Integrative Biology最新文献

The kidney tubule consists of a single layer of epithelial cells supported by the tubular basement membrane (TBM), a thin layer of specialized extracellular matrix (ECM). The mechanical properties of the ECM are important for regulating a wide range of cell functions including proliferation, differentiation and cell survival. Increased ECM stiffness plays a role in promoting multiple pathological conditions including cancer, fibrosis and heart disease. How changes in TBM mechanics regulate tubular epithelial cell behavior is not fully understood. Here we introduce a cell culture system that utilizes in vivo-derived TBM to investigate cell-matrix interactions in kidney proximal tubule cells. Basement membrane mechanics was controlled using genipin, a biocompatibility crosslinker. Genipin modification resulted in a dose-dependent increase in matrix stiffness. Crosslinking had a marginal but statistically significant impact on the diffusive molecular transport properties of the TBM, likely due to a reduction in pore size. Both native and genipin-modified TBM substrates supported tubular epithelial cell growth. Cells were able to attach and proliferate to form confluent monolayers. Tubular epithelial cells polarized and assembled organized cell-cell junctions. Genipin modification had minimal impact on cell viability and proliferation. Genipin stiffened TBM increased gene expression of pro-fibrotic cytokines and altered gene expression for N-cadherin, a proximal tubular epithelial specific cell-cell junction marker. This work introduces a new cell culture model for cell-basement membrane mechanobiology studies that utilizes in vivo-derived basement membrane. We also demonstrate that TBM stiffening affects tubular epithelial cell function through altered gene expression of cell-specific differentiation markers and induced increased expression of pro-fibrotic growth factors.

Saponins are amphipathic glycosides with detergent properties present in vegetables. These compounds, when ingested, can cause difficulties in absorbing nutrients from food and even induce inflammatory processes in the intestine. There is already some evidence that saponins can be degraded by β-glucosidases of the GH3 family. In the present study, we evaluated, through computational tools, the possibility of a β-glucosidase (AMBGL17) obtained from a metagenomic analysis of the Amazonian soil, to catalytically interact with a saponin present in soybean. For this, the amino acid sequence of AMBGL17 was used in a phylogenetic analysis to estimate its origin and to determine its three-dimensional structure. The 3D structure of the enzyme was used in a molecular docking analysis to evaluate its interaction with soy saponin as a ligand. The results of the phylogenetic analysis showed that AMBGL17 comes from a microorganism of the phylum Chloroflexi, probably related to species of the order Aggregatinales. Molecular docking showed that soybean saponin can interact with the catalytic site of AMBGL17, with the amino acid GLY345 being important in this catalytic interaction, especially with a β-1,2 glycosidic bond present in the carbohydrate portion of saponin. In conclusion, AMBGL17 is an enzyme with interesting biotechnological potential in terms of mitigating the anti-nutritional and pro-inflammatory effects of saponins present in vegetables used for human and animal food.

Multi-phenotypic screening of multiple zebrafish larvae plays an important role in enhancing the quality and speed of biological assays. Many microfluidic platforms have been presented for zebrafish phenotypic assays, but multi-organ screening of multiple larvae, from different needed orientations, in a single device that can enable rapid and large-sample testing is yet to be achieved. Here, we propose a multi-phenotypic quadruple-fish microfluidic chip for simultaneous monitoring of heart activity and fin movement of 5-7-day postfertilization zebrafish larvae trapped in the chip. In each experiment, fin movements of four larvae were quantified in the dorsal view in terms of fin beat frequency (FBF). Positioning of four optical prisms next to the traps provided the lateral views of the four larvae and enabled heart rate (HR) monitoring. The device's functionality in chemical testing was validated by assessing the impacts of ethanol on heart and fin activities. Larvae treated with 3% ethanol displayed a significant drop of 13.2 and 35.8% in HR and FBF, respectively. Subsequent tests with cadmium chloride highlighted the novel application of our device for screening the effect of heavy metals on cardiac and respiratory function at the same time. Exposure to 5 $mu$g/l cadmium chloride revealed a significant increase of 8.2% and 39.2% in HR and FBF, respectively. The device can be employed to monitor multi-phenotypic behavioral responses of zebrafish larvae induced by chemical stimuli in various chemical screening assays, in applications such as ecotoxicology and drug discovery.

Wound healing is an intrinsic process directed towards the restoration of damaged or lost tissue. The development of a dressing material having the ability to control the multiple aspects of the wound environment would be an ideal strategy to improve wound healing. Though natural silk proteins, fibroin, and sericin have demonstrated tissue regenerative properties, the efficacy of bioengineered silk proteins on wound healing is seldom assessed. Furthermore, silk proteins sans contaminants, having low molecular masses, and combining with other bioactive factors can hasten the wound healing process. Herein, recombinant silk proteins, fibroin and sericin, and their fusions with cecropin B were evaluated for their wound-healing effects using in vivo rat model. The recombinant silk proteins demonstrated accelerated wound closure in comparison to untreated wounds and treatment with Povidone. Among all groups, the treatment with recombinant sericin-cecropin B (RSC) showed significantly faster healing, greater than 90% wound closure by Day 12 followed by recombinant fibroin-cecropin B (RFC) (88.86%). Furthermore, histological analysis and estimation of hydroxyproline showed complete epithelialization, neovascularization, and collagenisation in groups treated with recombinant silk proteins. The wound healing activity was further verified by in vitro scratch assay using HADF cells, where the recombinant silk proteins induced cell proliferation and cell migration to the wound area. Additionally, wound healing-related gene expression showed recombinant silk proteins stimulated the upregulation of EGF and VEGF and regulated the expression of TGF-β1 and TGF-β3. Our results demonstrated the enhanced healing effects of the recombinant silk fusion proteins in facilitating complete tissue regeneration with scar-free healing. Therefore, the recombinant silks and their fusion proteins have great potential to be developed as smart bandages for wound healing.

During chemotherapy, structural and mechanical changes in malignant cells have been observed in several cancers, including leukaemia and pancreatic and prostate cancer. Such cellular changes may act as physical biomarkers for chemoresistance and cancer recurrence. This study aimed to determine how exposure to paclitaxel affects the intracellular stiffness of human oesophageal cancer of South African origin in vitro. A human oesophageal squamous cell carcinoma cell line WHCO1 was cultured on glass substrates (2D) and in collagen gels (3D) and exposed to paclitaxel for up to 48 h. Cellular morphology and stiffness were assessed with confocal microscopy, visually aided morpho-phenotyping image recognition and mitochondrial particle tracking microrheology at 24 and 48 h. In the 2D environment, the intracellular stiffness was higher for the paclitaxel-treated than for untreated cells at 24 and 48 h. In the 3D environment, the paclitaxel-treated cells were stiffer than the untreated cells at 24 h, but no statistically significant differences in stiffness were observed at 48 h. In 2D, paclitaxel-treated cells were significantly larger at 24 and 48 h and more circular at 24 but not at 48 h than the untreated controls. In 3D, there were no significant morphological differences between treated and untreated cells. The distribution of cell shapes was not significantly different across the different treatment conditions in 2D and 3D environments. Future studies with patient-derived primary cancer cells and prolonged drug exposure will help identify physical cellular biomarkers to detect chemoresistance onset and assess therapy effectiveness in oesophageal cancer patients.

Bipolar disorder (BP) is a lifelong psychiatric condition, which often disrupts the daily life of the patients. It is characterized by unstable and periodic mood changes, which cause patients to display unusual shifts in mood, energy, activity levels, concentration and the ability to carry out day-to-day tasks. BP is a major psychiatric condition, and it is still undertreated. The causes and neural mechanisms of bipolar disorder are unclear, and diagnosis is still mostly based on psychiatric examination, furthermore the unstable character of the disorder makes diagnosis challenging. Identification of the molecular mechanisms underlying the disease may improve the diagnosis and treatment rates. Single nucleotide polymorphisms (SNP) and transcriptome profiles of patients were studied along with signalling pathways that are thought to be associated with bipolar disorder. Here, we present a computational approach that uses publicly available transcriptome data from bipolar disorder patients and healthy controls. Along with statistical analyses, data are integrated with a genome-scale metabolic model and protein-protein interaction network. Healthy individuals and bipolar disorder patients are compared based on their metabolic profiles. We hypothesize that energy metabolism alterations in bipolar disorder relate to perturbations in amino-acid metabolism and neuron-astrocyte exchange reactions. Due to changes in amino acid metabolism, neurotransmitters and their secretion from neurons and metabolic exchange pathways between neurons and astrocytes such as the glutamine-glutamate cycle are also altered. Changes in negatively charged (-1) KIV and KMV molecules are also observed, and it indicates that charge balance in the brain is highly altered in bipolar disorder. Due to this fact, we also hypothesize that positively charged lithium ions may stabilize the disturbed charge balance in neurons in addition to its effects on neurotransmission. To the best of our knowledge, our approach is unique as it is the first study using genome-scale metabolic models in neuropsychiatric research.

The Gram-positive bacterium Bacillus subtilis produces a diverse range of secondary metabolites with different structures and activities. Among them, bacilysin is an enzymatically synthesized dipeptide that consists of L-alanine and L-anticapsin. Previous research by our group has suggested bacilysin's role as a pleiotropic molecule in its producer, B. subtilis PY79. However, the nature of protein interactions in the absence of bacilysin has not been defined. In the present work, we constructed a protein-protein interaction subnetwork by using Omics Integrator based on our recent comparative proteomics data obtained from a bacilysin-silenced strain, OGU1. Functional enrichment analyses on the resulting networks pointed to certain putatively perturbed pathways such as citrate cycle, quorum sensing and secondary metabolite biosynthesis. Various molecules, which were absent from the experimental data, were included in the final network. We believe that this study can guide further experiments in the identification and confirmation of protein-protein interactions in B. subtilis.

Systems biology analysis of intracellular signaling networks has tremendously expanded our understanding of normal and diseased cell behaviors and has revealed paths to finding proper therapeutic molecular targets. When it comes to neurons in the human brain, analysis of intraneuronal signaling networks provides invaluable information on learning, memory and cognition-related disorders, as well as potential therapeutic targets. However, neurons in the human brain form a highly complex neural network that, among its many roles, is also responsible for learning, memory formation and cognition. Given the impairment of these processes in mental and psychiatric disorders, one can envision that analyzing interneuronal processes, together with analyzing intraneuronal signaling networks, can result in a better understanding of the pathology and, subsequently, more effective target discovery. In this paper, a hybrid model is introduced, composed of the long-term potentiation (LTP) interneuronal process and an intraneuronal signaling network regulating CREB. LTP refers to an increased synaptic strength over a long period of time among neurons, typically induced upon occurring an activity that generates high-frequency stimulations (HFS) in the brain, and CREB is a transcription factor known to be highly involved in important functions of the cognitive and executive human brain such as learning and memory. The hybrid LTP-signaling model is analyzed using a proposed molecular fault diagnosis method. It allows to study the importance of various signaling molecules according to how much they affect an intercellular phenomenon when they are faulty, i.e. dysfunctional. This paper is intended to suggest another angle for understanding the pathology and therapeutic target discovery by classifying and ranking various intraneuronal signaling molecules based on how much their faulty behaviors affect an interneuronal process. Possible relations between the introduced hybrid analysis and the previous purely intracellular analysis are investigated in the paper as well.

Cancer is a highly fatal disease without effective early-stage diagnosis and proper treatment. Along with the oncoproteins and oncometabolites, several organelles from cancerous cells are also emerging as potential biomarkers. Mitochondria isolated from cancer cells are one such biomarker candidates. Cancerous mitochondria exhibit different profiles compared with normal ones in morphology, genomic, transcriptomic, proteomic and metabolic landscape. Here, the possibilities of exploring such characteristics as potential biomarkers through single-cell omics and Artificial Intelligence (AI) are discussed. Furthermore, the prospects of exploiting the biomarker-based diagnosis and its futuristic utilization through circulatory tumor cell technology are analyzed. A successful alliance of circulatory tumor cell isolation protocols and a single-cell omics platform can emerge as a next-generation diagnosis and personalized treatment procedure.

The brain microvascular endothelial cells (ECs) play an important role in protecting the brain from hazardous pathogens. However, some viral pathogens can smartly modulate the endothelial pathways to gain entry inside the brain. Further, these viruses can cause endothelial dysfunction which could develop serious neurological ailments. Epstein-Barr virus (EBV), an oncogenic virus, has also been linked to various neurological disorders. The virus primarily infects epithelial and B cells, however, it also has a tendency to infect ECs and cause endothelial activation. However, the impact of EBV influence on ECs is still underexplored. Studying the early events of virus-mediated cellular modulation could help in understanding the virus' infection strategy or aftermath. Raman microspectroscopy has been widely utilized in biomedical sciences to decipher cellular changes. To understand the EBV-influenced EC modulation by studying intracellular biomolecular changes at early time points, we utilized the Raman microspectroscopy tool. We treated the ECs with EBV and acquired the Raman spectra at different time points (2, 4, 6, 12, 24 and 36 h) and different sites (nucleus and periphery) to check changes in Raman intensities associated with specific biomolecules. In the EBV-treated cells, the status of various biomolecules in terms of Raman intensities was observed to be altered compared with uninfected cells. Specifically, the cholesterol, polysaccharide, nucleotides, nucleic acid and proline moieties were altered at different time points. We also investigated the possible correlation between these molecules using molecular network analysis and observed various associated factors. These factors could be influenced by EBV to alter the associated biomolecular levels. Our study paves the pathway to study EBV infection in human brain microvascular ECs and highlights specific biomolecular alterations, which can be focused for further mechanistic investigations.