Evolutionary Bioinformatics最新文献

筛选
英文 中文
Phylodynamic Investigation of Yellow Fever Virus Sheds New Insight on Geographic Dispersal Across Africa. 黄热病病毒的系统动力学研究为非洲的地理分布提供了新的视角。
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-12-17 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241309247
Babatunde Olanrewaju Motayo, Adewale Opayele, Paul Akiniyi Akinduti, Adedayo Omotayo Faneye, Isibor Patrick Omoregie
{"title":"Phylodynamic Investigation of Yellow Fever Virus Sheds New Insight on Geographic Dispersal Across Africa.","authors":"Babatunde Olanrewaju Motayo, Adewale Opayele, Paul Akiniyi Akinduti, Adedayo Omotayo Faneye, Isibor Patrick Omoregie","doi":"10.1177/11769343241309247","DOIUrl":"10.1177/11769343241309247","url":null,"abstract":"<p><strong>Background: </strong>Molecular epidemiology has shown the presence of four genotypes circulating across Africa, a paucity of data exists regarding phylogeography of the African Yellow fever (YF) genotypes. The need to fill this gap with spatiotemporal data from continuous YF outbreaks in Africa conceptualized this study; which aims to investigate the most recent transmission events and directional spread of yellow fever virus (YFV) using updated genomic sequence data.</p><p><strong>Methods: </strong>Yellow fever sequence data was utilized along with epidemiologic data from outbreaks in Africa, to analyze the case/fatality distribution and genetic diversity. Phylodynamic and phylogeographic were utilized to investigate ancestral history, virus population dynamics, and geographic dispersal of yellow fever across Africa.</p><p><strong>Results: </strong>There was a sharp increase in laboratory confirmed cases after year 2015, with Nigeria and the Democratic Republic of Congo having the highest numbers of cases. Phylogeny of the YF genotypes followed a previously reported pattern with distinct geographic clustering. Historical dispersal of YFV was discovered to have occurred from West into Central/East Africa, with recent introductions occurring in West Africa.</p><p><strong>Conclusions: </strong>We have shown the continuous circulation of YF in Africa, with distinct genotype distributions within the west and central African sub-regions. We have also shown the potential contribution of African genotypes, in the historical dispersal of yellow fever. We advocate for expanded and integrated molecular surveillance of YFV and other Arboviruses in Africa.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241309247"},"PeriodicalIF":1.7,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11650462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142848311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
In silico Characterization of a Hypothetical Protein (PBJ89160.1) from Neisseria meningitidis Exhibits a New Insight on Nutritional Virulence and Molecular Docking to Uncover a Therapeutic Target. 脑膜炎奈瑟菌假想蛋白(PBJ89160.1)的硅学特性分析为营养毒性和分子对接揭示治疗靶点提供了新的视角。
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-11-11 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241298307
Israt Jahan Asha, Shipan Das Gupta, Md Murad Hossain, Md Nur Islam, Nurun Nahar Akter, Mohammed Mafizul Islam, Shuvo Chandra Das, Dhirendra Nath Barman
{"title":"<i>In silico</i> Characterization of a Hypothetical Protein (PBJ89160.1) from <i>Neisseria meningitidis</i> Exhibits a New Insight on Nutritional Virulence and Molecular Docking to Uncover a Therapeutic Target.","authors":"Israt Jahan Asha, Shipan Das Gupta, Md Murad Hossain, Md Nur Islam, Nurun Nahar Akter, Mohammed Mafizul Islam, Shuvo Chandra Das, Dhirendra Nath Barman","doi":"10.1177/11769343241298307","DOIUrl":"https://doi.org/10.1177/11769343241298307","url":null,"abstract":"<p><strong>Objective: </strong><i>Neisseria meningitidis</i> is an encapsulated, diplococcus, kidney bean-shaped bacteria that causes bacterial meningitis. Our study hopes to advance our understanding of disease progression, the spread frequency of the bacteria in people, and the interactions between the bacteria and human body by identifying a functional protein, potentially serving as a target for meningococcal medicine in the future.</p><p><strong>Methods: </strong>A hypothetical protein HP (PBJ89160.1) from <i>N.</i> <i>meningitidis</i> was employed in this study for extensive structural and functional characterization. In the predictive functional role of HP, several constitutive bioinformatics approaches are applied, such as prediction of physiological properties, domain and motif family function, secondary and tertiary structure prediction, energy minimization, quality validation, docking, and ADMET analysis. To create the protein's three-dimensional (3D) structure, a template protein (PDB_ID: 3GXA) is used with 99% sequence identity by homology modeling technique with the HHpred server. To mitigate the pathogenicity associated with the HP function, it was docked with the natural ligand methionine and five other drug compounds like Verapamil, Loperamide, Thioridazine, Chlorpromazine, and Auranofine.</p><p><strong>Results: </strong>The protein is predicted to be acidic, soluble and hydrophilic by physicochemical properties analysis. Subcellular localization analysis demonstrated the protein to be periplasmic. The HP has an ATP-binding cassette transporter (also known as ABC transporter) involved in uptake of methionine (MetQ) that creates nutritional virulence in host. Energy minimization, multiple quality assessments, and validation value determination led to the conclusion that the HP model had a workable and acceptable quality. Following ADMET analysis and binding affinity assessments from the docking studies, Loperamide emerged as the most promising therapeutic compound, effectively inhibiting the ATP transporter activity of the HP.</p><p><strong>Conclusion: </strong>Comparative genomic analysis revealed that this protein is specific to <i>N. meningitidis</i> and has no homologs in human proteins, thereby identifying it as a potential target for therapeutic intervention.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241298307"},"PeriodicalIF":1.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11555745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142631739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative Phylogenetic Analysis and Protein Prediction Reveal the Taxonomy and Diverse Distribution of Virulence Factors in Foodborne Clostridium Strains. 系统发育比较分析和蛋白质预测揭示了食源性梭状芽孢杆菌菌株中病毒性因子的分类和多样化分布。
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-11-04 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241294153
Ming Zhang, Zhenzhen Yin
{"title":"Comparative Phylogenetic Analysis and Protein Prediction Reveal the Taxonomy and Diverse Distribution of Virulence Factors in Foodborne <i>Clostridium</i> Strains.","authors":"Ming Zhang, Zhenzhen Yin","doi":"10.1177/11769343241294153","DOIUrl":"10.1177/11769343241294153","url":null,"abstract":"<p><strong>Background: </strong><i>Clostridium botulinum</i> and <i>Clostridium perfringens</i>, 2 major foodborne pathogenic fusobacteria, have a variety of virulent protein types with nervous and enterotoxic pathogenic potential, respectively.</p><p><strong>Objective: </strong>The relationship between the molecular evolution of the 2 <i>Clostridium</i> genomes and virulence proteins was studied via a bioinformatics prediction method. The genetic stability, main features of gene coding and structural characteristics of virulence proteins were compared and analyzed to reveal the phylogenetic characteristics, diversity, and distribution of virulence factors of foodborne <i>Clostridium</i> strains.</p><p><strong>Methods: </strong>The phylogenetic analysis was performed via composition vector and average nucleotide identity based methods. Evolutionary distances of virulence genes relative to those of housekeeping genes were calculated via multilocus sequence analysis. Bioinformatics software and tools were used to predict and compare the main functional features of genes encoding virulence proteins, and the structures of virulence proteins were predicted and analyzed through homology modeling and a deep learning algorithm.</p><p><strong>Results: </strong>According to the diversity of toxins, genome evolution tended to cluster based on the protein-coding virulence genes. The evolutionary transfer distances of virulence genes relative to those of housekeeping genes in <i>C. botulinum</i> strains were greater than those in <i>C. perfringens</i> strains, and BoNTs and alpha toxin proteins were located extracellularly. The BoNTs have highly similar structures, but BoNT/A/B and BoNT/E/F have significantly different conformations. The beta2 toxin monomer structure is similar to but simpler than the alpha toxin monomer structure, which has 2 mobile loops in the N-terminal domain. The C-terminal domain of the CPE trimer forms a \"claudin-binding pocket\" shape, which suggests biological relevance, such as in pore formation.</p><p><strong>Conclusions: </strong>According to the genotype of protein-coding virulence genes, the evolution of <i>Clostridium</i> showed a clustering trend. The genetic stability, functional and structural characteristics of foodborne <i>Clostridium</i> virulence proteins reveal the taxonomy and diverse distribution of virulence factors.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241294153"},"PeriodicalIF":1.7,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142583424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence Matrix. 基于 VGGNet 卷积神经网络和灰度共现矩阵的预测自相互作用蛋白质的有效计算方法
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-10-21 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241292224
Dan-Hua Chu, Ji-Yong An, Xiao-Mei Nie
{"title":"An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence Matrix.","authors":"Dan-Hua Chu, Ji-Yong An, Xiao-Mei Nie","doi":"10.1177/11769343241292224","DOIUrl":"10.1177/11769343241292224","url":null,"abstract":"<p><strong>Introduction: </strong>Predicting Self-interacting proteins (SIPs) is a crucial area of research in predicting protein functions, as well as in understanding gene-disease and disease-drug associations. These interactions are integral to numerous cellular processes and play pivotal roles within cells. However, traditional methods for identifying SIPs through biological experiments are often expensive, time-consuming, and have long cycles. Therefore, the development of effective computational methods for accurately predicting SIPs is not only necessary but also presents a significant challenge.</p><p><strong>Results: </strong>In this research, we introduce a novel computational prediction technique, VGGNGLCM, which leverages protein sequence data. This method integrates the VGGNet deep convolutional neural network (VGGN) with the Gray-Level Co-occurrence Matrix (GLCM) to detect Self-interacting proteins associations. Specifically, we initially utilized Position Specific Scoring Matrix (PSSM) to capture protein evolutionary information and integrated key features from PSSM using GLCM. We then employed VGGNet as a predictive classifier, leveraging its capabilities for powerful learning and classification prediction. Subsequently, the extracted features were input into the VGGNet deep convolutional neural network to identify Self-interacting proteins. To evaluate the performance of the VGGNGLCM model, we conducted experiments using yeast and human datasets, achieving average accuracies of 95.68% and 97.72% respectively. Additionally, we compared the prediction performance of the VGGNet classifier with that of the Convolutional Neural Network (CNN) and the state-of-the-art Support Vector Machine (SVM) using the same feature extraction method. We also compared the prediction ability of VGGNGLCM with other existing approaches. The comparison results further demonstrate the superior performance of VGGNGLCM over other prediction models in this domain.</p><p><strong>Conclusion: </strong>The experimental verification further strengthens the evidence that VGGNGLCM is effective and robust compared to existing methods. It also highlights the high accuracy and robustness of the VGGNGLCM model in predicting Self-interacting proteins (SIPs). Consequently, we believe that the VGGNGLCM method serves as a valuable computational tool and can catalyze extensive bioinformatics research related to SIPs prediction.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241292224"},"PeriodicalIF":1.7,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11503870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comprehensive Profiling of Transcriptome and m6A Epitranscriptome Uncovers the Neurotoxic Effects of Yunaconitine on HT22 Cells. 转录组和 m6A 表转录组的全面分析揭示了滇乌头碱对 HT22 细胞的神经毒性作用
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-10-12 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241290461
Beian Lin, Jian Zhang, Mengting Chen, Xinyue Gao, Jiaxin Wen, Kun Tian, Yajiao Wu, Zekai Chen, Qiaomei Yang, An Zhu, Chunhong Du
{"title":"Comprehensive Profiling of Transcriptome and m6A Epitranscriptome Uncovers the Neurotoxic Effects of Yunaconitine on HT22 Cells.","authors":"Beian Lin, Jian Zhang, Mengting Chen, Xinyue Gao, Jiaxin Wen, Kun Tian, Yajiao Wu, Zekai Chen, Qiaomei Yang, An Zhu, Chunhong Du","doi":"10.1177/11769343241290461","DOIUrl":"10.1177/11769343241290461","url":null,"abstract":"<p><strong>Objective: </strong>To explore different mRNA transcriptome patterns and RNA N6-methyladenosine (m6A) alteration in yunaconitine (YA)-treated HT22 mouse hippocampal neuron, and uncover the role of abnormal mRNA expression and RNA m6A modification in YA-induced neurotoxicity.</p><p><strong>Methods: </strong>HT22 cells were treated with 0, 5, 10, and 50 μM of YA for 72 h to evaluate their viability and GSH content. Subsequently, mRNA-seq and MeRIP-seq analyses were performed on HT22 cells treated with 0 and 10 μM YA for 72 h, and molecular docking was used to simulate interactions between YA and differentially expressed m6A regulators. The mitochondrial membrane potential was examined using the JC-10 probe, and RT-qPCR was conducted to verify the expression levels of differentially expressed m6A regulatory factors, as well as to assess alterations in the mRNA expression levels of antioxidant genes.</p><p><strong>Results: </strong>YA treatment significantly reduced the viability of HT22 cells and decreased GSH content. The mRNA-seq analysis obtained 1018 differentially expressed genes, KEGG and GO enrichment results of differentially expressed genes mainly comprise the nervous system development, cholinergic synapse, response to oxidative stress, and mitochondrial inner membrane. A total of 7 differentially expressed m6A regulators were identified by MeRIP-seq. Notably, molecular docking results suggested a stable interaction between YA and most of the differentially expressed m6A regulators.</p><p><strong>Conclusion: </strong>This study showed that YA-induced HT22 cell damage was associated with the increased methylation modification level of target gene m6A and abnormal expression of m6A regulators.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241290461"},"PeriodicalIF":1.7,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11526304/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Label Transfer for Drug Disease Association in Three Meta-Paths 三种元路径中药物疾病关联的标签转移
IF 2.6 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-09-14 DOI: 10.1177/11769343241272414
Nam Anh Dao, Manh Hung Le, Xuan Tho Dang
{"title":"Label Transfer for Drug Disease Association in Three Meta-Paths","authors":"Nam Anh Dao, Manh Hung Le, Xuan Tho Dang","doi":"10.1177/11769343241272414","DOIUrl":"https://doi.org/10.1177/11769343241272414","url":null,"abstract":"The identification of potential interactions and relationships between diseases and drugs is significant in public health care and drug discovery. As we all know, experimenting to determine the drug-disease interactions is very expensive in both time and money. However, there are still many drug-disease associations that are still undiscovered and potential. Therefore, the development of computational methods to explore the relationship between drugs and diseases is very important and essential. Many computational methods for predicting drug-disease associations have been developed based on known interactions to learn potential interactions of unknown drug-disease pairs. In this paper, we propose 3 new main groups of meta-paths based on the heterogeneous biological network of drug-protein-disease objects. For each meta-path, we design a machine learning model, then an integrated learning method is formed by these models. We evaluated our approach on 3 standard datasets which are DrugBank, OMIM, and Gottlieb’s dataset. Experimental results demonstrate that the proposed method is better than some recent methods such as EMP-SVD, LRSSL, MBiRW, MPG-DDA, SCMFDD,. . . in some measures such as AUC, AUPR, and F1-score.","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"23 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Recombination Events Among SARS-CoV-2 Omicron Subvariants: Impact on Spike Interaction With ACE2 Receptor and Neutralizing Antibodies. SARS-CoV-2 Omicron 亚变体间的重组事件:尖峰与 ACE2 受体和中和抗体相互作用的影响
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-08-14 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241272415
Marwa Arbi, Marwa Khedhiri, Kaouther Ayouni, Oussema Souiai, Samar Dhouib, Nidhal Ghanmi, Alia Benkahla, Henda Triki, Sondes Haddad-Boubaker
{"title":"Recombination Events Among SARS-CoV-2 Omicron Subvariants: Impact on Spike Interaction With ACE2 Receptor and Neutralizing Antibodies.","authors":"Marwa Arbi, Marwa Khedhiri, Kaouther Ayouni, Oussema Souiai, Samar Dhouib, Nidhal Ghanmi, Alia Benkahla, Henda Triki, Sondes Haddad-Boubaker","doi":"10.1177/11769343241272415","DOIUrl":"10.1177/11769343241272415","url":null,"abstract":"<p><p>The recombination plays a key role in promoting evolution of RNA viruses and emergence of potentially epidemic variants. Some studies investigated the recombination occurrence among SARS-CoV-2, without exploring its impact on virus-host interaction. In the aim to investigate the burden of recombination in terms of frequency and distribution, the occurrence of recombination was first explored in 44 230 Omicron sequences among BQ subvariants and the under investigation \"ML\" (Multiple Lineages) denoted sequences, using 3seq software. Second, the recombination impact on interaction between the Spike protein and ACE2 receptor as well as neutralizing antibodies (nAbs), was analyzed using docking tools. Recombination was detected in 56.91% and 82.20% of BQ and ML strains, respectively. It took place mainly in spike and ORF1a genes. For BQ recombinant strains, the docking analysis showed that the spike interacted strongly with ACE2 and weakly with nAbs. The mutations S373P, S375F and T376A constitute a residue network that enhances the RBD interaction with ACE2. Thirteen mutations in RBD (S373P, S375F, T376A, D405N, R408S, K417N, N440K, S477N, P494S, Q498R, N501Y, and Y505H) and NTD (Y240H) seem to be implicated in immune evasion of recombinants by altering spike interaction with nAbs. In conclusion, this \"in silico\" study demonstrated that the recombination mechanism is frequent among Omicron BQ and ML variants. It highlights new key mutations, that potentially implicated in enhancement of spike binding to ACE2 (F376A) and escape from nAbs (RBD: F376A, D405N, R408S, N440K, S477N, P494S, and Y505H; NTD: Y240H). Our findings present considerable insights for the elaboration of effective prophylaxis and therapeutic strategies against future SARS-CoV-2 waves.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241272415"},"PeriodicalIF":1.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11325312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Single-cell RNA Sequencing Identifies Natural Kill Cell-Related Transcription Factors Associated With Age-Related Macular Degeneration. 单细胞 RNA 测序发现与老年性黄斑变性有关的天然杀伤细胞相关转录因子
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-08-14 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241272413
Yili Luo, Jianpeng Liu, Wangqiang Feng, Da Lin, Mengji Chen, Haihua Zheng
{"title":"Single-cell RNA Sequencing Identifies Natural Kill Cell-Related Transcription Factors Associated With Age-Related Macular Degeneration.","authors":"Yili Luo, Jianpeng Liu, Wangqiang Feng, Da Lin, Mengji Chen, Haihua Zheng","doi":"10.1177/11769343241272413","DOIUrl":"10.1177/11769343241272413","url":null,"abstract":"<p><strong>Background: </strong>Age-related Macular Degeneration (AMD) poses a growing global health concern as the leading cause of central vision loss in elderly people.</p><p><strong>Objection: </strong>This study focuses on unraveling the intricate involvement of Natural Killer (NK) cells in AMD, shedding light on their immune responses and cytokine regulatory roles.</p><p><strong>Methods: </strong>Transcriptomic data from the Gene Expression Omnibus database were utilized, employing single-cell RNA-seq analysis. High-dimensional weighted gene co-expression network analysis (hdWGCNA) and single-cell regulatory network inference and clustering (SCENIC) analysis were applied to reveal the regulatory mechanisms of NK cells in early-stage AMD patients. Machine learning models, such as random forests and decision trees, were employed to screen hub genes and key transcription factors (TFs) associated with AMD.</p><p><strong>Results: </strong>Distinct cell clusters were identified in the present study, especially the T/NK cluster, with a notable increase in NK cell abundance observed in AMD. Cell-cell communication analyses revealed altered interactions, particularly in NK cells, indicating their potential role in AMD pathogenesis. HdWGCNA highlighted the turquoise module, enriched in inflammation-related pathways, as significantly associated with AMD in NK cells. The SCENIC analysis identified key TFs in NK cell regulatory networks. The integration of hub genes and TFs identified <i>CREM, FOXP1, IRF1, NFKB2</i>, and <i>USF2</i> as potential predictors for AMD through machine learning.</p><p><strong>Conclusion: </strong>This comprehensive approach enhances our understanding of NK cell dynamics, signaling alterations, and potential predictive models for AMD. The identified TFs provide new avenues for molecular interventions and highlight the intricate relationship between NK cells and AMD pathogenesis. Overall, this study contributes valuable insights for advancing our understanding and management of AMD.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241272413"},"PeriodicalIF":1.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11325330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MicroRNA Transcriptomes Reveal Prevalence of Rare and Species-Specific Arm Switching Events During Zebrafish Ontogenesis. MicroRNA 转录组揭示斑马鱼本体发生过程中罕见和物种特异性臂切换事件的普遍性。
IF 1.7 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-07-24 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241263230
Arthur Casulli de Oliveira, Luiz Augusto Bovolenta, Lucas Figueiredo, Amanda De Oliveira Ribeiro, Beatriz Jacinto Alves Pereira, Talita Roberto Aleixo de Almeida, Vinicius Farias Campos, James G Patton, Danillo Pinhal
{"title":"MicroRNA Transcriptomes Reveal Prevalence of Rare and Species-Specific Arm Switching Events During Zebrafish Ontogenesis.","authors":"Arthur Casulli de Oliveira, Luiz Augusto Bovolenta, Lucas Figueiredo, Amanda De Oliveira Ribeiro, Beatriz Jacinto Alves Pereira, Talita Roberto Aleixo de Almeida, Vinicius Farias Campos, James G Patton, Danillo Pinhal","doi":"10.1177/11769343241263230","DOIUrl":"10.1177/11769343241263230","url":null,"abstract":"<p><p>In metazoans, microRNAs (miRNAs) are essential regulators of gene expression, affecting critical cellular processes from differentiation and proliferation, to homeostasis. During miRNA biogenesis, the miRNA strand that loads onto the RNA-induced Silencing Complex (RISC) can vary, leading to changes in gene targeting and modulation of biological pathways. To investigate the impact of these \"arm switching\" events on gene regulation, we analyzed a diverse range of tissues and developmental stages in zebrafish by comparing 5p and 3p arms accumulation dynamics between embryonic developmental stages, adult tissues, and sexes. We also compared variable arm usage patterns observed in zebrafish to other vertebrates including arm switching data from fish, birds, and mammals. Our comprehensive analysis revealed that variable arm usage events predominantly take place during embryonic development. It is also noteworthy that isomiR occurrence correlates to changes in arm selection evidencing an important role of microRNA distinct isoforms in reinforcing and modifying gene regulation by promoting dynamics switches on miRNA 5p and 3p arms accumulation. Our results shed new light on the emergence and coordination of gene expression regulation and pave the way for future investigations in this field.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241263230"},"PeriodicalIF":1.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11271096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Spatio-Temporal Expression Profiles of Silkworm Pseudogenes Provide Valuable Insights into Their Biological Roles. 蚕假基因的时空表达谱为了解其生物学作用提供了宝贵的视角
IF 2.6 4区 生物学
Evolutionary Bioinformatics Pub Date : 2024-06-14 eCollection Date: 2024-01-01 DOI: 10.1177/11769343241261814
Linrong Wan, Siyuan Su, Jinyun Liu, Bangxing Zou, Yaming Jiang, Beibei Jiao, Shaokuan Tang, Youhong Zhang, Cao Deng, Wenfu Xiao
{"title":"The Spatio-Temporal Expression Profiles of Silkworm Pseudogenes Provide Valuable Insights into Their Biological Roles.","authors":"Linrong Wan, Siyuan Su, Jinyun Liu, Bangxing Zou, Yaming Jiang, Beibei Jiao, Shaokuan Tang, Youhong Zhang, Cao Deng, Wenfu Xiao","doi":"10.1177/11769343241261814","DOIUrl":"10.1177/11769343241261814","url":null,"abstract":"<p><strong>Background: </strong>Pseudogenes are sequences that have lost the ability to transcribe RNA molecules or encode truncated but possibly functional proteins. While they were once considered to be meaningless remnants of evolution, recent researches have shown that pseudogenes play important roles in various biological processes. However, the studies of pseudogenes in the silkworm, an important model organism, are limited and have focused on single or only a few specific genes.</p><p><strong>Objective: </strong>To fill these gaps, we present a systematic genome-wide studies of pseudogenes in the silkworm.</p><p><strong>Methods: </strong>We identified the pseudogenes in the silkworm using the silkworm genome assemblies, transcriptome, protein sequences from silkworm and its related species. Then we used transcriptome datasets from 832 RNA-seq analyses to construct spatio-temporal expression profiles for these pseudogenes. Additionally, we identified tissue-specifically expressed and differentially expressed pseudogenes to further understand their characteristics. Finally, the functional roles of pseudogenes as lncRNAs were systematically analyzed.</p><p><strong>Results: </strong>We identified a total of 4410 pseudogenes, which were grouped into 4 groups, including duplications (DUPs), unitary pseudogenes (Unitary), processed pseudogenes (retropseudogenes, RETs), and fragments (FRAGs). The most of pseudogenes in the domestic silkworm were generated before the divergence of wild and domestic silkworm, however, the domestication may also involve in the accumulation of pseudogenes. These pseudogenes were clearly divided into 2 cluster, a highly expressed and a lowly expressed, and the posterior silk gland was the tissue with the most tissue-specific pseudogenes (199), implying these pseudogenes may be involved in the development and function of silkgland. We identified 3299 lncRNAs in these pseudogenes, and the target genes of these lncRNAs in silkworm pseudogenes were enriched in the egg formation and olfactory function.</p><p><strong>Conclusions: </strong>This study replenishes the genome annotations for silkworm, provide valuable insights into the biological roles of pseudogenes. It will also contribute to our understanding of the complex gene regulatory networks in the silkworm and will potentially have implications for other organisms as well.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"20 ","pages":"11769343241261814"},"PeriodicalIF":2.6,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11179516/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信