Sex differences in kidney metabolism may reflect sex-dependent outcomes in human diabetic kidney disease.

Diabetic kidney disease (DKD) is the main cause of chronic kidney disease (CKD) and progresses faster in males than in females. We identify sex-based differences in kidney metabolism and in the blood metabolome of male and female individuals with diabetes. Primary human proximal tubular epithelial cells (PTECs) from healthy males displayed increased mitochondrial respiration, oxidative stress, apoptosis, and greater injury when exposed to high glucose compared with PTECs from healthy females. Male human PTECs showed increased glucose and glutamine fluxes to the TCA cycle, whereas female human PTECs showed increased pyruvate content. The male human PTEC phenotype was enhanced by dihydrotestosterone and mediated by the transcription factor HNF4A and histone demethylase KDM6A. In mice where sex chromosomes either matched or did not match gonadal sex, male gonadal sex contributed to the kidney metabolism differences between males and females. A blood metabolomics analysis in a cohort of adolescents with or without diabetes showed increased TCA cycle metabolites in males. In a second cohort of adults with diabetes, females without DKD had higher serum pyruvate concentrations than did males with or without DKD. Serum pyruvate concentrations positively correlated with the estimated glomerular filtration rate, a measure of kidney function, and negatively correlated with all-cause mortality in this cohort. In a third cohort of adults with CKD, male sex and diabetes were associated with increased plasma TCA cycle metabolites, which correlated with all-cause mortality. These findings suggest that differences in male and female kidney metabolism may contribute to sex-dependent outcomes in DKD.

Pump-Less Platform Enables Long-Term Recirculating Perfusion of 3D Printed Tubular Tissues.

The direction and pattern of fluid flow affect vascular structure and function, in which vessel-lining endothelial cells exhibit variable cellular morphologies and vessel remodeling by mechanosensing. To recapitulate this microenvironment, some approaches have been reported to successfully apply unidirectional flow on endothelial cells in organ-on-a-chip systems. However, these platforms encounter drawbacks such as the dependency on pumps or confinement to closed microfluidic channels. These constraints impede their synergy with advanced biofabrication techniques like 3D bioprinting, thereby curtailing the potential to introduce greater complexity into engineered tissues. Herein, a pumpless recirculating platform (UniPlate) that enables unidirectional media recirculation through 3D printed tubular tissues, is demonstrated.The device is made of polystyrene via injection molding in combination with 3D printed sacrifical gelatin templates. Tubular blood vessels with unidirectional perfusion are firstly engineered. Then the design is expanded to incorporate duo-recirculating flow for culturing vascularized renal proximal tubules with glucose reabsorption function. In addition to media recirculation, human monocyte recirculation in engineered blood vessels is also demonstrated for over 24 h, with minimal loss of cells, cell viability, and inflammatory activation. UniPlate can be a valuable tool to more precisely control the cellular microenvironment of organ-on-a-chip systems for drug discovery.

D-CryptO: deep learning-based analysis of colon organoid morphology from brightfield images.

Stem cell-derived organoids are a promising tool to model native human tissues as they resemble human organs functionally and structurally compared to traditional monolayer cell-based assays. For instance, colon organoids can spontaneously develop crypt-like structures similar to those found in the native colon. While analyzing the structural development of organoids can be a valuable readout, using traditional image analysis tools makes it challenging because of the heterogeneities and the abstract nature of organoid morphologies. To address this limitation, we developed and validated a deep learning-based image analysis tool, named D-CryptO, for the classification of organoid morphology. D-CryptO can automatically assess the crypt formation and opacity of colorectal organoids from brightfield images to determine the extent of organoid structural maturity. To validate this tool, changes in organoid morphology were analyzed during organoid passaging and short-term forskolin stimulation. To further demonstrate the potential of D-CryptO for drug testing, organoid structures were analyzed following treatments with a panel of chemotherapeutic drugs. With D-CryptO, subtle variations in how colon organoids responded to the different chemotherapeutic drugs were detected, which suggest potentially distinct mechanisms of action. This tool could be expanded to other organoid types, like intestinal organoids, to facilitate 3D tissue morphological analysis.

Subtractive manufacturing with swelling induced stochastic folding of sacrificial materials for fabricating complex perfusable tissues in multi-well plates.

Organ-on-a-chip systems that recapitulate tissue-level functions have been proposed to improve in vitro-in vivo correlation in drug development. Significant progress has been made to control the cellular microenvironment with mechanical stimulation and fluid flow. However, it has been challenging to introduce complex 3D tissue structures due to the physical constraints of microfluidic channels or membranes in organ-on-a-chip systems. Inspired by 4D bioprinting, we develop a subtractive manufacturing technique where a flexible sacrificial material can be patterned on a 2D surface, swell and shape change when exposed to aqueous hydrogel, and subsequently degrade to produce perfusable networks in a natural hydrogel matrix that can be populated with cells. The technique is applied to fabricate organ-specific vascular networks, vascularized kidney proximal tubules, and terminal lung alveoli in a customized 384-well plate and then further scaled to a 24-well plate format to make a large vascular network, vascularized liver tissues, and for integration with ultrasound imaging. This biofabrication method eliminates the physical constraints in organ-on-a-chip systems to incorporate complex ready-to-perfuse tissue structures in an open-well design.

From Model System to Therapy: Scalable Production of Perfusable Vascularized Liver Spheroids in "Open-Top" 384-Well Plate.

Vasculature is a key component of many biological tissues and helps to regulate a wide range of biological processes. Modeling vascular networks or the vascular interface in organ-on-a-chip systems is an essential aspect of this technology. In many organ-on-a-chip devices, however, the engineered vasculatures are usually designed to be encapsulated inside closed microfluidic channels, making it difficult to physically access or extract the tissues for downstream applications and analysis. One unexploited benefit of tissue extraction is the potential of vascularizing, perfusing, and maturing the tissue in well-controlled, organ-on-a-chip microenvironments and then subsequently extracting that product for in vivo therapeutic implantation. Moreover, for both modeling and therapeutic applications, the scalability of the tissue production process is important. Here we demonstrate the scalable production of perfusable and extractable vascularized tissues in an "open-top" 384-well plate (referred to as IFlowPlate), showing that this system could be used to examine nanoparticle delivery to targeted tissues through the microvascular network and to model vascular angiogenesis. Furthermore, tissue spheroids, such as hepatic spheroids, can be vascularized in a scalable manner and then subsequently extracted for in vivo implantation. This simple multiple-well plate platform could not only improve the experimental throughputs of organ-on-a-chip systems but could potentially help expand the application of model systems to regenerative therapy.

Correction: Deep-LUMEN assay - human lung epithelial spheroid classification from brightfield images using deep learning.

Correction for 'Deep-LUMEN assay - human lung epithelial spheroid classification from brightfield images using deep learning' by Lyan Abdul et al., Lab Chip, 2020, DOI: .

Deep-LUMEN assay - human lung epithelial spheroid classification from brightfield images using deep learning.

Three-dimensional (3D) tissue models such as epithelial spheroids or organoids have become popular for pre-clinical drug studies. In contrast to 2D monolayer culture, the characterization of 3D tissue models from non-invasive brightfield images is a significant challenge. To address this issue, here we report a deep-learning uncovered measurement of epithelial networks (Deep-LUMEN) assay. Deep-LUMEN is an object detection algorithm that has been fine-tuned to automatically uncover subtle differences in epithelial spheroid morphology from brightfield images. This algorithm can track changes in the luminal structure of tissue spheroids and distinguish between polarized and non-polarized lung epithelial spheroids. The Deep-LUMEN assay was validated by screening for changes in spheroid epithelial architecture in response to different extracellular matrices and drug treatments. Specifically, we found the dose-dependent toxicity of cyclosporin can be underestimated if the effect of the drug on tissue morphology is not considered. Hence, Deep-LUMEN could be used to assess drug effects and capture morphological changes in 3D spheroid models in a non-invasive manner.

IFlowPlate-A Customized 384-Well Plate for the Culture of Perfusable Vascularized Colon Organoids.

Despite the complexity and structural sophistication that 3D organoid models provide, their lack of vascularization and perfusion limit the capability of these models to recapitulate organ physiology effectively. A microfluidic platform named IFlowPlate is engineered, which can be used to culture up to 128 independently perfused and vascularized colon organoids in vitro. Unlike traditional microfluidic devices, the vascularized organoid-on-chip device with an "open-well" design does not require any external pumping systems and allows tissue extraction for downstream analyses, such as histochemistry or even in vivo transplantation. By optimizing both the extracellular matrix (ECM) and the culture media formulation, patient-derived colon organoids are co-cultured successfully within a self-assembled vascular network, and it is found that the colon organoids grow significantly better in the platform under constant perfusion versus conventional static condition. Furthermore, a colon inflammation model with an innate immune function where circulating monocytes can be recruited from the vasculature, differentiate into macrophage, and infiltrate the colon organoids in response to tumor necrosis factor (TNF)- inflammatory cytokine stimulation is developed using the platform. With the ability to grow vascularized colon organoids under intravascular perfusion, the IFlowPlate platform could unlock new possibilities for screening potential therapeutic targets or modeling relevant diseases.