Annotation of biologically relevant ligands in UniProtKB using ChEBI

Mitochondrial genome-derived circRNAs: Orphan epigenetic regulators in molecular biology

Mitochondria are vital for cellular activities, influencing ATP production, Ca2+ signaling, and reactive oxygen species generation. It has been proposed that nuclear genome-derived circular RNAs (circRNAs) play a role in biological processes. For the first time, this study aims to comprehensively explore experimentally confirmed human mitochondrial genome-derived circRNAs (mt-circRNAs) via in-silico analysis. We utilized wide-ranging bioinformatics tools to anticipate their roles in molecular biology, involving miRNA sponging, protein antagonism, and peptide translation. Among five well-characterized mt-circRNAs, SCAR/mc-COX2 stands out as particularly significant with the potential to sponge around 41 different miRNAs, which target several genes mostly involved in endocytosis, MAP kinase, and PI3K-Akt pathways. Interestingly, circMNTND5 and mecciND1 specifically interact with miRNAs through their unique back-splice junction sequence. These exclusively targeted miRNAs (has-miR-5186, 6888-5p, 8081, 924, 672-5p) are predominantly associated with insulin secretion, proteoglycans in cancer, and MAPK signaling pathways. Moreover, all mt-circRNAs intricately affect the P53 pathway through miRNA sequestration. Remarkably, mc-COX2 and circMNTND5 appear to be involved in the RNA's biogenesis by antagonizing AGO1/2, EIF4A3, and DGCR8. All mt-circRNAs engaged with IGF2BP proteins crucial in redox signaling, and except mecciND1, they all potentially generate at least one protein resembling the immunoglobulin heavy chain protein. Given P53's function as a redox-sensitive transcription factor, and insulin's role as a crucial regulator of energy metabolism, their indirect interplay with mt-circRNAs could influence cellular outcomes. However, due to limited attention and infrequent data availability, it is advisable to conduct more thorough investigations to gain a deeper understanding of the functions of mt-circRNA.

Sorafenib and SIAIS361034, a novel PROTAC degrader of BCL-xL, display synergistic antitumor effects on hepatocellular carcinoma with minimal hepatotoxicity

The overexpression of BCL-xL is closely associated with poor prognosis in hepatocellular carcinoma (HCC). While the strategy of combination of BCL-xL and MCL-1 for treating solid tumors has been reported, it presents significant hepatotoxicity. SIAIS361034, a novel proteolysis targeting chimera (PROTAC) agent, selectively induces the ubiquitination and subsequent proteasomal degradation of BCL-xL through the CRBN-E3 ubiquitin ligase. When combined with sorafenib, SIAIS361034 showed a potent synergistic effect in inhibiting hepatocellular carcinoma development both in vitro and in vivo. Since SIAIS361034 exhibits a high degree of selectivity for degrading BCL-xL in hepatocellular carcinoma, the hepatotoxicity typically associated with the combined inhibition of BCL-xL and MCL-1 is significantly reduced, thereby greatly enhancing safety. Mechanistically, BCL-xL and MCL-1 sequester the BH3-only protein BIM on mitochondria at baseline. Treatment with SIAIS361034 and sorafenib destabilizes BIM/BCL-xL and BIM/MCL1 association, resulting in the liberation of more BIM proteins to trigger apoptosis. Additionally, we discovered a novel compensatory regulation mechanism in hepatocellular carcinoma cells. BIM can rapidly respond to changes in the balance between BCL-xL and MCL-1 through their co-transcription factor MEF2C to maintain apoptosis resistance. In summary, the combination therapy of SIAIS361034 and sorafenib represents an effective and safe approach for inhibiting hepatocellular carcinoma progression. The novel balancing mechanism may also provide insights for combination and precision therapies in the treatment of hepatocellular carcinoma.

Comparative Genomics Uncovers the Evolutionary Dynamics of Detoxification and Insecticide Target Genes Across 11 Phlebotomine Sand Flies

Sand flies infect more than 1 million people annually with Leishmania parasites and other bacterial and viral pathogens. Progress in understanding sand fly adaptations to xenobiotics has been hampered by the limited availability of genomic resources. To address this gap, we sequenced, assembled, and annotated the transcriptomes of 11 phlebotomine sand fly species. Subsequently, we leveraged these genomic resources to generate novel evolutionary insights pertaining to their adaptations to xenobiotics, including those contributing to insecticide resistance. Specifically, we annotated over 2,700 sand fly detoxification genes and conducted large-scale phylogenetic comparisons to uncover the evolutionary dynamics of the five major detoxification gene families: cytochrome P450s (CYPs), glutathione-S-transferases (GSTs), UDP-glycosyltransferases (UGTs), carboxyl/cholinesterases (CCEs), and ATP-binding cassette (ABC) transporters. Using this comparative approach, we show that sand flies have evolved diverse CYP and GST gene repertoires, with notable lineage-specific expansions in gene groups evolutionarily related to known xenobiotic metabolizers. Furthermore, we show that sand flies have conserved orthologs of (i) CYP4G genes involved in cuticular hydrocarbon biosynthesis, (ii) ABCB genes involved in xenobiotic toxicity, and (iii) two primary insecticide targets, acetylcholinesterase-1 (Ace1) and voltage gated sodium channel (VGSC). The biological insights and genomic resources produced in this study provide a foundation for generating and testing hypotheses regarding the molecular mechanisms underlying sand fly adaptations to xenobiotics.

Functional metagenomic analysis reveals potential inflammatory triggers associated with genetic risk for autoimmune disease

To assess functional differences between the microbiomes of individuals with autoimmune risk-associated human leukocyte antigen (HLA) genetics and autoimmune protection-associated HLA, we performed a metagenomic analysis of stool samples from 72 infants in the All Babies in Southeast Sweden general-population cohort and assessed haplotype-peptide binding affinities. Infants with risk-associated HLA DR3-DQ2.5 and DR4-DQ8 had a higher abundance of known pathogen-associated molecular patterns and virulence related genes than infants with protection-associated HLA DR15-DQ6.2. However, there was limited overlap in the type of inflammatory trigger between risk groups. Supported by a high Firmicutes/Bacteroides ratio and differentially abundant flagellated species, genes related to the synthesis of flagella were prominent in those with HLA DR3-DQ2.5. However, this haplotype had a significantly lower likelihood of binding affinity to flagellin peptides. O-antigen biosynthesis genes were significantly correlated with the risk genotypes and absent from protective genotype association, supported by the differential abundance of gram-negative bacteria seen in the risk-associated groups. Genes related to vitamin B biosynthesis stood out in higher abundance in infants with HLA DR3-DQ2.5/DR4-DQ8 heterozygosity compared to those with autoimmune-protective genetics. Prevotella species and genus were significantly abundant in all infant groups with high risk for autoimmune disease. The potential inflammatory triggers associated with genetic risk for autoimmunity have significant implications. These results suggest that certain HLA haplotypes may be creating the opportunity for dysbiosis and subsequent inflammation early in life by clearing beneficial microbes or not clearing proinflammatory microbes. This HLA gatekeeping may prevent genetically at-risk individuals from benefiting from probiotic therapies by restricting the colonization of those beneficial bacteria.

In-silico identification of putatively functional intergenic small open reading frames in the cucumber genome and their predicted response to biotic and abiotic stresses

The availability of high-throughput sequencing technologies increased our understanding of different genomes. However, the genomes of all living organisms still have many unidentified coding sequences. The increased number of missing small open reading frames (sORFs) is due to the length threshold used in most gene identification tools, which is true in the genic and, more importantly and surprisingly, in the intergenic regions. Scanning the cucumber genome intergenic regions revealed 420 723 sORF. We excluded 3850 sORF with similarities to annotated cucumber proteins. To propose the functionality of the remaining 416 873 sORF, we calculated their codon adaptation index (CAI). We found 398 937 novel sORF (nsORF) with CAI ≥ 0.7 that were further used for downstream analysis. Searching against the Rfam database revealed 109 nsORFs similar to multiple RNA families. Using SignalP-5.0 and NLS, identified 11 592 signal peptides. Five predicted proteins interacting with Meloidogyne incognita and Powdery mildew proteins were selected using published transcriptome data of host-pathogen interactions. Gene ontology enrichment interpreted the function of those proteins, illustrating that nsORFs' expression could contribute to the cucumber's response to biotic and abiotic stresses. This research highlights the importance of previously overlooked nsORFs in the cucumber genome and provides novel insights into their potential functions.

VAIV bio-discovery service using transformer model and retrieval augmented generation

BACKGROUND

There has been a considerable advancement in AI technologies like LLM and machine learning to support biomedical knowledge discovery.

MAIN BODY

We propose a novel biomedical neural search service called 'VAIV Bio-Discovery', which supports enhanced knowledge discovery and document search on unstructured text such as PubMed. It mainly handles with information related to chemical compound/drugs, gene/proteins, diseases, and their interactions (chemical compounds/drugs-proteins/gene including drugs-targets, drug-drug, and drug-disease). To provide comprehensive knowledge, the system offers four search options: basic search, entity and interaction search, and natural language search. We employ T5slim_dec, which adapts the autoregressive generation task of the T5 (text-to-text transfer transformer) to the interaction extraction task by removing the self-attention layer in the decoder block. It also assists in interpreting research findings by summarizing the retrieved search results for a given natural language query with Retrieval Augmented Generation (RAG). The search engine is built with a hybrid method that combines neural search with the probabilistic search, BM25.

CONCLUSION

As a result, our system can better understand the context, semantics and relationships between terms within the document, enhancing search accuracy. This research contributes to the rapidly evolving biomedical field by introducing a new service to access and discover relevant knowledge.

Geniposide effectively safeguards HT22 cells against Aβ-induced damage by activating mitophagy via the PINK1/Parkin signaling pathway

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the significant involvement of amyloid-beta (Aβ) peptide in its pathogenesis. Geniposide, derived from the versatile medicinal of Gardenia jasminoides, is one of the active compounds studied extensively. The objective was to explore the impact of geniposide on Aβ25-35-induced damage in HT22 cells, specifically focusing on its modulation of PINK1/Parkin-mediated mitophagy. In our investigation, geniposide exhibited remarkable restorative effects by enhancing cell viability and preserving the mitochondrial membrane potential. Moreover, it effectively reduced and mitigated the oxidative stress and apoptosis rates induced by Aβ25-35. Notably, geniposide exhibited the capacity to enhance autophagic flux, upregulate LC3II and Beclin-1 expression, and downregulate the expression of p62. Furthermore, geniposide positively influenced the expression of PINK1 and Parkin proteins, with molecular docking substantiating a strong interaction between geniposide and PINK1/Parkin proteins. Intriguingly, the beneficial outcomes of geniposide on alleviating the pronounced apoptosis rates, the overproduction of reactive oxygen species, and diminished the PINK1 and Parkin expression induced by Aβ25-35 were compromised by the mitophagy inhibitor cyclosporine A (CsA). Collectively, these findings suggested that geniposide potentially shields HT22 cells against neurodegenerative damage triggered by Aβ25-35 through the activation of mitophagy. The insights contribute valuable references to the defensive consequences against neurological damage of geniposide, thereby highlighting its potential as a therapeutic intervention in AD.

Design of multi-epitope vaccine candidate based on OmpA, CarO and ZnuD proteins against multi-drug resistant Acinetobacter baumannii

Acinetobacter baumannii has been identified as a major cause of nosocomial infections. Acinetobacter infections are often difficult to treat with multidrug resistant phenotypes. One of the most effective ways to combat infectious diseases is through vaccination. In this study, an attempt was made to select the most protective and potent immunostimulatory epitopes based on the epitope-rich domains of the ZnuD, OmpA and CarO proteins of Acinetobacter baumannii to design a vaccine that can protect against this infection. After predicting the epitope of B- and T-cells, seven antigenic regions of three proteins CarO, ZnuD and OmpA, were selected. These regions were bound by a GGGS linker. The binding affinity and molecular interactions of the vaccine with the immune receptors TLR2 and TLR4 were studied using molecular docking analysis. This vaccine design was subjected to in silico immune simulations using C-ImmSim. The designed vaccine was highly antigenic, non-allergenic and stable. TLR2 and TLR4 were selected to analyze the ability of the modeled chimeric protein to interact with immune system receptors. The results showed strong interaction between the designed protein vaccine with TLR2 (-18.8 kcal mol-1) and TLR4 (-15.1 kcal mol-1). To verify the stability of the interactions and the structure of the designed protein, molecular dynamics (MD) simulations were performed for 200 ns. Various analyses using MD showed that the protein structure is stable alone and in interaction with TLR2 and TLR4. The ability of the vaccine candidate protein to stimulate the immune system to produce the necessary cytokines and antibodies against Acinetobacter baumannii was also demonstrated by the ability of the protein designed using the C-ImmSim web server to induce an immune response. Therefore, the designed protein vaccine may be a suitable candidate for in vivo as well as in vitro studies against Acinetobacter baumannii infections.

Transverse aortic constriction multi-omics analysis uncovers pathophysiological cardiac molecular mechanisms

Time-course multi-omics data of a murine model of progressive heart failure (HF) induced by transverse aortic constriction (TAC) provide insights into the molecular mechanisms that are causatively involved in contractile failure and structural cardiac remodelling. We employ Illumina-based transcriptomics, Nanopore sequencing and mass spectrometry-based proteomics on samples from the left ventricle (LV) and right ventricle (RV, RNA only) of the heart at 1, 7, 21 and 56 days following TAC and Sham surgery. Here, we present Transverse Aortic COnstriction Multi-omics Analysis (TACOMA), as an interactive web application that integrates and visualizes transcriptomics and proteomics data collected in a TAC time-course experiment. TACOMA enables users to visualize the expression profile of known and novel genes and protein products thereof. Importantly, we capture alternative splicing events by assessing differential transcript and exon usage as well. Co-expression-based clustering algorithms and functional enrichment analysis revealed overrepresented annotations of biological processes and molecular functions at the protein and gene levels. To enhance data integration, TACOMA synchronizes transcriptomics and proteomics profiles, enabling cross-omics comparisons. With TACOMA (https://shiny.dieterichlab.org/app/tacoma), we offer a rich web-based resource to uncover molecular events and biological processes implicated in contractile failure and cardiac hypertrophy. For example, we highlight: (i) changes in metabolic genes and proteins in the time course of hypertrophic growth and contractile impairment; (ii) identification of RNA splicing changes in the expression of Tpm2 isoforms between RV and LV; and (iii) novel transcripts and genes likely contributing to the pathogenesis of HF. We plan to extend these data with additional environmental and genetic models of HF to decipher common and distinct molecular changes in heart diseases of different aetiologies. Database URL: https://shiny.dieterichlab.org/app/tacoma.

Mining drug-target interactions from biomedical literature using chemical and gene descriptions-based ensemble transformer model

Motivation

Drug-target interactions (DTIs) play a pivotal role in drug discovery, as it aims to identify potential drug targets and elucidate their mechanism of action. In recent years, the application of natural language processing (NLP), particularly when combined with pre-trained language models, has gained considerable momentum in the biomedical domain, with the potential to mine vast amounts of texts to facilitate the efficient extraction of DTIs from the literature.

Results

In this article, we approach the task of DTIs as an entity-relationship extraction problem, utilizing different pre-trained transformer language models, such as BERT, to extract DTIs. Our results indicate that an ensemble approach, by combining gene descriptions from the Entrez Gene database with chemical descriptions from the Comparative Toxicogenomics Database (CTD), is critical for achieving optimal performance. The proposed model achieves an F1 score of 80.6 on the hidden DrugProt test set, which is the top-ranked performance among all the submitted models in the official evaluation. Furthermore, we conduct a comparative analysis to evaluate the effectiveness of various gene textual descriptions sourced from Entrez Gene and UniProt databases to gain insights into their impact on the performance. Our findings highlight the potential of NLP-based text mining using gene and chemical descriptions to improve drug-target extraction tasks.

Availability and implementation

Datasets utilized in this study are accessible at https://dtis.drugtargetcommons.org/.

Genome-wide identification of MATE and ALMT genes and their expression profiling in mungbean (Vigna radiata L.) under aluminium stress

The Multidrug and toxic compound extrusion (MATE) and aluminium activated malate transporter (ALMT) gene families are involved in response to aluminium (Al) stress. In this study, we identified 48 MATE and 14 ALMT gene families in Vigna radiata genome and classified into 5 (MATE) and 3 (ALMT) clades by phylogenetic analysis. All the VrMATE and VrALMT genes were distributed across mungbean chromosomes. Tandem duplication was the main driving force for evolution and expansion of MATE gene family. Collinearity of mungbean with soybean indicated that MATE gene family is closely linked to Glycine max. Eight MATE transporters in clade 2 were found to be associated with previously characterized Al tolerance related MATEs in various plant species. Citrate exuding motif (CEM) was present in seven VrMATEs of clade 2. Promoter analysis revealed abundant plant hormone and stress responsive cis-elements. Results from quantitative real time-polymerase chain reaction (qRT-PCR) revealed that VrMATE19, VrMATE30 and VrALMT13 genes were markedly up-regulated at different time points under Al stress. Overall, this study offers a new direction for further molecular characterization of the MATE and ALMT genes in mungbean for Al tolerance.

Functional genomic analysis of the isolated potential probiotic Lactobacillus delbrueckii subsp. indicus TY-11 and its comparison with other Lactobacillus delbrueckii strains

Probiotics refer to living microorganisms that exert a variety of beneficial effects on human health. On the contrary, they also can cause infection, produce toxins within the body, and transfer antibiotic-resistant genes to the other microorganisms in the digestive tract necessitating a comprehensive safety assessment. This study aimed to conduct functional genomic analysis and some relevant biochemical tests to uncover the probiotic potentials of Lactobacillus delbrueckii subsp. indicus TY-11 isolated from native yogurt in Bangladesh. We also performed transmission electron microscopic (TEM) analysis, comparative genomic study as well as phylogenetic tree construction with 332 core genes from 262 genomes. The strain TY-11 was identified as Lactobacillus delbrueckii subsp. indicus, whose genome (1,916,674 bp) contained 1911 CDS, and no gene was identified for either antibiotic resistance or toxic metabolites. It carried genes for the degradation of toxic metabolites, treatment of lactose intolerance, toll-like receptor 2-dependent innate immune response, heat and cold shock, bile salts tolerance, and acidic pH tolerance. Genes were annotated for inhibiting pathogenic bacteria by inhibitory substances [bacteriocin: Helveticin-J (331 bp) and Enterolysin-A (275 bp), hydrogen peroxide, and acid]; blockage of adhesion sites; and competition for nutrients. The genes involved in its metabolic pathway were detected as suitable for digesting indigestible nutrients in the human gut. The TY-11 genome possessed an additional 37 core genes of subspecies indicus which were deficient in the core genome of the most popular subsp. bulgaricus. During the phenotypic testing, the isolate TY-11 demonstrated high antagonistic activity (inhibition zone of 21.33 ± 1.53 mm) against Escherichia coli ATCC 8739 and was not sensitive to any of the 10 tested antibiotics. This study was the first study to explore the molecular insights into probiotic roles, including antimicrobial activities and antibiotic sensitivity, of a representative strain (TY-11) of Lactobacillus delbrueckii subsp. indicus.

IMPORTANCE

This study aimed to conduct functional genomic analysis to uncover the probiotic potential of Lactobacillus delbrueckii subsp. indicus TY-11 isolated from native yogurt in Bangladesh. We also performed transmission electron microscopic (TEM) analysis, comparative genomic study as well as phylogenetic tree construction with 332 core genes from 262 genomes. In our current investigation, we revealed a number of common and unique excellences of the probiotic Lactobacillus delbrueckii subsp. indicus TY-11 that are likely to be important to illustrate its intestinal residence and probiotic roles. This is the first study to explore the molecular insights into intestinal residence and probiotic roles, including antimicrobial activities and antibiotic sensitivity, of a representative strain (TY-11) of Lactobacillus delbrueckii subsp. indicus.

Genomic analysis of a novel phage vB_SenS_ST1UNAM with lytic activity against Salmonella enterica serotypes

In this study, we present the complete annotated genome of a novel Salmonella phage, vB_SenS_ST1UNAM. This phage exhibits lytic activity against several Salmonella enterica serotypes, such as S. Typhi, S. Enteritidis, and S. Typhimurium strains, which are major causes of foodborne illness worldwide. Its genome consists of a linear, double-stranded DNA of 47,877 bp with an average G+C content of 46.6%. A total of 85 coding regions (CDS) were predicted, of which only 43 CDS were functionally assigned. Neither genes involved in the regulation of lysogeny, nor antibiotic resistance genes were identified. This phage harbors a lytic cassette that encodes a type II-holin and a Rz/Rz1-like spanin complex, along with a restriction-modification evasion system and a depolymerase that degrades Salmonella exopolysaccharide. Moreover, the comparative analysis with closely related phage genomes revealed that vB_SenS_ST1UNAM represents a novel genus, for which the genus "Gomezvirus" within the subfamily "ST1UNAM-like" is proposed.

Investigating potential mechanisms of vitamin D against thyroid cancer via network pharmacology and experimental validation

Thyroid cancer (TC) is one of the most common endocrine malignancies worldwide. Increasing evidence suggests that vitamin D (VD) has potential benefits in the treatment of TC. However, evidence regarding the targets and molecular mechanisms of VD in TC remains limited. In this study, we conducted network pharmacology, molecular docking, and experimental evaluation to explore the target genes, biological functions, and signaling pathways involved in this process. Network analysis revealed 77 potential target genes of VD against TC, and four hub target genes were identified: ESR1, KIT, CCND1, and PGR. Furthermore, we identified the biological processes (BP) and signaling pathways involving these potential target genes, and then determined the possible interaction between the hub targets and VD through molecular docking. Finally, through in vitro experiments, we found that VD effectively inhibits the proliferation of TC cells and downregulates the expression of the ESR1 gene. In conclusion, the effects of VD against TC involve multiple biological targets, BP, and signaling pathways. These findings provide scientific evidence for the application of VD in the treatment of TC.

SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features

Allergy is a hypersensitive condition in which individuals develop objective symptoms when exposed to harmless substances at a dose that would cause no harm to a "normal" person. Most current computational methods for allergen identification rely on homology or conventional machine learning using limited set of feature descriptors or validation on specific datasets, making them inefficient and inaccurate. Here, we propose SEP-AlgPro for the accurate identification of allergen protein from sequence information. We analyzed 10 conventional protein-based features and 14 different features derived from protein language models to gauge their effectiveness in differentiating allergens from non-allergens using 15 different classifiers. However, the final optimized model employs top 10 feature descriptors with top seven machine learning classifiers. Results show that the features derived from protein language models exhibit superior discriminative capabilities compared to traditional feature sets. This enabled us to select the most discriminatory baseline models, whose predicted outputs were aggregated and used as input to a deep neural network for the final allergen prediction. Extensive case studies showed that SEP-AlgPro outperforms state-of-the-art predictors in accurately identifying allergens. A user-friendly web server was developed and made freely available at https://balalab-skku.org/SEP-AlgPro/, making it a powerful tool for identifying potential allergens.

Exploring the effect of disease causing mutations in metal binding sites of human ARSA in metachromatic leukodystrophy

The arylsulfatase A (ARSA) gene is observed to be deficient in patients with metachromatic leukodystrophy (MLD), a type of lysosomal storage disease. MLD is a severe neurodegenerative disorder characterized by an autosomal recessive inheritance pattern. This study aimed to map the most deleterious mutations at the metal binding sites of ARSA and the amino acids in proximity to the mutated positions. We utilized an array of computational tools, including PredictSNP, MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT, SNAP, and ConSurf, to identify the most detrimental mutations potentially implicated in MLD collected from UniProt, ClinVar, and HGMD. Two mutations, D29N and D30H, as being extremely deleterious based on assessments of pathogenicity, conservation, biophysical characteristics, and stability analysis. The D29 and D30 are located at the metal-interacting regions of ARSA and found to undergo post-translational modification, specifically phosphorylation. Henceforth, the in-depth effect of metal binding upon mutation was examined using molecular dynamics simulations (MDS) before and after phosphorylation. The MDS results exhibited high deviation for the D29N and D30H mutations in comparison to the native, and the same was confirmed by significant residue fluctuation and reduced compactness. These structural alterations suggest that such mutations may influence protein functionality, offering potential avenues for personalized therapeutic and providing a basis for potential mutation-specific treatments for severe MLD patients.

Immunoinformatics and Reverse Vaccinology Approach for the Identification of Potential Vaccine Candidates against Vandammella animalimors

Vandammella animalimorsus is a Gram-negative and non-motile bacterium typically transmitted to humans through direct contact with the saliva of infected animals, primarily through biting, scratches, or licks on fractured skin. The absence of a confirmed post-exposure treatment of V. animalimorsus bacterium highlights the imperative for developing an effective vaccine. We intended to determine potential vaccine candidates and paradigm a chimeric vaccine against V. animalimorsus by accessible public data analysis of the strain by utilizing reverse vaccinology. By subtractive genomics, five outer membranes were prioritized as potential vaccine candidates out of 2590 proteins. Based on the instability index and transmembrane helices, a multidrug transporter protein with locus ID A0A2A2AHJ4 was designated as a potential candidate for vaccine construct. Sixteen immunodominant epitopes were retrieved by utilizing the Immune Epitope Database. The epitope encodes the strong binding affinity, nonallergenic properties, non-toxicity, high antigenicity scores, and high solubility revealing the more appropriate vaccine construct. By utilizing appropriate linkers and adjuvants alongside a suitable adjuvant molecule, the epitopes were integrated into a chimeric vaccine to enhance immunogenicity, successfully eliciting both adaptive and innate immune responses. Moreover, the promising physicochemical features, the binding confirmation of the vaccine to the major innate immune receptor TLR-4, and molecular dynamics simulations of the designed vaccine have revealed the promising potential of the selected candidate. The integration of computational methods and omics data has demonstrated significant advantages in discovering novel vaccine targets and mitigating vaccine failure rates during clinical trials in recent years.

Gut microbial β-glucuronidases influence endobiotic homeostasis and are modulated by diverse therapeutics

Hormones and neurotransmitters are essential to homeostasis, and their disruptions are connected to diseases ranging from cancer to anxiety. The differential reactivation of endobiotic glucuronides by gut microbial β-glucuronidase (GUS) enzymes may influence interindividual differences in the onset and treatment of disease. Using multi-omic, in vitro, and in vivo approaches, we show that germ-free mice have reduced levels of active endobiotics and that distinct gut microbial Loop 1 and FMN GUS enzymes drive hormone and neurotransmitter reactivation. We demonstrate that a range of FDA-approved drugs prevent this reactivation by intercepting the catalytic cycle of the enzymes in a conserved fashion. Finally, we find that inhibiting GUS in conventional mice reduces free serotonin and increases its inactive glucuronide in the serum and intestines. Our results illuminate the indispensability of gut microbial enzymes in sustaining endobiotic homeostasis and indicate that therapeutic disruptions of this metabolism promote interindividual response variabilities.

Engineering G protein-coupled receptors for stabilization

G protein-coupled receptors (GPCRs) are one of the most important families of targets for drug discovery. One of the limiting steps in the study of GPCRs has been their stability, with significant and time-consuming protein engineering often used to stabilize GPCRs for structural characterization and drug screening. Unfortunately, computational methods developed using globular soluble proteins have translated poorly to the rational engineering of GPCRs. To fill this gap, we propose GPCR-tm, a novel and personalized structurally driven web-based machine learning tool to study the impacts of mutations on GPCR stability. We show that GPCR-tm performs as well as or better than alternative methods, and that it can accurately rank the stability changes of a wide range of mutations occurring in various types of class A GPCRs. GPCR-tm achieved Pearson's correlation coefficients of 0.74 and 0.46 on 10-fold cross-validation and blind test sets, respectively. We observed that the (structural) graph-based signatures were the most important set of features for predicting destabilizing mutations, which points out that these signatures properly describe the changes in the environment where the mutations occur. More specifically, GPCR-tm was able to accurately rank mutations based on their effect on protein stability, guiding their rational stabilization. GPCR-tm is available through a user-friendly web server at https://biosig.lab.uq.edu.au/gpcr_tm/.

Unveiling cytokine charge disparity as a potential mechanism for immune regulation

Cytokines are small signaling proteins that regulate the immune responses to infection and tissue damage. Surface charges of cytokines determine their in vivo fate in immune regulation, e.g., half-life and distribution. The overall negative charges in the extracellular microenvironment and the acidosis during inflammation and infection may differentially impact cytokines with different surface charges for fine-tuned immune regulation via controlling tissue residential properties. However, the trend and role of cytokine surface charges has yet to be elucidated in the literature. Interestingly, we have observed that most pro-inflammatory cytokines have a negative charge, while most anti-inflammatory cytokines and chemokines have a positive charge. In this review, we extensively examined the surface charges of all cytokines and chemokines, summarized the pharmacokinetics and tissue adhesion of major cytokines, and analyzed the link of surface charge with cytokine biodistribution, activation, and function in immune regulation. Additionally, we identified that the general trend of charge disparity between pro- and anti-inflammatory cytokines represents a unique opportunity to develop precise immune modulation approaches, which can be applied to many inflammation-associated diseases including solid tumors, chronic wounds, infection, and sepsis.

Genome wide identification and expression profiling of ATP binding cassette (ABC) transporters gene family in lentil (Lens culinaris Medikus) under aluminium stress condition

Adenosine triphosphate-binding cassette transporters (ABC transporters) are involved in regulating plant growth, development and tolerance to environmental stresses. In this study, a total of 138 ABC transporter genes were identified in the lentil genome that were classified into eight subfamilies. Four lentil ABC transporters from subfamily B and I were clustered together with the previously characterized ABC transporter proteins related to aluminium (Al) detoxification. Lentil ABC transporter genes were distributed across the chromosomes. Tandem duplication was the main driving force for expansion of the ABC gene family. Collinearity of lentil with soybean indicated that ABC gene family is closely linked to Glycine max. ABC genes in the same subfamily showed similar gene structure and conserved motifs. The ABC promoter regions harboured a large number of plant hormones and multiple stress responsive cis-regulatory elements. The qRT-PCR showed that ABC genes had varied expression in roots of lentil at different time points under Al stress. This is the first report on genome wide identification and expression analyses of genes encoding ABC transporter genes in lentil which has provided in-depth insight for future research on evolution and elucidation of molecular mechanisms for aluminium tolerance.

The mechanism of polyphyllin in the treatment of gastric cancer was verified based on network pharmacology and experimental validation

Background

Polyphyllin is a class of saponins extracted from Paris polyphylla rhizomes and has been used in clinical application in China for more than 2000 years. However, the mechanism for treating gastric cancer (GC) is still unclear. This study was designed to predict the targets and mechanisms of total Polyphyllin from Paris polyphylla rhizomes for the treatment of GC.

Method

Firstly, PubChem and Swiss Target Prediction databases were utilized to collect the 12 ingredients of total Polyphyllin from Paris polyphylla rhizomes and their targets. GC-related genes were obtained from the GEO database. Then the intersecting targets to all these molecules that identified using Venny. Secondly, the intersecting targets were imported into STRING platform for protein-protein interaction (PPI) network. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted in DAVID website. In addition, the GEPIA was applied to perform the expression levels, transcript levels, staging, and overall survival of hub genes. In addition, we used AutoDock Vina to evaluate binding affinity of molecular docking between key ingredients and anti-GC targets. In vitro cell experiments, we detected the cell viability of gastric cancer cells at 24, 36, and 48 h using CCK-8 assay. The G0/G1 of cell cycle and apoptosis were detected by flow cytometry. Finally, quantitative real time polymerase chain reaction (qRT-PCR) was used to detect the level of hub genes, and Western blot was used to detect the changes of PI3K/Akt signal pathway.

Results

Firstly, we identified 12 ingredients and 286 targets of total Polyphyllin. A total of 2653 GC-related differentially expressed genes (DEGs) were collected, including 1366 up-regulated genes and 1287 down-regulated genes. Moreover, 45 targets were obtained after intersection. Secondly, results of the GO enrichment suggested that these genes were closely related to cell proliferation, migration and aging. KEGG analysis suggested that Polyphyllin in GC therapy were mostly regulated by multiple pathways, including the pathways in cancer, calcium signaling pathway, Rap1 signaling pathway, phospholipase D signaling pathway, etc. In addition, GEPIA results exhibited that PDGFRB, KIT, FGF1, GLI1, F2R, and HIF1A were associated with GC progression, stage, and survival. Besides, the molecular docking results further confirmed that the binding energy of Polyphyllin Ⅲ with HIF1A was minimal. In vitro cell experiments, Polyphyllin Ⅲ inhibited the cell viability of gastric cancer cells, blocked the cell cycle G0/G1 phase, and induced cell apoptosis. In addition, Polyphyllin Ⅲ down-regulated the mRNA levels of PDGFRB, KIT, FGF1, GLI1, F2R, and HIF1A, and regulated the PI3K/Akt signal pathway.

Conclusions

The results revealed that total Polyphyllin treated GC through multiple targets, multiple channels, and multiple pathways. In addition, Polyphyllin Ⅲ played an anti-gastric cancer role by inhibiting the proliferation of gastric cancer.

Integrated network analysis and experimental verification of the mechanisms employed by Compound Jixuecao Decoction to improve endoplasmic reticulum stress and apoptosis in chronic renal failure

ETHNOPHARMACOLOGICAL RELEVANCE

Compound Jixuecao Decoction (CJD) is a traditional Chinese herbal medicine prescribed in China to treat chronic renal failure (CRF). Previous studies have shown that CJD affects cell apoptosis and proliferation. However, the mechanism of its renal protective action has not been characterized.

AIM OF THE STUDY

To explore the mechanism(s) underlying the effect of CJD on endoplasmic reticulum stress (ERS) and apoptosis in the treatment of CRF using network pharmacology, molecular docking, molecular dynamics simulations, and in vivo studies.

MATERIALS AND METHODS

The compounds comprising CJD were extracted from the Traditional Chinese Medicine Systems Pharmacology Database. A Swiss target prediction database and similarity integration approach were employed to identify potential targets of these components. The GeneCards and DisGeNET databases were used to identify targets associated with CRF, apoptosis, and ERS. The STRING database was employed to analyze the protein-protein interactions (PPIs) associated with drug-disease crossover. A chemical composition-shared target network was established, and critical pathways were identified through gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The Protein Data Bank database was used to search key proteins, while molecular docking and dynamics simulations were performed between the top four CJD active ingredients and proteins involved in apoptosis and ERS in CRF. Subsequent in vivo studies using a 5/6 nephrectomy rat model of CRF were performed to verify the findings.

RESULTS

The 80 compounds identified in CJD yielded 875 target genes, of which 216 were potentially related to CRF. PPI network analysis revealed key targets via topology filtering. Enrichment analysis, molecular docking, and molecular dynamics simulation results suggested that CJD primarily targets mitofusin-2 (MFN2), B-cell lymphoma-2 (BCL2), BAX, protein kinase RNA-like ER kinase (PERK), and C/EBP homologous protein (CHOP) during CRF treatment. In vivo, CJD significantly increased the abundance of MFN2, BCL2, and significantly reduced the abundance of BAX, PERK, CHOP proteins in kidney tissues, indicating that CJD could improve apoptosis and ERS in CRF rats.

CONCLUSIONS

This study provides evidence that CJD effectively delays CFR through modulation of the MFN2 and PERK-eIF2α-ATF4-CHOP signaling pathways.

The Impact of Metagenomics on Biocatalysis

In the ever-growing demand for sustainable ways to produce high-value small molecules, biocatalysis has come to the forefront of greener routes to these chemicals. As such, the need to constantly find and optimise suitable biocatalysts for specific transformations has never been greater. Metagenome mining has been shown to rapidly expand the toolkit of promiscuous enzymes needed for new transformations, without requiring protein engineering steps. If protein engineering is needed, the metagenomic candidate can often provide a better starting point for engineering than a previously discovered enzyme on the open database or from literature, for instance. In this review, we highlight where metagenomics has made substantial impact on the area of biocatalysis in recent years. We review the discovery of enzymes in previously unexplored or 'hidden' sequence space, leading to the characterisation of enzymes with enhanced properties that originate from natural selection pressures in native environments.

A Multi-epitope Subunit Vaccine Identification and Development Against Scrub Typhus (Orientia tsutsugamushi) Using Immunoinformatics Approaches

Background The pathogen Orientia tsutsugamushi, which causes scrub typhus, is rapidly spreading throughout the tropics. As a measure to improve public health, the development of a vaccine for human use is essential. Scrub typhus is listed as one of the underdiagnosed and underreported febrile infections. This vector-borne zoonotic infection appears as eschar on the patient's skin. Methods Immunoinformatics was employed to predict the multi-epitope subunit vaccine that will activate both B and T cells. The final vaccine includes lipoprotein LprA as an adjuvant at the N-terminus along with B-cell, helper T lymphocyte (HTL), and cytotoxic T lymphocyte (CTL)-binding epitopes to boost immunogenicity. Assessing the vaccine's physiochemistry demonstrates that it is both antigenic and non-allergic. The vaccine structure was developed, enhanced, confirmed, and disulfide-engineered to provide the best possible model. Using molecular docking, the interaction of the produced vaccine with toll-like receptor 2 (TLR2) was analyzed, and the vaccine-receptor complex was stabilized by molecular dynamics (MD) simulation. According to in silico cloning, Escherichia coli can efficiently produce the recommended vaccine. Additionally, the efficacy of the in silico-developed vaccine must be evaluated in an in vitro and in vivo experiment. Results The developed vaccine successfully stimulates cellular and humoral immune responses. The vaccine, which has three B-cell epitopes, three HCL epitopes, and nine CTL epitopes, can bind firmly to immunological receptors. Dynamic investigations of the vaccine-receptor complex show a strong interaction and stable conformation. Conclusion In this study, the vaccine candidate demonstrated strong antigenicity, stability, and solubility while also being non-allergenic to host cells. The vaccine candidate's stability with the TLR2 immune receptor is established by binding studies, and in silico cloning verifies efficient and stable expression in the bacterial system.

Enhancing antigenic peptide discovery: Improved MHC-I binding prediction and methodology

The Major Histocompatibility Complex (MHC) is a critical element of the vertebrate cellular immune system, responsible for presenting peptides derived from intracellular proteins. MHC-I presentation is pivotal in the immune response and holds considerable potential in the realms of vaccine development and cancer immunotherapy. This study delves into the limitations of current methods and benchmarks for MHC-I presentation. We introduce a novel benchmark designed to assess generalization properties and the reliability of models on unseen MHC molecules and peptides, with a focus on the Human Leukocyte Antigen (HLA)-a specific subset of MHC genes present in humans. Finally, we introduce HLABERT, a pretrained language model that outperforms previous methods significantly on our benchmark and establishes a new state-of-the-art on existing benchmarks.

Role of PIGM and PIGX in glycosylphosphatidylinositol biosynthesis and human health (Review)

Glycosylphosphatidylinositol-glycan (GPI) is an anchor to specific cell surface proteins known as GPI-anchored proteins (APs) that are localized in lipid rafts and may act as cell co-receptors, enzymes and adhesion molecules. The present review investigated the significance of GPI biosynthesis class phosphatidylinositol-glycan (PIG)M and PIGX in GPI synthesis and their implications in human health conditions. PIGM encodes GPI-mannosyltransferase I (MT-I) enzyme that adds the first mannose to the GPI core structure. PIGX encodes the regulatory subunit of GPI-MT-I. The present review summarizes characteristics of the coding sequences of PIGM and PIGX, and their expression in humans, as well as the relevance of GPI-MT-I and the regulatory subunit in maintaining the presence of GPI-APs on the cell surface and their secretion. In addition, the association of PIGM mutations with paroxysmal nocturnal hemoglobinuria and certain types of GPI-deficiency disease and the altered expression of PIGM and PIGX in cancer were also reviewed. In addition, their interaction with other proteins was described, suggesting a complex role in cell biology. PIGM and PIGX are critical genes for GPI synthesis. Understanding gene and protein regulation may provide valuable insights into the role of GPI-APs in cellular processes.

Study on the potential mechanism of Qingxin Lianzi Yin Decoction on renoprotection in db/db mice via network pharmacology and metabolomics

BACKGROUND

Diabetic nephropathy (DN) was one of the most popular and most significant microvascular complications of diabetes mellitus. Qingxin Lianzi Yin Decoction (QXLZY) was a traditional Chinese classical formula, suitable for chronic urinary system diseases. QXLZY had good clinical efficacy in early DN, but the underlying molecular mechanism remained unrevealed.

PURPOSE

This study aimed to establish the content determination method of QXLZY index components and explore the mechanism of QXLZY on DN by network pharmacology and metabolomics studies.

METHODS

Firstly, the content determination methods of QXLZY were established with calycosin-7-O-β-d-glucoside, acteoside, baicalin and glycyrrhizic acid as index components. Secondly, pharmacological experiments of QXLZY were evaluated using db/db mice. UHPLC-LTQ-Orbitrap MS was used to carry out untargeted urine metabolomics, serum metabolomics, and kidney metabolomics studies. Thirdly, employing network pharmacology, key components and targets were analyzed. Finally, targeted metabolomics studies were performed on the endogenous constituents in biological samples for validation based on untargeted metabolomics results.

RESULTS

A method for the simultaneous determination of multiple index components in QXLZY was established, which passed the comprehensive methodological verification. It was simple, feasible, and scientific. The QXLZY treatment alleviated kidney injury of db/db mice, included the degree of histopathological damage and the level of urinary microalbumin/creatinine ratio. Untargeted metabolomics studies had identified metabolic dysfunction in pathways associated with amino acid metabolism in db/db mice. Treatment with QXLZY could reverse metabolite abnormalities and influence the pathways related to energy metabolism and amino acid metabolism. It had been found that pathways with a high degree were involved in signal transduction, prominently on amino acids metabolism and lipid metabolism, analyzed by network pharmacology. Disorders of amino acid metabolism did occur in db/db mice. QXLZY could revert the levels of metabolites, such as quinolinic acid, arginine, and asparagine.

CONCLUSION

This study was the first time to demonstrate that QXLZY alleviated diabetes-induced pathological changes in the kidneys of db/db mice by correcting disturbances in amino acid metabolism. This work could provide a new experimental basis and theoretical guidance for the rational application of QXLZY on DN, exploring the new pharmacological effect of traditional Chinese medicine, and promoting in-depth research and development.

Graph neural network model GGDisnet for identifying genes in gastrointestinal cancer and single-cell analysis

Gastrointestinal cancer, a highly prevalent form of cancer, has been the subject of extensive research resulting in the identification of numerous pathogenic genes. However, validation and exploration of these findings often require traditional biological experiments, which are time-consuming and limit the ability to make extensive assessments promptly. To address this challenge, this paper introduces GGDisnet, a novel model for identifying genes associated with gastrointestinal cancer. GGDisnet efficiently screens human genes, providing a set of genes with a high correlation to gastrointestinal cancer for reference. Comparative analysis with other models demonstrates GGDisnet's superior performance. Furthermore, we conducted enrichment and single-cell analyses based on GGDisnet-predicted genes, offering valuable clinical insights.

Introduction of protein vaccine candidate based on AP65, AP33, and α-actinin proteins against Trichomonas vaginalis parasite: an immunoinformatics design

BACKGROUND

Trichomonas vaginalis is the most common nonviral sexually transmitted disease (STI) worldwide. Vaccination is generally considered to be one of the most effective methods of preventing infectious diseases. Using AP65, AP33 and α-actinin proteins, this research aims to develop a protein vaccine against Trichomonas vaginalis.

METHODS

Based on the B-cell and T-cell epitope prediction servers, the most antigenic epitopes were selected, and with the necessary evaluations, epitope-rich domains of three proteins, AP65, AP33, and α-actinin, were selected and linked. Subsequently, the ability of the vaccine to interact with toll-like receptors 2 and 4 (TLR2 and TLR4) was assessed. The stability of the interactions was also studied by molecular dynamics for a duration of 100 nanoseconds.

RESULTS

The designed protein consists of 780 amino acids with a molecular weight of 85247.31 daltons. The results of the interaction of the vaccine candidate with TLR2 and TLR4 of the immune system also showed that there are strong interactions between the vaccine candidate protein with TLR2 (-890.7 kcal mol-1) and TLR4 (-967.3 kcal mol-1). All parameters studied to evaluate the stability of the protein structure and the protein-TLR2 and protein-TLR4 complexes showed that the structure of the vaccine candidate protein is stable alone and in complex with the immune system receptors. Investigation of the ability of the designed protein to induce an immune response using the C-ImmSim web server also showed that the designed protein is capable of stimulating B- and T-cell lymphocytes to produce the necessary cytokines and antibodies against Trichomonas vaginalis.

CONCLUSIONS

Overall, our vaccine may have potential protection against Trichomonas vaginalis. However, for experimental in vivo and in vitro studies, it may be a good vaccine candidate.

The IDSM mass spectrometry extension: searching mass spectra using SPARQL

SUMMARY

The Integrated Database of Small Molecules (IDSM) integrates data from small-molecule datasets, making them accessible through the SPARQL query language. Its unique feature is the ability to search for compounds through SPARQL based on their molecular structure. We extended IDSM to enable mass spectra databases to be integrated and searched for based on mass spectrum similarity. As sources of mass spectra, we employed the MassBank of North America database and the In Silico Spectral Database of natural products.

AVAILABILITY AND IMPLEMENTATION

The extension is an integral part of IDSM, which is available at https://idsm.elixir-czech.cz. The manual and usage examples are available at https://idsm.elixir-czech.cz/docs/ms. The source codes of all IDSM parts are available under open-source licences at https://github.com/idsm-src.

Comparative genomics reveals insight into the phylogeny and habitat adaptation of novel Amycolatopsis species, an endophytic actinomycete associated with scab lesions on potato tubers

A novel endophytic actinomycete, strain MEP2-6T, was isolated from scab tissues of potato tubers collected from Mae Fag Mai Sub-district, San Sai District, Chiang Mai Province, Thailand. Strain MEP2-6T is a gram-positive filamentous bacteria characterized by meso-diaminopimelic acid in cell wall peptidoglycan and arabinose, galactose, glucose, and ribose in whole-cell hydrolysates. Diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, and hydroxy-phosphatidylethanolamine were the major phospholipids, of which MK-9(H6) was the predominant menaquinone, whereas iso-C16:0 and iso-C15:0 were the major cellular fatty acids. The genome of the strain was 10,277,369 bp in size with a G + C content of 71.7%. The 16S rRNA gene phylogenetic and core phylogenomic analyses revealed that strain MEP2-6T was closely related to Amycolatopsis lexingtonensis NRRL B-24131T (99.4%), A. pretoriensis DSM 44654T (99.3%), and A. eburnea GLM-1T (98.9%). Notably, strain MEP2-6T displayed 91.7%, 91.8%, and 87% ANIb and 49%, 48.8%, and 35.4% dDDH to A. lexingtonensis DSM 44653T (=NRRL B-24131T), A. eburnea GLM-1T, and A. pretoriensis DSM 44654T, respectively. Based on phenotypic, chemotaxonomic, and genomic data, strain MEP2-6T could be officially assigned to a novel species within the genus Amycolatopsis, for which the name Amycolatopsis solani sp. nov. has been proposed. The type of strain is MEP2-6T (=JCM 36309T = TBRC 17632T = NBRC 116395T). Amycolatopsis solani MEP2-6T was strongly proven to be a non-phytopathogen of potato scab disease because stunting of seedlings and necrotic lesions on potato tuber slices were not observed, and there were no core biosynthetic genes associated with the BGCs of phytotoxin-inducing scab lesions. Furthermore, comparative genomics can provide a better understanding of the genetic mechanisms that enable A. solani MEP2-6T to adapt to the plant endosphere. Importantly, the strain smBGCs accommodated 33 smBGCs encoded for several bioactive compounds, which could be beneficially applied in the fields of agriculture and medicine. Consequently, strain MEP2-6T is a promising candidate as a novel biocontrol agent and antibiotic producer.

Overexpression of OsDUF6 increases salt stress tolerance in rice

BACKGROUND

Soil salinity is one of the primary environmental stresses faced in rice production. When plants are exposed to salt stress, a series of cellular balances will be disrupted. Dufulin is an immune-induced antiviral agent used in plants. The DUF gene family influences plant response to abiotic stress, and the functional role of OsDUF6(ABA98726.1) in rice response to salt stress is being investigated here.

RESULTS

Based on the transcriptome analysis of Dufulin treatment in inducing salt tolerance in rice, we selected the OsDUF6 protein located on the cell membrane and studied its molecular function by overexpressing OsDUF6. Salt-induced decreases in root, stem, and leaf length and increased leaf yellowing rate and Na+ concentration in the wild-type plant were mitigated in the overexpressed lines. OsDUF6 overexpression increased the enzymatic antioxidant activities of superoxide dismutase, peroxidase, catalase, and phenylalanine ammonia-lyase. OsDUF6 also played a positive role in Na+ transport as reflected by the increased growth of a salt-sensitive yeast mutant complemented with OsDUF6 in the presence of salt stress. In addition, Reverse transcription quantitative PCR analysis confirmed that the overexpression of OsDUF6 significantly changed the expression level of other genes related to growth and stress tolerance.

CONCLUSIONS

Combined with previously published data, our results supported the observation that OsDUF6 is an important functional factor in Dufulin-induced promotion of salt stress tolerance in rice.

Urea reduces the sustainability of soil Cd immobilization by upregulating the expression of AmSTOP1 and AmMATE genes in edible amaranth roots

After cadmium (Cd) immobilization remediation in contaminated farmland soil, which forms of nitrogen fertilizer should be implemented to keep its sustainability? Urea and nitrate were used to compare for their effects on the remobilization of stabilized Cd in the rhizosphere soil of edible amaranth at nitrogen concentrations of 60, 95, and 130 mg kg-1. The results showed that compared to nitrate nitrogen, the Cd content in shoots increased by 76.2%, 65.6%, and 148% after applying three different concentrations of urea, and the total remobilization amount of Cd also increased by 16.0%, 24.9%, and 14.0% respectively. Urea application promotes root secretion of citric acid, malic acid, pyruvate, and γ-aminobutyric acid, crucial in remobilizing stable Cd. The application of urea promoted the expression of genes involved in sucrose transport, glycolysis, the TCA cycle, amino acid secretion, citric acid efflux, and proton efflux. Arabidopsis heterologous expression and yeast one-hybrid assays identify critical roles of AmMATE42 and AmMATE43 in citric acid and fumaric acid efflux, with AmSTOP1 activating their transcription. Inhibition of SIZ1 expression in urea treatment reduce AmSTOP1 SUMOylation, leading to increased expression of AmMATE42 and AmMATE43 and enhanced organic acids efflux. Using edible amaranth as a model vegetable, we discovered that urea is not beneficial to preserving the sustainability of stabilized Cd during the reuse of remediated farmlands contaminated with Cd.

EpicTope: narrating protein sequence features to identify non-disruptive epitope tagging sites

Epitope tagging is an invaluable technique enabling the identification, tracking, and purification of proteins in vivo. We developed a tool, EpicTope, to facilitate this method by identifying amino acid positions suitable for epitope insertion. Our method uses a scoring function that considers multiple protein sequence and structural features to determine locations least disruptive to the protein's function. We validated our approach on the zebrafish Smad5 protein, showing that multiple predicted internally tagged Smad5 proteins rescue zebrafish smad5 mutant embryos, while the N- and C-terminal tagged variants do not, also as predicted. We further show that the internally tagged Smad5 proteins are accessible to antibodies in wholemount zebrafish embryo immunohistochemistry and by western blot. Our work demonstrates that EpicTope is an accessible and effective tool for designing epitope tag insertion sites. EpicTope is available under a GPL-3 license from: https://github.com/FriedbergLab/Epictope.

Control list of high-priority chemicals based on 5-HT-RI functionality and the human health interference effects selective CNN-GRU deep learning model

The antidepressant drug known as 5-HT reuptake inhibitor (5-HT-RI) was commonly detected in biological tissues and result in significant adverse health effects. Homology modeling was used to characterize the functionalities (efficacy and resistance), and the adverse outcome pathway was used to characterize its human health interferences (olfactory toxicity, neurotoxicity, and gut microbial interference). The convolutional neural network coupled with the gated recurrent unit (CNN-GRU) deep learning method was used to construct a comprehensive model of 5-HT-RI functionality and human health interference effects selectivity with small sample data. The architecture with 2 SE, 320 neuronal nodes and 6-folds cross-validation showed the best applicability. The results showed that the confidence interval of the constructed model reached 90 % indicating that the model had reliable prediction ability and generalization ability. Based on the CNN-GRU deep learning model, seven high-priority chemicals with a weak comprehensive effect, including D-VEN, (1R,4S)-SER, S-FLX, CTP, S-CTP, NEF, and VEN, were screened. Based on the molecular three-dimensional structure information, a comprehensive-effect three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed to confirm the reliability of the constructed control list of 5-HT-RI high-priority chemicals. Analysis with the ranking of calculated values based on the molecular dynamics method and predicted values based on the CNN-GRU deep learning model, we found that the consistency of the three methods was above 85 %. Additionally, by analyzing the sensitivity, molecular electrostatic potential, polar surface area of the comprehensive-effect CNN-GRU deep learning model, and the electrostatic field of the 3D-QSAR models, we found that the significant effects of five key characteristics (DM, Qyy, Qxz, I, and BP), molecular electronegativity, and polarity significantly affected the high-priority degree of 5-HT-RI. In this study, we provided reasonable and reliable prediction tools and discussed theoretical methods for the risk assessment of functionality and human health interference of emerging pollutants such as 5-HT-RI.

Alpha-glucosidase inhibitory and hypoglycemic effects of imidazole-bearing thioquinoline derivatives with different substituents: In silico, in vitro, and in vivo evaluations

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by high blood sugar levels. It was shown that modulating the activity of α-glucosidase, an enzyme involved in carbohydrate digestion and absorption, can improve blood sugar control and overall metabolic health in individuals with T2DM. As a result, in the current study, a series of imidazole bearing different substituted thioquinolines were designed and synthesized as α-glucosidase inhibitors. All derivatives exhibited significantly better potency (IC50 = 12.1 ± 0.2 to 102.1 ± 4.9 µM) compared to the standard drug acarbose (IC50 = 750.0 ± 5.0 µM). 8g as the most potent analog, indicating a competitive inhibition with Ki = 9.66 µM. Also, the most potent derivative was subjected to molecular docking and molecular dynamic simulation against α-glucosidase to determine its mode of action in the enzyme and study the complex's behavior over time. In vivo studies showed that 8g did not cause acute toxicity at 2000 mg/kg doses. Additionally, in a diabetic rat model, treatment with 8g significantly reduced fasting blood glucose levels and decreased blood glucose levels following sucrose loading compared to acarbose, a standard drug used for blood sugar control. The findings suggest that the synthesized compound 8g holds promise as an α-glucosidase inhibitor for improving blood sugar control and metabolic health.

Elucidating the anti-hypertensive mechanisms of Uncaria rhynchophylla-Alisma plantago-aquatica L: an integrated network pharmacology, cluster analysis, and molecular docking approach

Background: With the increasing global prevalence of hypertension, a condition that can severely affect multiple organs, there is a growing need for effective treatment options. Uncaria rhynchophylla-Alisma plantago-aquatica L. (UR-AP) is a traditional drug pair used for treating hypertension based on the liver-kidney synergy concept. However, the detailed molecular mechanisms underlying its efficacy remain unclear. Methods: This study utilized an integrative approach combining network pharmacology, cluster analysis, and molecular docking to uncover the bioactive components and targets of UR-AP in the treatment of hypertension. Initially, we extracted data from public databases to identify these components and targets. A Protein-Protein Interaction (PPI) network was constructed, followed by enrichment analysis to pinpoint the bioactive components, core targets, and pivotal pathways. Cluster analysis helped in identifying key sub-networks and hypothesizing primary targets. Furthermore, molecular docking was conducted to validate the interaction between the core targets and major bioactive components, thus confirming their potential efficacy in hypertension treatment. Results: Network pharmacological analysis identified 58 bioactive compounds in UR-AP, notably quercetin, kaempferol, beta-sitosterol (from Uncaria rhynchophylla), and Alisol B, alisol B 23-acetate (from Alisma plantago-aquatica L.), as pivotal bioactives. We pinpointed 143 targets common to both UR-AP and hypertension, highlighting MAPK1, IL6, AKT1, VEGFA, EGFR, and TP53 as central targets involved in key pathways like diastolic and endothelial function, anti-atherosclerosis, AGE-RAGE signaling, and calcium signaling. Cluster analysis emphasized IL6, TNF, AKT1, and VEGFA's roles in atherosclerosis and inflammation. Molecular docking confirmed strong interactions between these targets and UR-AP's main bioactives, underscoring their therapeutic potential. Conclusion: This research delineates UR-AP's pharmacological profile in hypertension treatment, linking traditional medicine with modern pharmacology. It highlights key bioactive components and their interactions with principal targets, suggesting UR-AP's potential as a novel therapeutic option for hypertension. The evidence from molecular docking studies supports these interactions, indicating the relevance of these components in affecting hypertension pathways. However, the study acknowledges its limitations, including the reliance on in silico analyses and the need for in vivo validation. These findings pave the way for future clinical research, aiming to integrate traditional medicine insights with contemporary scientific approaches for developing innovative hypertension therapies.

Novel genetic markers for chronic kidney disease in a geographically isolated population of Indigenous Australians: Individual and multiple phenotype genome-wide association study

BACKGROUND

Chronic kidney disease (CKD) is highly prevalent among Indigenous Australians, especially those in remote regions. The Tiwi population has been isolated from mainland Australia for millennia and exhibits unique genetic characteristics that distinguish them from other Indigenous and non-Indigenous populations. Notably, the rate of end-stage renal disease is up to 20 times greater in this population compared to non-Indigenous populations. Despite the identification of numerous genetic loci associated with kidney disease through GWAS, the Indigenous population such as Tiwi remains severely underrepresented and the increased prevalence of CKD in this population may be due to unique disease-causing alleles/genes.

METHODS

We used albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) to estimate the prevalence of kidney disease in the Tiwi population (N = 492) in comparison to the UK Biobank (UKBB) (N = 134,724) database. We then performed an exploratory factor analysis to identify correlations among 10 CKD-related phenotypes and identify new multi-phenotype factors. We subsequently conducted a genome-wide association study (GWAS) on all single and multiple phenotype factors using mixed linear regression models, adjusted for age, sex, population stratification, and genetic relatedness between individuals.

RESULTS

Based on ACR, 20.3% of the population was at severely increased risk of CKD progression and showed elevated levels of ACR compared to the UKBB population independent of HbA1c. A GWAS of ACR revealed novel association loci in the genes MEG3 (chr14:100812018:T:A), RAB36 (rs11704318), and TIAM2 (rs9689640). Additionally, multiple phenotypes GWAS of ACR, eGFR, urine albumin, and serum creatinine identified a novel variant that mapped to the gene MEIS2 (chr15:37218869:A:G). Most of the identified variants were found to be either absent or rare in the UKBB population.

CONCLUSIONS

Our study highlights the Tiwi population's predisposition towards elevated ACR, and the collection of novel genetic variants associated with kidney function. These associations may prove valuable in the early diagnosis and treatment of renal disease in this underrepresented population. Additionally, further research is needed to comprehensively validate the functions of the identified variants/genes.

Identification of self- and pathogen-targeted miRNAs from resistant and susceptible Theobroma cacao variety to black pod disease

Cacao (Theobroma cacao) is a highly valuable crop with growing demand in the global market. However, cacao farmers often face challenges posed by black pod disease caused by Phytophthora spp., with P. palmivora being the most dominant. Regulations of various gene expressions influence plant resistance to pathogens. One mechanism involves targeting the mRNA of virulence genes in the invading pathogens, suppressing their infection. However, resistance also could be suppressed by plant-derived miRNAs that target their own defence genes. The objective of this study is to identify differentially expressed miRNAs in black pod-resistant and susceptible cacao varieties and to predict their targets in T. cacao and P. palmivora transcripts. Extracted miRNA from resistant and susceptible varieties of T. Cacao was sequenced, identified, and matched to host and pathogen mRNA. In total, 54 known miRNAs from 40 miRNA families and 67 novel miRNAs were identified. Seventeen miRNAs were differentially expressed in susceptible variety compared to resistant one, with 9 miRNAs upregulated and 8 miRNAs downregulated. In T. cacao transcripts, the upregulated miRNAs were predicted to target several genes, including defence genes. The suppression of these defense genes can lead to a reduction in plant resistance against pathogen infection. In P. palmivora transcripts, the upregulated miRNAs were predicted to target several genes, including P. palmivora effector genes. In the future, limiting expression of miRNAs that target T. cacao's defence genes and applying miRNAs that target P. palmivora effector genes hold promise for enhancing cacao plant resistance against P. palmivora infection.

A proteomic approach to investigate the role of the MECP2 gene mutation in Rett syndrome redox regulatory pathways

Mutations in the X-linked methyl-CpG-binding 2 (MECP2) gene lead to Rett Syndrome (RTT; OMIM 312750), a devasting neurodevelopmental disorder. RTT clinical manifestations are complex and with different degrees of severity, going from autistic-like behavior to loss of acquired speech, motor skills and cardiac problems. Furthermore, the correlation between the type of MECP2 mutation and the clinical phenotype is still not fully understood. Contextually, different genotypes can differently affect the patient's phenotype and omics methodologies such as proteomics could be an important tool for a molecular characterization of genotype/phenotype correlation. The aim of our study was focused on evaluating RTT oxidative stress (OS) responses related to specific MECP2 gene mutations by using proteomics and bioinformatics approaches. Primary fibroblasts isolated from patients affected by R133C and R255× mutations were compared to healthy controls (HC). After clustering primary dermal fibroblasts based on their specific MECP2 mutations, fibroblast-derived protein samples were qualitative and quantitative analyzed, using a label free quantification (LFQ) analysis by mass spectrometry (MS), achieving a preliminary correlation for RTT genotype/phenotype. Among the identified proteins involved in redox regulation pathways, NAD(P)H:quinone acceptor oxidoreductase 1 (NQO1) was found to be absent in R255× cells, while it was present in R133C and in HC fibroblasts. Moreover, NQO1 aberrant gene regulation was also confirmed when cells were challenged with 100 μM hydrogen peroxide (H2O2). In conclusion, by employing a multidisciplinary approach encompassing proteomics and bioinformatics analyses, as well as molecular biology assays, the study uncovered phenotypic responses linked to specific MECP2 gene mutations. These findings contribute to a better understanding of the complexity of RTT molecular pathways, confirming the high heterogeneity among the patients.

Challenges and perspectives for naming lipids in the context of lipidomics

INTRODUCTION

Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied.

OBJECTIVES

In addition, their structures are varied and complex, which complicates their analysis. Indeed, the structural resolution does not always allow a complete level of annotation so the actual compound analysed will vary from study to study and should be clearly stated. For all these reasons the identification and naming of lipids is complicated and very variable from one study to another, it needs to be harmonized.

METHODS & RESULTS

In this position paper we will present and discuss the different way to name lipids (with chemoinformatic and semantic identifiers) and their importance to share lipidomic results.

CONCLUSION

Homogenising this identification and adopting the same rules is essential to be able to share data within the community and to map data on functional networks.

The SIB Swiss Institute of Bioinformatics Semantic Web of data

The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss/) is a federation of bioinformatics research and service groups. The international life science community in academia and industry has been accessing the freely available databases provided by SIB since its inception in 1998. In this paper we present the 11 databases which currently offer semantically enriched data in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable), as well as the Swiss Personalized Health Network initiative (SPHN) which also employs this enrichment. The semantic enrichment facilitates the manipulation of large data sets from public databases and private data sets. Examples are provided to illustrate that the data from the SIB databases can not only be queried using precise criteria individually, but also across multiple databases, including a variety of non-SIB databases. Data manipulation, be it exploration, extraction, annotation, combination, and publication, is possible using the SPARQL query language. Providing documentation, tutorials and sample queries makes it easier to navigate this web of semantic data. Through this paper, the reader will discover how the existing SIB knowledge graphs can be leveraged to tackle the complex biological or clinical questions that are being addressed today.

Structural aspects of RimP binding on small ribosomal subunit from Staphylococcus aureus

Ribosome biogenesis is an energy-intense multistep process where even minimal defects can cause severe phenotypes up to cell death. Ribosome assembly is facilitated by biogenesis factors such as ribosome assembly factors. These proteins facilitate the interaction of ribosomal proteins with rRNA and correct rRNA folding. One of these maturation factors is RimP which is required for efficient 16S rRNA processing and 30S ribosomal subunit assembly. Here, we describe the binding mode of Staphylococcus aureus RimP to the small ribosomal subunit and present a 4.2 Å resolution cryo-EM reconstruction of the 30S-RimP complex. Together with the solution structure of RimP solved by NMR spectroscopy and RimP-uS12 complex analysis by EPR, DEER, and SAXS approaches, we show the specificity of RimP binding to the 30S subunit from S. aureus. We believe the results presented in this work will contribute to the understanding of the RimP role in the ribosome assembly mechanism.

Molecular docking and dynamics simulations revealed the potential inhibitory activity of honey-iQfood ingredients against GSK-3β and CDK5 protein targets for brain health

Honey-iQfood is an herbal supplement made of a mixture of polyherbal extracts and wild honey. The mixture is traditionally claimed to improve various conditions related to brain cells and functions including dementia and Alzheimer's disease. Glycogen synthase kinase-3 beta (GSK-3β) and cyclin-dependent kinase 5 (CDK5) have been identified as being involved in the pathological hyperphosphorylation of tau proteins, which leads to the formation of neurofibrillary tangles and causes Alzheimer's disease. Therefore, this study was conducted to confirm the traditional claims by detection of active compounds, namely curcumin, gallic acid, catechin, rosmarinic acid, and andrographolide in the raw materials of Honey-iQfood through HPLC analysis, molecular docking, and dynamic simulations. Two potential compounds, andrographolide, and rosmarinic acid, produced the best binding affinities following the molecular docking of the active compounds against the GSK-3β and CDK5 targets. Andrographolide binds with GSK-3β at -8.2 kcal/mol, whereas rosmarinic acid binds to CDK5 targets at -8.6 kcal/mol. Molecular dynamics was further carried out to confirm the docking results and clarify their dynamic properties such as RMSD, RMSF, rGyr, SASA, PSA, and binding free energy. CDK5-andrographolide complexes had the best MM-GBSA score (-83.63 kcal/mol) compared to other complexes, indicating the better interaction profile and stability of the complex. These findings warrant further research into andrographolide and rosmarinic acid as efficient inhibitors of tau protein hyperphosphorylation to verify their therapeutic potential in brain-related illnesses.Communicated by Ramaswamy H. Sarma.

Integrated bioinformatics and network pharmacology identifying the mechanisms and molecular targets of Guipi Decoction for treatment of comorbidity with depression and gastrointestinal disorders

BACKGROUND

Guipi decoction (GPD) not only improves gastrointestinal (GI) function, but also depressive mood. The bioinformatics study aimed to reveal potential crosstalk genes and related pathways between depression and GI disorders. A network pharmacology approach was used to explore the molecular mechanisms and potential targets of GPD for the simultaneous treatment of depression comorbid GI disorders.

METHODS

Differentially expressed genes (DEGs) of major depressive disorder (MDD) were identified based on GSE98793 and GSE19738, and GI disorders-related genes were screened from the GeneCards database. Overlapping genes between MDD and GI disorders were obtained to identify potential crosstalk genes. Protein-protein interaction (PPI) network was constructed to screen for hub genes, signature genes were identified by LASSO regression analysis, and single sample gene set enrichment analysis (ssGSEA) was performed to analyze immune cell infiltration. In addition, based on the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, we screened the active ingredients and targets of GPD and identified the intersection targets of GPD with MDD and GI disorder-related genes, respectively. A "component-target" network was constructed using Cytoscape, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed.

RESULTS

The MDD-corrected dataset contained 2619 DEGs, and a total of 109 crosstalk genes were obtained. 14 hub genes were screened, namely SOX2, CRP, ACE, LEP, SHH, CDH2, CD34, TNF, EGF, BDNF, FN1, IL10, PPARG, and KIT. These genes were identified by LASSO regression analysis for 3 signature genes, including TNF, EGF, and IL10. Gamma.delta.T.cell was significantly positively correlated with all three signature genes, while Central.memory.CD4.T.cell and Central.memory.CD8.T.cell were significantly negatively correlated with EGF and TNF. GPD contained 134 active ingredients and 248 targets, with 41 and 87 relevant targets for the treatment of depression and GI disorders, respectively. EGF, PPARG, IL10 and CRP overlap with the hub genes of the disease.

CONCLUSION

We found that GPD may regulate inflammatory and oxidative stress responses through EGF, PPARG, IL10 and CRP targets, and then be involved in the treatment of both depression and GI disorders.

Optimizing the Extraction of Polyphenols from the Bark of Terminalia arjuna and an In-silico Investigation on its Activity in Colorectal Cancer

BACKGROUND

The interconnection between different fields of research has gained interest due to its cutting-edge perspectives in solving scientific problems. Terminalia arjuna is indigenously used in India for curing several diseases, and its pharmacological activities are being revisited in recent drug-repurposing research.

OBJECTIVES

Efficient ultrasound-assisted extraction of phytochemicals from the bark of Terminalia arjuna is highlighted in this study. Following the optimization of the extraction process, the crude hydroethanolic extract is subjected to phytochemical profiling and an in-silico investigation of its anti-cancer properties.

MATERIALS AND METHODS

A three-level four-factor Box-Behnken design is exploited to optimize four operational parameters, namely extraction time, ultrasonic power, ethanol concentration (as the extracting solvent) and solute (in g): solvent (in mL) ratio. At the optimum parametric condition, the crude extract is obtained, and its GC-MS analysis is carried out. An analysis of network pharmacology (by constructing and visualizing biological networks using Cytoscape) combined with molecular docking reveals the potential antineoplastic targets of the crude extract.

RESULTS

The ANOVA table exhibits the significance, adequacy and reliability of the proposed second-order polynomial model with the R² value of 0.917 and adjusted R² of 0.865. Experimental results portray the significant antioxidant potential of the prepared extract in its crude form. The GC-MS analysis of the crude extract predicts the extracted phytochemicals, while the constructed biological networks highlight its multi-targeted activity in colorectal cancer.

CONCLUSION

The study identifies three phytochemicals viz. luteolin, β-sitosterol and arjunic acid as potent anti-cancer agents and can be extended with in-vitro and in-vivo experiments to validate the in-silico results, thus establishing lead phytochemicals in multi-targeted colorectal cancer therapies.

Luteolin inhibits the JAK/STAT pathway to alleviate auditory cell apoptosis of acquired sensorineural hearing loss based on network pharmacology, molecular docking, molecular dynamics simulation, and experiments in vitro

PURPOSE

The study aimed to explore the mechanisms of luteolin in acquired sensorineural hearing loss (SNHL) through network pharmacology, molecular docking, molecular dynamics simulation, and experimental verification.

METHODS

First, the practices of network pharmacology were used to obtain the intersecting targets of luteolin and acquired SNHL, construct the PPI (Protein-Protein Interaction) network, conduct GO and KEGG enrichments, and establish luteolin-acquired SNHL-target-pathway network, aiming to gain the core targets and pathways. Then, the affinity between the core targets and luteolin was verified by molecular docking. Moreover, molecular dynamics (MD) simulation was applied to simulate the binding between targets and luteolin. Finally, with the HEI-OC1 cell line, some molecular biology techniques were adopted to verify the pharmacological actions of luteolin and the significance of the pathway from KEGG enrichment in luteolin-protecting auditory cell damage related to acquired SNHL.

RESULTS

14 intersecting targets were obtained, and the 10 core targets were further verified through molecular docking and MD simulation to get 5 core targets. The JAK/STAT was selected as the critical pathway through KEGG enrichment. Luteolin could dose-dependently alleviate auditory cell apoptosis by inhibiting the JAK/STAT pathway, confirmed by a series of experiments in vitro.

CONCLUSION

This study manifested that luteolin could reduce acquired SNHL-related auditory cell apoptosis through the JAK/STAT pathway, which provided a new idea for acquired SNHL pharmacological treatment.

Underlying Mechanism of Traditional Herbal Formula Chuang-Ling-Ye in the Treatment of Diabetic Foot Ulcer through Network Pharmacology and Molecular Docking

BACKGROUND

Chuang-Ling-Ye (CLY) has been clinically proven to be an effective Chinese medicine for the treatment of diabetic foot ulcers (DFU).

OBJECTIVES

This study aimed to investigate the possible mechanism of CLY in relation to DFU using network pharmacology and molecular docking.

MATERIALS AND METHODS

Firstly, relevant targets of CLY against DFU were obtained from TCMSP, Swiss Target Prediction database and GEO database. Then, topological analysis was employed by Cytoscape to screen the top 6 core active ingredients and the top 8 hub targets. Furthermore, the OmicShare Tools were applied for gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis. Finally, the results of network pharmacology were verified by molecular docking method.

RESULTS

CLY has 61 active compounds and 361 targets after de-duplication, and the top 8 hub targets were EGFR, TP53, CCND1, IL-1B, CREBBP, AR, PTGS2 and PGR. GO enrichment analysis is mainly related to signal transducer activity, receptor activity, and molecular transducer activity. KEGG pathway analysis indicated that these shared targets were primarily focused on AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, IL-17 signaling pathway, and JAK-STAT signaling pathway. Molecular docking results showed that physciondiglucoside, 2-cinnamoyl-glucose and kinobeon A were well bound with EGFR, IL-1B, AR and PTGS2.

CONCLUSION

This study demonstrated that CLY has anti-oxidative stress and anti-inflammatory effects in the treatment of DFU through various constituents, multiple targets, and multiple pathways, which provides a valuable point of reference for future investigations on CLY.

Hydrogen peroxide in breast milk is crucial for gut microbiota formation and myelin development in neonatal mice

Early life environment influences mammalian brain development, a growing area of research within the Developmental Origins of Health and Disease framework, necessitating a deeper understanding of early life factors on children's brain development. This study introduces a mouse model, LAO1 knockout mice, to investigate the relationship between breast milk, the gut microbiome, and brain development. The results reveal that breast milk's reactive oxygen species (ROS) are vital in shaping the neonatal gut microbiota. Decreased hydrogen peroxide (H2O2) levels in milk disrupt the gut microbiome and lead to abnormal metabolite production, including D-glucaric acid. This metabolite inhibits hippocampal myelin formation during infancy, potentially contributing to behavioral abnormalities observed in adulthood. These findings suggest that H2O2 in breast milk is crucial for normal gut microbiota formation and brain development, with implications for understanding and potentially treating neurodevelopmental disorders in humans.