our understanding and offers potential molecular breeding targets to enhance plant performance under Cu excess, which is significant for improving global food security and forest restoration.

Bacterial and Symbiodiniaceae communities' variation in corals with distinct traits and geographical distribution

Coral microbiomes play crucial roles in holobiont homeostasis and adaptation. The host's ability to populate broad ecological niches and to cope with environmental changes seems to be related to the flexibility of the coral microbiome. By means of high-throughput DNA sequencing we characterized simultaneously both bacterial (16S rRNA) and Symbiodiniaceae (ITS2) communities of four reef-building coral species (Mussismilia braziliensis, Mussismilia harttii, Montastraea cavernosa, and Favia gravida) that differ in geographic distribution and niche specificity. Samples were collected in a marginal reef system (Abrolhos, Brazil) in four sites of contrasting irradiance and turbidity. Biological filters governed by the host are important in shaping corals' microbiome structure. More structured associated microbial communities by reef site tend to occur in coral species with broader geographic and depth ranges, especially for Symbiodiniaceae, whereas the endemic and habitat-specialist host, M. braziliensis, has relatively more homogenous bacterial communities with more exclusive members. Our findings lend credence to the hypothesis that higher microbiome flexibility renders corals more adaptable to diverse environments, a trend that should be investigated in more hosts and reef areas.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations

Elucidating the molecular dependencies behind the cancer-type specificity of driver mutations may reveal new therapeutic opportunities. We hypothesized that developmental programs would impact the transduction of oncogenic signaling activated by a driver mutation and shape its cancer-type specificity. Therefore, we designed a computational analysis framework by combining single-cell gene expression profiles during fetal organ development, latent factor discovery, and information theory-based differential network analysis to systematically identify transcription factors that selectively respond to driver mutations under the influence of organ-specific developmental programs. After applying this approach to VHL mutations, which are highly specific to clear cell renal cell carcinoma (ccRCC), we revealed important regulators downstream of VHL mutations in ccRCC and used their activities to cluster patients with ccRCC into three subtypes. This classification revealed a more significant difference in prognosis than the previous mRNA profile-based method and was validated in an independent cohort. Moreover, we found that EP300, a key epigenetic factor maintaining the regulatory network of the subtype with the worst prognosis, can be targeted by a small inhibitor, suggesting a potential treatment option for a subset of patients with ccRCC. This work demonstrated an intimate relationship between organ development and oncogenesis from the perspective of systems biology, and the method can be generalized to study the influence of other biological processes on cancer driver mutations.

The global phosphorylation landscape of mouse oocytes during meiotic maturation

Phosphorylation is a key post-translational modification regulating protein function and biological outcomes. However, the phosphorylation dynamics orchestrating mammalian oocyte development remains poorly understood. In the present study, we apply high-resolution mass spectrometry-based phosphoproteomics to obtain the first global in vivo quantification of mouse oocyte phosphorylation. Of more than 8000 phosphosites, 75% significantly oscillate and 64% exhibit marked upregulation during meiotic maturation, indicative of the dominant regulatory role. Moreover, we identify numerous novel phosphosites on oocyte proteins and a few highly conserved phosphosites in oocytes from different species. Through functional perturbations, we demonstrate that phosphorylation status of specific sites participates in modulating critical events including metabolism, translation, and RNA processing during meiosis. Finally, we combine inhibitor screening and enzyme-substrate network prediction to discover previously unexplored kinases and phosphatases that are essential for oocyte maturation. In sum, our data define landscape of the oocyte phosphoproteome, enabling in-depth mechanistic insights into developmental control of germ cells.

Synergistic cytotoxicity and in vitro antioxidant activity of hederagenin and its glycoside from quinoa

Although a series of studies confirm the bioactivities of hederagenin and its glycosides, their synergistic effects and potential mechanisms are still worthy of further exploration. This work investigated the synergistic cytotoxicity and in vitro antioxidant activity of hederagenin and hederagenin 28-O-β-d-glucopyranoside (28-Glc-hederagenin). Hederagenin and 28-Glc-hederagenin inhibited HeLa cell growth and their combination further strengthened this effect. The combination of hederagenin and 28-Glc-hederagenin significantly increased the rate of apoptotic cells, suggesting the presence of a synergistic effect between the two substances. This combination also enhanced in vitro antioxidant activity compared with individual treatments. A network pharmacology and molecular docking-based approach was performed to explore the underlying mechanisms of hederagenin and 28-Glc-hederagenin against cervical cancer and oxidant damage. This work identified 18 related Kyoto Encyclopedia of Genes and Genome pathways, 202 related biological process terms, 17 related CC terms, and 35 related molecular function terms and then revealed 30 nodes and 196 edges. Subsequently, two highly connected clusters and the top four targets were identified. Molecular docking showed potent binding affinity of hederagenin and 28-Glc-hederagenin toward core targets associated with both cervical cancer and oxidant damage. This work may provide scientific basis for the combined use of hederagenin and its glycosides as dietary supplements.

Exploring potential biomarkers and lead molecules in gastric cancer by network biology, drug repurposing and virtual screening strategies

Gastric cancer poses a significant global health challenge, necessitating innovative approaches for biomarker discovery and therapeutic intervention. This study employs a multifaceted strategy integrating network biology, drug repurposing, and virtual screening to elucidate and expand the molecular landscape of gastric cancer. We identified and prioritized key genes implicated in gastric cancer by utilizing data from diverse databases and text-mining techniques. Network analysis underscored intricate gene interactions, emphasizing potential therapeutic targets such as CTNNB1, BCL2, TP53, etc, and highlighted ACTB among the top hub genes crucial in disease progression. Drug repurposing on 626 FDA-approved drugs for digestive system-related cancers revealed Norgestimate and Nimesulide as likely top candidates for gastric cancer, validated by molecular docking and dynamics simulations. Further, combinatorial synthesis of scaffold libraries derived from known chemotypes generated 56,160 virtual compounds, of which 76 new compounds were prioritized based on promising binding affinities and interactions at critical residues. Hotspot residue analysis identified GLU 214 and others as essential for ligand binding stability, enhancing compound efficacy and specificity. These findings support the therapeutic potential of targeting beta-actin protein in gastric cancer treatment, suggesting a future for further experimental validation and clinical translation. In conclusion, this study highlights the potential of repurposable drugs and virtual screening which can be used in combination with existing anti-gastric cancer drugs for gastric cancer therapy, emphasizing the role of computational methodologies in drug discovery.

Actin like 6A is a prognostic biomarker and associated with immune cell infiltration in cancers

PURPOSE

To investigate the role of Actin like 6 A (ACTL6A) in cancer and explore the potential mechanism of its function.

METHODS

Differential expression of ACTL6A was analyzed using Oncomine and TIMER database. Then, we downloaded data sets from TCGA database. The correlation between ACTL6A expression and survival in pan-cancer were analyzed by "survival", "survminer" R package and PrognoScan database. STRING (v 11.0) and stringAPP for Cytoscape v3.7.2 were used to predict ACTL6A associated genes. Copy number and methylation alterations of ACTL6A were analyzed using cBioPortal and GSCALite. Transcription factors were downloaded from The Human Transcription Factors Database and analyzed using "limma" R package, JASPAR and PROMO database. Correlations analysis between ACTL6A and immune cells were performed using TIMER and GEPIA database.

RESULTS

In our studies, we found that ACTL6A was widely upregulated in cancers, which might be attributed to its gene amplifications. Moreover, ACTL6A might regulated by transcription factors (TFs), including E2F1, YY1, CDX2 and HOXD10. In addition, high ACTL6A expression was associated with poor prognosis in most cancers. Meanwhile, ACTL6A was associated with the infiltration of immune cells, especially in liver hepatocellular carcinoma and brain lower grade glioma.

CONCLUSION

Amplification of ACTL6A is correlated with poor prognosis and contribute to immune cells infiltration in LIHC and LGG, which may provide immune-related therapeutic targets to guide clinical strategies.

On discovery of novel hub genes for ER+ and TN breast cancer types through RNA seq data analyses and classification models

Breast cancer (BC) is a malignant neoplasm which is classified into various types defined by underlying molecular factors such as estrogen receptor positive (ER+), progesterone receptor positive (PR+), human epidermal growth factor positive (HER2+) and triple negative (TNBC). Early detection of ER+ and TNBC is crucial in the choice of diagnosis and appropriate treatment strategy. Here we report the key genes associated to ER+ and TNBC using RNA-Seq analysis and machine learning models. Three ER+ and TNBC RNA seq datasets comprising 164 patients in-toto were selected for standard NGS hierarchical data processing and data analyses protocols. Enrichment pathway analysis and network analysis was done and finally top hub genes were identified. To come with a reliable classifier which could distinguish the distinct transcriptome patterns associated to ER+ and TNBC, ML models were built employing Naïve Bayes, SVM and kNN. 1730 common DEG's exhibiting significant logFC values with 0.05 p-value threshold were identified. A list of top ten hub genes were screened on the basis of maximal clique centrality (MCC) which included CDC20, CDK1, BUB1, AURKA, CDCA8, RRM2, TTK, CENPF, CEP55 and NDC80.These genes were found to be involved in crucial cell cycle pathways. k-Nearest Neighbor (kNN) model was observed to be best classifier with accuracy 84%, specificity 66% and sensitivity 95% to differentiate between ER+ and TNBC RNA-Seq transcriptomes. Our screened list of 10 hub genes can thus help unearth novel molecular signatures implicated in ER+ and TNBC onset, prognosis and design of novel protocols for breast cancer diagnostics and therapeutics.

Functional genomics identifies a small secreted protein that plays a role during the biotrophic to necrotrophic shift in the root rot pathogen Phytophthora medicaginis

Introduction

Hemibiotrophic Phytophthora are a group of agriculturally and ecologically important pathogenic oomycetes causing severe decline in plant growth and fitness. The lifestyle of these pathogens consists of an initial biotrophic phase followed by a switch to a necrotrophic phase in the latter stages of infection. Between these two phases is the biotrophic to necrotrophic switch (BNS) phase, the timing and controls of which are not well understood particularly in Phytophthora spp. where host resistance has a purely quantitative genetic basis.

Methods

To investigate this we sequenced and annotated the genome of Phytophthora medicaginis, causal agent of root rot and substantial yield losses to Fabaceae hosts. We analyzed the transcriptome of P. medicaginis across three phases of colonization of a susceptible chickpea host (Cicer arietinum) and performed co-regulatory analysis to identify putative small secreted protein (SSP) effectors that influence timing of the BNS in a quantitative pathosystem.

Results

The genome of P. medicaginis is ~78 Mb, comparable to P. fragariae and P. rubi which also cause root rot. Despite this, it encodes the second smallest number of RxLR (arginine-any amino acid-leucine-arginine) containing proteins of currently sequenced Phytophthora species. Only quantitative resistance is known in chickpea to P. medicaginis, however, we found that many RxLR, Crinkler (CRN), and Nep1-like protein (NLP) proteins and carbohydrate active enzymes (CAZymes) were regulated during infection. Characterization of one of these, Phytmed_10271, which encodes an RxLR effector demonstrates that it plays a role in the timing of the BNS phase and root cell death.

Discussion

These findings provide an important framework and resource for understanding the role of pathogenicity factors in purely quantitative Phytophthora pathosystems and their implications to the timing of the BNS phase.

Allele-Specific Hormone Dynamics in Highly Transgressive F2 Biomass Segregants in Sugarcane (Saccharum spp.)

Sugarcane holds global promise as a biofuel feedstock, necessitating a deep understanding of factors that influence biomass yield. This study unravels the intricate dynamics of plant hormones that govern growth and development in sugarcane. Transcriptome analysis of F2 introgression hybrids, derived from the cross of Saccharum officinarum "LA Purple" and wild Saccharum robustum "MOL5829", was conducted, utilizing the recently sequenced allele-specific genome of "LA Purple" as a reference. A total of 8059 differentially expressed genes were categorized into gene models (21.5%), alleles (68%), paralogs (10%), and tandemly duplicated genes (0.14%). KEGG analysis highlighted enrichment in auxin (IAA), jasmonic acid (JA), and abscisic acid (ABA) pathways, revealing regulatory roles of hormone repressor gene families (Aux/IAA, PP2C, and JAZ). Signaling pathways indicated that downregulation of AUX/IAA and PP2C and upregulation of JAZ repressor genes in high biomass segregants act as key players in influencing downstream growth regulatory genes. Endogenous hormone levels revealed higher concentrations of IAA and ABA in high biomass, which contrasted with lower levels of JA. Weighted co-expression network analysis demonstrated strong connectivity between hormone-related key genes and cell wall structural genes in high biomass genotypes. Expression analysis confirmed the upregulation of genes involved in the synthesis of structural carbohydrates and the downregulation of inflorescence and senescence-related genes in high biomass, which suggested an extended vegetative growth phase. The study underscores the importance of cumulative gene expression, including gene models, dominant alleles, paralogs, and tandemly duplicated genes and activators and repressors of disparate hormone (IAA, JA, and ABA) signaling pathways are the points of hormone crosstalk in contrasting biomass F2 segregants and could be applied for engineering high biomass acquiring varieties.

Syntrichia ruralis: emerging model moss genome reveals a conserved and previously unknown regulator of desiccation in flowering plants

Water scarcity, resulting from climate change, poses a significant threat to ecosystems. Syntrichia ruralis, a dryland desiccation-tolerant moss, provides valuable insights into survival of water-limited conditions. We sequenced the genome of S. ruralis, conducted transcriptomic analyses, and performed comparative genomic and transcriptomic analyses with existing genomes and transcriptomes, including with the close relative S. caninervis. We took a genetic approach to characterize the role of an S. ruralis transcription factor, identified in transcriptomic analyses, in Arabidopsis thaliana. The genome was assembled into 12 chromosomes encompassing 21 169 protein-coding genes. Comparative analysis revealed copy number and transcript abundance differences in known desiccation-associated gene families, and highlighted genome-level variation among species that may reflect adaptation to different habitats. A significant number of abscisic acid (ABA)-responsive genes were found to be negatively regulated by a MYB transcription factor (MYB55) that was upstream of the S. ruralis ortholog of ABA-insensitive 3 (ABI3). We determined that this conserved MYB transcription factor, uncharacterized in Arabidopsis, acts as a negative regulator of an ABA-dependent stress response in Arabidopsis. The new genomic resources from this emerging model moss offer novel insights into how plants regulate their responses to water deprivation.

Quantitative Phosphoproteomic Profiling of Mouse Sperm Maturation in Epididymis Revealed Kinases Important for Sperm Motility

Transcriptionally and translationally silent sperm undergo functional maturation during epididymis traverse, which provides sperm ability to move and is crucial for successful fertilization. However, the molecular mechanisms governing sperm maturation remain poorly understood, especially at the protein post-translational modification level. In this study, we conducted a comprehensive quantitative phosphoproteomic analysis of mouse epididymal sperm from different regions (caput, corpus, and cauda) to unveil the dynamics of protein phosphorylation during sperm maturation. We identified 6447 phosphorylation sites in 1407 phosphoproteins, and 345 phosphoproteins were differentially phosphorylated between caput and cauda sperm. Gene ontology and KEGG pathway analyses showed enrichment of differentially phosphorylated proteins in energy metabolism, sperm motility, and fertilization. Kinase substrate network analysis followed by inhibition assay and quantitative phosphoproteomics analysis showed that TSSK2 kinase is important for sperm motility and progressive motility. This study systemically characterized the intricate phosphorylation regulation during sperm maturation in the mouse epididymis, which can be a basis to elucidate sperm motility acquisition, and to offer potential targets for male contraception and the treatment of male infertility.

Proteomic Characterization of a 3D HER2+ Breast Cancer Model Reveals the Role of Mitochondrial Complex I in Acquired Resistance to Trastuzumab

HER2-targeted therapies, such as Trastuzumab (Tz), have significantly improved the clinical outcomes for patients with HER2+ breast cancer (BC). However, treatment resistance remains a major obstacle. To elucidate functional and metabolic changes associated with acquired resistance, we characterized protein profiles of BC Tz-responder spheroids (RSs) and non-responder spheroids (nRSs) by a proteomic approach. Three-dimensional cultures were generated from the HER2+ human mammary adenocarcinoma cell line BT-474 and a derived resistant cell line. Before and after a 15-day Tz treatment, samples of each condition were collected and analyzed by liquid chromatography-mass spectrometry. The analysis of differentially expressed proteins exhibited the deregulation of energetic metabolism and mitochondrial pathways. A down-regulation of carbohydrate metabolism and up-regulation of mitochondria organization proteins, the tricarboxylic acid cycle, and oxidative phosphorylation, were observed in nRSs. Of note, Complex I-related proteins were increased in this condition and the inhibition by metformin highlighted that their activity is necessary for nRS survival. Furthermore, a correlation analysis showed that overexpression of Complex I proteins NDUFA10 and NDUFS2 was associated with high clinical risk and worse survival for HER2+ BC patients. In conclusion, the non-responder phenotype identified here provides a signature of proteins and related pathways that could lead to therapeutic biomarker investigation.

Comparative Phenotypic and Transcriptomic Analyses Provide Novel Insights into the Molecular Mechanism of Seed Germination in Response to Low Temperature Stress in Alfalfa

Low temperature is the most common abiotic factor that usually occurs during the seed germination of alfalfa (Medicago sativa L.). However, the potential regulatory mechanisms involved in alfalfa seed germination under low temperature stress are still ambiguous. Therefore, to determine the relevant key genes and pathways, the phenotypic and transcriptomic analyses of low-temperature sensitive (Instict) and low-temperature tolerant (Sardi10) alfalfa were conducted at 6 and 15 h of seed germination under normal (20 °C) and low (10 °C) temperature conditions. Germination phenotypic results showed that Sardi10 had the strongest germination ability under low temperatures, which was manifested by the higher germination-related indicators. Further transcriptome analysis indicated that differentially expressed genes were mainly enriched in galactose metabolism and carbon metabolism pathways, which were the most commonly enriched in two alfalfa genotypes. Additionally, fatty acid metabolism and glutathione metabolism pathways were preferably enriched in Sardi10 alfalfa. The Weighted Gene Co-Expression Network Analysis (WGCNA) suggested that genes were closely related to galactose metabolism, fatty acid metabolism, and glutathione metabolism in Sardi10 alfalfa at the module with the highest correlation (6 h of germination under low temperature). Finally, qRT-PCR analysis further validated the related genes involved in the above pathways, which might play crucial roles in regulating seed germination of alfalfa under low temperature conditions. These findings provide new insights into the molecular mechanisms of seed germination underlying the low temperature stress in alfalfa.

Exploring molecular targets: herbal isolates in cervical cancer therapy

OBJECTIVE

Cervical cancer (CxCa) stands as a significant global health challenge, ranking fourth in cancer-related mortality among the female population. While chemotherapy regimens have demonstrated incremental progress in extending overall survival, the outlook for recurrent CxCa patients remains disheartening. An imperative necessity arises to delve into innovative therapeutic avenues, with molecular targeted therapy emerging as a promising candidate. Previous investigations have shed light on the therapeutic effectiveness of five distinct herbal compounds, epicatechin, curcumin, myricetin, jatrorrhizine, and arborinine, within the context of CxCa.

METHODS

A systems biology approach was employed to discern differentially expressed genes (DEGs) in CxCa tissues relative to healthy cervical epithelial tissues. A protein-protein interaction network (PPIN) was constructed, anchored in the genes related to CxCa. The central genes were discerned within the PPIN, and Kaplan-Meier survival curves explored their prognostic significance. An assessment of the binding affinity of the selected herbal compounds to the master regulator of prognostic markers in CxCa was conducted.

RESULTS

A significant correlation between the overexpression of MYC, IL6, JUN, RRM2, and VEGFA and an adverse prognosis in CxCa was indicated. The regulation of these markers is notably influenced by the transcription factor CEBPD. Molecular docking analysis indicated that the binding affinity between myricetin and the CEBPD DNA binding site was robust.

CONCLUSION

The findings presented herein have unveiled pivotal genes and pathways that play a central role in the malignant transformation of CxCa. CEBPD has emerged as a potential target for harnessing the therapeutic potential of myricetin in this context.

Weighted gene co-expression network analysis reveals genes related to growth performance in Hu sheep

Hu sheep are a unique breed in our country with great reproductive potential, the extent of whose breeding has been steadily rising in recent years. The study subjects in this experiment were 8-month-old Hu sheep (n = 112). First of all, the growth performance, slaughter performance and meat quality of their eye muscle quality were assessed, meanwhile their live weight, carcass weight, body length, body height, chest circumference, chest depth and tube circumference were respectively 33.81 ± 5.47 kg, 17.43 ± 3.21 kg, 60.36 ± 4.41 cm, 63.25 ± 3.88 cm, 72.03 ± 5.02 cm, 30.70 ± 2.32 cm and 7.36 ± 0.56 cm, with a significant difference between rams and ewes (P < 0.01). Following that, transcriptome sequencing was done, and candidate genes related to growth performance were identified using the weighted co-expression network analysis (WGCNA) approach, which was used to identified 15 modules, with the turquoise and blue modules having the strongest association with growth and slaughter performance, respectively. We discovered hub genes such as ARHGAP31, EPS8, AKT3, EPN1, PACS2, KIF1C, C12H1orf115, FSTL1, PTGFRN and IFIH1 in the gene modules connected with growth and slaughter performance. Our research identifies the hub genes associated with the growth and slaughter performance of Hu sheep, which play an important role in their muscle growth, organ and cartilage development, blood vessel development and energy metabolic pathways. Our findings might lead to the development of potentially-useful biomarkers for the selection of growth and slaughterer performance-related attributes of sheep and other livestock.

Combination of plant metabolites hinders starch digestion and glucose absorption while facilitating insulin sensitivity to diabetes

Introduction

Diabetes mellitus (DM) is a common endocrine disease resulting from interactions between genetic and environmental factors. Type II DM (T2DM) accounts for approximately 90% of all DM cases. Current medicines used in the treatment of DM have some adverse or undesirable effects on patients, necessitating the use of alternative medications.

Methods

To overcome the low bioavailability of plant metabolites, all entities were first screened through pharmacokinetic, network pharmacology, and molecular docking predictions. Experiments were further conducted on a combination of antidiabetic phytoactive molecules (rosmarinic acid, RA; luteolin, Lut; resveratrol, RS), along with in vitro evaluation (α-amylase inhibition assay) and diabetic mice tests (oral glucose tolerance test, OGTT; oral starch tolerance test, OSTT) for maximal responses to validate starch digestion and glucose absorption while facilitating insulin sensitivity.

Results

The results revealed that the combination of metabolites achieved all required criteria, including ADMET, drug likeness, and Lipinski rule. To determine the mechanisms underlying diabetic hyperglycemia and T2DM treatments, network pharmacology was used for regulatory network, PPI network, GO, and KEGG enrichment analyses. Furthermore, the combined metabolites showed adequate in silico predictions (α-amylase, α-glucosidase, and pancreatic lipase for improving starch digestion; SGLT-2, AMPK, glucokinase, aldose reductase, acetylcholinesterase, and acetylcholine M2 receptor for mediating glucose absorption; GLP-1R, DPP-IV, and PPAR-γ for regulating insulin sensitivity), in vitro α-amylase inhibition, and in vivo efficacy (OSTT versus acarbose; OGTT versus metformin and insulin) as nutraceuticals against T2DM.

Discussion

The results demonstrate that the combination of RA, Lut, and RS could be exploited for multitarget therapy as prospective antihyperglycemic phytopharmaceuticals that hinder starch digestion and glucose absorption while facilitating insulin sensitivity.

Identification of Novel Genes and Pathways of Ovarian Cancer Using a Comprehensive Bioinformatic Framework

Ovarian cancer (OC) is a significant contributor to gynecological cancer-related deaths worldwide, with a high mortality rate. Despite several advances in understanding the pathogenesis of OC, the molecular mechanisms underlying its development and prognosis remain poorly understood. Therefore, the current research study aimed to identify hub genes involved in the pathogenesis of OC that could serve as selective diagnostic and therapeutic targets. To achieve this, the dataset GEO2R was used to retrieve differentially expressed genes. The study identified a total of five genes (CDKN1A, DKK1, CYP1B1, NTS, and GDF15) that were differentially expressed in OC. Subsequently, a network analysis was performed using the STRING database, followed by the construction of a network using Cytoscape. The network analyzer tool in Cytoscape predicted 276 upregulated and 269 downregulated genes. Furthermore, KEGG analysis was conducted to identify different pathways related to OC. Subsequently, survival analysis was performed to validate gene expression alterations and predict hub genes, using a p-value of 0.05 as a threshold. Four genes (CDKN1A, DKK1, CYP1B1, and NTS) were predicted as significant hub genes, while one gene (GDF15) was predicted as non-significant. The adjusted P values of said predicted genes are 2.85E - 07, 5.49E - 06, 4.28E - 07, 1.43E - 07, and 3.70E - 07 for CDKN1A, DKK1, NTS, GDF15, and CYP1B1 respectively; additionally 6.08, 5.76, 5.74, 5.01, and 4.9 LogFc values of the said genes were predicted in GEO data set. In a boxplot analysis, the expression of these genes was analyzed in normal and tumor cells. The study found that three genes were highly expressed in tumor cells, while two genes (CDKN1A and DKK1) were more elevated in normal cells. According to the boxplot analysis for CDKN1A, 50% of tumor cells ranged between approx 3.8 and 5, while 50% of normal cells ranged between approx 6.9 and 7.9, which is greater than tumor cells. This shows that in normal cells, the CYP1B1 has a high expression level according to the GEPIA boxplot; addtionally the boxplot for DKK1 indicated that 50% of tumor cells ranged between approx 0 and 0.5, which was less than that of normal cells which ranged between approx 0.3 and 0.9. It shows that DKK1 is highly expressed in normal genes. Overall, the current study provides novel insights into the molecular mechanisms underlying OC. The identified hub genes and drug candidate targets could potentially serve as alternative diagnostic and therapeutic options for OC patients. Further research is needed to investigate the clinical significance of these findings and develop effective interventions that can improve the prognosis of patients with OC.

Multi-omics analysis reveals a crosstalk between ferroptosis and peroxisomes on steatotic graft failure after liver transplantation

To identify the mechanism underlying macrosteatosis (MaS)-related graft failure (GF) in liver transplantation (LT) by multi-omics network analysis. The transcriptome and metabolome were assayed in graft and recipient plasma in discovery (n = 68) and validation (n = 89) cohorts. Differentially expressed molecules were identified by MaS and GF status. Transcriptional regulatory networks were generated to explore the mechanism for MaS-related inferior post-transplant prognosis. The differentially expressed molecules associated with MaS and GF were enriched in ferroptosis and peroxisome-related pathways. Core features of MaS-related GF were presented on decreased transferrin and impaired anti-oxidative capacity dependent upon dysregulation of transcription factors hepatocyte nuclear factor 4A (HNF4A) and hypoxia-inducible factor 1A (HIF1A). Furthermore, miR-362-3p and miR-299-5p inhibited transferrin and HIF1A expression, respectively. Lower M2 macrophages but higher memory CD4 T cells were observed in MaS-related GF cases. These results were validated in clinical specimens and cellular models. Systemic analysis of multi-omics data depicted a panorama of biological pathways deregulated in MaS-related GF. Transcriptional regulatory networks centered on transferrin and anti-oxidant responses were associated with poor MaS graft quality, qualifying as potential targets to improve prognosis of patients after LT.

Network pharmacology-based screening of active constituents of Avicennia marina and their clinical biochemistry related mechanism against breast cancer

Breast cancer is the second major cause of cancer death in women globally. Avicennia marina is a medicinal plant that belongs to the family Acanthaceae and is known as grey or white mangrove. It has antioxidant, antiviral, anticancer, anti-inflammatory, and antibacterial activity in the treatment of various diseases including cancer. The goal of the study is to use a network pharmacology method to identify the potential phenomena of bioactive compounds of A. marina in the treatment of breast cancer and explore clinical biochemistry related aspects. A total of 74 active compounds of A. marina were retrieved from various databases as well as a literature review and collectively 429 targets of these compounds were identified by STITCH and Swiss Target Prediction databases. Breast cancer related 15606 potential targets were retrieved from the GeneCards database. A Venn diagram was drawn to find common key targets. To check the biological functions, the GO enrichment and KEGG pathways analysis of 171 key targets were performed through the DAVID database. To understand the interactions among key targets, Protein-protein interaction (PPI) studies were completed using the STRING database, and the Protein-Protein Interaction (PPI) network, as well as the compound-target-pathway network, was constructed using Cytoscape 3.9.0. Finally, molecular docking analysis of 5 hub genes named tumor protein 53 (TP53), catenin beta 1 (CTNNB1), interleukin 6 (IL6), tumor necrosis factor (TNF), and RAC-alpha serine/threonine protein kinases 1 (AKT1) with the active constituent of A. marina against breast cancer were performed. Additionally, a molecular docking study demonstrates that active drugs have a higher affinity for the target that may be used to decrease breast cancer. The molecular dynamic simulation analysis predicted the very stable behavior of docked complexes with no global structure deviations seen. The MMGBSA further supported strong intermolecular interactions with net energy values as; AKT1_Betulinic_acid (-20.97 kcal/mol), AKT1_Stigmasterol (-44.56 kcal/mol), TNF_Betulinic_acid (-28.68 kcal/mol) and TNF_Stigmastero (-29.47 kcal/mol).Communicated by Ramaswamy H. Sarma.

Decoding Arabidopsis thaliana CPK/SnRK Superfamily Kinase Client Signaling Networks Using Peptide Library and Mass Spectrometry

Members of the calcium-dependent protein kinase (CDPK/CPK) and SNF-related protein kinase (SnRK) superfamilies are commonly found in plants and some protists. Our knowledge of client specificity of the members of this superfamily is fragmentary. As this family is represented by over 30 members in Arabidopsis thaliana, the identification of kinase-specific and overlapping client relationships is crucial to our understanding the nuances of this large family of kinases as directed towards signal transduction pathways. Herein, we used the kinase client (KiC) assay-a relative, quantitative, high-throughput mass spectrometry-based in vitro phosphorylation assay-to identify and characterize potential CPK/SnRK targets of Arabidopsis. Eight CPKs (1, 3, 6, 8, 17, 24, 28, and 32), four SnRKs (subclass 1 and 2), and PPCK1 and PPCK2 were screened against a synthetic peptide library that contains 2095 peptides and 2661 known phosphorylation sites. A total of 625 in vitro phosphorylation sites corresponding to 203 non-redundant proteins were identified. The most promiscuous kinase, CPK17, had 105 candidate target proteins, many of which had already been discovered. Sequence analysis of the identified phosphopeptides revealed four motifs: LxRxxS, RxxSxxR, RxxS, and LxxxxS, that were significantly enriched among CPK/SnRK clients. The results provide insight into both CPK- and SnRK-specific and overlapping signaling network architectures and recapitulate many known in vivo relationships validating this large-scale approach towards discovering kinase targets.

Integrating Network Pharmacology and Molecular Docking Approach to Elucidate the Mechanism of Commiphora wightii for the Treatment of Rheumatoid Arthritis

Background

Rheumatoid arthritis (RA) is considered a notable prolonged inflammatory condition with no proper cure. Synovial inflammation and synovial pannus are crucial in the onset of RA. The "tumor-like" invading proliferation of new arteries is a keynote of RA. Commiphora wightii (C wightii) is a perennial, deciduous, and trifoliate plant used in several areas of southeast Asia to cure numerous ailments, including arthritis, diabetes, obesity, and asthma. Several in vitro investigations have indicated C wightii's therapeutic efficacy in the treatment of arthritis. However, the precise molecular action is yet unknown.

Material and methods

In this study, a network pharmacology approach was applied to uncover potential targets, active therapeutic ingredients and signaling pathways in C wightii for the treatment of arthritis. In the groundwork of this research, we examined the active constituent-compound-target-pathway network and evaluated that (Guggulsterol-V, Myrrhahnone B, and Campesterol) decisively donated to the development of arthritis by affecting tumor necrosis factor (TNF), PIK3CA, and MAPK3 genes. Later on, docking was employed to confirm the active components' efficiency against the potential targets.

Results

According to molecular-docking research, several potential targets of RA bind tightly with the corresponding key active ingredient of C wightii. With the aid of network pharmacology techniques, we conclude that the signaling pathways and biological processes involved in C wightii had an impact on the prevention of arthritis. The outcomes of molecular docking also serve as strong recommendations for future research. In the context of this study, network pharmacology combined with molecular docking analysis showed that C wightii acted on arthritis-related signaling pathways to exhibit a promising preventive impact on arthritis.

Conclusion

These results serve as the basis for grasping the mechanism of the antiarthritis activity of C wightii. However, further in vivo/in vitro study is needed to verify the reliability of these targets for the treatment of arthritis.

A Hadal Streptomyces-Derived Echinocandin Acylase Discovered through the Prioritization of Protein Families

Naturally occurring echinocandin B and FR901379 are potent antifungal lipopeptides featuring a cyclic hexapeptide nucleus and a fatty acid side chain. They are the parent compounds of echinocandin drugs for the treatment of severe fungal infections caused by the Candida and Aspergilla species. To minimize hemolytic toxicity, the native fatty acid side chains in these drug molecules are replaced with designer acyl side chains. The deacylation of the N-acyl side chain is, therefore, a crucial step for the development and manufacturing of echinocandin-type antibiotics. Echinocandin E (ECE) is a novel echinocandin congener with enhanced stability generated via the engineering of the biosynthetic machinery of echinocandin B (ECB). In the present study, we report the discovery of the first echinocandin E acylase (ECEA) using the enzyme similarity tool (EST) for enzymatic function mining across protein families. ECEA is derived from Streptomyces sp. SY1965 isolated from a sediment collected from the Mariana Trench. It was cloned and heterologously expressed in S. lividans TK24. The resultant TKecea66 strain showed efficient cleavage activity of the acyl side chain of ECE, showing promising applications in the development of novel echinocandin-type therapeutics. Our results also provide a showcase for harnessing the essentially untapped biodiversity from the hadal ecosystems for the discovery of functional molecules.

Blueprint of differentially expressed genes reveals the dynamic gene expression landscape and the gender biases in long COVID

BACKGROUND

Long COVID has appeared as a significant global health issue and is an extra burden to the healthcare system. It affects a considerable number of people throughout the globe. However, substantial research gaps have been noted in understanding the mechanism and genomic landscape during the long COVID infection. A study has aimed to identify the differentially expressed genes (DEGs) in long COVID patients to fill the gap.

METHODS

We used the RNA-seq GEO dataset acquired through the GPL20301 Illumina HiSeq 4000 platform. The dataset contains 36 human samples derived from PBMC (Peripheral blood mononuclear cells). Thirty-six human samples contain 13 non-long COVID individuals' samples and 23 long COVID individuals' samples, considered the first direction analysis. Here, we performed two-direction analyses. In the second direction analysis, we divided the dataset gender-wise into four groups: the non-long COVID male group, the long COVID male group, the non-long COVID female group, and the long COVID female group.

RESULTS

In the first analysis, we found no gene expression. In the second analysis, we identified 250 DEGs. During the DEG profile analysis of the non-long COVID male group and the long COVID male group, we found three upregulated genes: IGHG2, IGHG4, and MIR8071-2. Similarly, the analysis of the non-long COVID female group and the long COVID female group reveals eight top-ranking genes. It also indicates the gender biases of differentially expressed genes among long COVID individuals. We found several DEGs involved in PPI and co-expression network formation. Similarly, cluster enrichment and gene list enrichment analysis were performed, suggesting several genes are involved in different biological pathways or processes.

CONCLUSIONS

This study will help better understand the gene expression landscape in long COVID. However, it might help the discovery and development of therapeutics for long COVID.

Genome-wide identification of nitrate transporter 1/peptide transporter family (NPF) induced by arbuscular mycorrhiza in the maize genome

The Transporter 1/Peptide Transporter Family (NPF) is essential for the uptake and transport of nitrate nitrogen. Significant increases in nitrogen have been increasingly reported for many mycorrhizal plants, but there are few reports on maize. Here, we have identified the maize NPF family and screened for arbuscular mycorrhiza fungi (AMF) induced NPFs. In this study, a systematic analysis of the maize NPF gene family was performed. A total of 82 NPF genes were identified in maize. ZmNPF4.5 was strongly induced by AMF in both low and high nitrogen. Lotus japonicus hairy root-induced transformation experiments showed that ZmNPF4.5 promoter-driven GUS activity was restricted to cells containing tufts. Yeast backfill experiments indicate that ZmNPF4.5 functions in nitrate uptake. Therefore, we speculate that ZmNPF4.5 is a key gene for nitrate-nitrogen uptake in maize through the mycorrhizal pathway. This is a reference value for further exploring the acquisition of nitrate-nitrogen by maize through AMF pathway.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-024-01464-3.

Mechanism of Danggui Buxue decoction in the treatment of myocardial infarction based on network pharmacology and experimental identification

Background

Myocardial infarction (MI) remains one of the major causes of high morbidity and mortality worldwide. Danggui Buxue Decoction (DBD)-an ancient Chinese herbal decoction-has been used to prevent coronary heart disease, which was called "chest palsy" in ancient clinics. However, the mechanism of DBD in the treatment of MI remains unclear. The aim of this study was to explore the effect and mechanism of DBD on MI by combining network pharmacology with in vivo experiments.

Materials and methods

First, public databases were used to identify the key active chemicals and possible targets of DBD. The MI targets were obtained from the Therapeutic Target Database, and the function of the target genes in relation to linked pathways was investigated. Subsequently, Cytoscape software was used to build a target-signaling pathway network. Finally, the efficacy of DBD therapy on MI was validated using in vivo investigations combined with molecular docking.

Results

In traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), 27 bioactive compounds were screened from DBD. A total of 213 common targets were obtained, including 507 DBD targets and 2566 MI targets. Enrichment analysis suggests that PI3K/AKT is a potential signaling pathway for DBD-based protection. Immunofluorescence and protein blotting confirmed PI3K/AKT1, ERK2, and CASPASE-9 as the target proteins. Molecular docking analysis showed that quercetin, kaempferol, isoflavanones, isorhamnetin, hederagenin, and formononetin had high binding affinity to AKT1, ERK2, and CASPASE-9.

Conclusions

This study demonstrated that the therapeutic benefit of DBD on MI may be mediated via target proteins in the PI3K/AKT pathway, such as AKT1, ERK2, and CASPASE-9. Our study data can help to provide ideas and identify new treatment targets for MI.

Analyzing molecular signatures in preeclampsia and fetal growth restriction: Identifying key genes, pathways, and therapeutic targets for preterm birth

Background

Intrauterine growth restriction (IUGR) and preeclampsia (PE) are intricately linked with specific maternal health conditions, exhibit shared placental abnormalities, and play pivotal roles in precipitating preterm birth (PTB) incidences. However, the molecular mechanism underlying the association between PE and IUGR has not been determined. Therefore, we aimed to analyze the data of females with PE and those with PE + IUGR to identify the key gene(s), their molecular pathways, and potential therapeutic interactions.

Methods

In this study, a comprehensive relationship analysis of both PE and PE + IUGR was conducted using RNA sequence datasets. Using two datasets (GSE148241 and GSE114691), differential gene expression analysis via DESeq2 through R-programming was performed. Gene set enrichment analysis was performed using ClusterProfiler, protein‒protein interaction (PPI) networks were constructed, and cluster analyses were conducted using String and MCODE in Cytoscape. Functional enrichment analyses of the resulting subnetworks were performed using ClueGO software. The hub genes were identified under both conditions using the CytoHubba method. Finally, the most common hub protein was docked against a library of bioactive flavonoids and PTB drugs using the PyRx AutoDock tool, followed by molecular dynamic (MD) simulation analysis. Pharmacokinetic analysis was performed to determine the ADMET properties of the compounds using pkCSM.

Results

We identified eight hub genes highly expressed in the case of PE, namely, PTGS2, ENG, KIT, MME, CGA, GAPDH, GPX3, and P4HA1, and the network of the PE + IUGR gene set demonstrated that nine hub genes were overexpressed, namely, PTGS2, FGF7, FGF10, IL10, SPP1, MPO, THBS1, CYBB, and PF4. PTGS2 was the most common hub gene found under both conditions (PE and PEIUGR). Moreover, the greater (-9.1 kcal/mol) molecular binding of flavoxate to PTGS2 was found to have satisfactory pharmacokinetic properties compared with those of other compounds. The flavoxate-bound PTGS2 protein complex remained stable throughout the simulation; with a ligand fit to protein, i.e., a RMSD ranging from ∼2.0 to 4.0 Å and a RMSF ranging from ∼0.5 to 2.9 Å, was observed throughout the 100 ns analysis.

Conclusion

The findings of this study may be useful for treating PE and IUGR in the management of PTB.

Functional Redundant Microbiome Enhanced Anaerobic Digestion Efficiency under Ammonium Inhibition Conditions

Revealing the role of functional redundancy is of great importance considering its key role in maintaining the stability of microbial ecosystems in response to various disturbances. However, experimental evidence on this point is still lacking due to the difficulty in "manipulating" and depicting the degree of redundancy. In this study, manipulative experiments of functional redundancy were conducted by adopting the mixed inoculation strategy to evaluate its role in engineered anaerobic digestion systems under ammonium inhibition conditions. The results indicated that the functional redundancy gradient was successfully constructed and confirmed by evidence from pathway levels. All mixed inoculation groups exhibited higher methane production regardless of the ammonium level, indicating that functional redundancy is crucial in maintaining the system's efficiency. Further analysis of the metagenome-assembled genomes within different functional guilds revealed that the extent of redundancy decreased along the direction of the anaerobic digestion flow, and the role of functional redundancy appeared to be related to the stress level. The study also found that microbial diversity of key functional populations might play a more important role than their abundance on the system's performance under stress. The findings provide direct evidence and highlight the critical role of functional redundancy in enhancing the efficiency and stability of anaerobic digestion.

Improving impact of heparan sulfate on the endothelial glycocalyx abnormalities in atherosclerosis as revealed by glycan-protein interactome

Endothelial dysfunction induced by oxidative stress is an early predictor of atherosclerosis, which can cause various cardiovascular diseases. The glycocalyx layer on the endothelial cell surface acts as a barrier to maintain endothelial biological function, and it can be impaired by oxidative stress. However, the mechanism of glycocalyx damage during the development of atherosclerosis remains largely unclear. Herein, we established a novel strategy to address these issues from the glycomic perspective that has long been neglected. Using countercharged fluorescence protein staining and quantitative mass spectrometry, we found that heparan sulfate, a major component of the glycocalyx, was structurally altered by oxidative stress. Comparative proteomics and protein microarray analysis revealed several new heparan sulfate-binding proteins, among which alpha-2-Heremans-Schmid glycoprotein (AHSG) was identified as a critical protein. The molecular mechanism of AHSG with heparin was characterized through several methods. A heparan analog could relieve atherosclerosis by protecting heparan sulfate from degradation during oxidative stress and by reducing the accumulation of AHSG at lesion sites. In the present study, the molecular mechanism of anti-atherosclerotic effect of heparin through interaction with AHSG was revealed. These findings provide new insights into understanding of glycocalyx damage in atherosclerosis and lead to the development of corresponding therapeutics.

Integrative analysis reveals associations between oral microbiota dysbiosis and host genetic and epigenetic aberrations in oral cavity squamous cell carcinoma

Dysbiosis of the human oral microbiota has been reported to be associated with oral cavity squamous cell carcinoma (OSCC) while the host-microbiota interactions with respect to the potential impact of pathogenic bacteria on host genomic and epigenomic abnormalities remain poorly studied. In this study, the mucosal bacterial community, host genome-wide transcriptome and DNA CpG methylation were simultaneously profiled in tumors and their adjacent normal tissues of OSCC patients. Significant enrichment in the relative abundance of seven bacteria species (Fusobacterium nucleatum, Treponema medium, Peptostreptococcus stomatis, Gemella morbillorum, Catonella morbi, Peptoanaerobacter yurli and Peptococcus simiae) were observed in OSCC tumor microenvironment. These tumor-enriched bacteria formed 254 positive correlations with 206 up-regulated host genes, mainly involving signaling pathways related to cell adhesion, migration and proliferation. Integrative analysis of bacteria-transcriptome and bacteria-methylation correlations identified at least 20 dysregulated host genes with inverted CpG methylation in their promoter regions associated with enrichment of bacterial pathogens, implying a potential of pathogenic bacteria to regulate gene expression, in part, through epigenetic alterations. An in vitro model further confirmed that Fusobacterium nucleatum might contribute to cellular invasion via crosstalk with E-cadherin/β-catenin signaling, TNFα/NF-κB pathway and extracellular matrix remodeling by up-regulating SNAI2 gene, a key transcription factor of epithelial-mesenchymal transition (EMT). Our work using multi-omics approaches explored complex host-microbiota interactions and provided important insights into genetic and functional basis in OSCC tumorigenesis, which may serve as a precursor for hypothesis-driven study to better understand the causational relationship of pathogenic bacteria in this deadly cancer.

Targeting bladder cancer with Trigonella foenum-graecum: a computational study using network pharmacology and molecular docking

Trigonella foenum-graecum (TF-graecum), known as Hulba or Fenugreek, is one of the oldest known medicinal plants. It has been found to have antimicrobial, antifungal, antioxidant, wound-healing, anti-diarrheal, hypoglycemic, anti-diabetic, and anti-inflammatory activities. In our current report, we have collected and screened the active compounds of TF-graecum and their potential targets via different pharmacology platforms. Network construction shows that eight active compounds may act on 223 potential bladder cancer targets. The pathway enrichment analysis for the seven potential targets of the eight compounds selected, based on KEGG pathway analysis, was conducted to clarify the potential pharmacological effects. Finally, molecular docking and molecular dynamics simulation showed the stability of protein-ligand interactions. This study highlights the need for increased research into the potential medical benefits of this plant.Communicated by Ramaswamy H. Sarma.

Integrated analysis of differently expressed microRNAs and mRNAs at different postnatal stages reveals intramuscular fat deposition regulation in goats (Capra hircus)

Intramuscular fat refers to the adipose tissue distributed in the muscle. It is an important indicator that affects the quality of goat meat, and can directly affect the tenderness and flavor of goat meat. Our previous study revealed the mRNA that may be crucial for intramuscular fat deposition during goat growth; however, how the microRNAs (miRNAs) are involved in the process is largely unclear. In the present study, a total of 401 known miRNAs and 120 goat novel miRNAs, including 110 differentially expressed (DE) miRNAs, were identified among longissimus dorsi from three growth stages (2, 9, and 24 months) by miRNA sequencing. Combining analysis of the DE mRNAs and DE miRNAs was then performed by miRDB and miRwalk, and miR-145-5p and FOXO1, miR-487b-3p, and PPARG coactivator 1 α (PPARGC1A), miR-345-3p, and solute carrier family 2 member 4 (SLC2A4), etc. were shown to closely associate with lipid metabolism, which was then validated by a correlation analysis. The final DE mRNAs were significantly enriched in fatty acid transmembrane transport, fatty acid homeostasis, apelin signaling pathway, glucagon signaling pathway, insulin signaling pathway, and AMPK signaling pathway by gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Besides, miR-145-5p showed a certain effect on goat intramuscular fat metabolism by acting on the possible target gene Forkhead Box O1 (FOXO1). These data provide some theoretical support for improving the quality of goat meat.

Drying without dying: A genome database for desiccation-tolerant plants and evolution of desiccation tolerance

Desiccation is typically fatal, but a small number of land plants have evolved vegetative desiccation tolerance (VDT), allowing them to dry without dying through a process called anhydrobiosis. Advances in sequencing technologies have enabled the investigation of genomes for desiccation-tolerant plants over the past decade. However, a dedicated and integrated database for these valuable genomic resources has been lacking. Our prolonged interest in VDT plant genomes motivated us to create the "Drying without Dying" database, which contains a total of 16 VDT-related plant genomes (including 10 mosses) and incorporates 10 genomes that are closely related to VDT plants. The database features bioinformatic tools, such as blast and homologous cluster search, sequence retrieval, Gene Ontology term and metabolic pathway enrichment statistics, expression profiling, co-expression network extraction, and JBrowser exploration for each genome. To demonstrate its utility, we conducted tailored PFAM family statistical analyses, and we discovered that the drought-responsive ABA transporter AWPM-19 family is significantly tandemly duplicated in all bryophytes but rarely so in tracheophytes. Transcriptomic investigations also revealed that response patterns following desiccation diverged between bryophytes and angiosperms. Combined, the analyses provided genomic and transcriptomic evidence supporting a possible divergence and lineage-specific evolution of VDT in plants. The database can be accessed at http://desiccation.novogene.com. We expect this initial release of the "Drying without Dying" plant genome database will facilitate future discovery of VDT genetic resources.

Expression of immune related genes and possible regulatory mechanisms in different stages of non-alcoholic fatty liver disease

Background

Non-alcoholic fatty liver disease (NAFLD), which includes simple steatosis (SS) and non-alcoholic steatohepatitis (NASH), is a significant contributor to liver disease on a global scale. The change of immunity-related genes (IRGs) expression level leads to different immune infiltrations. However, the expression of IRGs and possible regulatory mechanisms involved in NAFLD remain unclear. The objective of our research is to investigate crucial genes linked to the development of NAFLD and the transition from SS to NASH.

Methods

Dataset GSE89632, which includes healthy controls, SS patients, and NASH patients, was obtained using the GEO database. To examine the correlation between sets of genes and clinical characteristics, we employed weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Hub genes were extracted using a network of protein-protein interactions (PPI) and three different machine learning algorithms. To validate the findings, another dataset that is publicly accessible and mice that were subjected to a high-fat diet (HFD) or MCD diet were utilized. Furthermore, the ESTIMATE algorithm and ssGSEA were employed to investigate the immune landscape in the normal versus SS group and SS versus NASH group, additionally, the relationship between immune infiltration and the expression of hub genes was also examined.

Results

A total of 28 immune related key genes were selected. Most of these genes expressed reverse patterns in the initial and progressive stages of NAFLD. GO and KEGG analyses showed that they were focused on the cytokine related pathways and immune cell activation and chemotaxis. After screening by various algorithms, we obtained two hub genes, including JUN and CCL20. Validation of these findings was confirmed by analyzing gene expression patterns in both the validation dataset and the mouse model. Ultimately, two hub genes were discovered to have a significant correlation with the infiltration of immune cells.

Conclusion

We proposed that there were dynamic changes in the expression levels of IRGs in different stages of NAFLD disease, which led to different immune landscapes in SS and NASH. The findings of our research could serve as a guide for the accurate management of various phases of NAFLD.

Neutral Sphingomyelinase 2 Inhibition Limits Hepatic Steatosis and Inflammation

Non-alcoholic fatty liver disease (NAFLD) is manifested by hepatic steatosis, insulin resistance, hepatocyte death, and systemic inflammation. Obesity induces steatosis and chronic inflammation in the liver. However, the precise mechanism underlying hepatic steatosis in the setting of obesity remains unclear. Here, we report studies that address this question. After 14 weeks on a high-fat diet (HFD) with high sucrose, C57BL/6 mice revealed a phenotype of liver steatosis. Transcriptional profiling analysis of the liver tissues was performed using RNA sequencing (RNA-seq). Our RNA-seq data revealed 692 differentially expressed genes involved in processes of lipid metabolism, oxidative stress, immune responses, and cell proliferation. Notably, the gene encoding neutral sphingomyelinase, SMPD3, was predominantly upregulated in the liver tissues of the mice displaying a phenotype of steatosis. Moreover, nSMase2 activity was elevated in these tissues of the liver. Pharmacological and genetic inhibition of nSMase2 prevented intracellular lipid accumulation and TNFα-induced inflammation in in-vitro HepG2-steatosis cellular model. Furthermore, nSMase2 inhibition ameliorates oxidative damage by rescuing PPARα and preventing cell death associated with high glucose/oleic acid-induced fat accumulation in HepG2 cells. Collectively, our findings highlight the prominent role of nSMase2 in hepatic steatosis, which could serve as a potential therapeutic target for NAFLD and other hepatic steatosis-linked disorders.

Redox regulation of m6A methyltransferase METTL3 in β-cells controls the innate immune response in type 1 diabetes

Type 1 diabetes (T1D) is characterized by the destruction of pancreatic β-cells. Several observations have renewed the interest in β-cell RNA sensors and editors. Here, we report that N 6-methyladenosine (m6A) is an adaptive β-cell safeguard mechanism that controls the amplitude and duration of the antiviral innate immune response at T1D onset. m6A writer methyltransferase 3 (METTL3) levels increase drastically in β-cells at T1D onset but rapidly decline with disease progression. m6A sequencing revealed the m6A hyper methylation of several key innate immune mediators, including OAS1, OAS2, OAS3 and ADAR1 in human islets and EndoC-βH1 cells at T1D onset. METTL3 silencing enhanced 2'-5'-oligoadenylate synthetase levels by increasing its mRNA stability. Consistently, in vivo gene therapy to prolong Mettl3 overexpression specifically in β-cells delayed diabetes progression in the non-obese diabetic mouse model of T1 D. Mechanistically, the accumulation of reactive oxygen species blocked upregulation of METTL3 in response to cytokines, while physiological levels of nitric oxide enhanced METTL3 levels and activity. Furthermore, we report that the cysteines in position C276 and C326 in the zinc finger domains of the METTL3 protein are sensitive to S-nitrosylation and are important to the METTL3-mediated regulation of oligoadenylate synthase mRNA stability in human β-cells. Collectively, we report that m6A regulates the innate immune response at the β-cell level during the onset of T1D in humans.

Acid phosphatase involved in phosphate homeostasis in Brassica napus and the functional analysis of BnaPAP10s

Purple acid phosphatases (PAPs) are involved in activating the rhizosphere's organic phosphorus (P) and promoting P recycling during plant development, especially under the long-term P deficiency conditions in acid soil. However, the function of BnaPAPs in response to P deficiency stress in Brassica napus has rarely been explored. In this study, we found that the acid phosphatase activities (APA) of rapeseed shoot and root increased under P deficienct conditions. Genome-wide identification found that 82 PAP genes were unevenly distributed on 19 chromosomes in B. napus, which could be divided into eight subfamilies. The segmental duplication events were the main driving force for expansion during evolution, and the gene structures and conserved motifs of most members within the same subfamily were highly conservative. Moreover, the expression levels of 37 and 23 different expressed genes were induced by low P in leaf and root, respectively. BnaA09.PAP10a and BnaC09.PAP10a were identified as candidate genes via interaction networks. Significantly, both BnaPAP10a overexpression lines significantly increased root-related APA and total phosphate concentration under P deficiency and ATP supply conditions, thereby improving plant growth and root length. In summary, our results provided a valuable foundation for further study of BnaPAP functions.

Multiomics Analyses With Stool-Type Stratification in Patient Cohorts and Blautia Identification as a Potential Bacterial Modulator in Type 2 Diabetes Mellitus

Heterogeneity in host and gut microbiota hampers microbial precision intervention of type 2 diabetes mellitus (T2DM). Here, we investigated novel features for patient stratification and bacterial modulators for intervention, using cross-sectional patient cohorts and animal experiments. We collected stool, blood, and urine samples from 103 patients with recent-onset T2DM and 25 healthy control subjects (HCs), performed gut microbial composition and metabolite profiling, and combined it with host transcriptome, metabolome, cytokine, and clinical data. Stool type (dry or loose stool), a feature of the stool microenvironment recently explored in microbiome studies, was used for stratification of patients with T2DM as it explained most of the variation in the multiomics data set among all clinical parameters in our covariate analysis. T2DM with dry stool (DM-DS) and loose stool (DM-LS) were clearly differentiated from HC and each other by LightGBM models, optimal among multiple machine learning models. Compared with DM-DS, DM-LS exhibited discordant gut microbial taxonomic and functional profiles, severe host metabolic disorder, and excessive insulin secretion. Further cross-measurement association analysis linked the differential microbial profiles, in particular Blautia abundances, to T2DM phenotypes in our stratified multiomics data set. Notably, oral supplementation of Blautia to T2DM mice induced inhibitory effects on lipid accumulation, weight gain, and blood glucose elevation with simultaneous modulation of gut bacterial composition, revealing the therapeutic potential of Blautia. Our study highlights the clinical implications of stool microenvironment stratification and Blautia supplementation in T2DM, offering promising prospects for microbial precision treatment of metabolic diseases.

ARTICLE HIGHLIGHTS

Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes

Exploring the molecular basis of disease severity in rare disease scenarios is a challenging task provided the limitations on data availability. Causative genes have been described for Congenital Myasthenic Syndromes (CMS), a group of diverse minority neuromuscular junction (NMJ) disorders; yet a molecular explanation for the phenotypic severity differences remains unclear. Here, we present a workflow to explore the functional relationships between CMS causal genes and altered genes from each patient, based on multilayer network community detection analysis of complementary biomedical information provided by relevant data sources, namely protein-protein interactions, pathways and metabolomics. Our results show that CMS severity can be ascribed to the personalized impairment of extracellular matrix components and postsynaptic modulators of acetylcholine receptor (AChR) clustering. This work showcases how coupling multilayer network analysis with personalized -omics information provides molecular explanations to the varying severity of rare diseases; paving the way for sorting out similar cases in other rare diseases.

Disulfidptosis characterizes the tumor microenvironment and predicts immunotherapy sensitivity and prognosis in bladder cancer

Background

Bladder cancer (BLCA) is prone to metastasis and has poor prognosis with unsatisfactory treatment responsiveness. Disulfidptosis is a recently discovered, novel mode of cell death that is closely associated with human cancers. However, a comprehensive analysis of the relationship between disulfidptosis and BLCA is lacking. Therefore, this study aimed to explore the potential effect of disulfidptosis on BLCA and identify a biomarker for evaluating the prognosis and immunotherapy of patients with BLCA.

Material and methods

We acquired BLCA RNA sequencing data from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) cohort (containing 19 normal samples and 409 tumor samples) and the GES39281 cohort (containing 94 tumor samples) which were used for external validation of the signature. Initially, we performed unsupervised consensus clustering to explore disulfidptosis-related subgroups. We then conducted functional enrichment analysis on these subgroups to gain insights into their biological significance and evaluate their immunotherapy response and chemotherapy sensitivity. Next, we conducted Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression to construct a prognostic signature in the TCGA training set for prognosis-related differentially expressed genes (DEGs) in the disulfidptosis-related subgroups. Subsequently, we used a receiver operating characteristic (ROC) curve and independent prognostic analysis to validate the predictive performance of the signature in the TCGA testing and the GES39281 cohorts. Finally, we explored the therapeutic value of this signature in patients with BLCA, in terms of immunotherapy and chemotherapy.

Result

In this study, we obtained two subgroups: DRG-high (238 samples) and DRG-low (160 samples). The DRG-high group exhibited a poor survival rate compared to the DRG-low group and had a significant association with tumor grade, stage, and metastasis. Additionally, several pathways related to cancer and the immune system were enriched in the high-DRG group. Moreover, the DRG-high group exhibited higher expression of PD1 and CTLA4 and had a better response to immunotherapy in patients with both PD1 and CTLA4 positivity. Conversely, the DRG-high group was more sensitive to common chemotherapeutic agents. A prognostic signature was created, consisting of COL5A1, DIRAS3, NKG7, and POLR3G and validated as having a robust predictive capability. Patients in the low-risk-score group had more immune cells associated with tumor suppression and better immunotherapy outcomes.

Conclusion

This study contributes to our understanding of the characteristics of disulfidptosis-related subgroups in BLCA. Disulfidptosis-related signatures can be used to assess the prognosis and immunotherapy of patients with BLCA.

Comprehensive transcriptomic analysis unveils the interplay of mRNA and LncRNA expression in shaping collagen organization and skin development in Dezhou donkeys

The primary focus of donkey hide gelatin processing lies in the dermal layer of donkey hide due to its abundant collagen content. However, the molecular mechanism involved in collagen organization and skin development in donkey skin tissue across various developmental stages remains incomplete. The current study aims to investigate the transcriptomic screening of lncRNAs and mRNA associated with skin development and collagen organization across different ages in Dezhou donkeys' skin. In the pursuit of this objective, we used nine skin tissue samples obtained from Dezhou donkeys at various ages including 8-month fetal stage, followed by 2 and 8 years. RNA-seq analysis was performed for the transcriptomic profiling of differentially expressed genes (DEGs) and lncRNAs associated with skin development in different age groups. Our investigation revealed the presence of 6,582, 6,455, and 405 differentially expressed genes and 654, 789, and 29 differentially expressed LncRNAs within the skin tissues of Dezhou donkeys when comparing young donkeys (YD) vs. middle-aged donkeys (MD), YD vs. old donkeys (OD), and MD vs. OD, respectively. Furthermore, we identified Collagen Type I Alpha 1 Chain (COL1A1), Collagen Type III Alpha 1 Chain (COL3A1), and Collagen Type VI Alpha 5 Chain (COL6A5) as key genes involved in collagen synthesis, with COL1A1 being subject to cis-regulation by several differentially expressed LncRNAs, including ENSEAST00005041187, ENSEAST00005038497, and MSTRG.17248.1, among others. Interestingly, collagen organizational and skin development linked pathways including Protein digestion and absorption, metabolic pathways, Phosphatidylinositol 3-Kinase-Protein Kinase B signaling pathway (PI3K-Akt signaling pathway), Extracellular Matrix-Receptor Interaction (ECM-receptor interaction), and Relaxin signaling were also reported across different age groups in Dezhou donkey skin. These findings enhance our comprehension of the molecular mechanisms underlying Dezhou donkey skin development and collagen biosynthesis and organization, thus furnishing a solid theoretical foundation for future research endeavors in this domain.

Exploring the molecular mechanism of Chlorella vulgaris in response to androstenedione exposure based on genes continuously up-regulated in transcription analysis

Androstenedione (ADSD) is one of the widely detected androgens in diverse aquatic environments. However, there were few reports on the molecular mechanism of Chlorella vulgaris exposure to ADSD. In our previous research, we have investigated the genes associated with chlorophyll metabolism in Chlorella vulgaris response to ADSD. In this study, we focus on continuously up-regulated genes to explore the mechanism underlying Chlorella vulgaris resistance to ADSD toxicity. Chlorella vulgaris was exposed to ADSD with five concentration gradients. The continuously up-regulated genes were enriched by Series Test of Cluster (STC) analysis and verified by qRT-PCR. Microalgae Super Oxidase Dimutase (SOD) and Microalgae Malonic dialdehyde (MDA), two indicators of oxidative stress, were determined by ELISA after exposure to ADSD. The results showed that ADSD can stimulate the production of extracellular polymeric substances (EPS) and lead to enlargement in the cell body of Chlorella vulgaris. In addition, steroid biosynthesis and oxidoreductase activity processes were consistently up-regulated upon exposure to ADSD. In conclusion, our study highlighted the crucial role of phenotypic modification, hormone synthesis, and redox mechanisms in protecting Chlorella vulgaris cells from the harmful effects of ADSD contamination.

Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks

Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.

A 19-Gene Signature of Serous Ovarian Cancer Identified by Machine Learning and Systems Biology: Prospects for Diagnostics and Personalized Medicine

Ovarian cancer is a major cause of cancer deaths among women. Early diagnosis and precision/personalized medicine are essential to reduce mortality and morbidity of ovarian cancer, as with new molecular targets to accelerate drug discovery. We report here an integrated systems biology and machine learning (ML) approach based on the differential coexpression analysis to identify candidate systems biomarkers (i.e., gene modules) for serous ovarian cancer. Accordingly, four independent transcriptome datasets were statistically analyzed independently and common differentially expressed genes (DEGs) were identified. Using these DEGs, coexpressed gene pairs were unraveled. Subsequently, differential coexpression networks between the coexpressed gene pairs were reconstructed so as to identify the differentially coexpressed gene modules. Based on the established criteria, "SOV-module" was identified as being significant, consisting of 19 genes. Using independent datasets, the diagnostic capacity of the SOV-module was evaluated using principal component analysis (PCA) and ML techniques. PCA showed a sensitivity and specificity of 96.7% and 100%, respectively, and ML analysis showed an accuracy of up to 100% in distinguishing phenotypes in the present study sample. The prognostic capacity of the SOV-module was evaluated using survival and ML analyses. We found that the SOV-module's performance for prognostics was significant (p-value = 1.36 × 10-4) with an accuracy of 63% in discriminating between survival and death using ML techniques. In summary, the reported genomic systems biomarker candidate offers promise for personalized medicine in diagnosis and prognosis of serous ovarian cancer and warrants further experimental and translational clinical studies.

Mechanisms Involved in Therapeutic Effects of Scutellaria baicalensis Georgi in Oral Squamous Cell Carcinoma Based on Systems Biology and Structural Bioinformatics Approaches

Objective

Oral squamous cell carcinoma (OSCC) is the most frequent oral cancer, constituting more than 90% of all oral carcinomas. The 5-year survival rate of OSCC patients is not satisfactory, and therefore, there is an urgent need for new practical therapeutic approaches besides the current therapies to overcome OSCC. Scutellaria baicalensis Georgi (SBG) is a plant of the family Lamiaceae with several pharmaceutical properties such as antioxidant, anti-inflammatory, and anticancer effects. Previous studies have demonstrated the curative effects of SBG in OSCC.

Methods

A systems biology approach was conducted to identify differentially expressed miRNAs (DEMs) in OSCC patients with a dismal prognosis compared to OSCC patients with a favorable prognosis. A protein interaction map (PIM) was built based on DEMs targets, and the hub genes within the PIM were indicated. Subsequently, the prognostic role of the hubs was studied using Kaplan-Meier curves. Next, the binding affinity of SBG's main components, including baicalein, wogonin, oroxylin-A, salvigenin, and norwogonin, to the prognostic markers in OSCC was evaluated using molecular docking analysis.

Results

Survival analysis showed that overexpression of CAV1, SERPINE1, ACTB, SMAD3, HMGA2, MYC, EIF2S1, HSPA4, HSPA5, and IL6 was significantly related to a poor prognosis in OSCC. Besides, molecular docking analysis demonstrated the ΔGbinding and inhibition constant values between SBG's main components and SERPINE1, ACTB, HMGA2, EIF2S1, HSPA4, and HSPA5 were as <-8.00 kcal/mol and nanomolar concentration, respectively. The most salient binding affinity was observed between wogonin and SERPINE1 with a criterion of ΔGbinding < -10.02 kcal/mol.

Conclusion

The present results unraveled potential mechanisms involved in therapeutic effects of SBG in OSCC based on systems biology and structural bioinformatics analyses.