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Results for “gene function”

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PubMed1992

Loss of gene function through rapid mitotic cycles in the Drosophila embryo.

The early developmental period in Drosophila is characterized by rapid mitotic divisions, when the body pattern becomes organized by a cascade of segmentation gene activity. During this process localized expression of the gap gene knirps (kni) is required to establish abdomen segmentation. The knirps-related gene (knrl) encodes a kni-homologous nuclear hormone receptor-like protein and shares the spatial patterns of kni expression. The two genes differ with respect to the size of their transcription units; kni contains 1 kilobase and knrl 19 kilobases of intron sequences. The consequence of this difference in intron size is that knrl cannot substitute for kni segmentation function, although it gains this ability when expressed from an intronless transgene. Here we show that the length of mitotic cycles provides a physiological barrier to transcript size, and is therefore a significant factor in controlling developmental gene activity during short 'phenocritical' periods. The required coordination of cycle length and gene size provides severe constraints towards the evolution of rapid development.

Amino Acid Sequence↗
PubMed1975

chlD gene function in molybdate activation of nitrate reductase.

chlD mutants of Escherichia coli lack active nitrate reductase but form normal levels of this enzyme when the medium is supplemented with 10-3 M molybdate. When chlD mutants were grown in unsupplemented medium and then incubated with molybdate in the presence of chloramphenicol, they formed about 5% the normal level of nitrate reductase. Some chlD mutants or the wild type grown in medium supplemented with tungstate accumulated an inactive protein which was electrophoretically identical to active nitrate reductase. Addition of molybdate to those cells in the presence of chloramphenicol resulted in the formation of fully induced levels of nitrate reductase. Two chlD mutants, including a deletion mutant, failed to accumulate the inactive protein and to form active enzyme under the same conditions. Insertion of 99-Mo into the enzyme protein paralleled activation; 185-W could not be demonstrated to be associated with the accumulated inactive protein. The rates of activation of nitrate reductase at varying molybdate concentrations indicated that the chlD gene product facilitates the activation of nitrate reductase at concentrations of molybdate found in normal growth media. At high concentrations, molybdate circumvented this function in chlD mutants and appeared to activate nitrate reductase by a mass action process. We conclude that the chlD gene plays two distinguishable roles in the formation of nitrate reductase in E. coli. It is involved in the accumulation of fully induced levels of the nitrate reductase protein in the cell membrane and it facilitates the insertion of molybdenum to form the active enzyme.

Cell-Free System↗
PubMed2025

Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models.

Reasoning about hypotheses and updating knowledge through empirical observations are central to scientific discovery. In this work, we applied logic-based machine learning methods to drive biological discovery by guiding experimentation. Genome-scale metabolic network models (GEMs) - comprehensive representations of metabolic genes and reactions - are widely used to evaluate genetic engineering of biological systems. However, GEMs often fail to accurately predict the behaviour of genetically engineered cells, primarily due to incomplete annotations of gene interactions. The task of learning the intricate genetic interactions within GEMs presents computational and empirical challenges. To efficiently predict using GEM, we describe a novel approach called Boolean Matrix Logic Programming (BMLP) by leveraging Boolean matrices to evaluate large logic programs. We developed a new system, [Formula: see text], which guides cost-effective experimentation and uses interpretable logic programs to encode a state-of-the-art GEM of a model bacterial organism. Notably, [Formula: see text] successfully learned the interaction between a gene pair with fewer training examples than random experimentation, overcoming the increase in experimental design space. [Formula: see text] enables rapid optimisation of metabolic models to reliably engineer biological systems for producing useful compounds. It offers a realistic approach to creating a self-driving lab for biological discovery, which would then facilitate microbial engineering for practical applications.

Active learning↗
PubMed1979

Replication and gene functions of the bacteriocinogenic plasmid CloDF13.

The replication and genetic constitution of plasmid CloDF13 was studied using mutants of CloDF13 obtained by NTG mutagenesis, insertion of the ampicillin transposon Tn901, or deletion of particular CloDF13 DNA regions. Analysis of the polypeptides encoded by these mutant plasmids enabled us to locate six genes on the CloDF13 physical map. These genes cover about 60% of the coding capacity of CloDF13. A large part of the CloDF13 genome (about 30%) is involved in the conjugal transfer of this plasmid. This transfer region codes for at least two polypeptides, polypeptide B (61,000 daltons) and C (24,000 daltons). Those CloDF13 DNA regions responsible for the synthesis of the cloacin protein and immunity protein were also mapped on the plasmid genome. In addition we were able, using a copy mutant of CloDF13, CloDF13-cop3, to locate those DNA sequences involved in interaction with male-specific RNA phages and bacteriophage P1. For replication of CloDF13, two regions are essential. One region, from 43% to 64%, affects the stability of CloDF13-cop3 plasmids. In the case of the CloDF13-cop3 mutant, deletion of this region results in the generation of multimeric plasmid molecules accompanied by an impaired segregation of plasmid DNA molecules to daughter cells. The second region, from about 1.8% to 11.5%, contains an origin of replication as well as well as DNA sequences involved in the control of CloDF13 replication. The replication of CloDF13 starts at about 3% on the CloDF13 physical map and proceeds unidirectionally counter-clockwise.

Bacterial Proteins↗
PubMed2025

Construction of a prognostic model for gastric cancer based on immune infiltration and microenvironment, and exploration of MEF2C gene function.

BACKGROUND: Advanced gastric cancer (GC) exhibits a high recurrence rate and a dismal prognosis. Myocyte enhancer factor 2c (MEF2C) was found to contribute to the development of various types of cancer. Therefore, our aim is to develop a prognostic model that predicts the prognosis of GC patients and initially explore the role of MEF2C in immunotherapy for GC. METHODS: Transcriptome sequence data of GC was obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and PRJEB25780 cohort for subsequent immune infiltration analysis, immune microenvironment analysis, consensus clustering analysis and feature selection for definition and classification of gene M and N. Principal component analysis (PCA) modeling was performed based on gene M and N for the calculation of immune checkpoint inhibitor (ICI) Score. Then, a Nomogram was constructed and evaluated for predicting the prognosis of GC patients, based on univariate and multivariate Cox regression. Functional enrichment analysis was performed to initially investigate the potential biological mechanisms. Through Genomics of Drug Sensitivity in Cancer (GDSC) dataset, the estimated IC50 values of several chemotherapeutic drugs were calculated. Tumor-related transcription factors (TFs) were retrieved from the Cistrome Cancer database and utilized our model to screen these TFs, and weighted correlation network analysis (WGCNA) was performed to identify transcription factors strongly associated with immunotherapy in GC. Finally, 10 patients with advanced GC were enrolled from Sun Yat-sen University Cancer Center, including paired tumor tissues, paracancerous tissues and peritoneal metastases, for preparing sequencing library, in order to perform external validation. RESULTS: Lower ICI Score was correlated with improved prognosis in both the training and validation cohorts. First, lower mutant-allele tumor heterogeneity (MATH) was associated with lower ICI Score, and those GC patients with lower MATH and lower ICI Score had the best prognosis. Second, regardless of the T or N staging, the low ICI Score group had significantly higher overall survival (OS) compared to the high ICI Score group. For its mechanisms, consistently, for Camptothecin, Doxorubicin, Mitomycin, Docetaxel, Cisplatin, Vinblastine, Sorafenib and Paclitaxel, all of the IC50 values were significantly lower in the low ICI Score group compared to the high ICI Score group. As a result, based on univariate and multivariate Cox regression, ICI Score was considered to be an independent prognostic factor for GC. And our Nomogram showed good agreement between predicted and actual probabilities. Based on CIBERSORT deconvolution analysis, there was difference of immune cell composition found between high and low ICI Score groups, probably affecting the efficacy of immunotherapy. Then, MEF2C, a tumor-related transcription factor, was screened out by WGCNA analysis. Higher MEF2C expression is significantly correlated with a worse OS. Moreover, its higher expression is also negatively correlated with tumor mutation burden (TMB) and microsatellite instability (MSI), but positively correlated with several immunosuppressive molecules, indicating MEF2C may exert its influence on tumor development by upregulating immunosuppressive molecules. Finally, based on transcriptome sequencing data on 10 paired tumor tissues from Sun Yat-sen University Cancer Center, MEF2C expression was significantly lower in paracancerous tissues compared to tumor tissues and peritoneal metastases, and it was also lower in tumor tissues compared to peritoneal metastases, indicating a potential positive association between MEF2C expression and tumor invasiveness. CONCLUSIONS: Our prognostic model can effectively predict outcomes and facilitate stratification GC patients, offering valuable insights for clinical decision-making. The identified transcription factor MEF2C can serve as a biomarker for assessing the efficacy of immunotherapy for GC.

Humans↗
PubMed2025

Exploring diagnostic m6A regulators in primary open-angle glaucoma: insight from gene signature and possible mechanisms by which key genes function.

PURPOSE: The purpose of this study was to interrogate the potential role of N6-methyladenosine (m6A) regulators in the process of trabecular meshwork (TM) tissue damage in patients with primary open-angle glaucoma (POAG). METHODS: Firstly, the expression profile of m6A regulators in TM tissues of POAG patients was comprehensively analyzed by bioinformatics analysis; Plasmid transfection and siRNA gene interference were used to enhance or weaken the expression levels of YTHDC2 in human trabecular meshwork cells (HTMCs); Cell migration ability was detected by transwell chamber assay; Immunofluorescence staining assay was used to evaluate the expression of extracellular matrix (ECM) related proteins. RESULTS: Through the analysis of GSE27276 database, 5 m6A regulators with different expression in POAG were screened out. The results of random forest model showed that these 5 m6A regulators exhibited diagnostic potential and were characteristic genes of POAG. All POAG samples could be effectively divided into two groups based on the expression levels of these 5 hub m6A regulators. Immune cell infiltration analysis indicated that the levels of activated CD8+ T cells and regulatory T cells were different in the two subtypes. HTMC oxidative stress cell model and TGF-β2 stimulation cell model were further constructed to verify the expression of the aforementioned hub m6A regulators, and it was found that YTHDC2 mRNA showed the same expression trend in both models. The silencing of YTHDC2 enhanced the migration ability of HTMCs and increased the synthesis ability of ECM. However, when YTHDC2ΔYTH, which lacks the YTH domain, is overexpressed in HTMCs, there is no significant change in the ECM synthesis ability. CONCLUSIONS: The differentially expressed m6A regulators in TM tissues may serve as potential diagnostic biomarkers for POAG. And, in HTMCs, the expression level of YTHDC2 mRNA was changed under oxidative stress or TGF-β2 intervention, and then exerted its regulation on cell migration and ECM synthesis capability through m6A modification, which may be an important part of the disease process of POAG.

Humans↗