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Sphabmixay, P.

Publications and source records attributed to Sphabmixay, P..

3 recordsLinked to original sources

A Microphysiological Model of Progressive Human Hepatic Insulin Resistance

Background & AimsHepatic insulin resistance is a fundamental phenomenon observed in both Type 2 diabetes (T2D) and metabolic (dysfunction) associated fatty liver disease (MAFLD). The relative contributions of nutrients, hyperinsulinemia, hormones, inflammation, and other cues are difficult to parse in vivo as they are convoluted by interplay between the local and systemic events. Here, we used a well-established human liver microphysiological system (MPS) to establish a physiologically-relevant insulin-responsive metabolic baseline and probe how primary human hepatocytes respond to controlled perturbations in insulin, glucose, and free fatty acids (FFAs). MethodsReplicate liver MPS were maintained in media with either 200 pM (normal) or 800 pM (T2D) insulin for up to 3 weeks. Conditions of standard glucose (5.5 mM), hyperglycemia (11 mM glucose), normal (20{micro}M) and elevated FFA (100 {micro}M), alone and in combination were used at each insulin concentration, either continuously or reversing back to standard media after 2 weeks of simulated T2D conditions. Hepatic glucose production, activation of signaling pathways, insulin clearance, transcriptome analysis, and intracellular lipid and bile acid accumulation were assessed. ResultsHyperinsulinemia alone induces insulin resistance after one week of exposure, while hyperglycemia and increased FFAs significantly exacerbate this phenotype. Hyperinsulinemia, along with elevated glucose and FFAs, transcriptionally predisposes hepatocytes to insulin resistance through altered metabolic and immune signaling pathways. The phenotypes observed in hyperinsulinemia and nutrient overload are partially reversible upon return to normophysiologic conditions. ConclusionsOur enhanced in vitro model, replicating multiple aspects of the insulin-resistant condition, offers improved insights into disease mechanisms with relevance to human physiology. Lay SummaryThe many nutritional, hormonal, and systemic inflammatory factors that contribute to the loss of sensitivity to insulin in Type 2 Diabetes and other metabolic disorders are difficult to parse in human patients, and animal models fail to capture all the human dimensions of the relevant biology. We, therefore, developed a microphysiological systems model, involving a microfluidic platform that cultures a simulated human liver for weeks at a time, under controlled nutrient and hormone concentrations, to analyze how the effects of nutrition (glucose and free fatty acids) together with increased insulin cause pathological features seen in human liver in vivo. We found that continually high levels of insulin predispose the liver to some of these features, along with reversal when the nutritional and insulin levels were restored to healthy values.

bioengineering↗

ViRNN: A Deep Learning Model for Viral Host Prediction

Viral outbreaks are on the rise in the world, with the current outbreak of COVID-19 being among one of the worst thus far. Many of these outbreaks were the result of zoonotic transfer between species, and thus understanding and predicting the host of a virus is very important. With the rise of sequencing technologies it is becoming increasingly easy to sequence the full genomes of viruses, databases of publicly available viral genomes are widely available. We utilize a convolutional and recurrent neural network architecture (ViRNN) to predict the hosts for the Coronaviridae family (Coronaviruses) amongst the eleven most common hosts of this family. Our architecture performed with an overall accuracy of 90.55% on our test dataset, with a micro-average AUC-PR of 0.97. Performance was variable per host. ViRNN outperformed previously published methods like k-nearest neighbors and support vector machines, as well as previously published deep learning based methods. Saliency maps based on integrated gradients revealed a number of proteins in the viral genome that may be important interactions determining viral infection in hosts. Overall, this method provides an adaptable classifier capable of predicting host species from viral genomic sequence with high accuracy.

genetics↗

Primary human colonic mucosal barrier crosstalk with super oxygen-sensitive Faecalibacterium prausnitzii in continuous culture

The gut microbiome plays an important role in human health and disease. Gnotobiotic animal and in vitro cell-based models provide some informative insights into mechanistic crosstalk. However, there is no existing system for a chronic co-culture of a human colonic mucosal barrier with super oxygen-sensitive commensal microbes, hindering the study of human-microbe interactions in a controlled manner. Here, we investigated the effects of an abundant super oxygen-sensitive commensal anaerobe, Faecalibacterium prausnitzii, on a primary human mucosal barrier using a Gut-MIcrobiome (GuMI) physiome platform that we designed and fabricated. Chronic continuous co-culture of F. prausnitzii for two days with colon epithelia, enabled by continuous flow of completely anoxic apical media and aerobic basal media, resulted in a strictly anaerobic apical environment fostering growth of and butyrate production by F. prausnitzii, while maintaining a stable colon epithelial barrier. We identified elevated differentiation and hypoxia-responsive genes and pathways in the platform compared with conventional aerobic static culture of the colon epithelia, attributable to a combination of anaerobic environment and continuous medium replenishment. Furthermore, we demonstrated anti-inflammatory effects of F. prausnitzii through HDAC and the TLR-NFKB axis. Finally, we identified that butyrate largely contributes to the anti-inflammatory effects by downregulating TLR3 and TLR4. Our results are consistent with some clinical observations regarding F. prausnitzii, thus motivating further studies employing this platform with more complex engineered colon tissues for understanding the interaction between the human colonic mucosal barrier and microbiota, pathogens, or engineered bacteria.Competing Interest StatementA provisional patent was filed.View Full Text

bioengineering↗