Integrative Biology最新文献

Oxygen levels vary in the environment. Oxygen availability has a major effect on almost all organisms, and oxygen is far more than a substrate for energy production. However, less is known about related biological processes under hypoxic conditions and about the adaptations to changing oxygen concentrations. The yeast Saccharomyces cerevisiae can adapt its metabolism for growth under different oxygen concentrations and can grow even under anaerobic conditions. Therefore, we developed a microfluidic device that can generate serial, accurately controlled oxygen concentrations for single-cell studies of multiple yeast strains. This device can construct a broad range of oxygen concentrations, [O2] through on-chip gas-mixing channels from two gases fed to the inlets. Gas diffusion through thin polydimethylsiloxane (PDMS) can lead to the equilibration of [O2] in the medium in the cell culture layer under gas cover regions within 2 min. Here, we established six different and stable [O2] varying between ~0.1 and 20.9% in the corresponding layers of the device designed for multiple parallel single-cell culture of four different yeast strains. Using this device, the dynamic responses of different yeast transcription factors and metabolism-related proteins were studied when the [O2] decreased from 20.9% to serial hypoxic concentrations. We showed that different hypoxic conditions induced varying degrees of transcription factor responses and changes in respiratory metabolism levels. This device can also be used in studies of the aging and physiology of yeast under different oxygen conditions and can provide new insights into the relationship between oxygen and organisms. Integration, innovation and insight: Most living cells are sensitive to the oxygen concentration because they depend on oxygen for survival and proper cellular functions. Here, a composite microfluidic device was designed for yeast single-cell studies at a series of accurately controlled oxygen concentrations. Using this device, we studied the dynamic responses of various transcription factors and proteins to changes in the oxygen concentration. This study is the first to examine protein dynamics and temporal behaviors under different hypoxic conditions at the single yeast cell level, which may provide insights into the processes involved in yeast and even mammalian cells. This device also provides a base model that can be extended to oxygen-related biology and can acquire more information about the complex networks of organisms.

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area-either because of a smaller size or a change in beam orientation-have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

Breast cancer, more prevalent in women, often arises due to abnormalities in the MRN-checkpoint sensor genes (MRN-CSG), responsible for DNA damage detection and repair. Abnormality in this complex is due to the suppression of various effectors such as siRNAs, miRNAs, and transcriptional factors responsible for breast tumor progression. This study analyzed breast tumor samples (n = 60) and identified four common miRNAs (miR-1-3p, miR-210-3p, miR-16-5p, miR-34a-5p) out of 12, exploring their interactions with MRN-CSG. The 3D structures of these miRNA-MRN-CSG complexes displayed strong thermodynamic stability. Screening 7711 natural compounds resulted in two natural compounds (F0870-0001 and F0922-0471) with the lowest ligand binding energies (ΔG = -8.4 to-11.6 kcal/mol), targeting two common miRNAs. Docking results showed that one natural compound (PubChem id-5 281 614) bound to all MRN-CSG components (ΔG = -6.2 to -7.3 kcal/mol), while F6782-0723 bound only to RAD50 and NBN. These compounds exhibited minimal dissociation constants (Kd and Ki) and thermodynamically stable minimum free energy (MMGBSA) values. Molecular dynamics simulations indicated highly stable natural compound-MRN-CSG complexes, with consistent RMSD, RMSF, and strong residual correlation. These top-selected compounds displayed robust intermolecular H-bonding, low carcinogenicity, low toxicity, and drug-like properties. Consequently, these compounds hold promise for regulating miRNA and MRN-CSG DNA repair mechanisms in breast cancer therapy. Insight Box: This study investigated breast tumor samples (n = 60) and identified four miRNAs (miR-1-3p, miR-210-3p, miR-16-5p, miR-34a-5p) that interact with MRN-checkpoint sensor genes (MRN-CSG), crucial for DNA damage repair. Screening 7711 natural compounds highlighted two compounds (F0870-0001 and F0922-0471) with the lowest binding energies (ΔG = -8.4 to -11.6 kcal/mol), targeting two common miRNAs (miR-1-3p and miR-34a-5p). Another natural compound (PubChem id-5 281 614, ΔG = -6.2 to -7.3 kcal/mol) bound all MRN-CSG components, while F6782-0723 targeted RAD50 and NBN. These compounds showed strong binding stability, favorable MMGBSA values, and minimal dissociation constants. Molecular dynamics simulations confirmed the stability and drug-like properties of these compounds, indicating their potential in breast cancer therapy by modulating miRNA and MRN-CSG DNA repair mechanisms.

Recent findings in cancer research have pointed towards the bidirectional interaction between circadian and hypoxia pathways. However, little is known about their crosstalk mechanism. In this work, we aimed to investigate this crosstalk at a network level utilizing the omics information of gallbladder cancer. Differential gene expression and pathway enrichment analysis were used for selecting the crucial genes from both the pathways, followed by the construction of a logical crosstalk model using GINsim. Functional circuit identification and node perturbations were then performed. Significant node combinations were used to investigate the temporal behavior of the network through MaBoSS. Lastly, the model was validated using published in vitro experimentations. Four new positive circuits and a new axis viz. BMAL1/ HIF1αβ/ NANOG, responsible for stemness were identified. Through triple node perturbations viz.a. BMAL:CLOCK (KO or E1) + P53 (E1) + HIF1α (KO); b. P53 (E1) + HIF1α (KO) + MYC (E1); and c. HIF1α (KO) + MYC (E1) + EGFR (KO), the model was able to inhibit cancer growth and maintain a homeostatic condition. This work provides an architecture for drug simulation analysis to entrainment circadian rhythm and in vitro experiments for chronotherapy-related studies. Insight Box. Circadian rhythm and hypoxia are the key dysregulated processes which fuels-up the cancer growth. In the present work we have developed a gallbladder cancer (GBC) specific Boolean model, utilizing the RNASeq data from GBC dataset and tissue specific interactions. This work adequately models the bidirectional nature of interactions previously illustrated in experimental papers showing the effect of hypoxia on dysregulation of circadian rhythm and the influence of this disruption on progression towards metastasis. Through the dynamical study of the model and its response to different perturbations, we report novel triple node combinations that can be targeted to efficiently reduce GBC growth. This network can be used as a generalized framework to investigate different crosstalk pathways linked with cancer progression.

Efflux transporters are a fundamental component of both prokaryotic and eukaryotic cells, play a crucial role in maintaining cellular homeostasis, and represent a key bridge between single cell and population levels. From a biomedical perspective, they play a crucial role in drug resistance (and especially multi-drug resistance, MDR) in a range of systems spanning bacteria and human cancer cells. Typically, multiple efflux transporters are present in these cells, and the efflux transporters transport a range of substrates (with partially overlapping substrates between transporters). Furthermore, in the context of drug resistance, the levels of transporters may be elevated either due to extra or intracellular factors (feedforward regulation) or due to the drug itself (feedback regulation). As a consequence, there is a real need for a transparent systems-level understanding of the collective functioning of a set of transporters and their response to one or more drugs. We develop a systems framework for this purpose and examine the functioning of sets of transporters, their interplay with one or more drugs and their regulation (both feedforward and feedback). Using computational and analytical work, we obtain transparent insights into the systems level functioning of a set of transporters arising from the interplay between the multiplicity of drugs and transporters, different drug-transporter interaction parameters, sequestration and feedback and feedforward regulation. These insights transparently arising from the most basic consideration of a multiplicity of transporters have broad relevance in natural biology, biomedical engineering and synthetic biology. Insight, Innovation, Integration: Innovation: creating a structured systems framework for evaluating the impact of multiple transporters on drug efflux and drug resistance. Systematic analysis allows us to evaluate the effect of multiple transporters on one/more drugs, and dissect associated resistance mechanisms. Integration allows for elucidation of key cause-and-effect relationships and a transparent systems-level understanding of the collective functioning of transporters and their impact on resistance, revealing the interplay of key underlying factors. Systems-level insights include the essentially different behaviour of transporters as part of a group; unintuitive effects of influx; effects of elevated transporter-levels by feedforward and drug-induced mechanisms. Relevance: a systems understanding of efflux, their role in MDR, providing a framework/platform for use in designing treatment, and in synthetic biology design.

Collective dynamics of cells in confined geometry regulate several biological processes including cell migration, proliferation, differentiation, and communication. In this work, combining simulation with experimental data, we studied the oscillatory motion of epithelial sheets in smaller areas of confinement, and we linked the monolayer maturation induced-jamming with the wave formation. We showed that epithelial cell populations with delayed jamming properties use the additional time available from this delay to coordinate their movement, generating wave motion in larger areas of confinement compared to control populations. Furthermore, the effects of combining geometric confinement with contact guiding micro-gratings on this wave formation were investigated. We demonstrated that collective migratory oscillations under large geometrical confinement depend on the jamming state of the cell monolayers. The early dynamical state of the experimental results obtained was simulated by self-propelled Voronoi computations, comparing cells with solid-like and fluid-like behavior. Together our model describes the wave formation under confinement and the nodal oscillatory dynamics of the early dynamic stage of the system. Insight Box: Collective behavior of cells in confined spaces impacts biological processes. Through experimental data combined with simulations, the oscillatory motion of epithelial sheets in small areas of confinement was described. A correlation between the level of cell jamming and the formation of waves was detected. Cell populations with delayed jamming presented wave motion in larger confinement areas. The effects of combining geometric confinement with substrate micro-gratings demonstrated that the collective migratory oscillations in large confinement areas rely on the jamming state of cells. The early dynamical state was simulated using self-propelled Voronoi computations that help to understand wave formation under confinement and the nodal oscillatory dynamics of early-stage systems.

Diabetes is a rising global metabolic disorder and leads to long-term consequences. As a multifactorial disease, the gene-associated mechanisms are important to know. This study applied a bioinformatics approach to explore the molecular underpinning of type 2 diabetes mellitus through differential gene expression analysis. We used microarray datasets GSE16415 and GSE29226 to identify differentially expressed genes between type 2 diabetes and normal samples using R software. Following that, using the STRING database, the protein-protein interaction network was constructed and further analyzed by Cytoscape software. The EnrichR database was used for Gene Ontology and pathway enrichment analysis to explore key pathways and functional annotations of hub genes. We also used miRTarBase and TargetScan databases to predict miRNAs targeting hub genes. We identified 21 hub genes in type 2 diabetes, some showing more significant changes in the PPI network. Our results revealed that GLUL, SLC32A1, PC, MAPK10, MAPT, and POSTN genes are more important in the PPI network and can be experimentally investigated as therapeutic targets. Hsa-miR-492 and hsa-miR-16-5p are suggested for diagnosis and prognosis by targeting GLUL, SLC32A1, PC, MAPK10, and MAPT genes involved in the insulin signaling pathway. Insight: Type 2 diabetes, as a rising global and multifactorial disorder, is important to know the gene-associated mechanisms. In an integrative bioinformatics analysis, we integrated different finding datasets to put together and find valuable diagnostic and prognostic hub genes and miRNAs. In contrast, genes, RNAs, and enzymes interact systematically in pathways. Using multiple databases and software, we identified differential expression between hub genes of diabetes and normal samples. We explored different protein-protein interaction networks, gene ontology, key pathway analysis, and predicted miRNAs that target hub genes. This study reported 21 significant hub genes and some miRNAs in the insulin signaling pathway for innovative and potential diagnostic and therapeutic purposes.

Immune responses against cancer are inherently stochastic, with small numbers of individual T cells within a larger ensemble of lymphocytes initiating the molecular cascades that lead to tumor cytotoxicity. A potential source of this intra-tumor variability is the differential ability of immune cells to respond to tumor cells. Classical microwell co-cultures of T cells and tumor cells are inadequate for reliably culturing and analyzing low cell numbers needed to probe this variability, and have failed in recapitulating the heterogeneous small domains observed in tumors. Here we leverage a membrane displacement trap array technology that overcomes limitations of conventional microwell plates for immunodynamic studies. The microfluidic platform supports on-demand formation of dense nanowell cultures under continuous perfusion reflecting the tumor microenvironment, with real-time monitoring of T cell proliferation and activation within each nanowell. The system enables selective ejection of cells for profiling by fluorescence activated cell sorting, allowing observed on-chip variability in immune response to be correlated with off-chip quantification of T cell activation. The technology offers new potential for probing the molecular origins of T cell heterogeneity and identifying specific cell phenotypes responsible for initiating and propagating immune cascades within tumors. Insight Box Variability in T cell activation plays a critical role in the immune response against cancer. New tools are needed to unravel the mechanisms that drive successful anti-tumor immune response, and to support the development of novel immunotherapies utilizing rare T cell phenotypes that promote effective immune surveillance. To this end, we present a microfluidic cell culture platform capable of probing differential T cell activation in an array of nanoliter-scale wells coupled with off-chip cell analysis, enabling a high resolution view of variable immune response within tumor / T cell co-cultures containing cell ensembles orders of magnitude smaller than conventional well plate studies.

In B cells, the chemokine receptor CXCR3 is expressed only by a subset of B cells. However, CXCR3 is highly expressed in a rare type of B-cell lymphoma known as Mantle Cell Lymphoma (MCL) and CXCR3 inhibitor impairs proliferation and induces apoptosis in the MCL cell line JeKo-1. Despite this, the mechanism responsible for maintaining high levels of CXCR3 in MCL cells remains unclear. In this study, we assessed CXCR3 expression and amplification in MCL samples and confirmed that CXCR3 is overexpressed in MCL tissues. We also observed that CXCR3 amplification is present in a small portion of MCL patients and is associated with MCL classification. We then screened ubiquitin-specific proteases (USPs) that might control the degradation of CXCR3 protein. Our investigation revealed that USP35 acts as a potent stabilizer of CXCR3 protein. Knockdown of USP35 substantially reduced the CXCR3 protein levels in JeKo-1 cells, resulting in reduced cell viability, cell cycle arrest, increased apoptosis, and mitigated migration and invasion in these cells. At the molecular level, USP35 deubiquitinates and stabilizes CXCR3. USP35 deficiency attenuated the activation of the JAK1/STAT1 pathway and reduced the expression of β-catenin and c-Myc in JeKo-1 cells. Furthermore, we observed that overexpression of CXCR3 rescued the impaired tumorigenicity of USP35-deficient JeKo-1 cells, and the mechanism may be related to the fact that USP35 promotes CXCR3 deubiquitination to stabilize its expression. These findings collectively demonstrate the oncogenic role of the USP35-CXCR3 axis in JeKo-1 MCL cells.

The standard model of the cell membrane potential Vm describes it as arising from diffusion currents across a membrane with a constant electric field, with zero electric field outside the cell membrane. However, the influence of Vm has been shown to extend into the extracellular space where it alters the cell's ζ-potential, the electrical potential measured a few nm from the cell surface which defines how the cell interacts with charged entities in its environment, including ions, molecules, and other cells. The paradigm arising from surface science is that the ζ-potential arises only from fixed membrane surface charge, and has consequently received little interest. However, if the ζ-potential can mechanistically and dynamically change by alteration of Vm, it allows the cell to dynamically alter cell-cell and cell-molecule interactions and may explain previously unexplained electrophysiological behaviours. Whilst the two potentials Vm and ζ are rarely reported together, they are occasionally described in different studies for the same cell type. By considering published data on these parameters across multiple cell types, as well as incidences of unexplained but seemingly functional Vm changes correlating with changes in cell behaviour, evidence is presented that this may play a functional role in the physiology of red blood cells, macrophages, platelets, sperm, ova, bacteria and cancer. Understanding how these properties will improve understanding of the role of electrical potentials and charges in the regulation of cell function and in the way in which cells interact with their environment. Insight  The zeta (ζ) potential is the electrical potential a few nm beyond the surface of any suspensoid in water. Whilst typically assumed to arise only from fixed charges on the cell surface, recent and historical evidence shows a strong link to the cell's membrane potential Vm, which the cell can alter mechanistically through the use of ion channels. Whilst these two potentials have rarely been studied simultaneously, this review collates data across multiple studies reporting Vm, ζ-potential, electrical properties of changes in cell behaviour. Collectively, this points to Vm-mediated ζ-potential playing a significant role in the physiology and activity of blood cells, immune response, developmental biology and egg fertilization, and cancer among others.