A LncRNA-miRNA-mRNA ceRNA regulatory network based tuberculosis prediction model

Whole-transcriptome sequencing of phagocytes reveals a ceRNA network contributing to natural resistance to tuberculosis infection

Tuberculosis (TB) is a major fatal infectious disease globally, exhibiting high morbidity rates and impacting public health and other socio-economic factors. However, some individuals are resistant to TB infection and are referred to as "Resisters". Resisters remain uninfected even after exposure to high load of Mycobacterium tuberculosis (Mtb). To delineate this further, this study aimed to investigate the factors and mechanisms influencing the Mtb resistance phenotype. We assayed the phagocytic capacity of peripheral blood mononuclear cells (PBMCs) collected from Resisters, patients with latent TB infection (LTBI), and patients with active TB (ATB), following infection with fluorescent Mycobacterium bovis Bacillus Calmette-Guérin (BCG). Phagocytosis was stronger in PBMCs from ATB patients, and comparable in LTBI patients and Resisters. Subsequently, phagocytes were isolated and subjected to whole transcriptome sequencing and small RNA sequencing to analyze transcriptional expression profiles and identify potential targets associated with the resistance phenotype. The results revealed that a total of 277 mRNAs, 589 long non-coding RNAs, 523 circular RNAs, and 35 microRNAs were differentially expressed in Resisters and LTBI patients. Further, the endogenous competitive RNA (ceRNA) network was constructed from differentially expressed genes after screening. Bioinformatics, statistical analysis, and quantitative real-time polymerase chain reaction were used for the identification and validation of potential crucial targets in the ceRNA network. As a result, we obtained a ceRNA network that contributes to the resistance phenotype. TCONS_00034796-F3, ENST00000629441-DDX43, hsa-ATAD3A_0003-CYP17A1, and XR_932996.2-CERS1 may be crucial association pairs for resistance to TB infection. Overall, this study demonstrated that the phagocytic capacity of PBMCs was not a determinant of the resistance phenotype and that some non-coding RNAs could be involved in the natural resistance to TB infection through a ceRNA mechanism.

The Competing Endogenous RNAs Regulatory Genes Network Mediates Leaf Shape Variation and Main Effector Gene Function in Mulberry Plant (Morus alba)

Mulberry plants (Morus alba) have leaf shapes, ranging from unlobed to lobed, which are crucial for yield, growth, and adaptability, indicating their ability to adapt to their environment. Competing endogenous RNAs (ceRNAs) constitute a web of RNAs within the organism's transcriptional regulatory system, including protein-coding genes (mRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and others. In this study, samples for ceRNA sequencing were categorized into two groups: whole leaves and lobed leaves, each group with three replicates. In addition, we isolated, cloned, and characterized the precursor miRNA (miR156x) from the leaves of M. alba. miR156x precursor had a length of 107 base pairs and a minimum folding free energy of 50.27 kcal/mol. We constructed a pCAMBIA-35S-GUS-miR156x dual overexpression vector and established a transient transformation system for mulberry. At an optimal transformation solution (OD600 = 0.7), the GUS gene showed a higher expression in the leaves of transiently transformed mulberry with miR156x overexpression, four days after transformation, while the target genes of miR156x had decreased expression in the same leaves. Investigations into the transgenic mulberry plants uncovered various modifications to physio-chemical parameters including POD, SOD, PRO, MDA, soluble proteins and sugars, and chlorophyl content. miRNAs in the plants were found to act as negative regulators of gene expression in response to changes in leaf shape regulation, which was confirmed in vitro using dual-luciferase reporter assays. Subsequently, we cloned Maspl3 in vitro and conducted GST-Pull down assays, obtaining multiple proteins that interacted with the Maspl3 gene. This indicates that the miR156x/Maspl3/MSTRG.25812.1 regulatory module contributes to the differences in mulberry leaf shape.

The Identification and Comparative Analysis of Non-Coding RNAs in Spores and Mycelia of Penicillium expansum

Penicillium expansum is the most popular post-harvest pathogen and causes blue mold disease in pome fruit and leads to significant economic losses worldwide every year. However, the fundamental regulation mechanisms of growth in P. expansum are unclear. Recently, non-coding RNAs (ncRNAs) have attracted more attention due to critical roles in normalizing gene expression and maintaining cellular genotypes in organisms. However, the research related to ncRNAs in P. expansum have not been reported. Therefore, to provide an overview of ncRNAs on composition, distribution, expression changes, and potential targets in the growth process, a comparative transcriptomic analysis was performed on spores and mycelia of P. expansum in the present study. A total of 2595 novel mRNAs, 3362 long non-coding RNAs (lncRNAs), 10 novel microRNAs (miRNAs), 86 novel small interfering RNAs (siRNAs), and 11,238 circular RNAs (circRNAs) were predicted and quantified. Of these, 1482 novel mRNAs, 5987 known mRNAs, 2047 lncRNAs, 40 miRNAs, 38 novel siRNAs, and 9235 circRNAs were differentially expressed (DE) in response to the different development stages. Afterward, the involved functions and pathways of DE RNAs were revealed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database enrichment analysis. The interaction networks between mRNAs, lncRNAs, and miRNAs were also predicted based on their correlation coefficient of expression profiles. Among them, it was found that miR168 family members may play important roles in fungal growth due to their central location in the network. These findings will contribute to a better understanding on regulation machinery at the RNA level on fungal growth and provide a theoretical basis to develop novel control strategies against P. expansum.

The exploration of shared genes and molecular mechanisms of systemic lupus erythematosus and atherosclerosis

OBJECTIVE

Despite widespread recognition, the mechanisms underlying the relationship between systemic lupus erythematosus (SLE) and atherosclerosis (AS) are still unclear. Our study aimed to explore the shared genetic signature and molecular mechanisms of SLE and AS using a bioinformatics approach.

METHODS

Gene expression profiles of GSE50772 (contains peripheral blood mononuclear cells from 61 SLE patients and 20 normal samples) and GSE100927 (contains 69 AS plaque tissue samples and 35 control samples) were downloaded from the Gene Expression Database (GEO) before the differentially expressed genes were obtained using the "limma" package in R. The differential genes were then subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using the DAVID online platform to annotate their functions. The intersection targets of PPI and WGCNA were used as key shared genes for SLE and AS with their diagnostic value as shared genes being verified through ROC curves. Finally, Cytoscape 3.7.2 software was used to construct a miRNA-mRNA network map associated with the shared genes.

RESULTS

A total of 246 DEGs were identified, including 189 upregulated genes and 57 downregulated genes, which were mainly enriched in signaling pathways such as TNF signaling pathway, IL-17 signaling pathway, and NF-kB signaling pathway. The molecular basis for the relationship between SLE and AS may be the aforementioned signaling pathways. Following ROC curve validation, the intersection of PPI and WGCNA, as well as AQP9, CCR1, CD83, CXCL1, and FCGR2A, resulted in the identification of 15 shared genes.

CONCLUSION

The study provided a new perspective on the common molecular mechanisms between SLE and AS, and the key genes and pathways that were identified as being part of these pathways may offer fresh perspectives and suggestions for further experimental research.

HOTAIR/miR-203/CAV1 Crosstalk Influences Proliferation, Migration, and Invasion in the Breast Cancer Cell

In recent years, malignant breast cancer metastasis has caused a great increase in mortality. Research on the genetic and molecular mechanisms of malignant breast cancer has continued to deepen, and targeted therapy has become the general trend. Among them, competing endogenous RNA (ceRNA)-related molecules have received much attention. Homeobox transcript antisense RNA (HOTAIR) has been reported to function extensively as a ceRNA in breast cancer. Notably, miR-203 and Caveolin 1 (CAV1) have also been found to play a role in breast cancer. However, the relationship between the three remains unclear. In this study, we present a new mechanic through bioinformatics tool and basic experiments: the HOTAIR/miR-203/CAV1 axis, which complemented the role network of HOTAIR as a ceRNA, thus, it will provide a novel potential idea for breast cancer research and therapy.

Identification of biomarkers for early diagnosis of multiple myeloma by weighted gene co-expression network analysis and their clinical relevance

BACKGROUND

Multiple myeloma is an incurable hematologic malignancy, its early diagnosis is important. However, the biomarker for early diagnosis is limited; hence more need to be identified. The present study aimed to explore the easily tested new biomarker in multiple myeloma by weighted gene co-expression network analysis (WGCNA).

METHODS

Differentially expressed genes (DEGs) were screened using GSE47552. WGCNA was used to screen hub genes. Subsequently. Hub genes of multiple myeloma were obtained by intersection of DEGs and WGCNA. We used the T-test to screen highly expressed genes. Then, the diagnostic value of key genes was evaluated by the receiver operating characteristic (ROC) curve. Finally, expression levels of key genes were tested and proved by RT-PCR.

RESULTS

278 DEGs were screened by Limma package. Three modules were most significantly correlated with multiple myeloma. 238 key genes were screened after the intersection of WGCNA with DEGs. In addition, SNORNA is rarely studied in multiple myeloma, and ROC curve analysis in our prediction model showed that SNORA71A had a good prediction effect (p = 0.07). The expression of SNORA71A was increased in samples of multiple myeloma (P = 0.05). RT-PCR results showed that SNORA71A was upregulated in 51 patient specimens compared to the healthy group (P < 0.05). Linear correlation analysis showed that creatinine was positively correlated with SNORA71A (r = 0.49 P = 0.0002).

CONCLUSIONS

This study found that SNORA71A was up-regulated and associated with the clinical stages in multiple myeloma; it suggests that SNORA71A could be used as a novel biomarker for early diagnosis and a potential therapeutic target in multiple myeloma.