Variety Of Complex Biological Processes Research Articles

Fusing Multiple Biological Networks to Effectively Predict miRNA-disease Associations

Background: MicroRNAs (miRNAs) are a class of endogenous non-coding RNAs with about 22 nucleotides, and they play a significant role in a variety of complex biological processes. Many researches have shown that miRNAs are closely related to human diseases. Although the biological experiments are reliable in identifying miRNA-disease associations, they are timeconsuming and costly. Objective: Thus, computational methods are urgently needed to effectively predict miRNA-disease associations. Methods: In this paper, we proposed a novel method, BIRWMDA, based on a bi-random walk model to predict miRNA-disease associations. Specifically, in BIRWMDA, the similarity network fusion algorithm is used to combine the multiple similarity matrices to obtain a miRNA-miRNA similarity matrix and a disease-disease similarity matrix, then the miRNA-disease associations were predicted by the bi-random walk model. Results: To evaluate the performance of BIRWMDA, we ran the leave-one-out cross-validation and 5-fold cross-validation, and their corresponding AUCs were 0.9303 and 0.9223 ± 0.00067, respectively. To further demonstrate the effectiveness of the BIRWMDA, from the perspective of exploring disease-related miRNAs, we conducted three case studies of breast neoplasms, prostate neoplasms and gastric neoplasms, where 48, 50 and 50 out of the top 50 predicted miRNAs were confirmed by literature, respectively. From the perspective of exploring miRNA-related diseases, we conducted two case studies of hsa-mir-21 and hsa-mir-155, where 7 and 5 out of the top 10 predicted diseases were confirmed by literatures, respectively. Conclusion: The fusion of multiple biological networks could effectively predict miRNA-diseases associations. We expected BIRWMDA to serve as a biological tool for mining potential miRNAdisease associations.

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer

BackgroundExisting studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer.MethodsAn established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis.ResultsUsing canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR < 0.05). We then found that these 436 regulatory regions were associated with 74 potential target genes. After functional enrichment analysis, we observed that these potential target genes were enriched in cancer-associated pathways. We further demonstrated that using the gene expression signals and the epithelial tissue proportion extracted from this integration framework could stratify patient prognoses more accurately, outperforming predictions based on only omics or image features.ConclusionThis integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets.

Synthesis of Al3+-doping-TiO2 monodisperse microspheres and their application for phosphopeptides and glycopeptides enrichment

Glycosylation and phosphorylation are two of the most common and important post-translational modifications (PTMs) of proteins, which play critical roles in regulating a variety of complex biological processes and involvement in many diseases. Due to the low abundance of phosphopeptides and glycopeptides, highly selective enrichment methods are crucial to the identification of protein phosphorylation and glycosylation by mass spectrometry (MS). Here, monodisperse uniform Al3+-doping-TiO2 mixed oxide microspheres were easily synthesized. The morphology was controlled by a sol-gel method, during the hydrothermal treatment. The obtained microspheres with uniform particle size distribution (about 1–2 μm)，high surface area and improved pore structures, were characterized by SEM, TEM, XRD and N2 adsorption-desorption isotherms. Al3+-doping-TiO2 was applied in enriching glycopeptides and phosphopeptides respectively or simultaneously by using different enrichment conditions, achieving selective enrichment of glycopeptides and phosphopeptides. 20 glycopeptides and 25 phosphopeptides enriched from the tryptic digest mixtures of human serum immunoglobulin G (IgG) and α-casein (molar ratio of 1:1) were obviously observed with greatly improved signal-to-noise (S/N) ratio. Meanwhile, the enrichment results of non-fat milk and human serum also show the enrichment selectivity from complex biological samples. This study will provide a novel insight for selective enrichment of glycopeptides and phosphopeptides in post-translational modification proteomics research.

Laser-based 3D bioprinting for spatial and size control of tumor spheroids and embryoid bodies

3D multicellular aggregates, and more advanced organotypic systems, have become central tools in recent years to study a wide variety of complex biological processes. Most notably, these model systems have become mainstream within oncology (multicellular tumor spheroids) and regenerative medicine (embryoid bodies) research. However, the biological behavior of these in vitro tissue surrogates is extremely sensitive to their aggregate size and geometry. Indeed, both of these geometrical parameters are key in producing pathophysiological gradients responsible for cellular and structural heterogeneity, replicating in vivo observations. Moreover, the fabrication techniques most widely used for producing these models lack the ability to accurately control cellular spatial location, an essential component for regulating homotypic and heterotypic cell signaling. Herein, we report on a 3D bioprinting technique, laser direct-write (LDW), that enables precise control of both spatial patterning and size of cell-encapsulating microbeads. The generated cell-laden beads are further processed into core-shelled structures, allowing for the growth and formation of self-contained, self-aggregating cells (e.g., breast cancer cells, embryonic stem cells). Within these structures we demonstrate our ability to produce multicellular tumor spheroids (MCTSs) and embryoid bodies (EBs) with well-controlled overall size and shape, that can be designed on demand. Furthermore, we investigated the impact of aggregate size on the uptake of a commonly employed ligand for receptor-mediated drug delivery, Transferrin, indicating that larger tumor spheroids exhibit greater spatial heterogeneity in ligand uptake. Taken together, these findings establish LDW as a versatile biomanufacturing platform for bioprinting and patterning core-shelled structures to generate size-controlled 3D multicellular aggregates. Statement of SignificanceMulticellular 3D aggregates are powerful in vitro models used to study a wide variety of complex biological processes, particularly within oncology and regenerative medicine. These tissue surrogates are fabricated using environments that encourage cellular self-assembly. However, specific applications require control of aggregate size and position to recapitulate key in vivo parameters (e.g., pathophysiological gradients and homotypic/heterotypic cell signaling). Herein, we demonstrate the ability to create and spatially pattern size-controlled embryoid bodies and tumor spheroids, using laser-based 3D bioprinting. Furthermore, we investigated the effect of tumor spheroid size on internalization of Transferrin, a common ligand for targeted therapy, finding greater spatial heterogeneity in our large aggregates. Overall, this technique offers incredible promise and flexibility for fabricating idealized 3D in vitro models.

Combining single molecule counting with bead-based multiplexing to quantify biological inflammation time course following skeletal muscle injury.

Bead-based analysis methods allow for the exploration of a variety of complex biological processes. In particular, these techniques can be applied to better understand how peripheral muscle injury contributes to systemic inflammation. Understanding how these two processes affect one another can give additional insight concerning how changes in inflammation effect readiness to perform in exercise and work environments. The present method sought to combine the strengths of bead-based multiplexing with the precision and low-end detection of single molecule counting (SMC) methods. We used performance of an extreme aerobic exercise session (i.e. half-marathon race) to cause a defined quantity of lower body muscle injury and a systemic inflammatory response lasting up to 24 h. Using a high-sensitivity, multiplex assay (Milliplex; Millipore-Sigma) we were able to identify 9 of 21 cytokines that were significantly elevated at either 4 or 24 h post half-marathon performance. Despite the known role of IL-1β, IL-6, and TNF-α in the pro-inflammatory response, they did not appear to change based on the multiplex analysis. We thus, conducted further analysis using an SMC assay and found increases in IL-1β, IL-6, and TNF-α at 4 h compared to 24 h post exercise. This method approach demonstrates how combining two common, bead-based protein assays can increase the amount of meaningful biological information that can be collected. We anticipate that this approach will be useful in a variety of inflammation-associated disease states.

SNMDA: A novel method for predicting microRNA-disease associations based on sparse neighbourhood.

miRNAs are a class of small noncoding RNAs that are associated with a variety of complex biological processes. Increasing studies have shown that miRNAs have close relationships with many human diseases. The prediction of the associations between miRNAs and diseases has thus become a hot topic. Although traditional experimental methods are reliable, they could only identify a limited number of associations as they are time‐consuming and expensive. Consequently, great efforts have been made to effectively predict reliable disease‐related miRNAs based on computational methods. In this study, we present a novel approach to predict the potential microRNA‐disease associations based on sparse neighbourhood. Specifically, our method takes advantage of the sparsity of the miRNA‐disease association network and integrates the sparse information into the current similarity matrices for both miRNAs and diseases. To demonstrate the utility of our method, we applied global LOOCV, local LOOCV and five‐fold cross‐validation to evaluate our method, respectively. The corresponding AUCs are 0.936, 0.882 and 0.934. Three types of case studies on five common diseases further confirm the performance of our method in predicting unknown miRNA‐disease associations. Overall, results show that SNMDA can predict the potential associations between miRNAs and diseases effectively.

Ultrathin Au nanowires assisted magnetic graphene-silica ZIC-HILIC composites for highly specific enrichment of N-linked glycopeptides

Protein glycosylation has been proven to participate in a variety of complex biological processes; however, the low abundance of glycopeptides in natural samples makes it essential to develop methods to isolate and enrich glycopeptides. In this study, a novel ultrathin Au nanowire assisted zwitterionic hydrophilic magnetic graphene oxide (GO-Fe3O4/SiO2/AuNWs/L-Cys) was synthesized with the good biocompatibility of GO, strong magnetic responses of Fe3O4, large surface area of ultrathin Au nanowires and excellent hydrophilicity of L-Cys via four simple and rapid steps. The ultrathin Au nanowires have a one-dimensional structure and were easily grafted with an abundant amount of L-Cys for the enrichment of glycopeptides. After the GO-Fe3O4/SiO2/AuNWs/L-Cys composites were applied to glycopeptide enrichment, 26 glycopeptides from a human IgG digest could be identified, with a detection limit as low as 10 fmol. Due to the abundant amount of grafted L-Cys, the composites also showed a large binding capacity (150 μg mg−1). Furthermore, the composites were applied for the analysis of real biological samples. A total of 793 glycopeptides from 467 glycoproteins were identified in three replicate analyses of 40 μg of mouse liver proteins. The results demonstrated the great potential of GO-Fe3O4/SiO2/AuNWs/L-Cys composites for the analysis of glycoproteins.

Monitoring in real-time focal adhesion protein dynamics in response to a discrete mechanical stimulus.

The adhesion of cells to the extracellular matrix is a hierarchical, force-dependent, multistage process that evolves at several temporal scales. An understanding of this complex process requires a precise measurement of forces and its correlation with protein responses in living cells. We present a method to quantitatively assess live cell responses to a local and specific mechanical stimulus. Our approach combines atomic force microscopy with fluorescence imaging. Using this approach, we evaluated the recruitment of adhesion proteins such as vinculin, focal adhesion kinase, paxillin, and zyxin triggered by applying forces in the nN regime to live cells. We observed in real time the development of nascent adhesion sites, evident from the accumulation of early adhesion proteins at the position where the force was applied. We show that the method can be used to quantify the recruitment characteristic times for adhesion proteins in the formation of focal complexes. We also found a spatial remodeling of the mature focal adhesion protein zyxin as a function of the applied force. Our approach allows the study of a variety of complex biological processes involved in cellular mechanotransduction.

17β-Estradiol regulates the first steps of skeletal muscle cell differentiation via ER-α-mediated signals

17beta-Estradiol (E(2)) mediates a wide variety of complex biological processes determining the growth and development of reproductive tract as well as nonreproductive tissues of male and female individuals. While E(2) effects on the reproductive system, bone, and cardiovascular system are quite well established, less is known about how it affects the physiology of other tissues. Skeletal muscle is a tissue that is expected to be E(2) responsive since both isoforms of estrogen receptor (ER-alpha and ER-beta) are expressed. Significant sex-related differences have been described in skeletal muscle, although the role played by E(2) and the mechanisms underlying it remain to be determined. Here, we demonstrate that E(2) increases the glucose transporter type 4 translocation at membranes as well as the expression of well-known differentiation markers of myogenesis (i.e., myogenin and myosin heavy chain) in rat myoblast cells (L6). These E(2)-induced effects require rapid extranuclear signals and the presence of ER-alpha, whereas no contribution of IGF-I receptor has been observed. In particular, ER-alpha-dependent Akt activation participates in regulating the first step of myogenic differentiation. Moreover, both receptors mediate the E(2)-induced activation of p38, which, in turn, affects the expression of myogenin and myosin heavy chain. All together, these data indicate that E(2) should be included in the list of skeletal muscle trophic factors.

Structural specificity of heparin binding in the fibroblast growth factor family of proteins.

Heparin and heparan sulfate glycosaminoglycans (HSGAGs) mediate a wide variety of complex biological processes by specifically binding proteins and modulating their biological activity. One of the best studied model systems for protein-HSGAG interactions is the fibroblast growth factor (FGF) family of molecules, and recent observations have demonstrated that the specificity of a given FGF ligand binding to its cognate receptor (FGFR) is mediated by distinct tissue-specific HSGAG sequences. Although it has been known that sulfate and carboxylate groups in the HSGAG chain play a key role by interacting with basic residues on the proteins, there is little understanding of how these ionic interactions provide the necessary specificity for protein binding. In this study, using all of the available crystal structures of different FGFs and FGF-HSGAG complexes, we show that in addition to the ionic interactions, optimal van der Waals contact between the HSGAG oligosaccharide and the protein is also very important in influencing the specificity of FGF-HSGAG interactions. Although the overall helical structure is maintained in the FGF-bound HSGAG compared with unbound HSGAG, we observe distinct changes in the backbone torsion angles of the oligosaccharide chain induced upon protein binding. These changes result in local deviations in the helical axis that provide optimal ionic and van der Waals contact with the protein. A specific conformation and topological arrangement of the HSGAG-binding loops of FGF, on the other hand, impose structural constraints that induce the local deviations in the HSGAG structure, thereby enabling maximum contact between HSGAG and the protein.

Ancient origins of nitric oxide signaling in biological systems.

The simple gas nitric oxide (NO) controls a variety of complex biological processes, including blood pressure homeostasis, platelet aggregation, and transmission of signals by the nervous system. NO is also important for immune system function, playing key roles in the activation of macrophages and cellular defenses against microbial pathogens. Recent studies have revealed that some responses to NO are similar to those among very distantly related organisms; these findings suggest that many of the biological functions of NO have an evolutionarily ancient origin.