BMC Molecular and Cell Biology最新文献

{"title":"ESCRT machinery plays a role in microautophagy in yeast","authors":"S. Morshed, M. Tasnin, T. Ushimaru","doi":"10.21203/rs.3.rs-19822/v2","DOIUrl":"https://doi.org/10.21203/rs.3.rs-19822/v2","url":null,"abstract":"Background Microautophagy, which degrades cargos by direct lysosomal/vacuolar engulfment of cytoplasmic cargos, is promoted after nutrient starvation and the inactivation of target of rapamycin complex 1 (TORC1) protein kinase. In budding yeast, microautophagy has been commonly assessed using processing assays with green fluorescent protein (GFP)-tagged vacuolar membrane proteins, such as Vph1 and Pho8. The endosomal sorting complex required for transport (ESCRT) system is proposed to be required for microautophagy, because degradation of vacuolar membrane protein Vph1 was compromised in ESCRT-defective mutants. However, ESCRT is also critical for the vacuolar sorting of most vacuolar proteins, and hence reexamination of the involvement of ESCRT in microautophagic processes is required. Results Here, we show that the Vph1-GFP processing assay is unsuitable for estimating the involvement of ESCRT in microautophagy, because Vph1-GFP accumulated highly in the prevacuolar class E compartment in ESCRT mutants. In contrast, GFP-Pho8 and Sna4-GFP destined for vacuolar membranes via an alternative adaptor protein-3 (AP-3) pathway, were properly localized on vacuolar membranes in ESCRT-deficient cells. Nevertheless, microautophagic degradation of GFP-Pho8 and Sna4-GFP after TORC1 inactivation was hindered in ESCRT mutants, indicating that ESCRT is indeed required for microautophagy after nutrient starvation and TORC1 inactivation. Conclusions These findings provide evidence for the direct role of ESCRT in microautophagy induction.","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49423929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IMPARO: inferring microbial interactions through parameter optimisation.","authors":"Rajith Vidanaarachchi, Marnie Shaw, Sen-Lin Tang, Saman Halgamuge","doi":"10.1186/s12860-020-00269-y","DOIUrl":"10.1186/s12860-020-00269-y","url":null,"abstract":"<p><strong>Background: </strong>Microbial Interaction Networks (MINs) provide important information for understanding bacterial communities. MINs can be inferred by examining microbial abundance profiles. Abundance profiles are often interpreted with the Lotka Volterra model in research. However existing research fails to consider a biologically meaningful underlying mathematical model for MINs or to address the possibility of multiple solutions.</p><p><strong>Results: </strong>In this paper we present IMPARO, a method for inferring microbial interactions through parameter optimisation. We use biologically meaningful models for both the abundance profile, as well as the MIN. We show how multiple MINs could be inferred with similar reconstructed abundance profile accuracy, and argue that a unique solution is not always satisfactory. Using our method, we successfully inferred clear interactions in the gut microbiome which have been previously observed in in-vitro experiments.</p><p><strong>Conclusions: </strong>IMPARO was used to successfully infer microbial interactions in human microbiome samples as well as in a varied set of simulated data. The work also highlights the importance of considering multiple solutions for MINs.</p>","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":"21 Suppl 1","pages":"34"},"PeriodicalIF":2.8,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-020-00269-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38288771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IL6/sIL6R regulates TNFα-inflammatory response in synovial fibroblasts through modulation of transcriptional and post-transcriptional mechanisms","authors":"A. Valin, M. J. Del Rey, Cristina Municio, A. Usategui, M. Romero, Jesús Fernández-Felipe, J. Cañete, F. Blanco, Y. Ruano, G. Criado, J. Pablos","doi":"10.21203/rs.3.rs-32228/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-32228/v1","url":null,"abstract":"Introduction The clinical efficacy of specific interleukin-6 inhibitors has confirmed the central role of IL6 in rheumatoid arthritis (RA). However the local role of IL6, in particular in synovial fibroblasts (SF) as a direct cellular target to IL6/sIL6R signal is not well characterized. The purpose of the study was to characterize the crosstalk between TNFα and IL6/sIL6R signaling to the effector pro-inflammatory response of SF. Methods SF lines were stimulated with either TNFα, IL6/sIL6R, or both together, for the time and dose indicated for each experiment, and where indicated, cells were treated with inhibitors actinomycin D, adalimumab, ruxolitinib and cycloheximide. mRNA expression of cytokines, chemokines and matrix metalloproteases (MMPs) were analyzed by quantitative RT-PCR. Level of IL8/CXCL8 and CCL8 in culture supernatants was measured by ELISA. Mononuclear and polymorphonuclear cells migration assays were assessed by transwell using conditioned medium from SF cultures. Statistical analyses were performed as indicated in the corresponding figure legends and a p -value < 0.05 was considered statistically significant. Results The stimulation of SF with IL6/sIL6R and TNFα, cooperatively promotes the expression of mono- and lymphocytic chemokines such as IL6, CCL8 and CCL2, as well as matrix degrading enzymes such as MMP1, while inhibiting the induction of central neutrophil chemokines such as IL8/CXCL8. These changes in the pattern of chemokines expression resulted in reduced polymorphonuclear (PMN) and increased mononuclear cells (MNC) chemoattraction by SF. Mechanistic analyses of the temporal expression of genes demonstrated that the cooperative regulation mediated by these two factors is mostly induced through de novo transcriptional mechanisms activated by IL6/sIL6R. Furthermore, we also demonstrate that TNFα and IL6/sIL6R cooperation is partially mediated by the expression of secondary factors signaling through JAK/STAT pathways. Conclusions These results point out to a highly orchestrated response to IL6 in TNFα-induced SF and provide additional insights into the role of IL6/sIL6R in the context of RA, highlighting the contribution of IL6/sIL6R to the interplay of SF with other inflammatory cells.","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2020-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44184015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of tumor cell senescence in non-professional phagocytosis and cell-in-cell structure formation","authors":"Dorian Gottwald, F. Putz, Nora Hohmann, M. Büttner-Herold, M. Hecht, R. Fietkau, L. Distel","doi":"10.21203/rs.3.rs-29627/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-29627/v1","url":null,"abstract":"Background Non-professional phagocytosis is usually triggered by stimuli such as necrotic cell death. In tumor therapy, the tumors often disappear slowly and only long time after the end of therapy. Here, tumor therapy inactivates the cells by inducing senescence. Therefore, study focused whether senescence is a stimulus for non-professional phagocytosis or whether senescent cells themselves phagocytize non-professionally. Results Senescence was induced in cell lines by camptothecin and a phagocytosis assay was performed. In tissue of a cohort of 192 rectal cancer patients senescence and non-professional phagocytosis was studied by anti-histone H3K9me3 and anti-E-cadherin staining. Senescent fibroblasts and pancreas carcinoma cells phagocytize necrotic cells but are not phagocytized. In the tissue of rectal carcinoma, senescent cells can phagocytize and can be phagocytized. A high number of senescent cells and, at the same time, high numbers of non-professional phagocytizing cells in the rectal carcinoma tissue lead to an extremely unfavorable prognosis regarding overall survival. Conclusion Senescent cells can be non-professionally phagocytized and at the same time they can non-professionally phagocytize in vivo. In vitro experiments indicate that it is unlikely that senescence is a strong trigger for non-professional phagocytosis. Combined high rates of non-professional phagocytosis and high rates of senescence are an extremely poor prognostic factor for overall survival.","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2020-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48091722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix.","authors":"Abel Chandra,&nbsp;Alok Sharma,&nbsp;Abdollah Dehzangi,&nbsp;Daichi Shigemizu,&nbsp;Tatsuhiko Tsunoda","doi":"10.1186/s12860-019-0240-1","DOIUrl":"https://doi.org/10.1186/s12860-019-0240-1","url":null,"abstract":"<p><strong>Background: </strong>The biological process known as post-translational modification (PTM) is a condition whereby proteomes are modified that affects normal cell biology, and hence the pathogenesis. A number of PTMs have been discovered in the recent years and lysine phosphoglycerylation is one of the fairly recent developments. Even with a large number of proteins being sequenced in the post-genomic era, the identification of phosphoglycerylation remains a big challenge due to factors such as cost, time consumption and inefficiency involved in the experimental efforts. To overcome this issue, computational techniques have emerged to accurately identify phosphoglycerylated lysine residues. However, the computational techniques proposed so far hold limitations to correctly predict this covalent modification.</p><p><strong>Results: </strong>We propose a new predictor in this paper called Bigram-PGK which uses evolutionary information of amino acids to try and predict phosphoglycerylated sites. The benchmark dataset which contains experimentally labelled sites is employed for this purpose and profile bigram occurrences is calculated from position specific scoring matrices of amino acids in the protein sequences. The statistical measures of this work, such as sensitivity, specificity, precision, accuracy, Mathews correlation coefficient and area under ROC curve have been reported to be 0.9642, 0.8973, 0.8253, 0.9193, 0.8330, 0.9306, respectively.</p><p><strong>Conclusions: </strong>The proposed predictor, based on the feature of evolutionary information and support vector machine classifier, has shown great potential to effectively predict phosphoglycerylated and non-phosphoglycerylated lysine residues when compared against the existing predictors. The data and software of this work can be acquired from https://github.com/abelavit/Bigram-PGK.</p>","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":"20 Suppl 2","pages":"57"},"PeriodicalIF":2.8,"publicationDate":"2019-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-019-0240-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37474073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of novel mouse TLR9 agonists using a random forest approach.","authors":"Varun Khanna,&nbsp;Lei Li,&nbsp;Johnson Fung,&nbsp;Shoba Ranganathan,&nbsp;Nikolai Petrovsky","doi":"10.1186/s12860-019-0241-0","DOIUrl":"10.1186/s12860-019-0241-0","url":null,"abstract":"<p><strong>Background: </strong>Toll-like receptor 9 is a key innate immune receptor involved in detecting infectious diseases and cancer. TLR9 activates the innate immune system following the recognition of single-stranded DNA oligonucleotides (ODN) containing unmethylated cytosine-guanine (CpG) motifs. Due to the considerable number of rotatable bonds in ODNs, high-throughput in silico screening for potential TLR9 activity via traditional structure-based virtual screening approaches of CpG ODNs is challenging. In the current study, we present a machine learning based method for predicting novel mouse TLR9 (mTLR9) agonists based on features including count and position of motifs, the distance between the motifs and graphically derived features such as the radius of gyration and moment of Inertia. We employed an in-house experimentally validated dataset of 396 single-stranded synthetic ODNs, to compare the results of five machine learning algorithms. Since the dataset was highly imbalanced, we used an ensemble learning approach based on repeated random down-sampling.</p><p><strong>Results: </strong>Using in-house experimental TLR9 activity data we found that random forest algorithm outperformed other algorithms for our dataset for TLR9 activity prediction. Therefore, we developed a cross-validated ensemble classifier of 20 random forest models. The average Matthews correlation coefficient and balanced accuracy of our ensemble classifier in test samples was 0.61 and 80.0%, respectively, with the maximum balanced accuracy and Matthews correlation coefficient of 87.0% and 0.75, respectively. We confirmed common sequence motifs including 'CC', 'GG','AG', 'CCCG' and 'CGGC' were overrepresented in mTLR9 agonists. Predictions on 6000 randomly generated ODNs were ranked and the top 100 ODNs were synthesized and experimentally tested for activity in a mTLR9 reporter cell assay, with 91 of the 100 selected ODNs showing high activity, confirming the accuracy of the model in predicting mTLR9 activity.</p><p><strong>Conclusion: </strong>We combined repeated random down-sampling with random forest to overcome the class imbalance problem and achieved promising results. Overall, we showed that the random forest algorithm outperformed other machine learning algorithms including support vector machines, shrinkage discriminant analysis, gradient boosting machine and neural networks. Due to its predictive performance and simplicity, the random forest technique is a useful method for prediction of mTLR9 ODN agonists.</p>","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":"20 Suppl 2","pages":"56"},"PeriodicalIF":2.8,"publicationDate":"2019-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-019-0241-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37473788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of acid radical ion binding residues by K-nearest neighbors classifier.","authors":"Liu Liu,&nbsp;Xiuzhen Hu,&nbsp;Zhenxing Feng,&nbsp;Xiaojin Zhang,&nbsp;Shan Wang,&nbsp;Shuang Xu,&nbsp;Kai Sun","doi":"10.1186/s12860-019-0238-8","DOIUrl":"https://doi.org/10.1186/s12860-019-0238-8","url":null,"abstract":"<p><strong>Background: </strong>Proteins perform their functions by interacting with acid radical ions. Recently, it was a challenging work to precisely predict the binding residues of acid radical ion ligands in the research field of molecular drug design.</p><p><strong>Results: </strong>In this study, we proposed an improved method to predict the acid radical ion binding residues by using K-nearest Neighbors classifier. Meanwhile, we constructed datasets of four acid radical ion ligand (NO₂^-, CO₃^2-, SO₄^2-, PO₄^3-) binding residues from BioLip database. Then, based on the optimal window length for each acid radical ion ligand, we refined composition information and position conservative information and extracted them as feature parameters for K-nearest Neighbors classifier. In the results of 5-fold cross-validation, the Matthew's correlation coefficient was higher than 0.45, the values of accuracy, sensitivity and specificity were all higher than 69.2%, and the false positive rate was lower than 30.8%. Further, we also performed an independent test to test the practicability of the proposed method. In the obtained results, the sensitivity was higher than 40.9%, the values of accuracy and specificity were higher than 84.2%, the Matthew's correlation coefficient was higher than 0.116, and the false positive rate was lower than 15.4%. Finally, we identified binding residues of the six metal ion ligands. In the predicted results, the values of accuracy, sensitivity and specificity were all higher than 77.6%, the Matthew's correlation coefficient was higher than 0.6, and the false positive rate was lower than 19.6%.</p><p><strong>Conclusions: </strong>Taken together, the good results of our prediction method added new insights in the prediction of the binding residues of acid radical ion ligands.</p>","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":"20 Suppl 3","pages":"52"},"PeriodicalIF":2.8,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-019-0238-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37445803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recognizing ion ligand binding sites by SMO algorithm.","authors":"Shan Wang,&nbsp;Xiuzhen Hu,&nbsp;Zhenxing Feng,&nbsp;Xiaojin Zhang,&nbsp;Liu Liu,&nbsp;Kai Sun,&nbsp;Shuang Xu","doi":"10.1186/s12860-019-0237-9","DOIUrl":"https://doi.org/10.1186/s12860-019-0237-9","url":null,"abstract":"<p><strong>Background: </strong>In many important life activities, the execution of protein function depends on the interaction between proteins and ligands. As an important protein binding ligand, the identification of the binding site of the ion ligands plays an important role in the study of the protein function.</p><p><strong>Results: </strong>In this study, four acid radical ion ligands (NO₂^-,CO₃^2-,SO₄^2-,PO₄^3-) and ten metal ion ligands (Zn²⁺,Cu²⁺,Fe²⁺,Fe³⁺,Ca²⁺,Mg²⁺,Mn²⁺,Na⁺,K⁺,Co²⁺) are selected as the research object, and the Sequential minimal optimization (SMO) algorithm based on sequence information was proposed, better prediction results were obtained by 5-fold cross validation.</p><p><strong>Conclusions: </strong>An efficient method for predicting ion ligand binding sites was presented.</p>","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":"20 Suppl 3","pages":"53"},"PeriodicalIF":2.8,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-019-0237-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37446185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Binding of Brucella protein, Bp26, to select extracellular matrix molecules","authors":"Yasmin ElTahir, Amna Al-Araimi, Remya R. Nair, K. Autio, H. Tu, J. C. Leo, W. Al-Marzooqi, Eugene H. Johnson","doi":"10.1186/s12860-019-0239-7","DOIUrl":"https://doi.org/10.1186/s12860-019-0239-7","url":null,"abstract":"","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":"20 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-019-0239-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65674483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of high glucose conditions on the expansion and differentiation capabilities of mesenchymal stromal cells derived from rat endosteal niche","authors":"A. Al-Qarakhli, N. Yusop, R. Waddington, R. Moseley","doi":"10.1186/s12860-019-0235-y","DOIUrl":"https://doi.org/10.1186/s12860-019-0235-y","url":null,"abstract":"","PeriodicalId":9099,"journal":{"name":"BMC Molecular and Cell Biology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12860-019-0235-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46675373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}