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1.
Braz. j. biol ; 83: e243910, 2023. tab, graf
Article in English | MEDLINE, LILACS, VETINDEX | ID: biblio-1278525

ABSTRACT

Abstract Nucleotide excision repair (NER) acts repairing damages in DNA, such as lesions caused by cisplatin. Xeroderma Pigmentosum complementation group C (XPC) protein is involved in recognition of global genome DNA damages during NER (GG-NER) and it has been studied in different organisms due to its importance in other cellular processes. In this work, we studied NER proteins in Trypanosoma cruzi and Trypanosoma evansi, parasites of humans and animals respectively. We performed three-dimensional models of XPC proteins from T. cruzi and T. evansi and observed few structural differences between these proteins. In our tests, insertion of XPC gene from T. evansi (TevXPC) in T. cruzi resulted in slower cell growth under normal conditions. After cisplatin treatment, T. cruzi overexpressing its own XPC gene (TcXPC) was able to recover cell division rates faster than T. cruzi expressing TevXPC gene. Based on these tests, it is suggested that TevXPC (being an exogenous protein in T. cruzi) interferes negatively in cellular processes where TcXPC (the endogenous protein) is involved. This probably occurred due interaction of TevXPC with some endogenous molecules or proteins from T.cruzi but incapacity of interaction with others. This reinforces the importance of correctly XPC functioning within the cell.


Resumo O reparo por excisão de nucleotídeos (NER) atua reparando danos no DNA, como lesões causadas por cisplatina. A proteína Xeroderma Pigmentosum complementation group C (XPC) está envolvida no reconhecimento de danos pela via de reparação global do genoma pelo NER (GG-NER) e tem sido estudada em diferentes organismos devido à sua importância em outros processos celulares. Neste trabalho, estudamos proteínas do NER em Trypanosoma cruzi e Trypanosoma evansi, parasitos de humanos e animais, respectivamente. Modelos tridimensionais das proteínas XPC de T. cruzi e T. evansi foram feitos e observou-se poucas diferenças estruturais entre estas proteínas. Durante testes, a inserção do gene XPC de T. evansi (TevXPC) em T. cruzi resultou em crescimento celular mais lento em condições normais. Após o tratamento com cisplatina, T. cruzi superexpressando seu próprio gene XPC (TcXPC) foi capaz de recuperar as taxas de divisão celular mais rapidamente do que T. cruzi expressando o gene TevXPC. Com base nesses testes, sugere-se que TevXPC (sendo uma proteína exógena em T. cruzi) interfere negativamente nos processos celulares em que TcXPC (a proteína endógena) está envolvida. Isso provavelmente ocorreu pois TevXPC é capaz de interagir com algumas moléculas ou proteínas endógenas de T.cruzi, mas é incapaz de interagir com outras. Isso reforça a importância do correto funcionamento de XPC dentro da célula.


Subject(s)
Humans , Animals , Trypanosoma cruzi/genetics , Xeroderma Pigmentosum , DNA Damage/genetics , Computational Biology , DNA-Binding Proteins/genetics , DNA-Binding Proteins/metabolism , DNA Repair/genetics
2.
Medicina (Ribeirão Preto) ; 54(1)jul, 2021. fig.
Article in Portuguese | LILACS | ID: biblio-1353725

ABSTRACT

RESUMO: Modelo do estudo: Trata-se de um estudo experimental in vitro com abordagem computacional. Objetivo: Ana-lisar a existência de interação entre as drogas hidrofóbicas bezafibrato e hidroclorotiazida com a hemoglobina a fim de prever alterações na biodisponibilidade das drogas, bem como na função proteica. Metodologia: Testes de interação in vitro entre a hemoglobina bovina e bezafibrato ou hidroclorotiazida foram realizados por espectrofo-tometria; análises dos sítios de interação e extrapolações para a hemoglobina humana foram feitas por técnicas de bioinformática. Resultados: Os testes in vitro demonstraram diminuição de absorbância (k) em 405 nm igual a 8,75 x 10-4 min-1 para o bezafibrato e 6,25 x 10-4 min--1 para a hidroclorotiazida. A diminuição sugere interação das drogas com a hemoglobina, sendo que o bezafibrato parece interagir com afinidade ligeiramente maior. As análises in silico mostraram que as drogas se ligam à porção proteica da hemoglobina. A constante de afinidade de ligação obtida por ancoragem molecular para o bezafibrato com a hemoglobina bovina (-8,3 kcal/mol) corrobora com o valor experimental de k e com o maior número de interações observadas, em relação à hidroclorotiazida (-6,6 kcal/mol). O mesmo padrão é observado para a interação do bezafibrato (-7,6 kcal/mol) e da hidroclorotiazida (-6,7 kcal/mol) com a hemoglobina humana. Conclusão: As técnicas de espectrofotometria e bioinformática utilizadas sugerem a possibilidade de interação da hemoglobina com drogas de natureza hidrofóbica, como bezafibrato e hi-droclorotiazida, sendo que essa interação pode afetar a função normal da hemoglobina e alterar a farmacodinâmica e farmacocinética das drogas prejudicando sua eficiência terapêutica. (AU)


ABSTRACT: Study model: It is an in vitro experimental study with a computational approach. Objective: Analyze the presence of interaction between hydrophobic drugs bezafibrate and hydrochlorothiazide and hemoglobin to predict bioavailability changes as well as in the protein function. Metodology: The in vitro tests to evaluate the interaction between the bovine hemoglobin and bezafibrate and hydrochlorothiazide were perfomed by spectrophotometry; bioinformatic tools made interaction analysis and extrapolation for human hemoglobin. Results: The in vitro tests showed a decrease in the absorbance (k) at 405 nm equal to 8.75 x 10-4 min-1 for bezafibrate and 6.25 x 10-4 min-1 for hydrochlorothiazide. The decrease suggests an interaction between the drugs and hemoglobin, for bezafibrate this interaction seems to be stronger than hydrochlorothiazide. The in silico analysis showed that the drugs bind to the protein portion of the hemoglobin. The binding affinity constant obtained by molecular docking from bezafibrate and bovine hemoglobin (-8.3 Kcal/mol) sustain the experimental value of k and the greater number of interactions observed in relation to hydrochlorothiazide (-6.6 kcal/mol). The same pattern was observed for interaction of bezafibrate (-7.6 kcal/mol) and hydrochlorothiazide (-6.7 kcal/mol) with human hemoglobin. Conclusion: The spectrophotometry and bioinformatic methods suggested the possibility of hemoglobin interaction with hydrophobic drugs such as bezafibrate and hydrochlorothiazide; this interaction could affect the normal function of hemoglobin and change the pharmacodynamics and pharmacokinetics of drugs impairing their therapeutic efficiency. (AU)


Subject(s)
Spectrophotometry , Hemoglobins , Computational Biology , Molecular Docking Simulation
3.
Rev. cuba. inform. méd ; 13(1): e389, ene.-jun. 2021. tab, graf
Article in Spanish | LILACS, CUMED | ID: biblio-1251726

ABSTRACT

El presente trabajo aborda una experiencia en la implementación del aula invertida. Se emplea como estrategia de investigación un estudio de caso efectuado en la Universidad de las Ciencias Informáticas (UCI), de 16 estudiantes de Ingeniería en Bioinformática. En los resultados obtenidos, se confirma la relación entre la interactividad, motivación, trabajo y aprendizaje colaborativo y la evaluación formativa; además, que el diseño de actividades de aprendizaje y su evaluación en el modelo de aula invertida con el desarrollo de estrategias de estudiantes prosumidores de videos contribuye a que estos mejoren sus habilidades comunicativas e informáticas. Se concluye que la evaluación debe estimular el aprendizaje colaborativo, la interactividad, la tolerancia, la motivación y la responsabilidad en los entornos virtuales(AU)


This paper presents an experience in the flipped classroom teaching. A case study conducted at the University of Informatics Science (UCI, acronym in Spanish) with 16 Bioinformatics Engineering students. In the results obtained, the relationship between interactivity, motivation, work and collaborative learning and formative evaluation is confirmed; in addition, the design of learning activities and assessment in the flipped classroom model with the development of strategies for video prosumers students helps them to improve their communication and computer skills. It is concluded that evaluation should stimulate collaborative learning, interactivity, tolerance, motivation and responsibility in virtual environments(AU)


Subject(s)
Software , Computational Biology/methods
4.
Braz. j. med. biol. res ; 54(3): e10152, 2021. tab, graf
Article in English | LILACS | ID: biblio-1153522

ABSTRACT

The goal of this study was to identify potential transcriptomic markers in pediatric septic shock prognosis by an integrative analysis of multiple public microarray datasets. Using the R software and bioconductor packages, we performed a statistical analysis to identify differentially expressed (DE) genes in pediatric septic shock non-survivors, and further performed functional interpretation (enrichment analysis and co-expression network construction) and classification quality evaluation of the DE genes identified. Four microarray datasets (3 training datasets and 1 testing dataset, 252 pediatric patients with septic shock in total) were collected for the integrative analysis. A total of 32 DE genes (18 upregulated genes; 14 downregulated genes) were identified in pediatric septic shock non-survivors. Enrichment analysis revealed that those DE genes were strongly associated with acute inflammatory response to antigenic stimulus, response to yeast, and defense response to bacterium. A support vector machine classifier (non-survivors vs survivors) was also trained based on DE genes. In conclusion, the DE genes identified in this study are suggested as candidate transcriptomic markers for pediatric septic shock prognosis and provide novel insights into the progression of pediatric septic shock.


Subject(s)
Humans , Child , Shock, Septic/diagnosis , Shock, Septic/genetics , Transcriptome , Biomarkers , Computational Biology , Gene Expression Profiling , Microarray Analysis
5.
Braz. j. med. biol. res ; 54(11): e11363, 2021. graf
Article in English | LILACS | ID: biblio-1339445

ABSTRACT

Cervical cancer (CC) is the most common malignant tumor in females. Although persistent high-risk human papillomavirus (HPV) infection is a leading factor that causes CC, few women with HPV infection develop CC. Therefore, many mechanisms remain to be explored, such as aberrant expression of oncogenes and tumor suppressor genes. To identify promising prognostic factors and interpret the relevant mechanisms of CC, the RNA sequencing profile of CC was downloaded from the Cancer Genome Atlas and the Gene Expression Omnibus databases. The GSE63514 dataset was analyzed, and differentially expressed genes (DEGs) were obtained by weighted coexpression network analysis and the edgeR package in R. Fifty-three shared genes were mainly enriched in nuclear chromosome segregation and DNA replication signaling pathways. Through a protein-protein interaction network and prognosis analysis, the kinesin family member 14 (KIF14) hub gene was extracted from the set of 53 shared genes, which was overexpressed and associated with poor overall survival (OS) and disease-free survival (DFS) of CC patients. Mechanistically, gene set enrichment analysis showed that KIF14 was mainly enriched in the glycolysis/gluconeogenesis signaling pathway and DNA replication signaling pathway, especially in the cell cycle signaling pathway. RT-PCR and the Human Protein Atlas database confirmed that these genes were significantly increased in CC samples. Therefore, our findings indicated the biological function of KIF14 in cervical cancer and provided new ideas for CC diagnosis and therapies.


Subject(s)
Humans , Female , Uterine Cervical Neoplasms/genetics , Papillomavirus Infections , Gene Expression Regulation, Neoplastic , Cell Cycle/genetics , Kinesin/genetics , Oncogene Proteins , Disease-Free Survival , Computational Biology , Protein Interaction Maps
6.
Mem. Inst. Oswaldo Cruz ; 116: e200634, 2021. graf
Article in English | LILACS | ID: biblio-1154876

ABSTRACT

The availability of Trypanosomatid genomic data in public databases has opened myriad experimental possibilities that have contributed to a more comprehensive understanding of the biology of these parasites and their interactions with hosts. In this review, after brief remarks on the history of the Trypanosoma cruzi and Leishmania genome initiatives, we present an overview of the relevant contributions of genomics, transcriptomics and functional genomics, discussing the primary obstacles, challenges, relevant achievements and future perspectives of these technologies.


Subject(s)
Trypanosoma cruzi/genetics , Genome, Protozoan/genetics , Leishmania/genetics , Computational Biology , Genomics
7.
Braz. arch. biol. technol ; 64: e21210007, 2021. tab, graf
Article in English | LILACS | ID: biblio-1339314

ABSTRACT

Abstract Improving the accuracy of protein secondary structure prediction has been an important task in bioinformatics since it is not only the starting point in obtaining tertiary structure in hierarchical modeling but also enhances sequence analysis and sequence-structure threading to help determine structure and function. Herein we present a model based on DSPRED classifier, a hybrid method composed of dynamic Bayesian networks and a support vector machine to predict 3-state secondary structure information of proteins. We used the SCOPe (Structural Classification of Proteins-extended) database to train and test the model. The results show that DSPRED reached a Q3 accuracy rate of 82.36% when trained and tested using proteins from all SCOPe classes. We compared our method with the popular PSIPRED on the SCOPe test datasets and found that our method outperformed PSIPRED.


Subject(s)
Protein Structure, Secondary , Support Vector Machine , Artificial Intelligence , Computational Biology/methods
8.
Clinics ; 76: e2052, 2021. tab, graf
Article in English | LILACS | ID: biblio-1153974

ABSTRACT

OBJECTIVES: Single nucleotide variants (SNVs) are the most common type of genetic variation among humans. High-throughput sequencing methods have recently characterized millions of SNVs in several thousand individuals from various populations, most of which are benign polymorphisms. Identifying rare disease-causing SNVs remains challenging, and often requires functional in vitro studies. Prioritizing the most likely pathogenic SNVs is of utmost importance, and several computational methods have been developed for this purpose. However, these methods are based on different assumptions, and often produce discordant results. The aim of the present study was to evaluate the performance of 11 widely used pathogenicity prediction tools, which are freely available for identifying known pathogenic SNVs: Fathmn, Mutation Assessor, Protein Analysis Through Evolutionary Relationships (Phanter), Sorting Intolerant From Tolerant (SIFT), Mutation Taster, Polymorphism Phenotyping v2 (Polyphen-2), Align Grantham Variation Grantham Deviation (Align-GVGD), CAAD, Provean, SNPs&GO, and MutPred. METHODS: We analyzed 40 functionally proven pathogenic SNVs in four different genes associated with differences in sex development (DSD): 17β-hydroxysteroid dehydrogenase 3 (HSD17B3), steroidogenic factor 1 (NR5A1), androgen receptor (AR), and luteinizing hormone/chorionic gonadotropin receptor (LHCGR). To evaluate the false discovery rate of each tool, we analyzed 36 frequent (MAF>0.01) benign SNVs found in the same four DSD genes. The quality of the predictions was analyzed using six parameters: accuracy, precision, negative predictive value (NPV), sensitivity, specificity, and Matthews correlation coefficient (MCC). Overall performance was assessed using a receiver operating characteristic (ROC) curve. RESULTS: Our study found that none of the tools were 100% precise in identifying pathogenic SNVs. The highest specificity, precision, and accuracy were observed for Mutation Assessor, MutPred, SNP, and GO. They also presented the best statistical results based on the ROC curve statistical analysis. Of the 11 tools evaluated, 6 (Mutation Assessor, Phanter, SIFT, Mutation Taster, Polyphen-2, and CAAD) exhibited sensitivity >0.90, but they exhibited lower specificity (0.42-0.67). Performance, based on MCC, ranged from poor (Fathmn=0.04) to reasonably good (MutPred=0.66). CONCLUSION: Computational algorithms are important tools for SNV analysis, but their correlation with functional studies not consistent. In the present analysis, the best performing tools (based on accuracy, precision, and specificity) were Mutation Assessor, MutPred, and SNPs&GO, which presented the best concordance with functional studies.


Subject(s)
Humans , Computational Biology , Mutation, Missense/genetics , Virulence , Polymorphism, Single Nucleotide , Sexual Development , Mutation
10.
São Paulo; s.n; 2021. 92 p. ilust, tabelas.
Thesis in Portuguese | LILACS, Inca | ID: biblio-1223738

ABSTRACT

Mutações somáticas não sinônimas podem iniciar a tumorigênese e, também, uma resposta citotóxica antitumoral. Com o desenvolvimento das tecnologias de sequenciamento, tornou-se possível identificar as mutações em todos os genes humanos e, consequentemente, as variantes que induzem uma resposta imune (neoantígenos), representando uma oportunidade para pacientes que possam se beneficiar de imunoterapias, mas também um desafio com a necessidade de várias camadas de informações e a integração computacional de vários tipos de dados. Neste trabalho, foi desenvolvido o pipeline de identificação de neoantígeno neo2P, o qual realiza a integração completa de todos os passos necessários para a detecção e neoantígenos e apresentou uma eficiência computacional superior de até seis vezes em comparação com outro método. Além disso, foi proposto um score para priorizaração das mutações somáticas a partir da distribuição dos níveis da expressão gênica de 9.679 pacientes de 32 projetos do TCGA, o qual apresentou um poder de discriminação (AUC) próximo ou superior a 0.7 na maioria das coortes avaliadas. O neo2P foi aplicado em um conjunto de dados de pacientes com melanoma e foram identificados aspectos adicionais da relação de neoantígenos e aspectos imunes, como a expressão de alguns genes marcadores que podem estar relacionados com a resposta ao tratamento. Adicionalmente, a carga de neoantígenos detectados pelo neo2P estratificou, de maneira significativa, pacientes respondedores (R) e não respondedores (NR) quando comparado com o marcador TMB


Somatic non-synonymous mutations can initiate tumorigenesis and, conversely, anti-tumor cytotoxic T cell (CTL) responses. With the development of next-generation sequencing, it has become feasible to detect mutation-derived neoantigens within exome and thereby predict potential neoantigens, which represents an opportunity to patients that may be treated with immunotherapies, but also a challenge due to multiple layers of information and a computational integration of several types of data. In this work, it was developed a neoantigen identification pipeline called neo2P, which integrates all the necessary steps involved for neoantigen detection and presented a six-times superior computational efficiency compared to another method. In addition, a score was proposed to prioritize somatic mutations based on the distribution of gene expression levels in 9,679 patients from 32 TCGA projects, which showed a stratification ability (AUC) close to or greater than 0.7 in most evaluated cohorts.neo2P was applied to a dataset of patients with melanoma and additional aspects of the relationship between neoantigens and immune aspects were identified, such as the expression of some marker genes that may be related to the treatment response. Additionally, the neoantigen load detected by neo2P significantly stratified responders (R) and non-responders (NR) patients when compared to the TMB marker


Subject(s)
Prognosis , Gene Expression , Computational Biology , Immunotherapy , Melanoma
11.
Article in English | WPRIM | ID: wpr-880615

ABSTRACT

OBJECTIVES@#To study the gene expression of adipose tissue CD14@*METHODS@#The data of GSE54350 were obtained from the public database of gene expression profiling. The data were pre-processed by Network Analyst, String 11.0, Cytoscape 3.7.1, and other analytical software. The differentially expressed genes were analyzed by gene ontology biological function and kyoto encycopedia of genes and genomes (KEGG) signaling pathway to establish differential gene protein interaction network, transcription factor-gene regulatory network, microRNA-gene regulatory network, environmental factors-gene regulatory network, and other interaction systems.@*RESULTS@#The gene expression pattern of CD14@*CONCLUSIONS@#The gene expression of adipose tissue CD14


Subject(s)
Adipose Tissue , Computational Biology , DNA-Binding Proteins , Diabetes Mellitus, Type 2/genetics , Gene Expression , Gene Expression Profiling , Gene Regulatory Networks , Humans , MicroRNAs/genetics , Muscle Proteins
12.
Article in Chinese | WPRIM | ID: wpr-887869

ABSTRACT

Objective To explore the function and mechanism of related genes in the occurrence and development of liver cancer, and the possibility of key genes as potential biomarkers and prognostic indicators for the treatment of liver cancer.Methods We selected 4 datasets(GSE57957, GSE121248, GSE36376 and GSE14520)from the GEO database.With


Subject(s)
Biomarkers, Tumor/genetics , Carrier Proteins , Computational Biology , Cytochrome P-450 CYP2E1 , Cytochrome P-450 CYP3A , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Glycoproteins , Humans , Liver Neoplasms/genetics , Prognosis , Protein Interaction Maps
13.
Chinese Journal of Biotechnology ; (12): 2836-2844, 2021.
Article in Chinese | WPRIM | ID: wpr-887846

ABSTRACT

It has been reported that ODB genes play an important role in homologous recombination-directed DNA repair, suggesting their potential applications in plant breeding. To analyze the expression characteristics of tobacco NtODB gene, the cDNA sequence of NtODB was obtained using in silico cloning technique. The physicochemical properties, signal peptide, and advanced structures of the predicted protein were analyzed using bioinformatics tools. The results showed that the NtODB gene has a 579-bp open reading frame which encodes a protein with 192 amino acid residues. The protein NtODB is predicted to be alkaline and hydrophilic. Real-time quantitative PCR showed that NtODB was constitutively expressed in different tissues. Subcellular localization showed that NtODB was mainly expressed in cell membrane and chloroplast. These results may help us to better understand and elucidate the roles of ODB genes in the homologous recombination-directed DNA repair.


Subject(s)
Amino Acid Sequence , Base Sequence , Cloning, Molecular , Computational Biology , Computer Simulation , DNA, Complementary , Phylogeny , Plant Breeding , Tobacco/genetics
14.
Article in Chinese | WPRIM | ID: wpr-880178

ABSTRACT

OBJECTIVE@#To analyze and predict the effect of coronavirus infection on hematopoietic system and potential intervention drugs, and explore their significance for coronavirus disease 2019 (COVID-19).@*METHODS@#The gene expression omnibus (GEO) database was used to screen the whole genome expression data related with coronavirus infection. The R language package was used for differential expression analysis and KEGG/GO enrichment analysis. The core genes were screened by PPI network analysis using STRING online analysis website. Then the self-developed apparent precision therapy prediction platform (EpiMed) was used to analyze diseases, drugs and related target genes.@*RESULTS@#A database in accordance with the criteria was found, which was derived from SARS coronavirus. A total of 3606 differential genes were screened, including 2148 expression up-regulated genes and 1458 expression down-regulated genes. GO enrichment mainly related with viral infection, hematopoietic regulation, cell chemotaxis, platelet granule content secretion, immune activation, acute inflammation, etc. KEGG enrichment mainly related with hematopoietic function, coagulation cascade reaction, acute inflammation, immune reaction, etc. Ten core genes such as PTPRC, ICAM1, TIMP1, CXCR5, IL-1B, MYC, CR2, FSTL1, SOX1 and COL3A1 were screened by protein interaction network analysis. Ten drugs with potential intervention effects, including glucocorticoid, TNF-α inhibitor, salvia miltiorrhiza, sirolimus, licorice, red peony, famciclovir, cyclosporine A, houttuynia cordata, fluvastatin, etc. were screened by EpiMed plotform.@*CONCLUSION@#SARS coronavirus infection can affect the hematopoietic system by changing the expression of a series of genes. The potential intervention drugs screened on these grounds are of useful reference significance for the basic and clinical research of COVID-19.


Subject(s)
COVID-19 , Computational Biology , Follistatin-Related Proteins , Hematopoietic System , Humans , Pharmaceutical Preparations , SARS-CoV-2
15.
Article in Chinese | WPRIM | ID: wpr-880142

ABSTRACT

OBJECTIVE@#To analyze gene expression profile of T cell lymphoma Jurkat cell line treated with paclitaxel by computational biology based on next generation sequencing and to explore the possible molecular mechanism of paclitaxel resistance to T cell lymphoma at gene level.@*METHODS@#IC50 of paclitaxel on Jurkat cell line was determined by CCK-8 assay. Gene expression profile of Jurkat cells treated with paclitaxel was acquired by next generation sequencing technology. Gene microarray data related to human T cell lymphoma were screened from Gene Expression Omnibus (GEO) database (including 720 cases of T cell lymphoma and 153 cases of normal tissues). Combined with the sequencing data, differential expression genes (DEGs) were intersected and screened. DAVID database was used for enrichment analysis of GO function and KEGG pathway to determine and visualize functional entries of DEGs, and protein-protein interactions network of DEGs was drawn. The levels of gene expression were detected and verified by RT-qPCR.@*RESULTS@#CCK-8 results showed that the proliferation of Jurkat cells was inhibited by paclitaxel depended on the concentration apparently. Treated by paclitaxel for 48 h, P<0.05 and |log2(FC)|≥1 were used as filter criteria on the results of RNA Sequencing (RNA-Seq) and GeoChip, 351 DEGs were found from Jurkat cells, including 323 up-regulated genes and 28 down-regulated genes. The GO functional annotation and KEGG pathway enrichment analysis showed that the role of paclitaxel was mainly concentrated in protein heterodimerization activity, nucleosome assembly and transcriptional dysregulation in cancer, etc. The results of RT-qPCR were consistent with those of the sequencing analysis, which verified the reliability of this sequencing.@*CONCLUSION@#Paclitaxel can affect the proliferation and apoptosis of T-cell lymphoma by up-regulating JUN gene, orphan nuclear receptor NR4A family genes and histone family genes.


Subject(s)
Computational Biology , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , High-Throughput Nucleotide Sequencing , Humans , Lymphoma, T-Cell , Paclitaxel , Reproducibility of Results
16.
Article in Chinese | WPRIM | ID: wpr-879620

ABSTRACT

OBJECTIVE@#To construct the differential expression profile of microRNA (miRNA) in plasma of patients with type 2 diabetes mellitus (T2DM) and explore the possibility of using miRNA as the target for diagnosis and treatment of T2DM.@*METHODS@#Agilent miRNA microarray was used to determine the expression profiles of miRNA in the plasma of patients with T2DM (FC> 2, P< 0.05). The result was verified by real-time quantitative PCR (RT-qPCR). Candidate miRNA was analyzed by bioinformatic tools.@*RESULTS@#In total 122 differentially expressed miRNAs were identified. Among these, 14 were selected by multi-source intersection screening, which included 5 up-regulated genes and 9 down regulated genes. RT-qPCR showed that the expression of hsa-miR-185-5p and hsa-miR-328-5p have significantly increased in T2DM patients (P< 0.05). Bioinformatic analysis suggested that these miRNAs may be involved in the pathogenesis of T2DM through insulin secretion and PI3K-AKT signaling pathway.@*CONCLUSION@#Differential expression of hsa-miR-185-5p and hsa-miR-328-5p in the plasma may be closely associated with the pathogenesis of T2DM.


Subject(s)
Computational Biology , Diabetes Mellitus, Type 2/genetics , Humans , MicroRNAs/genetics , Phosphatidylinositol 3-Kinases , Signal Transduction
17.
Article in Chinese | WPRIM | ID: wpr-879095

ABSTRACT

The aim of this paper was to explore the key genes and pathogenesis of ischemic stroke(IS) by bioinformatics, and predict the potential traditional Chinese medicines for IS. Based on the gene-chip raw data set of GSE22255 from National Center of Biotechnology Information(NCBI), the article enrolled in 20 patients with ischemic stroke and 20 sex-and age-matched controls, and differentially expressed genes(DEGs) were screened based on R language software. The DAVID tool and R language software were used to perform gene ontology(GO) biological process enrichment analysis and Kyoto encyclopedia of genes and gnomes(KEGG) pathway enrichment analysis. The DEGs were imported into STRING to construct a protein-protein interaction network, and the Molecular Complexity Module(MCODE) plug-in of Cytoscape software was used to visualize and analyze the key functional modules. Moreover, the core genes and the medical ontology information retrieval platform(Coremine Medical) were mapped to each other to screen the traditional Chinese medicines and construct drug-active ingredient-target network. Compared with healthy controls, 14 DEGs were obtained, of which 12 genes were up-regulated and 2 genes were down-regulated. DEGs were mainly involved in immune response, inflammatory process, signal transduction, and cell proliferation regulation. The interleukin-17(IL-17), nuclear factor kappaB(NF-κB), tumor necrosis factor(TNF), nucleotide binding oligomerization domain(NOD)-like receptor and other signaling pathways were involved in KEGG pathway enrichment analysis. The key modules of the DEGs-encoding protein interaction network mainly focused on 7 genes of TNF, JUN, recombinant immediate early response 3(IER3), recombinant early growth response protein 1(EGR1), prostaglandin-endoperoxide synthase 2(PTGS2), C-X-C motif chemokine ligand 8(CXCL8) and C-X-C motif chemokine ligand 2(CXCL2), which were involved in biological processes widely such as neuroinflammation and immunity. TNF and JUN were the key nodes in this module, which might become potential biological markers for diagnosis and prognosis evaluation of IS. The potential traditional Chinese medicines for the treatment of IS includes Salviae Miltiorrhizae Radix et Rhizoma, Croci Stigma, Scutellariae Radix, and Cannabis Fructus. The occurrence of stroke was the result of multiple factors. Dysregulation of genes and pathways related to immune regulation and inflammation may be the key link for the development of IS. This study provided research direction and theoretical basis for further exploring the mechanism of action of traditional Chinese medicine in the treatment of IS and searching for potential drug targets.


Subject(s)
Brain Ischemia , China , Computational Biology , Gene Expression Profiling , Humans , Ischemic Stroke , Medicine, Chinese Traditional , Stroke/genetics
18.
Article in Chinese | WPRIM | ID: wpr-879091

ABSTRACT

NAC(NAM/ATAF/CUC) protein plays an important role in plant growth and development, secondary cell wall formation and stress response. In this study, based on the sequencing data of Angelica dahurica, the NAC family was systematically analyzed using bioinformatics methods and its expression pattern was analyzed. Studies showed that 75 candidate genes had been selected from the NAC transcription factor family of A. dahurica, with the protein size of 148-641, all of which were unstable hydrophilic proteins. Most NAC proteins were localized in the nucleus, and had complete NAC domain. Phylogenetic analysis of NAC family proteins of A.dahurica and Arabidopsis thaliana showed that among the 17 subfamilies, NAC members were unevenly distributed in each subfamily, indicating that the evolution of species is developing in multiple directions. Among them, ANAC063 subfamily contained no NAC sequence of A. dahurica, which might be due to the functional evolution of the species. Analysis of protein transmembrane structure and signal peptide showed that NAC transcription factor could carry out transmembrane transportation, but its signal peptide function had not been found. Expression analysis showed that most transcription factors responded to abiotic stress and hormones to varying degrees, and the effects of hormones were obvious, especially ABA and IAA. In different organs of A. dahurica, most members of the NAC family had higher expression in root phloem, followed by root xylem. This study lays a foundation for further research on the function of A. dahurica NAC transcription factor and for solving the biological problems of A. dahurica.


Subject(s)
Angelica , Computational Biology , Gene Expression Regulation, Plant , Phylogeny , Plant Proteins/metabolism , Stress, Physiological , Transcription Factors/metabolism
19.
Chinese Journal of Biotechnology ; (12): 1578-1602, 2021.
Article in Chinese | WPRIM | ID: wpr-878656

ABSTRACT

Since its birth in the early 1990s, metabolic engineering technology has gone 30 years rapid development. As one of the preferred chassis for metabolic engineering, S. cerevisiae cells have been engineered into microbial cell factories for the production of a variety of bulk chemicals and novel high value-added bioactive compounds. In recent years, synthetic biology, bioinformatics, machine learning and other technologies have also greatly contributed to the technological development and applications of metabolic engineering. This review summarizes the important technological development for metabolic engineering of S. cerevisiae in the past 30 years. Firstly, classical metabolic engineering tools and strategies were reviewed, followed by reviewing systems metabolic engineering and synthetic biology driven metabolic engineering approaches. The review is concluded with discussing future perspectives for metabolic engineering of S. cerevisiae in the light of state-of-the-art technological development.


Subject(s)
Computational Biology , Metabolic Engineering , Saccharomyces cerevisiae/genetics , Synthetic Biology
20.
Article in Chinese | WPRIM | ID: wpr-888106

ABSTRACT

The longevity mechanism of ginseng(Panax ginseng) is related to its strong meristematic ability. In this paper, this study used bioinformatic methods to identify the members of the ginseng TCP gene family in the whole genome and analyzed their sequence characteristics. Then, quantitative real-time fluorescent PCR was performed to analyze the TCP genes containing elements rela-ted to meristem expression in the taproots, fibrous roots, stems, and leaves. According to the data, this study further explored the expression specificity of TCP genes in ginseng tissues, which facilitated the dissection of the longevity mechanism of ginseng. The ginseng TCP members were identified and analyzed using PlantTFDB, ExPASy, MEME, PLANTCARE, TBtools, MEGA and DNAMAN. The results demonstrated that there were 60 TCP gene family members in ginseng, and they could be divided into two classes: Class Ⅰ and Class Ⅱ, in which the Class Ⅱ possessed two subclasses: CYC-TCP and CIN-TCP. The deduced TCP proteins in ginseng had the length of 128-793 aa, the isoelectric point of 4.49-9.84 and the relative molecular mass of 14.2-89.3 kDa. They all contained the basic helix-loop-helix(bHLH) domain. There are a variety of stress response-related cis-acting elements in the promoter regions of ginseng TCP genes, and PgTCP20-PgTCP24 contained the elements associated with meristematic expression. The transcription levels of PgTCP20-PgTCP24 were high in fibrous roots and leaves, but low in stems, indicating the tissue-specific expression of ginseng TCP genes. The Class Ⅰ TCP members which contained PgTCP20-PgTCP23, may be important regulators for the growth and development of ginseng roots.


Subject(s)
Computational Biology , Gene Expression Regulation, Plant , Multigene Family , Panax/metabolism , Phylogeny , Plant Proteins/metabolism , Transcription Factors/metabolism
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