Functional & Integrative Genomics最新文献

Background

Hepatocellular carcinoma (HCC), a globally common cancer, often presents late and shows high resistance to chemotherapy, resulting in suboptimal treatment efficacy. Components from traditional Chinese medicines have been recognized for their anti-cancer properties.

Objective

Exploring the mechanism of Schisandra chinensis lignans and acteoside in suppressing Epithelial-Mesenchymal Transition (EMT) in hepatoma cells through the Extracellular signal-Regulated Kinases (ERK)1/2 pathway and identifying biomarkers, molecular subtypes, and targets via multi-omics for precision oncology.

Methods

Proliferation was assessed using cell counting kit-8 (CCK-8) assays, with scratch and transwell assays for evaluating invasion and migration. Flow cytometry quantified apoptosis rates. Expression levels of CCL20, p-ERK1/2, c-Myc, Vimentin, and E-cadherin/N-cadherin were analyzed by real-time PCR and Western blot. Tumor volume was calculated with a specific formula, and growth.

Results

The Schisandra chinensis lignans and acteoside combination decreased CCL20 expression, inhibited hepatoma proliferation and migration, and enhanced apoptosis in a dose- and time-dependent manner. Molecular analysis revealed increased E-cadherin and decreased N-cadherin, p-ERK1/2, c-Myc, and Vimentin expression, indicating ERK1/2 pathway modulation. In vivo, treated nude mice showed significantly reduced tumor growth and volume.

Conclusion

Schisandra chinensis lignans and acteoside potentially counteract CCL20-induced EMT, invasion, and migration in hepatocellular carcinoma cells via the ERK1/2 pathway, enhancing apoptosis. Multi-omics analysis further aids in pinpointing novel biomarkers for precision cancer therapy.

With the growing population, demand for food has dramatically increased, and fisheries, including aquaculture, are expected to play an essential role in sustaining demand with adequate quantities of protein and essential vitamin supplements, employment generation, and GDP growth. Unfortunately, the incidence of emerging/re-emerging AMR pathogens annually occurs because of anthropogenic activities and the frequent use of antibiotics in aquaculture. These AMR pathogens include the WHO's top 6 prioritized ESKAPE pathogens (nosocomial pathogens: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.), extended-spectrum beta lactases (ESBLs) and carbapenemase-producing E. coli, which pose major challenges to the biomagnification of both nonnative and native antibiotic-resistant bacteria in capture and cultured fishes. Although implementing the rational use of antibiotics represents a promising mitigation measure, this approach is practically impossible due to the lack of awareness among farmers about the interplay between antimicrobial use and the emergence of antimicrobial resistance (AMR). Nevertheless, to eradicate these ‘superbugs,’ CRISPR/Cas (clustered regularly interspersed short palindromic repeats/CRISPR associate protein) has turned out to be a novel approach owing to its ability to perform precise site-directed targeting/knockdown/reversal of specific antimicrobial resistance genes in vitro and to distinguish AMR-resistant bacteria from a plethora of commensal aquatic bacteria. Along with highlighting the importance of virulent multidrug resistance genes in bacteria, this article aims to provide a holistic picture of CRISPR/Cas9-mediated genome editing for combating antimicrobial-resistant bacteria isolated from various aquaculture and marine systems, as well as insights into different types of CRISPR/Cas systems, delivery methods, and challenges associated with developing CRISPR/Cas9 antimicrobial agents.

For the study of species evolution, chloroplast gene expression, and transformation, the chloroplast genome is an invaluable resource. Codon usage bias (CUB) analysis is a tool that is utilized to improve gene expression and investigate evolutionary connections in genetic transformation. In this study, we analysed chloroplast genome differences, codon usage patterns and the sources of variation on CUB in 14 Annonaceae species using bioinformatics tools. The study showed that there was a significant variation in both gene sizes and numbers between the 14 species, but conservation was still maintained. It’s worth noting that there were noticeable differences in the IR/SC sector boundary and the types of SSRs among the 14 species. The mono-nucleotide repeat type was the most common, with A/T repeats being more prevalent than G/C repeats. Among the different types of repeats, forward and palindromic repeats were the most abundant, followed by reverse repeats, and complement repeats were relatively rare. Codon composition analysis revealed that all 14 species had a frequency of GC lower than 50%. Additionally, it was observed that the proteins in-coding sequences of chloroplast genes tend to end with A/T at the third codon position. Among these species, 21 codons exhibited bias (RSCU > 1), and there were 8 high-frequency (HF) codons and 5 optimal codons that were identical across the species. According to the ENC-plot and Neutrality plot analysis, natural selection had less impact on the CUB of A. muricate and A. reticulata. Based on the PR2-plot, it was evident that base G had a higher frequency than C, and T had a higher frequency A. The correspondence analysis (COA) revealed that codon usage patterns different in Annonaceae.

Sulfate transporter (SULTR) proteins are in charge of the transport and absorption on sulfate substances, and have been reported to play vital roles in the biological processes of plant growth and stress response. However, there were few reports of genome-wide identification and expression-pattern analysis of SULTRs in Hibiscus mutabilis. Gossypium genus is a ideal model for studying the allopolyploidy, therefore two diploid species (G. raimondii and G. arboreum) and two tetraploid species (G. hirsutum and G. barbadense) were chosen in this study to perform bioinformatic analyses, identifying 18, 18, 35, and 35 SULTR members, respectively. All the 106 cotton SULTR genes were utilized to construct the phylogenetic tree together with 11 Arabidopsis thaliana, 13 Oryza sativa, and 8 Zea mays ones, which was divided into Group1-Group4. The clustering analyses of gene structures and 10 conserved motifs among the cotton SULTR genes showed the consistent evolutionary relationship with the phylogenetic tree, and the results of gene-duplication identification among the four representative Gossypium species indicated that genome-wide or segment duplication might make main contributions to the expansion of SULTR gene family in cotton. Having conducted the cis-regulatory element analysis in promoter region, we noticed that the existing salicylic acid (SA), jasmonic acid (JA), and abscisic acid (ABA) elements could have influences with expression levels of cotton SULTR genes. The expression patterns of GhSULTR genes were also investigated on the 7 different tissues or organs and the developing ovules and fibers, most of which were highly expressed in root, stem, sepal, receptacel, ovule at 10 DPA, and fiber at 20 and 25 DPA. In addition, more active regulatory were observed in GhSULTR genes responding to multiple abiotic stresses, and 12 highly expressed genes showed the similar expression patterns in the quantitative Real-time PCR experiments under cold, heat, salt, and drought treatments. These findings broaden our insight into the evolutionary relationships and expression patterns of the SULTR gene family in cotton, and provide the valuable information for further screening the vital candidate genes on trait improvement.

COVID-19 is associated with heterogeneous outcome. Early identification of a severe progression of the disease is essential to properly manage the patients and improve their outcome. Biomarkers reflecting an increased inflammatory response, as well as individual features including advanced age, male gender, and pre-existing comorbidities, are risk factors of severe COVID-19. Yet, these features show limited accuracy for outcome prediction. The aim was to evaluate the prognostic value of whole blood transcriptome at an early stage of the disease. Blood transcriptome of patients with mild pneumonia was profiled. Patients with subsequent severe COVID-19 were compared to those with favourable outcome, and a molecular predictor based on gene expression was built. Unsupervised classification discriminated patients who would later develop a COVID-19-related severe pneumonia. The corresponding gene expression signature reflected the immune response to the viral infection dominated by a prominent type I interferon, with IFI27 among the most over-expressed genes. A 48-genes transcriptome signature predicting the risk of severe COVID-19 was built on a training cohort, then validated on an external independent cohort, showing an accuracy of 81% for predicting severe outcome. These results identify an early transcriptome signature of severe COVID-19 pneumonia, with a possible relevance to improve COVID-19 patient management.

Accurate estimation of population allele frequency (AF) is crucial for gene discovery and genetic diagnostics. However, determining AF for frameshift-inducing small insertions and deletions (indels) faces challenges due to discrepancies in mapping and variant calling methods. Here, we propose an innovative approach to assess indel AF. We developed CRAFTS-indels (Calculating Regional Allele Frequency Targeting Small indels), an algorithm that combines AF of distinct indels within a given region and provides “regional AF” (rAF). We tested and validated CRAFTS-indels using three independent datasets: gnomAD v2 (n=125,748 samples), an internal dataset (IGM; n=39,367), and the UK BioBank (UKBB; n=469,835). By comparing rAF against standard AF, we identified rare indels with rAF exceeding standard AF (sAF≤10^-4 and rAF>10^-4) as “rAF-hi” indels. Notably, a high percentage of rare indels were “rAF-hi”, with a higher proportion in gnomAD v2 (11-20%) and IGM (11-22%) compared to the UKBB (5-9% depending on the CRAFTS-indels’ parameters). Analysis of the overlap of regions based on their rAF with low complexity regions and with ClinVar classification supported the pertinence of rAF. Using the internal dataset, we illustrated the utility of CRAFTS-indel in the analysis of de novo variants and the potential negative impact of rAF-hi indels in gene discovery. In summary, annotation of indels with cohort specific rAF can be used to handle some of the limitations of current annotation pipelines and facilitate detection of novel gene disease associations. CRAFTS-indels offers a user-friendly approach to providing rAF annotation. It can be integrated into public databases such as gnomAD, UKBB and used by ClinVar to revise indel classifications.

Breast cancer severely affects women health. 70% of breast cancer are estrogen receptor positive. Breast cancer stem cells are a group of tumor with plasticity, causing tumor relapse and metastasis. RUNX3 is a tumor suppressor frequently inactivated in estrogen receptor positive breast cancer. However, the mechanism of how RUNX3 is involved in the regualation of cancer stem cell traits in estrogen receptor positive breast cancer remains elusive. In this study, we utilized cut-tag assay to investigate the binding profile RUNX3 in BT474 and T47D cell, and confirmed EXOSC4 as the bona-fide target of RUNX3; RUNX3 could bind to the promoter are of EXOSC4 to suppress its expression. Furthermore, EXOSC4 could increase the colony formation, cell invasion and mammosphere formation ability of breast cancer cells and upregulate the the expression of SOX2 and ALDH1. Consistent with these findings, EXOSC4 was associated with poorer survival for Luminal B/Her2 breast cancer patiens. At last, we confirmed that EXOSC4 mediated the tumor suppressive role of RUNX3 in breast cancer cells. In conclusion, we demonstrate that RUNX3 directly binds to the promoter region of EXOSC4, leading to the suppression of EXOSC4 expression and exerting a tumor-suppressive effect in estrogen receptor postivive breast cancer cells.