Evaluating the inhibitory priority of Bcl-xL to Bad, tBid and Bax by using live-cell imaging assay.

Molecular regulatory network among the B cell leukemia-2 (Bcl-2) family proteins is a research hotspot on apoptosis. The inhibitory priority of anti-apoptotic Bcl-2 family proteins (such as Bcl-xL) to pro-apoptotic Bcl-2 family proteins (such as Bad, tBid and Bax) determines the outcome of their interactions. Based on over-expression model system, we here evaluate the inhibitory priority of Bcl-xL to Bad, tBid and Bax by using live-cell imaging assay on cell viability. Fluorescence images of living cells co-expressing CFP-Bcl-xL and YFP-Bad or YFP-tBid or YFP-Bax showed that Bcl-xL markedly inhibited Bad/tBid/Bax-mediated apoptosis, revealing that Bcl-xL inhibits the proapoptotic function of Bad, tBid and Bax. In the case of equimolar co-expression of Bad and CFP-Bcl-xL, the inhibition of Bcl-xL on tBid/Bax mediate-apoptosis was completely relieved. Moreover, co-expression of tBid-P2A-CFP-Bcl-xL significantly relieved the inhibition of Bcl-xL on the pro-apoptotic ability Bax, suggesting that Bcl-xL preferentially inhibits the pro-apoptotic ability of Bad over tBid, subsequently to Bax.

Regulatory network analysis of transcription factors, microRNAs, target genes and host genes in human multiple myeloma.

In recent years, molecular biologists have achieved great advance in micro RNA (miRNA) and gene investigation about the pathogenesis of multiple myeloma (MM). Existing research data of the transcription factors (TFs) and miRNAs is disperse and unorganized, which prevents researchers from investigating the mechanism and analyze regulatory pathways of MM systematically. In our research, regulatory interactions among miRNAs, TFs, host genes and target genes were imported to construct regulatory networks at three levels, including the abnormally expressed network and the related network as well as the global network. The abnormally expressed network was primary investigated cause it was an experimentally validated topological network, and it systematically explained the regulatory mechanism of MM. Its outstanding significance lies in that if we correct each abnormally expressed gene and miRNA to normal expression level by transcriptional control adjustment, thus the whole genetic expression network will return to normal state, and MM may not relapse. Additionally, analyses and comparisons to upstream as well as downstream of abnormally expressed miRNAs and genes in three networks highlighted some important regulators and key signaling pathways. For example, STAT3 and hsa-miR-125b, PIAS3 and hsa-miR-21 respectively formed self adaptation feedback regulations. The current research proposed a novel perspective to systematically explained the regulatory mechanism of MM and may contribute to further research and therapy of carcinomas.

Live-cell super-resolution imaging unconventional dynamics and assemblies of nuclear pore complexes.

Super-resolution microscopy has promoted the development of cell biology, but imaging proteins with low copy numbers in cellular structures remains challenging. The limited number of designated proteins within nuclear pore complexes (NPCs) impedes continuous observation in live cells, although they are often used as a standard for evaluating various SR methods. To address this issue, we tagged POM121 with Halo-SiR and imaged it using structured illumination microscopy with sparse deconvolution (Sparse-SIM). Remarkably, POM121-SiR exhibited more than six-fold fluorescence intensity and four-fold enhanced contrast compared to the same protein labeled with tandem-linked mCherry, while showing negligible photo-bleaching during SR imaging for 200 frames. Using this technique, we discovered various types of NPCs, including ring-like and cluster-like structures, and observed dynamic remodeling along with the sequential appearance of different Nup compositions. Overall, Halo-SiR with Sparse-SIM is a potent tool for extended SR imaging of dynamic structures of NPCs in live cells, and it may also help visualize proteins with limited numbers in general.

Superresolution live-cell imaging reveals that the localization of TMEM106B to filopodia in oligodendrocytes is compromised by the hypomyelination-related D252N mutation.

Hypomyelination leukodystrophies constitute a group of heritable white matter disorders exhibiting defective myelin development. Initially identified as a lysosomal protein, the TMEM106B D252N mutant has recently been associated with hypomyelination. However, how lysosomal TMEM106B facilitates myelination and how the D252N mutation disrupts that process are poorly understood. We used superresolution Hessian structured illumination microscopy (Hessian-SIM) and spinning disc-confocal structured illumination microscopy (SD-SIM) to find that the wild-type TMEM106B protein is targeted to the plasma membrane, filopodia, and lysosomes in human oligodendrocytes. The D252N mutation reduces the size of lysosomes in oligodendrocytes and compromises lysosome changes upon starvation stress. Most importantly, we detected reductions in the length and number of filopodia in cells expressing the D252N mutant. PLP1 is the most abundant myelin protein that almost entirely colocalizes with TMEM106B, and coexpressing PLP1 with the D252N mutant readily rescues the lysosome and filopodia phenotypes of cells. Therefore, interactions between TMEM106B and PLP1 on the plasma membrane are essential for filopodia formation and myelination in oligodendrocytes, which may be sustained by the delivery of these proteins from lysosomes via exocytosis.

Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics.

Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR imaging. However, it suffers from an out-of-focus background that leads to reconstruction artifacts. Previous post hoc background suppression methods are prone to human bias, fail at densely labeled structures, and are nonlinear. Here, we propose a physical model-based Background Filtering method for living cell SR imaging combined with the 2D-SIM reconstruction procedure (BF-SIM). BF-SIM helps preserve intricate and weak structures down to sub-70 nm resolution while maintaining signal linearity, which allows for the discovery of dynamic actin structures that, to the best of our knowledge, have not been previously monitored.

Burkitt lymphoma-associated network construction and important network motif analysis.

Biological and medical researchers have discovered numerous transcription factors (TFs), microRNAs (miRNAs) and genes associated with Burkitt lymphoma (BL) through individual experiments; however, their regulatory mechanisms remain unclear. In the present study, BL-dysregulated and BL-associated networks were constructed to investigate these mechanisms. All data and regulatory associations were from known data resources and literature. The dysregulated network consisted of dysregulated TFs, miRNAs and genes, and partially determined the pathogenesis mechanisms underlying BL. The BL-associated network consisted of BL-associated TFs, miRNAs and genes. It has been indicated that the network motif consisted of TFs, miRNAs and genes serve potential functions in numerous biological processes within cancer. Two of the most studied network motifs are feedback loop (FBL) and feed-forward loop (FFL). The important network motifs were extracted, including the FBL motif, 3-nodes FFL motif and 4-nodes motif, from BL-dysregulated and BL-associated networks, and 10 types of motifs were identified from BL-associated network. Finally, 26/31 FBL motifs, 45/75 3-nodes FFL motifs and 54/94 4-nodes motifs were obtained from the dysregulated/associated networks. A total of four TFs (E2F1, NFKB1, E2F4 and TCF3) exhibit complicated regulation associations in BL-associated networks. The biological network does not demonstrate the dysregulated status for healthy people. When the individual becomes unwell, their biological network exhibits a dysregulated status. If the dysregulated status is regulated to a normal status by a number of medical methods, the diseases may be treated successfully. BL-dysregulated networks serve important roles in pathogenesis mechanisms underlying BL regulation of the dysregulated network, which may be an effective strategy that contributes to gene therapy for BL.

Network analysis of microRNAs, transcription factors, target genes and host genes in nasopharyngeal carcinoma.

Numerous studies on the morbidity of nasopharyngeal carcinoma (NPC) have identified several genes, microRNAs (miRNAs or miRs) and transcription factors (TFs) that influence the pathogenesis of NPC. However, summarizing all the regulatory networks involved in NPC is challenging. In the present study, the genes, miRNAs and TFs involved in NPC were considered as the nodes of the so-called regulatory network, and the associations between them were investigated. To clearly represent these associations, three regulatory networks were built seperately, namely, the differentially expressed network, the associated network and the global network. The differentially expressed network is the most important one of these three networks, since its nodes are differentially expressed genes whose mutations may lead to the development of NPC. Therefore, by modifying the aberrant expression of those genes that are differentially expressed in this network, their dysregulation may be corrected and the tumorigenesis of NPC may thus be prevented. Analysis of the aforementioned three networks highlighted the importance of certain pathways, such as self-adaptation pathways, in the development of NPC. For example, cyclin D1 (CCND1) was observed to regulate Homo sapiens-miR-20a, which in turn targeted CCND1. The present study conducted a systematic analysis of the pathogenesis of NPC through the three aforementioned regulatory networks, and provided a theoretical model for biologists. Future studies are required to evaluate the influence of the highlighted pathways in NPC.

Analysis of microRNA and gene networks in human chronic myelogenous leukemia.

Molecular biologists have identified a number of genes and microRNAs (miRs) associated with chronic myelogenous leukemia (CML). However, their underlying mechanisms in CML remain unclear. In the present study, three regulatory networks of genes and miRs were constructed to elucidate the underlying mechanisms of CML. The first network was the experimentally validated network of miRs and genes. The second was the dysregulatory network of CML, consisting of dysregulated genes and miRs, contributing to the pathogenesis of CML. The third was the CML­associated network, consisting of CML­associated genes and miRs. In addition to dysregulated genes and miRs, the associated network includes non­dysregulated genes and miRs that contribute to prevention, diagnosis, metastasis and therapy of CML. Key pathways were extracted and compared to distinguish the similarities and differences between dysregulatory nodes among the three networks. V-myb avian myeloblastosis viral oncogene homolog and miR­155 were observed to form a feedback loop module in the dysregulatory network. Regulation of the dysregulatory network may present as a strategy for gene therapy of CML. The current study provides an improved understanding of the molecular mechanisms of, and a potential treatment strategy for, CML.

Network analysis of microRNAs, transcription factors, target genes and host genes in human anaplastic astrocytoma.

Numerous studies have investigated the roles played by various genes and microRNAs (miRNAs) in neoplasms, including anaplastic astrocytoma (AA). However, the specific regulatory mechanisms involving these genes and miRNAs remain unclear. In the present study, associated biological factors (miRNAs, transcription factors, target genes and host genes) from existing studies of human AA were combined methodically through the interactions between genes and miRNAs, as opposed to studying one or several. Three regulatory networks, including abnormally expressed, related and global networks were constructed with the aim of identifying significant gene and miRNA pathways. Each network is composed of three associations between miRNAs targeted at genes, transcription factors (TFs) regulating miRNAs and miRNAs located on their host genes. Among these, the abnormally expressed network, which involves the pathways of previously identified abnormally expressed genes and miRNAs, partially indicated the regulatory mechanism underlying AA. The network contains numerous abnormal regulation associations when AA emerges. By modifying the abnormally expressed network factors to a normal expression pattern, the faulty regulation may be corrected and tumorigenesis of AA may be prevented. Certain specific pathways are highlighted in AA, for example PTEN which is targeted by miR-21 and miR-106b, regulates miR-25 which in turn targets TP53. PTEN and miR-21 have been observed to form feedback loops. Furthermore, by comparing and analyzing the pathway predecessors and successors of abnormally expressed genes and miRNAs in three networks, similarities and differences of regulatory pathways may be identified and proposed. In summary, the present study aids in elucidating the occurrence, mechanism, prevention and treatment of AA. These results may aid further investigation into therapeutic approaches for this disease.

Network analysis of microRNAs and genes in human osteosarcoma.

To date, numerous studies have suggested that microRNAs (miRNAs) and genes play key roles in osteosarcoma (OS); however, the majority of these studies have been conducted with a specific focus on either the genes or the miRNAs, which has made the regulatory mechanisms of OS difficult to decipher. The aim of the present study was to systematically investigate the elements [genes, miRNAs and transcription factors (TFs)] associated with the morbidity of OS and to explore the associations among these elements, instead of focusing on one or several elements. The scattered data were collected from existing studies of OS, and three regulatory networks (abnormally expressed, related and global) were constructed to explore OS at a macroscopic level. The abnormally expressed network showed the numerous incorrect data linkages that are present when OS emerges, making it useful as a map of the faults in OS. In theory, the correction of these errors could lead to the prevention and even cure of the disease. Unlike studies in which cancer networks have been formed based purely on gene data, the present study focused on genes and miRNAs, as well as the associations among them, to form the regulatory networks of OS. The constructed regulatory networks were shown to contain numerous self-adaptation associations, which may aid in the analysis of the pathogenesis of OS. By comparing and analyzing the similarities and differences, a number of important pathways were highlighted. A notable finding was the predicted TFs obtained by the P-Match method, which could be used to further study the pathogenesis of OS. In the present study, the mechanism of OS has been systematically analyzed and a theoretical foundation for the mechanism has been provided, which may assist the development of gene therapy targeting OS.

Regulatory Network of MicroRNAs, Host Genes, Target Genes and Transcription Factors in Human Esophageal Squamous Cell Carcinoma.

Abnormally expressed microRNAs (miRNAs) and genes have been found to play key roles in esophageal squamous cell carcinoma (ESCC), but little is known about the underlying mechanisms. The aim of this paper was to assess inter-relationships and the regulatory mechanisms of ESCC through a network-based approach. We built three regulatory networks: an abnormally expressed network, a related network and a global network. Unlike previous examples, containing information only on genes or miRNAs, the prime focus was on relationships. It is worth noting that abnormally expressed network emerged as a fault map of ESCC. Theoretically, ESCC might be treated and prevented by correcting the included errors. In addition, the predicted transcription factors (TFs) obtained by the P-match method also warrant further study. Our results may further guide gene therapy researchers in the study of ESCC.

microRNA and gene networks in human laryngeal cancer.

Genes and microRNAs (miRNAs) are considered to be key biological factors in human carcinogenesis. To date, considerable data have been obtained regarding genes and miRNAs in cancer; however, the regulatory mechanisms associated with the genes and miRNAs in cancer have yet to be fully elucidated. The aim of the present study was to use the key genes and miRNAs associated with laryngeal cancer (LC) to construct three regulatory networks (differentially expressed, LC-related and global). A network topology of the development of LC, involving 10 differentially expressed miRNAs and 55 differentially expressed genes, was obtained. These genes exhibited multiple identities, including target genes of miRNA, transcription factors (TFs) and host genes. The key regulatory interactions were determined by comparing the similarities and differences among the three networks. The nodes and pathways in LC, as well as the association between each pair of factors within the networks, such as TFs and miRNA, miRNA and target genes and miRNA and its host gene, were discussed. The mechanisms of LC involved certain key pathways featuring self-adaptation regulation and nodes without direct predecessors or successors. The findings of the present study have further elucidated the pathogenesis of LC and are likely to be beneficial for future research into LC.

Networks of micrornas and genes in acute lymphoblastic leukemia.

In the present study, three regulatory networks, including a network of differentially expressed factors, a related network and a global network, were constructed hierarchically in order to analyze the association between genes, micro (mi)RNAs and transcriptional factors (TFs) in a systematical approach, rather than focusing on only one or several miRNAs or TFs. By analyzing and comparing the similarities and differences among these three networks, a number of key pathways were highlighted. In addition, identifying the upstream and the downstream nodes, which were composed of differentially expressed genes and miRNAs in the networks provided assistance in identifying associations between circle­regulations or self­adaptation regulations among these elements. In the present study, the TP53 gene and the TP53 pathway were observed to be important in acute lymphoblastic leukemia (ALL). However, the predicted transcriptional factors, including EFKB1 and E2F1, which were found with self­adaptaion associations and certain abnormally expressed miRNAs in the network of differentially expressed factors, requires further examination in further investigations of the pathogenesis of ALL. The confirmation of these factors may be of significance to ALL.

The network of microRNAs, transcription factors, target genes and host genes in human renal cell carcinoma.

At present, scientists have performed numerous studies investigating the morbidity of renal cell carcinoma (RCC) in the genetic and microRNA (miRNA) fields, obtaining a substantial amount of knowledge. However, the experimentally validated data of genes, miRNA and transcription factors (TFs) cannot be found in a unified form, which makes it challenging to decipher the regulatory mechanisms. In the present study, the genes, miRNAs and TFs involved in RCC are regarded as elements in the regulatory network, and the present study therefore focuses on the association between each entity. Three regulatory networks were constructed hierarchically to indicate the regulatory association between the genes, miRNAs and TFs clearly, including the differentially expressed, associated and global networks. All the elements were macroscopically investigated in these networks, instead of only investigating one or several of them. The present study not only compared and analyzed the similarities and the differences between the three networks, but also systematically expounded the pathogenesis of RCC and supplied theoretical foundations for future gene therapy investigations. Following the construction of the three networks, certain important pathways were highlighted. The upstream and downstream element table of differentially expressed genes and miRNAs was listed, in which self-adaption associations and circle-regulations were identified. In future studies, the identified genes and miRNAs should be granted more attention.

Network analysis of microRNAs, genes and their regulation in mantle cell lymphoma.

The pathogenesis of mantle cell lymphoma, a special subtype of lymphoma that is invasive and indolent and has a median survival of 3 to 4 years, is still partially unexplained. Much research about genes and miRNAs has been conducted in recent years, but interactions and regulatory relations of genetic elements which may play a vital role in genesis of MCL have attracted only limited attention. The present study concentrated on regulatory relations about genes and miRNAs contributing to MCL pathogenesis. Numerous experimentally validated raw data were organized into three topology networks, comprising differentially expressed, associated and global examples. Comparison of similarities and dissimilarities of the three regulating networks, paired with the analysis of the interactions between pairs of elements in every network, revealed that the differentially expressed network illuminated the carcinogenicity mechanism of MCL and the related network further described the regulatory relations involved, including prevention, diagnosis, development and therapy. Three kinds of regulatory relations for host genes including miRNAs, miRNAs targeting genes and genes regulating miRNAs were concluded macroscopically. Regulation of the differentially expressed miRNAs was also analyzed, in terms of abnormal gene expression affecting the MCL pathogenesis. Special regulatory relations were uncovered. For example, auto-regulatory loops were found in the three topology networks, key pathways of the nodes being highlighted. The present study focused on a novel point of view revealing important influencing factors for MCL pathogenesis.

Regulatory network of microRNAs, target genes, transcription factors and host genes in endometrial cancer.

Genes and microRNAs (miRNAs) have important roles in human oncology. However, most of the biological factors are reported in disperse form which makes it hard to discover the pathology. In this study, genes and miRNAs involved in human endometrial cancer(EC) were collected and formed into regulatory networks following their interactive relations, including miRNAs targeting genes, transcription factors (TFs) regulating miRNAs and miRNAs included in their host genes. Networks are constructed hierarchically at three levels: differentially expressed, related and global. Among the three, the differentially expressed network is the most important and fundamental network that contains the key genes and miRNAs in EC. The target genes, TFs and miRNAs are differentially expressed in EC so that any mutation in them may impact on EC development. Some key pathways in networks were highlighted to analyze how they interactively influence other factors and carcinogenesis. Upstream and downstream pathways of the differentially expressed genes and miRNAs were compared and analyzed. The purpose of this study was to partially reveal the deep regulatory mechanisms in EC using a new method that combines comprehensive genes and miRNAs together with their relationships. It may contribute to cancer prevention and gene therapy of EC.

Systematical analysis of cutaneous squamous cell carcinoma network of microRNAs, transcription factors, and target and host genes.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNA molecules found in multicellular eukaryotes which are implicated in development of cancer, including cutaneous squamous cell carcinoma (cSCC). Expression is controlled by transcription factors (TFs) that bind to specific DNA sequences, thereby controlling the flow (or transcription) of genetic information from DNA to messenger RNA. Interactions result in biological signal control networks. MATERIALS AND METHODS: Molecular components involved in cSCC were here assembled at abnormally expressed, related and global levels. Networks at these three levels were constructed with corresponding biological factors in term of interactions between miRNAs and target genes, TFs and miRNAs, and host genes and miRNAs. Up/down regulation or mutation of the factors were considered in the context of the regulation and significant patterns were extracted. RESULTS: Participants of the networks were evaluated based on their expression and regulation of other factors. Sub-networks with two core TFs, TP53 and EIF2C2, as the centers are identified. These share self-adapt feedback regulation in which a mutual restraint exists. Up or down regulation of certain genes and miRNAs are discussed. Some, for example the expression of MMP13, were in line with expectation while others, including FGFR3, need further investigation of their unexpected behavior. CONCLUSIONS: The present research suggests that dozens of components, miRNAs, TFs, target genes and host genes included, unite as networks through their regulation to function systematically in human cSCC. Networks built under the currently available sources provide critical signal controlling pathways and frequent patterns. Inappropriate controlling signal flow from abnormal expression of key TFs may push the system into an incontrollable situation and therefore contributes to cSCC development.

MicroRNA and gene networks in human diffuse large B-cell lymphoma.

Molecular biologists have collected considerable data regarding the involvement of genes and microRNAs (miRNAs) in cancer. However the underlying mechanisms of cancer with regard to genes and miRNAs remain unclear. The aim of the present study was to evaluate diffuse large B-cell lymphoma (DLBCL) and construct regulatory networks of genes and miRNAs to gradually reveal the underlying mechanisms of DLBCL development. The first differential expression network that is presented is an experimentally validated network of miRNAs and genes. This network presents known biological regulatory associations among miRNAs and genes in the human body. The second network is a DLBCL differential expression network. Differentially expressed gene and miRNA data regarding DLBCL were collected and, based on the first network and the differentially expressed data, the second network was inferred, which demonstrates the irregular regulatory associations that may lead to the occurrence of DLBCL. The third network is a DLBCL-associated network. This network is comprised of non-differentially expressed genes and miRNAs that contribute to numerous DLBCL processes. The similarities and differences among the three networks were extracted and compared to distinguish key regulatory associations; furthermore, important signaling pathways in DLBCL were identified. The present study partially clarified the pathogenesis of DLBCL and provided an improved understanding of the underlying molecular mechanisms, as well as a potential treatment for DLBCL.

Construction and analysis of regulatory genetic networks in cervical cancer based on involved microRNAs, target genes, transcription factors and host genes.

Over recent years, genes and microRNA (miRNA/miR) have been considered as key biological factors in human carcinogenesis. During cancer development, genes may act as multiple identities, including target genes of miRNA, transcription factors and host genes. The present study concentrated on the regulatory networks consisting of the biological factors involved in cervical cancer in order to investigate their features and affect on this specific pathology. Numerous raw data was collected and organized into purposeful structures, and adaptive procedures were defined for application to the prepared data. The networks were therefore built with the factors as basic components according to their interacting associations. The networks were constructed at three levels of interdependency, including a differentially-expressed network, a related network and a global network. Comparisons and analyses were made at a systematic level rather than from an isolated gene or miRNA. Critical hubs were extracted in the core networks and notable features were discussed, including self-adaption feedback regulation. The present study expounds the pathogenesis from a novel point of view and is proposed to provide inspiration for further investigation and therapy.

Networks of MicroRNAs and genes in retinoblastomas.

Through years of effort, researchers have made notable progress in gene and microRNA fields about retinoblastoma morbidity. However, experimentally validated data for genes, microRNAs (miRNAs) and transcription factors (TFs) can only be found in a scattered form, which makes it difficult to conclude the relationship between genes and retinoblastoma systematically. In this study, we regarded genes, miRNAs and TFs as elements in the regulatory network and focused on the relationship between pairs of examples. In this way, we paid attention to all the elements macroscopically, instead of only researching one or several. To show regulatory relationships over genes, miRNAs and TFs clearly, we constructed 3 regulatory networks hierarchically, including a differentially expressed network, a related network and a global network, for analysis of similarities and comparison of differences. After construction of the three networks, important pathways were highlighted. We constructed an upstream and downstream element table of differentially expressed genes and miRNAs, in which we found self-adaption relations and circle-regulation. Our study systematically assessed factors in the pathogenesis of retinoblastoma and provided theoretical foundations for gene therapy researchers. In future studies, especial attention should be paid to the highlighted genes and miRNAs.