Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or ...pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.
Colorectal cancer is the third most common cancer in males and second in females. This disease can be caused by genetic and acquired/environmental factors. Microsatellite instability (MSI) is one of ...the major mechanisms in colorectal cancer. This mechanism is a specific condition of genetic hyper mutability that results from incompetent DNA mismatch repair. MSI has been applied to classify different colorectal cancer subtypes. However, the effects of MSI status on gene expression are largely unknown. In our study, we integrated the gene expression profile and MSI status of all CRC samples from the TCGA database, and then categorized the CRC samples into three subgroups, namely, MSI‐stable, MSI‐low, and MSI‐high, according to the MSI status. We applied a novel computational method based on machine learning and screened the genes specifically expressed for the different colorectal cancer subtypes. The results showed the distinct mechanisms of the different colorectal cancer subtypes with MSI status and provided the genes that may be the optimal standards to further classify the various molecular subtypes of colorectal cancer with distinct MSI status.
What's new?
Microsatellite instability (MSI), a key genetic mechanism implicated in colorectal cancer (CRC), is linked to drug reactivity and sensitivity in CRC patients and is useful for CRC subtype classification. Yet, little is known about the identity of MSI‐associated genes or their role in CRC. Here, combined analysis of datasets on gene‐expression profile and MSI status enabled the investigation of a number of differentially expressed genes from CRC samples. Genes optimal for the classification of CRC subtypes with different MSI statuses were identified. The gene panel could facilitate the discovery of biomarkers specific for CRCs with known MSI status.
Synthetic lethality is the synthesis of mutations leading to cell death. Tumor‐specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in ...molecular biology, such as RNAi and CRISPR/Cas9 gene editing, efforts have been made to systematically identify synthetic lethal interactions, especially for frequently mutated genes in cancers. However, elucidating the mechanism of synthetic lethality remains a challenge because of the complexity of its influencing conditions. In this study, we proposed a new computational method to identify critical functional features that can accurately predict synthetic lethal interactions. This method incorporates several machine learning algorithms and encodes protein‐coding genes by an enrichment system derived from gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to represent their functional features. We built a random forest‐based prediction engine by using 2120 selected features and obtained a Matthews correlation coefficient of 0.532. We examined the top 15 features and found that most of them have potential roles in synthetic lethality according to previous studies. These results demonstrate the ability of our proposed method to predict synthetic lethal interactions and provide a basis for further characterization of these particular genetic combinations.
A computational analysis of synthetic lethality was performed in this study. Synthetic lethality gene pairs were encoded via enrichment theory of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Advanced computational methods were adopted to build an optimal prediction model and extract important features.
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The low ionic conductivity at room temperature and poor dimensional stability at high temperature of polyethylene oxide (PEO)-based solid electrolytes greatly limit the development ...and utilization of solid polymer electrolytes (SPEs). To reconcile the contradiction between electrochemical performance and mechanical strength of PEO-based SPEs, a cross-linking structure with active –CH2CH2O- soft chains that doped with rigid segments is designed and prepared through a method of green ultraviolet irradiation without solvent. The obtained solid film shows a high ionic conductivity of 0.2 mS·cm−1 and an ionic transference number of 0.51 at room temperature. The activation energy value of 1.92 kJ·mol−1 gives evidence for a favorable migration mechanism of PTP-SPE. A combination of flexibility and strength can be realized by molecular structure design with a tensile elongation of 40%. The reversible overpotential in galvanostatic cycling over 500 h of a Li||Li symmetrical cell indicates that the compact PTP-SPE can inhibit the formation of lithium dendrites. This work provides a new strategy for designing high-performance composite solid electrolytes at room temperature.
Cancer stem cells (CSCs) are cancer‐initiating cells that are not only a source of tumorigenesis but also the cause of tumour progression, metastasis and therapy resistance. EBV‐associated gastric ...cancer (EBVaGC) is a distinct subtype of gastric cancer with unique clinicopathological and molecular features. However, whether CSCs exist in EBVaGC, and the tumorigenic mechanism of EBV, remains unclear. Here, NOD/SCID mice were injected subcutaneously with the EBVaGC cell line SNU719 and treated with 5‐fluorouracil weekly. Successive generations of xenografts yielded a highly malignant EBVaGC cell line, SNU‐4th, which displays properties of CSCs and mainly consists of CD44+CD24− cells. In SNU‐4th cells, an EBV‐encoded circRNA, ebv‐circLMP2A, expression increased and plays crucial roles in inducing and maintaining stemness phenotypes through targeting miR‐3908/TRIM59/p53 axis. Additionally, high expression of ebv‐circLMP2A is significantly associated with metastasis and poor prognosis in patients with EBVaGC. These findings not only provide evidence for the existence of CSCs in EBVaGC and elucidate the pathogenic mechanism of ebv‐circLMP2A in EBVaGC, but also provide a promising therapeutic target for EBVaGC.
Synopsis
The circRNA LMP2A produced by the Epstein‐Barr virus induces stemness of EBV‐associated gastric cancer cells by attenuating the tumor suppressive effect of the miR‐3908/TRIM59/p53 axis, thereby promoting metastasis and tumor progression.
Cells with properties of cancer stem cells were isolated form EBV‐associated gastric cancer (EBVaGC).
The levels of an EBV‐encoded circRNA (ebv‐circLMP2A) are significantly increased in EBVaGC.
ebv‐circLMP2A has crucial roles in inducing and maintaining cancer stemness in EBVaGC.
High expression of ebv‐circLMP2A is significantly associated with metastasis and poor prognosis in EBVaGC patients.
The circRNA LMP2A produced by the Epstein‐Barr virus induces stemness of EBV‐associated gastric cancer cells by attenuating the tumor suppressive effect of the miR‐3908/TRIM59/p53 axis, thereby promoting metastasis and tumor progression.
Adult neural stem cells (NSCs) are a group of multi‐potent, self‐renewing progenitor cells that contribute to the generation of new neurons and oligodendrocytes. Three subtypes of NSCs can be ...isolated based on the stages of the NSC lineage, including quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs). Although it is widely accepted that these three groups of NSCs play different roles in the development of the nervous system, their molecular signatures are poorly understood. In this study, we applied the Monte‐Carlo Feature Selection (MCFS) method to identify the gene expression signatures, which can yield a Matthews correlation coefficient (MCC) value of 0.918 with a support vector machine evaluated by ten‐fold cross‐validation. In addition, some classification rules yielded by the MCFS program for distinguishing above three subtypes were reported. Our results not only demonstrate a high classification capacity and subtype‐specific gene expression patterns but also quantitatively reflect the pattern of the gene expression levels across the NSC lineage, providing insight into deciphering the molecular basis of NSC differentiation.
The program of MCFS method produced six IF‐THEN rules for identification of different subtypes of NSCs. The performance of these IF‐THEN rules is quite good and these rules provide a more clear picture for the classification of each NSC.
Breast cancer is regarded worldwide as a severe human disease. Various genetic variations, including hereditary and somatic mutations, contribute to the initiation and progression of this disease. ...The diagnostic parameters of breast cancer are not limited to the conventional protein content and can include newly discovered genetic variants and even genetic modification patterns such as methylation and microRNA. In addition, breast cancer detection extends to detailed breast cancer stratifications to provide subtype-specific indications for further personalized treatment. One genome-wide expression-methylation quantitative trait loci analysis confirmed that different breast cancer subtypes have various methylation patterns. However, recognizing clinically applied (methylation) biomarkers is difficult due to the large number of differentially methylated genes. In this study, we attempted to re-screen a small group of functional biomarkers for the identification and distinction of different breast cancer subtypes with advanced machine learning methods. The findings may contribute to biomarker identification for different breast cancer subtypes and provide a new perspective for differential pathogenesis in breast cancer subtypes.
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Co3O4 has been extensively studied as an anode material for lithium-ion batteries (LIBs) because of its high theoretical capacity. However, during the charging-discharging processes, ...the issues of large volume change and low electric conductivity arise, which significantly limit the practical applications of Co3O4. To solve these issues, a Co3O4/CeO2 heterostructure derived from metal-organic frameworks (MOFs) was designed and synthesized through one-step microwave synthesis. Benefiting from the mesoporous structure and presence of hetero-components, Co3O4/CeO2 having the molar ratio of Co/Ce = 5:1 (denoted as 5Co3O4/CeO2) exhibits high reversible capacity and excellent cycling stability when used as an anode material for LIBs. Specifically, compared to a single-phase Co3O4 anode, which shows a capacity of 538.6 mAh/g after 100 cycles, 5Co3O4/CeO2 exhibits a higher capacity (1131.2 mAh/g at 100 mA/g). This study provides a novel strategy for using rare earth components to modify electrode materials.
This work investigated the metastable pitting corrosion mechanism of laser powder bed fusion (LPBF) produced Ti–6Al–4V. The passive films of samples were produced by potentiostatic polarization in ...NaCl solutions with different concentrations, and electrochemical measurements were employed to understand the influence of Cl- on the characteristics of passive films. The frequency of pitting nucleation and the pit dimension increase with increased Cl- concentration. The attack of Cl- promotes the dissolution of passive films. A higher density of oxygen vacancies is produced in passive film because of the ingressive Cl-, resulting in the condensation of voids and pitting corrosion.
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•A Ti-6Al-4V alloy was fabricated by laser powder bed fusion (LPBF) method.•Metastable pitting corrosion of the samples was investigated in NaCl solutions.•Cl- suppresses the formation of passive film formed on LPBF-produced sample.•The passive film has higher flux of oxygen vacancies in 10 wt% NaCl solution.•The condensation of cation-anion-vacancy associations triggers voids and pitting.
Targeted saturation mutagenesis of crop genes could be applied to produce genetic variants with improved agronomic performance. However, tools for directed evolution of plant genes, such as ...error-prone PCR or DNA shuffling, are limited
. We engineered five saturated targeted endogenous mutagenesis editors (STEMEs) that can generate de novo mutations and facilitate directed evolution of plant genes. In rice protoplasts, STEME-1 edited cytosine and adenine at the same target site with C > T efficiency up to 61.61% and simultaneous C > T and A > G efficiency up to 15.10%. STEME-NG, which incorporates the nickase Cas9-NG protospacer-adjacent motif variant, was used with 20 individual single guide RNAs in rice protoplasts to produce near-saturated mutagenesis (73.21%) for a 56-amino-acid portion of the rice acetyl-coenzyme A carboxylase (OsACC). We also applied STEME-1 and STEME-NG for directed evolution of the OsACC gene in rice and obtained herbicide resistance mutations. This set of two STEMEs will accelerate trait development and should work in any plants amenable to CRISPR-based editing.
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