Fatty Acid Ethyl Esters Induce Intestinal Epithelial Barrier Dysfunction via a Reactive Oxygen Species-Dependent Mechanism in a Three-Dimensional Cell Culture Model

Background & Aims

Evidence is accumulating that ethanol and its oxidative metabolite, acetaldehyde, can disrupt intestinal epithelial integrity, an important factor contributing to ethanol-induced liver injury. However, ethanol can also be metabolized non-oxidatively generating phosphatidylethanol and fatty acid ethyl esters (FAEEs). This study aims to investigate the effects of FAEEs on barrier function, and to explore the role of oxidative stress as possible mechanism.

Methods

Epithelial permeability was assessed by paracellular flux of fluorescein isothiocyanate-conjugated dextran using live cell imaging. Cell integrity was evaluated by lactate dehydrogenase release. Localization and protein levels of ZO-1 and occludin were analyzed by immunofluorescence and cell-based ELISA, respectively. Intracellular oxidative stress and cellular ATP levels were measured by dichlorofluorescein and luciferase driven bioluminescence, respectively.

Results

In vitro, ethyl oleate and ethyl palmitate dose dependently increased permeability associated with disruption and decreased ZO-1 and occludin protein levels, respectively, and increased intracellular oxidative stress without compromising cell viability. These effects could partially be attenuated by pretreatment with the antioxidant, resveratrol, pointing to the role of oxidative stress in the FAEEs-induced intestinal barrier dysfunction.

Conclusions

These findings show that FAEEs can induce intestinal barrier dysfunction by disrupting the tight junctions, most likely via reactive oxygen species-dependent mechanism.     

Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI

Functional magnetic resonance imaging (fMRI) measures brain activity by detecting the blood-oxygen-level dependent (BOLD) response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new, independent validation data. These results open the door to a new type of fMRI analysis that more accurately reflects the true neuronal activity.     

In Vitro Analysis of Metabolites Secreted during Infection of Lung Epithelial Cells by Cryptococcus neoformans

Cryptococcus neoformans is an encapsulated basidiomycetous yeast commonly associated with pigeon droppings and soil. The opportunistic pathogen infects humans through the respiratory system and the metabolic implications of C. neoformans infection have yet to be explored. Studying the metabolic profile associated with the infection could lead to the identification of important metabolites associated with pulmonary infection. Therefore, the aim of the study was to simulate cryptococcal infection at the primary site of infection, the lungs, and to identify the metabolic profile and important metabolites associated with the infection at low and high multiplicity of infections (MOI). The culture supernatant of lung epithelial cells infected with C. neoformans at MOI of 10 and 100 over a period of 18 hours were analysed using gas chromatography mass spectrometry. The metabolic profiles obtained were further analysed using multivariate analysis and the pathway analysis tool, MetaboAnalyst 2.0. Based on the results from the multivariate analyses, ten metabolites were selected as the discriminatory metabolites that were important in both the infection conditions. The pathways affected during early C. neoformans infection of lung epithelial cells were mainly the central carbon metabolism and biosynthesis of amino acids. Infection at a higher MOI led to a perturbance in the β-alanine metabolism and an increase in the secretion of pantothenic acid into the growth media. Pantothenic acid production during yeast infection has not been documented and the β-alanine metabolism as well as the pantothenate and CoA biosynthesis pathways may represent underlying metabolic pathways associated with disease progression. Our study suggested that β-alanine metabolism and the pantothenate and CoA biosynthesis pathways might be the important pathways associated with cryptococcal infection.     

Coupling spatial segregation with synthetic circuits to control bacterial survival

Engineered bacteria have great potential for medical and environmental applications. Fulfilling this potential requires controllability over engineered behaviors and scalability of the engineered systems. Here, we present a platform technology, microbial swarmbot, which employs spatial arrangement to control the growth dynamics of engineered bacteria. As a proof of principle, we demonstrated a safeguard strategy to prevent unintended bacterial proliferation. In particular, we adopted several synthetic gene circuits to program collective survival in Escherichia coli: the engineered bacteria could only survive when present at sufficiently high population densities. When encapsulated by permeable membranes, these bacteria can sense the local environment and respond accordingly. The cells inside the microbial swarmbot capsules will survive due to their high densities. Those escaping from a capsule, however, will be killed due to a decrease in their densities. We demonstrate that this design concept is modular and readily generalizable. Our work lays the foundation for engineering integrated and programmable control of hybrid biological–material systems for diverse applications.     

Cross-correlation analysis of invasive mango mealybug and its associated natural enemies in relation to meteorological factors: implications for biological control

Damage caused by invasive downey snow line mealybug, Rastrococcus iceryoides Green (Hemiptera: Pseudococcidae) has been reported to vary between 30% to complete crop loss where no control measure is applied. The current studies seek to determine factors influencing R. iceryoides population outbreaks, parasitoid – host and predator–prey relationships as well as predict optimal management strategies through weather modelling over a period of 28 months from 2008 to 2010 in Tanzania. The highest incidence of R. iceryoides was recorded during the dry season coinciding with the major mango fruiting season. The relationship between R. iceryoides and the parasitoid was positive but not significant, which implies the influence on outbreaks was negligible probably due to low percent parasitism (<12%). However, the predator abundance was directly and significantly related to that of R. iceryoides. Average temperature, average relative humidity, rainfall, and R. iceryoides abundance were autocorrelated to each other. Cross-correlation coef?cients vary significantly from ?0.286 to 0.589 for the pair-variable between R. iceryoides, temperature, relative humidity, rainfall, parasitism and predators. Our findings showed that temperature was the key climatic variable that significantly influenced R. iceryoides outbreaks while rainfall was significantly negatively associated with the pest. Time series analyses show R. iceryoides population increased 4 months after an increase in average temperature in all the sites, 11 months after rainfall and 11 months after relative humidity in Kibaha and Dar es Salaam, respectively. Our findings revealed that R. iceryoides is an excellent target for classical biological control. Thus, the importation of promising co-evolved parasitoid specific to R. iceryoides from the aboriginal home is crucial in formulating an efficient and sustainable management approaches against the invasive mealybug pest in mango agro-ecosystems.     

Proteomics analysis of cytokine-induced dysfunction and death in insulin-producing INS-1E cells: new insights into the pathways involved

Cytokines released by islet-infiltrating immune cells play a crucial role in beta-cell dysfunction and apoptotic cell death in the pathogenesis of type 1 diabetes and after islet transplantation. RNA studies revealed complex pathways of genes being activated or suppressed during this beta-cell attack. The aim of the present study was to analyze protein changes in insulin-producing INS-1E cells exposed to inflammatory cytokines in vitro using two-dimensional DIGE. Within two different pH ranges we observed 2214 +/- 164 (pH 4-7) and 1641 +/- 73 (pH 6-9) spots. Analysis at three different time points (1, 4, and 24 h of cytokine exposure) revealed that the major changes were taking place only after 24 h. At this time point 158 proteins were altered in expression (4.1%, n = 4, p < or = 0.01) by a combination of interleukin-1beta and interferon-gamma, whereas only 42 and 23 proteins were altered by either of the cytokines alone, giving rise to 199 distinct differentially expressed spots. Identification of 141 of these by MALDI-TOF/TOF revealed proteins playing a role in insulin secretion, cytoskeleton organization, and protein and RNA metabolism as well as proteins associated with endoplasmic reticulum and oxidative stress/defense. We investigated the interactions of these proteins and discovered a significant interaction network (p < 1.27e-05) containing 42 of the identified proteins. This network analysis suggests that proteins of different pathways act coordinately in a beta-cell dysfunction/apoptotic beta-cell death interactome. In addition the data suggest a central role for chaperones and proteins playing a role in RNA metabolism. As many of these identified proteins are regulated at the protein level or undergo post-translational modifications, a proteomics approach, as performed in this study, is required to provide adequate insight into the mechanisms leading to beta-cell dysfunction and apoptosis. The present findings may open new avenues for the understanding and prevention of beta-cell loss in type 1 diabetes.