Curated Papers > Recent high-impact research on "organoids" (IF≥30, in the past five years)

Evaluation of variability in human kidney organoids.

Literature Information

DOI	10.1038/s41592-018-0253-2
PMID	30573816
Journal	Nature methods
Impact Factor	32.1
JCR Quartile	Q1
Publication Year	2019
Times Cited	133
Keywords	kidney organoids, transcriptional variation, single-cell profiling, nephron patterning, personalized medicine
Literature Type	Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't
ISSN	1548-7091
Pages	79-87
Issue	16(1)
Authors	Belinda Phipson, Pei X Er, Alexander N Combes, Thomas A Forbes, Sara E Howden, Luke Zappia, Hsan-Jan Yen, Kynan T Lawlor, Lorna J Hale, Jane Sun, Ernst Wolvetang, Minoru Takasato, Alicia Oshlack, Melissa H Little

TL;DR

This study investigates transcriptional variations in kidney organoids derived from human pluripotent stem cells, revealing significant batch-to-batch differences primarily related to nephron maturation despite strong correlations within individual differentiation batches. The findings highlight the importance of understanding these variations to enhance the utility of kidney organoids in personalized medicine and functional genomics.

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kidney organoids · transcriptional variation · single-cell profiling · nephron patterning · personalized medicine

Abstract

The utility of human pluripotent stem cell-derived kidney organoids relies implicitly on the robustness and transferability of the protocol. Here we analyze the sources of transcriptional variation in a specific kidney organoid protocol. Although individual organoids within a differentiation batch showed strong transcriptional correlation, we noted significant variation between experimental batches, particularly in genes associated with temporal maturation. Single-cell profiling revealed shifts in nephron patterning and proportions of component cells. Distinct induced pluripotent stem cell clones showed congruent transcriptional programs, with interexperimental and interclonal variation also strongly associated with nephron patterning. Epithelial cells isolated from organoids aligned with total organoids at the same day of differentiation, again implicating relative maturation as a confounder. This understanding of experimental variation facilitated an optimized analysis of organoid-based disease modeling, thereby increasing the utility of kidney organoids for personalized medicine and functional genomics.

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Primary Questions Addressed

1. What are the key factors contributing to transcriptional variation in kidney organoids across different experimental batches?
2. How does the maturation timeline of kidney organoids affect their functional characteristics and applicability in disease modeling?
3. In what ways can the insights gained from studying nephron patterning improve the protocols for generating kidney organoids?
4. What implications does interclonal variation have on the reproducibility and reliability of kidney organoid studies?
5. How can the findings related to epithelial cell alignment with total organoids enhance the understanding of organoid development and differentiation?

Key Findings

Research Background and Purpose

The study investigates the variability in transcriptional profiles of kidney organoids derived from human induced pluripotent stem cells (iPSCs). It aims to understand the sources of variation that affect the reproducibility and transferability of kidney organoid protocols, which are crucial for modeling kidney diseases and advancing personalized medicine.

Main Methods/Materials/Experimental Design

The researchers employed a comprehensive approach involving bulk RNA sequencing (RNA-seq) and single-cell RNA-seq to analyze kidney organoids. The differentiation protocol began with thawing human iPSCs and culturing them in a stepwise manner to form organoids. The key steps are summarized in the following flowchart:

The study included 57 whole organoids and 8,323 single cells, focusing on variations between differentiation batches, iPSC clones, and isolated epithelial compartments.

Key Results and Findings

• Significant transcriptional variation was observed between experimental batches, especially in genes related to nephron maturation.
• Single-cell profiling revealed changes in nephron patterning and the proportions of various cell types within the organoids.
• A set of highly variable genes was identified, reflecting differences in organoid maturation and nephron segmentation.
• The results indicated that batch-to-batch variation was the primary source of transcriptional variability, more so than interclonal differences.

Main Conclusions/Significance/Innovation

The findings highlight the importance of controlling for batch variability when using kidney organoids for disease modeling. The study provides a framework for optimizing organoid-based analyses in personalized medicine, emphasizing the need for concurrent differentiations and careful experimental design to mitigate variability. Additionally, it introduces a list of highly variable genes that can be used to enhance the accuracy of disease-related transcriptional analyses.

Research Limitations and Future Directions

• The study acknowledges that while the kidney organoid protocol is robust, it still faces challenges in achieving consistent maturation across different lines.
• Future research should focus on refining differentiation protocols to minimize variability and exploring the application of the identified variable genes in understanding disease mechanisms.
• The authors suggest that the approach of enriching specific cell types within organoids may improve the detection of relevant transcriptional changes in disease models.

Summary Table of Key Aspects

Aspect	Details
Study Focus	Variability in kidney organoid transcriptional profiles
Methods Used	Bulk RNA-seq, single-cell RNA-seq, and statistical modeling
Key Findings	Significant batch variation, maturation-related gene variability
Conclusions	Importance of controlling batch effects for reproducibility
Future Directions	Improve differentiation protocols, explore specific cell type analysis

Literatures Citing This Work

1. Single-cell analysis reveals congruence between kidney organoids and human fetal kidney. - Alexander N Combes;Luke Zappia;Pei Xuan Er;Alicia Oshlack;Melissa H Little - Genome medicine (2019)
2. Revealing potential cardiac manifestation of ADPKD using iPS cell-derived cardiomyocytes. - Ryuji Morizane - EBioMedicine (2019)
3. From gene to treatment: supporting rare disease translational research through model systems. - Julija Hmeljak;Monica J Justice - Disease models & mechanisms (2019)
4. Kidney organoids in translational medicine: Disease modeling and regenerative medicine. - Tomoya Miyoshi;Ken Hiratsuka;Edgar Garcia Saiz;Ryuji Morizane - Developmental dynamics : an official publication of the American Association of Anatomists (2020)
5. Reporter-based fate mapping in human kidney organoids confirms nephron lineage relationships and reveals synchronous nephron formation. - Sara E Howden;Jessica M Vanslambrouck;Sean B Wilson;Ker Sin Tan;Melissa H Little - EMBO reports (2019)
6. The myriad possibility of kidney organoids. - Pinyuan Tian;Rachel Lennon - Current opinion in nephrology and hypertension (2019)
7. Advances in our understanding of genetic kidney disease using kidney organoids. - Melissa H Little;Catherine Quinlan - Pediatric nephrology (Berlin, Germany) (2020)
8. Generation of Human PSC-Derived Kidney Organoids with Patterned Nephron Segments and a De Novo Vascular Network. - Jian Hui Low;Pin Li;Elaine Guo Yan Chew;Bingrui Zhou;Keiichiro Suzuki;Tian Zhang;Michelle Mulan Lian;Meng Liu;Emi Aizawa;Concepcion Rodriguez Esteban;Kylie Su Mei Yong;Qingfeng Chen;Josep M Campistol;Mingliang Fang;Chiea Chuen Khor;Jia Nee Foo;Juan Carlos Izpisua Belmonte;Yun Xia - Cell stem cell (2019)
9. Kidney organoids: accurate models or fortunate accidents. - Melissa H Little;Alexander N Combes - Genes & development (2019)
10. Building a better model of the retina. - Milica Radisic - eLife (2019)

... (123 more literatures)

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