Molecular BioSystems最新文献

Enhanced cell motility is one of the primary features of cancer. Accumulated evidence demonstrates that Epidermal Growth Factor Receptor (EGFR) mediated pathways play an important role in breast cancer cell proliferation and migration. We have quantified the MDA-MB-231 breast cancer cell migration in response to the stimulation of EGFR pathways with their ligand EGF to determine how the cell motility of MDA-MB-231 cells depends on the ligand concentration and gradient. Analysis at the single cell level combined with mathematical modeling and the ability to vary the ligand concentration and gradients locally using microfluidic devices allowed us to separate the unique contributions of ligand concentration and ligand gradient to cell motility. We tracked the motility of 6600 cells individually using time lapse imaging under varying EGF stimulation conditions. Trajectory analysis of the tracked cells using non-linear multivariate regression models showed that: (i) cell migration of MDA-MB-231 breast cancer cells depends on the ligand gradient but not on the ligand concentration. This observation was valid for both the total (direction independent) and directed (along gradient direction) cell velocities. Although the dependence of the directed motility on ligand gradient is to be expected, the dependence of the total velocity solely on ligand gradient was an unexpected novel observation. (ii) Enhancement of the motilities of individual cells in a population upon exposure to the ligand was highly heterogeneous, and only a very small percentage of cells responded strongly to the external stimuli. Separating out the non-responding cells using quantitative analysis of individual cell motilities enabled us to establish that enhanced motility of the responding cells indeed increases monotonically with increasing EGF gradient. (iii) A large proportion of cells in a population were unresponsive to ligand stimulation, and their presence introduced considerable random intrinsic variability to the observations. This indicated that studying cell motilities at the individual cell level is necessary to better capture the biological reality and that population averaging methods should be avoided. Studying motilities at the individual cell level is particularly important to understand the biological processes that are possibly driven by the action of a small portion of cells in a population, such as metastasis. We discuss the implications of our results on the total and chemotactic movement of cancer cells in the tumor microenvironment.

Metabolic profiling provides an unbiased view of the physiological status of an organism as a “function” of the metabolic composition of a measured sample. Here, we propose a simple LC-MS based workflow for metabolic profiling of volume-restricted samples, namely individual 20 μm-thick histological sections of a mouse kidney. The main idea of this workflow is to re-use the material after an RPLC-MS run, namely using the volume remaining in the vial after injection, and then introducing a phase changing step to enable HILIC-MS analysis. To test the applicability of the workflow and its ability to extract valuable biological information, we applied it to an animal model of polycystic kidney disease (PKD).

2,5-Hexanedione (HD) is an important bioactive metabolite of n-hexane, which mediates the neurotoxicity of the parent compound. Increasing evidence suggests that over-activated autophagy can lead to autophagic neuronal death; however, whether the excessive autophagy is involved in HD-induced neurotoxicity remains unknown. To investigate the effect of HD on autophagy and to find its underlying mechanism, we respectively treated VSC4.1 cells with 5, 15 and 25 mM HD for 24 h. Our results show that HD induced excessive autophagy of VSC4.1 cells in a dose-dependent manner, also, the over-activated autophagy was significantly mitigated in the presence of PI3K activator or Akt activator or mTOR activator. These results indicate that HD induces excessive autophagy of VSC4.1 cells by repressing the PI3K/Akt/mTOR signaling pathway. LDH assay showed that HD contributed to a concentration dependent increase in VSC4.1 cell death, which was significantly reduced by the administration of PIK-III, an autophagy inhibitor. These results also indicate that HD induces autophagic death of VSC4.1 cells via the signaling pathway.

Imaging mass spectrometry (IMS) is recognized as a powerful tool to investigate the spatial distribution of untargeted or targeted molecules of a wide variety of samples including tissue sections. Leishmania is a protozoan parasite that causes different clinical manifestations in mammalian hosts. Leishmaniasis is a major public health risk in different continents and represents one of the most important neglected diseases. Cutaneous lesions from mice experimentally infected with Leishmania spp. were investigated by matrix-assisted laser desorption ionization MS using the SCiLS Lab software for statistical analysis. Being applied to cutaneous leishmaniasis (CL) for the first time, MALDI-IMS was used to search for peptides and low molecular weight proteins (2–10 kDa) as candidates for potential biomarkers. Footpad sections of Balb/c mice infected with (i) Leishmania amazonensis or (ii) Leishmania major were imaged. The comparison between healthy and infected skin highlighted a set of twelve possible biomarker proteins for L. amazonenis and four proteins for L. major. Further characterization of these proteins could reveal how these proteins act in pathology progression and confirm their values as biomarkers.

Under the current deluge of omics, module networks distinctively emerge as methods capable of not only identifying inherently coherent groups (modules), thus reducing dimensionality, but also hypothesizing cause–effect relationships between modules and their regulators. Module networks were first designed in the transcriptomic era and further exploited in the multi-omic context to assess (for example) miRNA regulation of gene expression. Despite a number of available implementations, expansion of module networks to other omics is constrained by a limited characterization of the solutions' (modules plus regulators) accuracy and stability – an immediate need for the better characterization of molecular biology complexity in silico. We hence carefully assessed for LemonTree – a popular and open source module network implementation – the dependency of the software performances (sensitivity, specificity, false discovery rate, solutions' stability) on the input parameters and on the data quality (sample size, expression noise) based on synthetic and real data. In the process, we uncovered and fixed an issue in the code for the regulator assignment procedure. We concluded this evaluation with a table of recommended parameter settings. Finally, we applied these recommended settings to gut-intestinal metagenomic data from rheumatoid arthritis patients, to characterize the evolution of the gut-intestinal microbiome under different pharmaceutical regimens (methotrexate and prednisone) and we inferred innovative clinical recommendations with therapeutic potential, based on the computed module network.

The intrinsically disordered protein (IDP) Chz.core, which is the interaction core of Chz1, shows binding preference to histone variant H2A.z. Although there are several studies on the binding process of Chz.core, the detailed coupled binding–folding processes are still elusive. In this study, we explored the coupled binding–folding mechanism and the effect of flexibility by continuously monitoring the flexibility degree of Chz.core. We applied an all-atom structure-based model (SBM), which takes advantage of providing both backbone and sidechain information about the conformational changes of Chz.core during binding. We presented a somewhat different “fly-casting” picture that the long IDP can undergo a tertiary stretching and bending with larger capture radii than ordered proteins. Our results suggest that the higher flexibility of Chz.core contributes to the shorter times for capturing events, leading to higher recognition efficiencies. In addition, compared to the ordered proteins, the high flexibility of the intrinsically disordered protein enables Chz.core to have a lower binding barrier and a faster association rate, which are favorable for the binding process to its partner H2A.z–H2B.

In recent years, many efforts have been made in the field of computational modeling of cancerous tumors, in order to obtain a better understanding and predictions of their growth patterns. Furthermore, constraint-based modeling of metabolic networks has become increasingly popular, which is appropriate for the systems-level reconstruction of cell physiology. The goal of the current study is to integrate a multiscale agent-based modeling framework with a constraint-based metabolic network model of cancer cells in order to simulate the three dimensional early growth of avascular tumors. In order to develop the integrated model, a previously published generic metabolic network model of cancer cells was introduced into a multiscale agent-based framework. This model is initiated with a single tumor cell. Nutrients can diffuse through the simulation space and the cells uptake or excrete metabolites, grow, proliferate or become necrotic based on certain defined criteria and flux values of particular reactions. The simulation was run for a period of 20 days and the plots corresponding to various features such as the growth profile and necrotic core evolution were obtained. These features were compared with the ones observed in other (experimental) studies. One interesting characteristic of our modeling is that it provides us with the ability to predict gene expression patterns through different layers of a tumor, which can have important implications, especially in drug target selection in the field of cancer therapy.

Calcium homeostasis is a key factor in the regulation of cardiac excitation–contraction coupling. Calcium dynamics in cardiomyocytes is governed by ATP which depends on insulin dependent glucose concentration, via the glucose transporter type 4 (GLUT4) transporter. It would therefore be interesting to see how calcium dynamics changes in a cardiomyocyte under diabetic conditions. We proposed and analysed a four dimensional ordinary differential equation (ODE) model to capture the interdependency of calcium dynamics on glucose uptake and ATP generation. More specifically, we looked for the role of GLUT4, energy metabolism, L-type channels, RyR2 channels, SERCA2a pumps and leakage rate in the normal functioning of cardiomyocytes. To understand the system dynamics, we first obtained the stability and Hopf-bifurcation criteria of steady state and then through parameter perturbation we captured the role of different parameters in maintaining normal calcium oscillation (frequency 40 to 180 beats per minute and amplitude ≥0.4 μM) and hence normal cardiac function. We observed that any divergence in the GLUT4 activity (especially a decrease in the glucose uptake rate) might cause abnormal calcium oscillation, leading to cardiac dysfunction (CD). Our study finally hypothesizes that a regulated sarcoplasmic reticulum (SR) calcium flux could be a possible therapeutic strategy to maintain normal calcium dynamics in diabetic heart and to prevent possible CD.

In this study, we explore the structural and dynamic adaptations of the Tryptophan synthase α-subunit in a ligand bound state in psychrophilic, mesophilic and hyperthermophilic organisms at different temperatures by MD simulations. We quantify the global and local fluctuations in the 40 ns time scale by analyzing the root mean square deviation/fluctuations. The distinct behavior of the active site and loop 6 is observed with the elevation of temperature. Protein stability relies more on electrostatic interactions, and these interactions might be responsible for the stability of varying temperature evolved proteins. The paper also focuses on the effect of temperature on protein dynamics and stability governed by the distinct behavior of the ligand associated with its retention, binding and dissociation over the course of time. The integration of principle component analysis and a free energy landscape was useful in identifying the conformational space accessible to ligand bound homologues and how the presence of the ligand alters the conformational and dynamic properties of the protein.

Prostate cancer is one of the most significant male health concerns worldwide, and various researchers carrying out molecular diagnostics have indicated that genetic interactions with biological and behavioral factors play an important role in the overall risk and prognosis of this disease. Single nucleotide polymorphisms are increasingly becoming strong biomarker candidates to identify the susceptibility of individuals to prostate cancer. We carried out risk association of different stages of prostate cancer to a number of single nucleotide polymorphisms to identify the susceptible alleles in a New Zealand population and checked the interaction with environmental factors as well. We identified a number of single nucleotide polymorphisms to have associations specifically to the risk of prostate cancer and aggressiveness of the disease, and also certain single nucleotide polymorphisms to be vulnerable to the reported behavioral factors. We have addressed “special” environmental conditions prevalent in New Zealand, which can be used as a model for a bigger worldwide study.