Towards a better understanding of diabetes mellitus using organoid models

Beydag-Tasöz, Belin Selcen; Yennek, Siham; Grapin-Botton, Anne

doi:10.1038/s41574-022-00797-x

Cited by 25 publications

(15 citation statements)

References 227 publications

(338 reference statements)

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“…Prior research suggests a close association between CRC and the gut microbiome, with modifications in the microbiome contributing to CRC development through factors such as inflammatory disorders, microbial metabolites, or virulence factors [87][88][89][90]. In contrast, other conditions like diabetes or obesity are suspected to be multi-factorial and subject to a complex interplay of genetic and environmental factors [91,92].…”

Section: Discussionmentioning

confidence: 99%

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Matchado,

Rühlemann,

Reitmeier

et al. 2024

Microbial Genomics

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Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

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Section: Discussionmentioning

confidence: 99%

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Matchado,

Rühlemann,

Reitmeier

et al. 2024

Microbial Genomics

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“…Engineering strategies such as microfluidic‐based devices have been successfully implemented for high‐throughput conformal coating of islets, [ 44 ] and pancreas‐on‐a‐chip devices have been proposed as a way to enable real‐time measurements of various parameters such as insulin secretion, oxygen levels, oxidative stress, and more. [ 45 ]…”

Section: In Vitro and In Vivo Models Of T1dmentioning

confidence: 99%

Advances in the Use of Biologics and Biomaterials toward the Improvement of Pancreatic Islet Graft Survival in Type 1 Diabetes

Yitayew,

Luginina,

Tabrizian

2024

Advanced NanoBiomed Research

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Islet transplantation is a curative treatment for patients suffering from type 1 diabetes and has the potential to replace current treatment strategies involving the exogenous administration of insulin. Despite this potential, there are many hurdles in achieving successful long‐term graft survival due to autoimmune and foreign body reactions leading to graft rejection coupled with donor shortage and potential adverse effects from the need for long‐term administration of immunosuppressive drugs. As a result, various approaches have been proposed to increase the viability and function of islet grafts during isolation and ex vivo culture with the use of growth factors, hormones, and other therapeutic agents. In addition, other strategies have addressed how to enhance or maintain islet graft performance after implantation with improvements on immunosuppressive drug regimens and the use of biomaterials to encapsulate and protect the cells from graft rejection. This review focuses on the recent advances in strategies to improve islet viability and function with the addition of exogenous compounds and the implementation of conformal coating as a promising tool for immunoprotection of islet transplants.

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“…Recently, islet and liver organoids derived from patients or grown from pluripotent stem cells (PSC) became available. [ 34 ] A metabolic cross‐talk between these different organoids can be modeled using organ‐on‐chip (OoC) technology that combines tissue and micro engineering. [ 35 ] In a pioneering study, co‐culture of human pancreatic islet micro‐tissues and liver spheroids was done in a Transwell‐based OoC platform.…”

Section: Introductionmentioning

confidence: 99%

Pump‐Less, Recirculating Organ‐on‐Chip (rOoC) Platform to Model the Metabolic Crosstalk between Islets and Liver

Aizenshtadt,

Wang,

Abadpour

et al. 2024

Adv Healthcare Materials

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Type 2 diabetes mellitus (T2DM), obesity, and metabolic dysfunction‐associated steatotic liver disease (MASLD) are epidemiologically correlated disorders with a worldwide growing prevalence. While the mechanisms leading to the onset and development of these conditions are not fully understood, predictive tissue representations for studying the coordinated interactions between central organs that regulate energy metabolism, particularly the liver and pancreatic islets, are needed. Here, a dual pump‐less recirculating Organ‐on‐Chip (dual‐rOoC) platform that combines human pluripotent stem cell (sc)‐derived sc‐liver and sc‐islet organoids is presented. The platform reproduces key aspects of the metabolic cross‐talk between both organs, including glucose levels and selected hormones, and supports the viability and functionality of both sc‐islet and sc‐liver organoids while preserving a reduced release of pro‐inflammatory cytokines. In a model of metabolic disruption in response to treatment with high lipids and fructose, sc‐liver organoids exhibit hallmarks of steatosis and insulin resistance, while sc‐islets produce pro‐inflammatory cytokines on‐chip. Finally, the platform reproduces known effects of anti‐diabetic drugs on‐chip. Taken together, the platform provides a basis for functional studies of obesity, T2DM, and MASLD on‐chip, as well as for testing potential therapeutic interventions.This article is protected by copyright. All rights reserved

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Towards a better understanding of diabetes mellitus using organoid models

Cited by 25 publications

References 227 publications

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Advances in the Use of Biologics and Biomaterials toward the Improvement of Pancreatic Islet Graft Survival in Type 1 Diabetes

Pump‐Less, Recirculating Organ‐on‐Chip (rOoC) Platform to Model the Metabolic Crosstalk between Islets and Liver

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