System-level protein interaction network analysis and molecular dynamics study reveal interaction of ferulic acid with PTGS2 as a natural radioprotector

Ferulic acid is a crucial bioactive component of broccoli, wheat, and rice bran and is also an essential natural product that has undergone significant research. Ferulic acid's precise mode of action and effect on system-level protein networks have not been thoroughly investigated. An interactome was built using the STRING database and Cytoscape tools, utilizing 788 key proteins collected from PubMed literature to identify the ferulic acid-governed regulatory action on protein interaction network (PIN). The scale-free biological network of ferulic acid-rewired PIN is highly interconnected. We discovered 15 sub-modules using the MCODE tool for sub-modulization analysis and 153 enriched signaling pathways. Further, functional enrichment of top bottleneck proteins revealed the FoxO signaling pathway involved in enhancing cellular defense against oxidative stress. The selection of the critical regulatory proteins of the ferulic acid-rewired PIN was completed by performing analyses of topological characteristics such as GO term/pathways analysis, degree, bottleneck, molecular docking, and dynamics investigations. The current research derives a precise molecular mechanism for ferulic acid's action on the body. This in-depth in silico model would aid in understanding how ferulic acid origins its antioxidant and scavenging properties in the human body.Communicated by Ramaswamy H. Sarma.

Microbiome composition and function within the Kellet's whelk perivitelline fluid

Microbiomes have gained significant attention in ecological research, owing to their diverse interactions and essential roles within different organismal ecosystems. Microorganisms, such as bacteria, archaea, and viruses, have profound impact on host health, influencing digestion, metabolism, immune function, tissue development, and behavior. This study investigates the microbiome diversity and function of Kellet's whelk (Kelletia kelletii) perivitelline fluid (PVF), which sustains thousands of developing K. kelletii embryos within a polysaccharide and protein matrix. Our core microbiome analysis reveals a diverse range of bacteria, with the Roseobacter genus being the most abundant. Additionally, genes related to host-microbe interactions, symbiosis, and quorum sensing were detected, indicating a potential symbiotic relationship between the microbiome and Kellet's whelk embryos. Furthermore, the microbiome exhibits gene expression related to antibiotic biosynthesis, suggesting a defensive role against pathogenic bacteria and potential discovery of novel antibiotics. Overall, this study sheds light on the microbiome's role in Kellet's whelk development, emphasizing the significance of host-microbe interactions in vulnerable life history stages. To our knowledge, ours is the first study to use 16S sequencing coupled with RNA sequencing (RNA-seq) to profile the microbiome of an invertebrate PVF.IMPORTANCEThis study provides novel insight to an encapsulated system with strong evidence of symbiosis between the microbial inhabitants and developing host embryos. The Kellet's whelk perivitelline fluid (PVF) contains microbial organisms of interest that may be providing symbiotic functions and potential antimicrobial properties during this vulnerable life history stage. This study, the first to utilize a comprehensive approach to investigating Kellet's whelk PVF microbiome, couples 16S rRNA gene long-read sequencing with RNA-seq. This research contributes to and expands our knowledge on the roles of beneficial host-associated microbes.

Physical Peculiarity of Two Sites in Human Promoters: Universality and Diverse Usage in Gene Function

Since the discovery of physical peculiarities around transcription start sites (TSSs) and a site corresponding to the TATA box, research has revealed only the average features of these sites. Unsettled enigmas include the individual genes with these features and whether they relate to gene function. Herein, using 10 physical properties of DNA, including duplex DNA free energy, base stacking energy, protein-induced deformability, and stabilizing energy of Z-DNA, we clarified for the first time that approximately 97% of the promoters of 21,056 human protein-coding genes have distinctive physical properties around the TSS and/or position -27; of these, nearly 65% exhibited such properties at both sites. Furthermore, about 55% of the 21,056 genes had a minimum value of regional duplex DNA free energy within TSS-centered ±300 bp regions. Notably, distinctive physical properties within the promoters and free energies of the surrounding regions separated human protein-coding genes into five groups; each contained specific gene ontology (GO) terms. The group represented by immune response genes differed distinctly from the other four regarding the parameter of the free energies of the surrounding regions. A vital suggestion from this study is that physical-feature-based analyses of genomes may reveal new aspects of the organization and regulation of genes.

Lung Fibroblasts from Chronic Obstructive Pulmonary Disease Subjects Have a Deficient Gene Expression Response to Cigarette Smoke Extract Compared to Healthy

Background and aim

Cigarette smoking is the most common cause of chronic obstructive pulmonary disease (COPD) but more mechanistic studies are needed. Cigarette smoke extract (CSE) can elicit a strong response in many COPD-related cell types, but no studies have been performed in lung fibroblasts. Therefore, we aimed to investigate the effect of CSE on gene expression in lung fibroblasts from healthy and COPD subjects.

Patients and methods

Primary lung fibroblasts, derived from six healthy and six COPD subjects (all current or ex-smokers), were either unstimulated (baseline) or stimulated with 30% CSE for 4 h prior to RNA isolation. The mRNA expression levels were measured using the NanoString nCounter Human Fibrosis V2 panel (760 genes). Pathway enrichment was assessed for unique gene ontology terms of healthy and COPD.

Results

At baseline, a difference in the expression of 17 genes was found in healthy and COPD subjects. Differential expression of genes after CSE stimulation resulted in significantly less changes in COPD lung fibroblasts (70 genes) than in healthy (207 genes), with 51 genes changed in both. COPD maintained low NOTCH signaling throughout and upregulated JUN >80%, indicating an increase in apoptosis. Healthy downregulated the Mitogen-activated protein kinase (MAPK) signaling cascade, including a ≥50% reduction in FGF2, CRK, TGFBR1 and MEF2A. Healthy also downregulated KAT6A and genes related to cell proliferation, all together indicating possible cell senescence signaling.

Conclusion

Overall, COPD lung fibroblasts responded to CSE stimulation with a very different and deficient expression profile compared to healthy. Highlighting that stimulated healthy cells are not an appropriate substitute for COPD cells which is important when investigating the mechanisms of COPD.

Genomic data of two chickpea populations sharing a potential Ascochyta blight resistance region

Chickpea (Cicer arietinum L.) is one of the most important crops worldwide and a valuable nutritional source. The availability of data from different genotypes and populations is important for the comprehension of the biology and trait control of chickpea. Tissue from young leaves was collected from adult plants and sequenced using an Illumina HiSeq X platform, which provided sequencing data for a total of 169 individuals from two different populations. Furthermore, functional annotation was performed with BLAST2GO software in a candidate region for resistance to Ascochyta blight, a devastating disease that produces huge yield reductions if the growth conditions are optimal for the fungus. A total of 273 different genes in a region spanning ∼4.67 Mb in chromosome 4 were fully annotated. The raw DNA sequences and functional annotation data can be reused by the scientific community for the analysis of different agronomic traits of interest in chickpea.

Black sheep, dark horses, and colorful dogs: a review on the current state of the Gene Ontology with respect to iron homeostasis in Arabidopsis thaliana

Cellular homeostasis of the micronutrient iron is highly regulated in plants and responsive to nutrition, stress, and developmental signals. Genes for iron management encode metal and other transporters, enzymes synthesizing chelators and reducing substances, transcription factors, and several types of regulators. In transcriptome or proteome datasets, such iron homeostasis-related genes are frequently found to be differentially regulated. A common method to detect whether a specific cellular pathway is affected in the transcriptome data set is to perform Gene Ontology (GO) enrichment analysis. Hence, the GO database is a widely used resource for annotating genes and identifying enriched biological pathways in Arabidopsis thaliana. However, iron homeostasis-related GO terms do not consistently reflect gene associations and levels of evidence in iron homeostasis. Some genes in the existing iron homeostasis GO terms lack direct evidence of involvement in iron homeostasis. In other aspects, the existing GO terms for iron homeostasis are incomplete and do not reflect the known biological functions associated with iron homeostasis. This can lead to potential errors in the automatic annotation and interpretation of GO term enrichment analyses. We suggest that applicable evidence codes be used to add missing genes and their respective ortholog/paralog groups to make the iron homeostasis-related GO terms more complete and reliable. There is a high likelihood of finding new iron homeostasis-relevant members in gene groups and families like the ZIP, ZIF, ZIFL, MTP, OPT, MATE, ABCG, PDR, HMA, and HMP. Hence, we compiled comprehensive lists of genes involved in iron homeostasis that can be used for custom enrichment analysis in transcriptomic or proteomic studies, including genes with direct experimental evidence, those regulated by central transcription factors, and missing members of small gene families or ortholog/paralog groups. As we provide gene annotation and literature alongside, the gene lists can serve multiple computational approaches. In summary, these gene lists provide a valuable resource for researchers studying iron homeostasis in A. thaliana, while they also emphasize the importance of improving the accuracy and comprehensiveness of the Gene Ontology.

Cellular Morphology and Transcriptome Comparative Analysis of Astragalus membranaceus Bunge Sprouts Cultured In Vitro under Different LED Light

Astragalus membranaceus, the major components of which are saponins, flavonoids, and polysaccharides, has been established to have excellent pharmacological activity. After ginseng, it is the second most used medicinal plant. To examine the utility of A. membranaceus as a sprout crop for plant factory cultivation, we sought to establish a functional substance control model by comparing the transcriptomes of sprouts grown in sterile, in vitro culture using LED light sources. Having sown the seeds of A. membranaceus, these were exposed to white LED light (continuous spectrum), red LED light (632 nm, 1.58 μmol/m²/s), or blue LED light (465 nm, 1.44 μmol/m²/s) and grown for 6 weeks; after which, the samples were collected for transcriptome analysis. Scanning electron microscopy analysis of cell morphology in plants exposed to the three light sources revealed that leaf cell size was largest in those plants exposed to red light, where the thickest stem was observed in plants exposed to white light. The total number of genes in A. membranaceus spouts determined via de novo assembly was 45,667. Analysis of differentially expressed genes revealed that for the comparisons of blue LED vs. red LED, blue LED vs. white LED, and red LED vs. white LED, the numbers of upregulated genes were 132, 148, and 144, respectively. Binding, DNA integration, transport, phosphorylation, DNA biosynthetic process, membrane, and plant-type secondary cell wall biogenesis were the most enriched in the comparative analysis of blue LED vs. red LED, whereas Binding, RNA-templated DNA biosynthetic process, DNA metabolic process, and DNA integration were the most enriched in the comparative analysis of blue vs. white LED, and DNA integration and resolution of meiotic recombination intermediates were the most enrichment in the comparison between red LED vs. white LED. The GO term associated with flavonoid biosynthesis, implying the functionality of A. membranaceus, was the flavonoid biosynthetic process, which was enriched in the white LED vs. red LED comparison. The findings of this study thus indicate that different LED light sources can differentially influence the transcriptome expression pattern of A. membranaceus sprouts, which can provide a basis for establishing a flavonoid biosynthesis regulation model and thus, the cultivation of high-functional Astragalus sprouts.

Neuroprotective effects of long noncoding RNAs involved in ischemic postconditioning after ischemic stroke

During acute reperfusion, the expression profiles of long noncoding RNAs in adult rats with focal cerebral ischemia undergo broad changes. However, whether long noncoding RNAs are involved in neuroprotective effects following focal ischemic stroke in rats remains unclear. In this study, RNA isolation and library preparation was performed for long noncoding RNA sequencing, followed by determining the coding potential of identified long noncoding RNAs and target gene prediction. Differential expression analysis, long noncoding RNA functional enrichment analysis, and co-expression network analysis were performed comparing ischemic rats with and without ischemic postconditioning rats. Rats were subjected to ischemic postconditioning via the brief and repeated occlusion of the middle cerebral artery or femoral artery. Quantitative real-time reverse transcription-polymerase chain reaction was used to detect the expression levels of differentially expressed long noncoding RNAs after ischemic postconditioning in a rat model of ischemic stroke. The results showed that ischemic postconditioning greatly affected the expression profile of long noncoding RNAs and mRNAs in the brains of rats that underwent ischemic stroke. The predicted target genes of some of the identified long noncoding RNAs (cis targets) were related to the cellular response to ischemia and stress, cytokine signal transduction, inflammation, and apoptosis signal transduction pathways. In addition, 15 significantly differentially expressed long noncoding RNAs were identified in the brains of rats subjected to ischemic postconditioning. Nine candidate long noncoding RNAs that may be related to ischemic postconditioning were identified by a long noncoding RNA expression profile and long noncoding RNA-mRNA co-expression network analysis. Expression levels were verified by quantitative real-time reverse transcription-polymerase chain reaction. These results suggested that the identified long noncoding RNAs may be involved in the neuroprotective effects associated with ischemic postconditioning following ischemic stroke. The experimental animal procedures were approved by the Animal Experiment Ethics Committee of Kunming Medical University (approval No. KMMU2018018) in January 2018.

QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs

The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein–protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated.

Analysis of Four Types of Leukemia Using Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Scores

AIM AND OBJECTIVE

Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia can be classified into four types: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and chronic myelogenous leukemia (CML). More than forty drugs are applicable to different types of leukemia based on the discrepant pathogenesis. Therefore, the identification of specific drug-targeted biological processes and pathways is helpful to determinate the underlying pathogenesis among such four types of leukemia.

METHODS

In this study, the gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were highly related to drugs for leukemia were investigated for the first time. The enrichment scores for associated GO terms and KEGG pathways were calculated to evaluate the drugs and leukemia. The feature selection method, minimum redundancy maximum relevance (mRMR), was used to analyze and identify important GO terms and KEGG pathways.

RESULTS

Twenty Go terms and two KEGG pathways with high scores have all been confirmed to effectively distinguish four types of leukemia.

CONCLUSION

This analysis may provide a useful tool for the discrepant pathogenesis and drug design of different types of leukemia.

Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method

LncRNAs plays an important role in the regulation of gene expression. Identification of cancer-related lncRNAs GO terms and KEGG pathways is great helpful for revealing cancer-related functional biological processes. Therefore, in this study, we proposed a computational method to identify novel cancer-related lncRNAs GO terms and KEGG pathways. By using existing lncRNA database and Max-relevance Min-redundancy (mRMR) method, GO terms and KEGG pathways were evaluated based on their importance on distinguishing cancer-related and non-cancer-related lncRNAs. Finally, GO terms and KEGG pathways with high importance were presented and analyzed. Our literature reviewing showed that the top 10 ranked GO terms and pathways were really related to interpretable tumorigenesis according to recent publications.

Analysis of key GO terms and KEGG pathways associated with carcinogenic chemicals

Cancer is one of the serious disease that causes several human deaths every year. Up to now, we have spent lots of time and money to investigate this disease, thereby designing effective treatments. Previous studies mainly focus on studying genetic background of different subtypes of cancer and neglect another important factor, environmental factor. Carcinogenic chemical is one of the type of environmental factor, exposure of such chemical may definitely initiate and promote the tumorigenesis. In this study, we tried to partly describe the differences between carcinogenic and non-carcinogenic chemicals using gene ontology (GO) terms and KEGG pathways. The carcinogenic and non-carcinogenic chemicals that were retrieved from Carcinogenic Potency Database (CPDB) were encoded into numeric vectors using the enrichment theories of GO terms and KEGG pathways. Then, the minimal redundancy maximal relevance (mRMR) method was adopted to analyze all features, resulting in some important GO terms and KEGG pathways. The extensive analysis of the identified GO terms and KEGG pathways indicate that they all play roles during the tumorigenesis, inducing that they can be key indicator for identification of carcinogenic chemicals.

Improved surfaceome coverage with a label-free nonaffinity-purified workflow

The proteins of the cellular plasma membrane (PM) perform important functions relating to homeostasis and intercellular communication. Due to its overall low cellular abundance, amphipathic character, and low membrane-to-cytoplasm ratio, the PM proteome has been challenging to isolate and characterize, and is poorly represented in standard LC-MS/MS analyses. In this study, we employ sucrose gradient ultracentrifugation for the enrichment of the PM proteome, without chemical labeling and affinity purification, together with GeLCMS and use subsequent bioinformatics tools to select proteins associated with the PM/cell surface, herein referred to as the surfaceome. Using this methodology, we identify over 1900 cell surface associated proteins in a human acute myeloid leukemia cell line. These surface proteins comprise almost 50% of all detected cellular proteins, a number that substantially exceeds the depth of coverage in previously published studies describing the leukemia surfaceome.